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Abstracts of Articles in 2013
To request any journal reprints, please contact us.- Accounting for receptor flexibility, and enhanced sampling methods in computer aided drug design
- Molecular Recognition and Ligand Association
- Accelerated Molecular Dynamics: An efficient enhanced sampling method for biomolecular simulations
- On the Role of Dewetting Transitions in Host-Guest Binding Free Energy Calculations
- Structural insight into the separate roles of IP4 and DAD in activation of histone deacetylase 3
- Antibacterial drug leads targeting isoprenoid biosynthesis
- w-REXAMD: A Hamiltonian replica exchange approach to improve free energy calculations for systems with kinetically-trapped conformations
- Solvent fluctuations in hydrophobic cavity-ligand binding kinetics
- Fluoroketone Inhibition of Ca++-Independent Phospholipase A2 through Binding Pocket Association Defined by Hydrogen/Deuterium Exchange and Molecular Dynamics.
- Mapping the Population of Protein Conformational Energy Sub-states from NMR Dipolar Couplings
- Evaluation of Hydration Free Energy by the Level-Set Variational Implicit-Solvent Model with the Coulomb-Field Approximation
- Structure-based Network Analysis of an Evolved G-Protein Coupled Receptor Homodimer Interface
- Farnesyl diphosphate synthase inhibitors from in silico screening
- Effect of histidine protonation and rotameric states on virtual screening of M. tuberculosis RmlC
- AutoGrow 3.0: An Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor Design
- Correlated Motions and Residual Frustration in Thrombin
- Discovery of Staphylococcus aureus Sortase A Inhibitors Using Virtual Screening and the Relaxed Complex Scheme.
- Assessing the Two-body Diffusion Tensor Calculated by Bead Models
- Population Based Reweighting of Scaled Molecular Dynamics
- Phase-Field Approach to Implicit Solvation of Biomolecules with Coulomb-Field Approximation.
- Comparing Neural-Network Scoring Functions and the State of the Art: Applications to Common Library Screening.
- Activation and dynamic network of the M2 muscarinic receptor.
- Iterative Molecular Dynamics – Rosetta Protein Structure Refinement Protocol to Improve Model Quality.
- Insertion of the Ca2+-Independent Phospholipase A2 into a Phospholipid Bilayer via Coarse-Grained and Atomistic Molecular Dynamics Simulations.
- Influence of neighboring reactive particles on diffusion-limited reactions.
- Multi-core CPU or GPU-accelerated Multiscale Modeling for Biomolecular Complexes.
- Inactivating mutation in Histone deacetylase 3 stabilizes its active conformation.
- Simulations of Biased Agonists in the β2 Adrenergic Receptor with Accelerated Molecular Dynamics.
- Variational Implicit-Solvent Modeling of Host-Guest Binding: A Case Study on Cucurbit[7]uril.
- Substrate-dependent dynamics of UDP-galactopyranose mutase: implications for drug design.
- Improving the Efficiency of Free Energy Calculations in the Amber Molecular Dynamics Package.
- Mapping of Allosteric Druggable Sites in Activation-Associated Conformers of the M2 Muscarinic Receptor.
- Molecular and Subcellular-Scale Modeling of Nucleotide Diffusion in the Cardiac Myofilament Lattice
- Structure, mechanism, and dynamics of UDP-galactopyranose mutase.
- Accelerated Molecular Dynamics Simulations with the AMOEBA Polarizable Force Field on graphics processing units.
- Utilizing a dynamical description of IspH to aid in the development of novel antimicrobial drugs.
Accounting for receptor flexibility, and enhanced sampling methods in computer aided drug designChem. Biol. Drug Disc., Vol. 81, Issue 1, pp. 41−49 (2013) [PubMed 23253130]
Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup.
Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup.
Molecular Recognition and Ligand AssociationAnn. Revs. Phys. Chem., Vol. 64, pp. 151−176 (2013) [PubMed 23473376]
We review recent developments in our understanding of molecular recognition and ligand association, focusing on two major viewpoints: First, studies that highlight new physical insight into the molecular recognition process and the driving forces determining thermodynamic signatures of binding. Second, recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational ensembles composed of multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of ensemble-averaged experimental observables. Physics-based approaches are increasingly expanding their power in pharmacology applications.
We review recent developments in our understanding of molecular recognition and ligand association, focusing on two major viewpoints: First, studies that highlight new physical insight into the molecular recognition process and the driving forces determining thermodynamic signatures of binding. Second, recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational ensembles composed of multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of ensemble-averaged experimental observables. Physics-based approaches are increasingly expanding their power in pharmacology applications.
Accelerated Molecular Dynamics: An efficient enhanced sampling method for biomolecular simulationsRamachandran Symposium Book (2013)
On the Role of Dewetting Transitions in Host-Guest Binding Free Energy CalculationsJ. Chem. Theory Comput.,Vol. 9, Issue 1, pp. 46-53 (2013) [PubMed 23316123]
We use thermodynamic integration (TI) and explicit solvent molecular dynamics (MD) simulation to estimate the absolute free energy of host-guest binding. In the unbound state, water molecules visit all of the internally accessible volume of the host, which is fully hydrated on all sides. Upon binding of an apolar guest, the toroidal host cavity is fully dehydrated; thus, during the intermediate λ stages along the integration, the hydration of the host fluctuates between hydrated and dehydrated states. Estimating free energies by TI can be especially challenging when there is a considerable difference in hydration between the two states of interest. We investigate these aspects using the popular TIP3P and TIP4P water models. TI free energy estimates through MD largely depend on water-related interactions, and water dynamics significantly affect the convergence of binding free energy calculations. Our results indicate that wetting/dewetting transitions play a major role in slowing the convergence of free energy estimation. We employ two alternative approaches-one analytical and the other empirically based on actual MD sampling-to correct for the standard state free energy. This correction is sizable (up to 4 kcal/mol), and the two approaches provide corrections that differ by about 1 kcal/mol. For the system considered here, the TIP4P water model combined with an analytical correction for the standard state free energy provides higher overall accuracy. This observation might be transferable to other systems in which water-related contributions dominate the binding process.
We use thermodynamic integration (TI) and explicit solvent molecular dynamics (MD) simulation to estimate the absolute free energy of host-guest binding. In the unbound state, water molecules visit all of the internally accessible volume of the host, which is fully hydrated on all sides. Upon binding of an apolar guest, the toroidal host cavity is fully dehydrated; thus, during the intermediate λ stages along the integration, the hydration of the host fluctuates between hydrated and dehydrated states. Estimating free energies by TI can be especially challenging when there is a considerable difference in hydration between the two states of interest. We investigate these aspects using the popular TIP3P and TIP4P water models. TI free energy estimates through MD largely depend on water-related interactions, and water dynamics significantly affect the convergence of binding free energy calculations. Our results indicate that wetting/dewetting transitions play a major role in slowing the convergence of free energy estimation. We employ two alternative approaches-one analytical and the other empirically based on actual MD sampling-to correct for the standard state free energy. This correction is sizable (up to 4 kcal/mol), and the two approaches provide corrections that differ by about 1 kcal/mol. For the system considered here, the TIP4P water model combined with an analytical correction for the standard state free energy provides higher overall accuracy. This observation might be transferable to other systems in which water-related contributions dominate the binding process.
Structural insight into the separate roles of IP4 and DAD in activation of histone deacetylase 3Protein Sci., Vol. 22, Issue 1, pp. 83-92 (2013) [PubMed 23139175]
Histone deacetylases (HDACs) repress transcription by deacetylating acetyllysines on specific histone tails. HDAC3 is implicated in neurodegenerative diseases, certain leukemias, and even in disrupting HIV-1 latency. A recent crystal structure of HDAC3 in complex with the deacetylase-activating domain (DAD) of its corepressor complex revealed an inositol tetraphosphate (IP4) molecule at the protein-protein interface. IP4 was shown to play an important, yet mechanistically ambiguous, role in the activity of HDAC3. The goal of this article is to explore the conformational ensemble of HDAC3 in its inactive apo state and in the presence of each or both of DAD and IP4. Using triplicate, 100 ns molecular dynamic simulations, we study the apo, ternary, and intermediate DAD-bound or IP4-bound HDAC3 states. We find that a population-shift effect is induced by the presence of each corepressor, and is most notable in the presence of both. Our results offer new insights into the change in dynamics necessary for the activation of HDAC3 and highlight the roles of IP4 and DAD in this process.
Histone deacetylases (HDACs) repress transcription by deacetylating acetyllysines on specific histone tails. HDAC3 is implicated in neurodegenerative diseases, certain leukemias, and even in disrupting HIV-1 latency. A recent crystal structure of HDAC3 in complex with the deacetylase-activating domain (DAD) of its corepressor complex revealed an inositol tetraphosphate (IP4) molecule at the protein-protein interface. IP4 was shown to play an important, yet mechanistically ambiguous, role in the activity of HDAC3. The goal of this article is to explore the conformational ensemble of HDAC3 in its inactive apo state and in the presence of each or both of DAD and IP4. Using triplicate, 100 ns molecular dynamic simulations, we study the apo, ternary, and intermediate DAD-bound or IP4-bound HDAC3 states. We find that a population-shift effect is induced by the presence of each corepressor, and is most notable in the presence of both. Our results offer new insights into the change in dynamics necessary for the activation of HDAC3 and highlight the roles of IP4 and DAD in this process.
Antibacterial drug leads targeting isoprenoid biosynthesisProc. Natl. Acad. Sci. USA, Vol. 110, Issue 1, pp. 123−128 (2013) [PubMed 23248302]
With the rise in resistance to antibiotics such as methicillin, there is a need for new drugs. We report here the discovery and X-ray crystallographic structures of 10 chemically diverse compounds (benzoic, diketo, and phosphonic acids, as well as a bisamidine and a bisamine) that inhibit bacterial undecaprenyl diphosphate synthase, an essential enzyme involved in cell wall biosynthesis. The inhibitors bind to one or more of the four undecaprenyl diphosphate synthase inhibitor binding sites identified previously, with the most active leads binding to site 4, outside the catalytic center. The most potent leads are active against Staphylococcus aureus [minimal inhibitory concentration (MIC)(90) ∼0.25 µg/mL], and one potently synergizes with methicillin (fractional inhibitory concentration index = 0.25) and is protective in a mouse infection model. These results provide numerous leads for antibacterial development and open up the possibility of restoring sensitivity to drugs such as methicillin, using combination therapies.
With the rise in resistance to antibiotics such as methicillin, there is a need for new drugs. We report here the discovery and X-ray crystallographic structures of 10 chemically diverse compounds (benzoic, diketo, and phosphonic acids, as well as a bisamidine and a bisamine) that inhibit bacterial undecaprenyl diphosphate synthase, an essential enzyme involved in cell wall biosynthesis. The inhibitors bind to one or more of the four undecaprenyl diphosphate synthase inhibitor binding sites identified previously, with the most active leads binding to site 4, outside the catalytic center. The most potent leads are active against Staphylococcus aureus [minimal inhibitory concentration (MIC)(90) ∼0.25 µg/mL], and one potently synergizes with methicillin (fractional inhibitory concentration index = 0.25) and is protective in a mouse infection model. These results provide numerous leads for antibacterial development and open up the possibility of restoring sensitivity to drugs such as methicillin, using combination therapies.
w-REXAMD: A Hamiltonian replica exchange approach to improve free energy calculations for systems with kinetically-trapped conformationsJ Chem Theory Comput., Vol. 9, Issue 1, pp. 18−23 (2013) [PubMed 23316122]
Free energy governs the equilibrium extent of many biological processes. High barriers separating free energy minima often limit the sampling in molecular dynamics (MD) simulations, leading to inaccurate free energies. Here, we demonstrate enhanced sampling and improved free energy calculations, relative to conventional MD, using windowed accelerated MD within a Hamiltonian replica exchange framework (w-REXAMD). We show that for a case in which multiple conformations are separated by large free energy barriers, w-REXAMD is a useful enhanced sampling technique, without any necessary reweighting.
Free energy governs the equilibrium extent of many biological processes. High barriers separating free energy minima often limit the sampling in molecular dynamics (MD) simulations, leading to inaccurate free energies. Here, we demonstrate enhanced sampling and improved free energy calculations, relative to conventional MD, using windowed accelerated MD within a Hamiltonian replica exchange framework (w-REXAMD). We show that for a case in which multiple conformations are separated by large free energy barriers, w-REXAMD is a useful enhanced sampling technique, without any necessary reweighting.
Solvent fluctuations in hydrophobic cavity-ligand binding kineticsProc. Natl. Acad. Sci. USA, Vol. 110, Issue 4, pp. 1197−1202 (2013) [PubMed 23297241]
Water plays a crucial part in virtually all protein-ligand binding processes in and out of equilibrium. Here, we investigate the role of water in the binding kinetics of a ligand to a prototypical hydrophobic pocket by explicit-water molecular dynamics (MD) simulations and implicit diffusional approaches. The concave pocket in the unbound state exhibits wet/dry hydration oscillations whose magnitude and time scale are significantly amplified by the approaching ligand. In turn, the ligand's stochastic motion intimately couples to the slow hydration fluctuations, leading to a sixfold-enhanced friction in the vicinity of the pocket entrance. The increased friction considerably decelerates association in the otherwise barrierless system, indicating the importance of molecular-scale hydrodynamic effects in cavity-ligand binding arising due to capillary fluctuations. We derive and analyze the diffusivity profile and show that the mean first passage time distribution from the MD simulation can be accurately reproduced by a standard Brownian dynamics simulation if the appropriate position-dependent friction profile is included. However, long-time decays in the water-ligand (random) force autocorrelation demonstrate violation of the Markovian assumption, challenging standard diffusive approaches for rate prediction. Remarkably, the static friction profile derived from the force correlations strongly resembles the profile derived on the Markovian assumption apart from a simple shift in space, which can be rationalized by a time-space retardation in the ligand's downhill dynamics toward the pocket. The observed spatiotemporal hydrodynamic coupling may be of biological importance providing the time needed for conformational receptor-ligand adjustments, typical of the induced-fit paradigm.
Water plays a crucial part in virtually all protein-ligand binding processes in and out of equilibrium. Here, we investigate the role of water in the binding kinetics of a ligand to a prototypical hydrophobic pocket by explicit-water molecular dynamics (MD) simulations and implicit diffusional approaches. The concave pocket in the unbound state exhibits wet/dry hydration oscillations whose magnitude and time scale are significantly amplified by the approaching ligand. In turn, the ligand's stochastic motion intimately couples to the slow hydration fluctuations, leading to a sixfold-enhanced friction in the vicinity of the pocket entrance. The increased friction considerably decelerates association in the otherwise barrierless system, indicating the importance of molecular-scale hydrodynamic effects in cavity-ligand binding arising due to capillary fluctuations. We derive and analyze the diffusivity profile and show that the mean first passage time distribution from the MD simulation can be accurately reproduced by a standard Brownian dynamics simulation if the appropriate position-dependent friction profile is included. However, long-time decays in the water-ligand (random) force autocorrelation demonstrate violation of the Markovian assumption, challenging standard diffusive approaches for rate prediction. Remarkably, the static friction profile derived from the force correlations strongly resembles the profile derived on the Markovian assumption apart from a simple shift in space, which can be rationalized by a time-space retardation in the ligand's downhill dynamics toward the pocket. The observed spatiotemporal hydrodynamic coupling may be of biological importance providing the time needed for conformational receptor-ligand adjustments, typical of the induced-fit paradigm.
Fluoroketone Inhibition of Ca++-Independent Phospholipase A2 through Binding Pocket Association Defined by Hydrogen/Deuterium Exchange and Molecular Dynamics.J. Amer. Chem. Soc., Vol. 135, Issue 4, pp. 1330−1337 (2013) [PubMed 23256506]
The mechanism of inhibition of Group VIA Ca2+-independent phospholipase A2 (iPLA2) by fluoroketone (FK) ligands is examined using a combination of deuterium exchange mass spectrometry (DXMS) and molecular dynamics (MD). Models for iPLA2 were built by homology with the known structure of patatin and equilibrated by extensive MD simulations. Empty pockets were identified during the simulations and studied for their ability to accommodate FK inhibitors. Ligand docking techniques showed that the potent inhibitor 1,1,1,3-tetrafluoro-7-phenylheptan-2-one (PHFK) forms favorable interactions inside an active site pocket where it blocks the entrance of phospholipid substrates. The polar fluoroketone head group is stabilized by hydrogen bonds with residues Gly486, Gly487, and Ser519. The nonpolar aliphatic chain and aromatic group are stabilized by hydrophobic contacts with Met544, Val548, Phe549, Leu560, and Ala640. The binding mode is supported by DXMS experiments showing an important decrease of deuteration in the contact regions in the presence of the inhibitor. The discovery of the precise binding mode of FK ligands to the iPLA2sub> should greatly improve our ability to design new inhibitors with higher potency and selectivity.
The mechanism of inhibition of Group VIA Ca2+-independent phospholipase A2 (iPLA2) by fluoroketone (FK) ligands is examined using a combination of deuterium exchange mass spectrometry (DXMS) and molecular dynamics (MD). Models for iPLA2 were built by homology with the known structure of patatin and equilibrated by extensive MD simulations. Empty pockets were identified during the simulations and studied for their ability to accommodate FK inhibitors. Ligand docking techniques showed that the potent inhibitor 1,1,1,3-tetrafluoro-7-phenylheptan-2-one (PHFK) forms favorable interactions inside an active site pocket where it blocks the entrance of phospholipid substrates. The polar fluoroketone head group is stabilized by hydrogen bonds with residues Gly486, Gly487, and Ser519. The nonpolar aliphatic chain and aromatic group are stabilized by hydrophobic contacts with Met544, Val548, Phe549, Leu560, and Ala640. The binding mode is supported by DXMS experiments showing an important decrease of deuteration in the contact regions in the presence of the inhibitor. The discovery of the precise binding mode of FK ligands to the iPLA2sub> should greatly improve our ability to design new inhibitors with higher potency and selectivity.
Mapping the Population of Protein Conformational Energy Sub-states from NMR Dipolar CouplingsAngew. Chem. Int. Ed., Vol. 52, Issue 11, pp. 3181−3185 (2013) [PubMed 23371543]
Evaluation of Hydration Free Energy by the Level-Set Variational Implicit-Solvent Model with the Coulomb-Field ApproximationJ. Chem. Theory Comput., Vol. 9, Issue 3, pp. 1778−1787 (2013) [PubMed 23505345]
In this article, we systematically apply a novel implicit-solvent model, the variational implicit-solvent model (VISM) together with the Coulomb-Field Approximation (CFA), to calculate the hydration free energy of a large set of small organic molecules. Because these molecules have been studied in detail by molecular dynamics simulations and other implicit-solvent models, they provide a good benchmark for evaluating the performance of VISM-CFA. With all-atom Amber force field parameters, VISM-CFA is able to reproduce well not only the experimental and MD simulated total hydration free energy but also the polar and nonpolar contributions individually. The correlation between VISM-CFA and experiments is R 2 = 0.763 for the total hydration free energy, with a root-mean-square deviation (RMSD) of 1.83 kcal/mol, and the correlation to results from TIP3P explicit water MD simulations is R 2 = 0.839 with a RMSD = 1.36 kcal/mol. In addition, we demonstrate that VISM captures dewetting phenomena in the p53/MDM2 complex and hydrophobic characteristics in the system. This work demonstrates that the level-set VISM-CFA can be used to study the energetic behavior of realistic molecular systems with complicated geometries in solvation, protein-ligand binding, protein-protein association, and protein folding processes.
In this article, we systematically apply a novel implicit-solvent model, the variational implicit-solvent model (VISM) together with the Coulomb-Field Approximation (CFA), to calculate the hydration free energy of a large set of small organic molecules. Because these molecules have been studied in detail by molecular dynamics simulations and other implicit-solvent models, they provide a good benchmark for evaluating the performance of VISM-CFA. With all-atom Amber force field parameters, VISM-CFA is able to reproduce well not only the experimental and MD simulated total hydration free energy but also the polar and nonpolar contributions individually. The correlation between VISM-CFA and experiments is R 2 = 0.763 for the total hydration free energy, with a root-mean-square deviation (RMSD) of 1.83 kcal/mol, and the correlation to results from TIP3P explicit water MD simulations is R 2 = 0.839 with a RMSD = 1.36 kcal/mol. In addition, we demonstrate that VISM captures dewetting phenomena in the p53/MDM2 complex and hydrophobic characteristics in the system. This work demonstrates that the level-set VISM-CFA can be used to study the energetic behavior of realistic molecular systems with complicated geometries in solvation, protein-ligand binding, protein-protein association, and protein folding processes.
Structure-based Network Analysis of an Evolved G-Protein Coupled Receptor Homodimer InterfaceProtein Science, Volume 22, Issue 6, 745-754 (2013) [PubMed 23553730]
Crystallographic structures and experimental assays of human CXC chemokine receptor type 4 (CXCR4) provide strong evidence for the capacity to homodimerize, potentially as a means of allosteric regulation. Even so, how this homodimer forms and its biological significance has yet to be fully characterized. By applying principles from network analysis, sequence-based approaches such as statistical coupling analysis to determine coevolutionary residues, can be used in conjunction with molecular dynamics simulations to identify residues relevant to dimerization. Here, the predominant coevolution sector lies along the observed dimer interface, suggesting functional relevance. Furthermore, coevolution scoring provides a basis for determining significant nodes, termed hubs, in the network formed by residues found along the interface of the homodimer. These node residues coincide with hotspots indicating potential druggability. Drug design efforts targeting such key residues could potentially result in modulation of binding and therapeutic benefits for disease states, such as lung cancers, lymphomas and latent HIV-1 infection. Furthermore, this method may be applied to any protein-protein interaction.
Crystallographic structures and experimental assays of human CXC chemokine receptor type 4 (CXCR4) provide strong evidence for the capacity to homodimerize, potentially as a means of allosteric regulation. Even so, how this homodimer forms and its biological significance has yet to be fully characterized. By applying principles from network analysis, sequence-based approaches such as statistical coupling analysis to determine coevolutionary residues, can be used in conjunction with molecular dynamics simulations to identify residues relevant to dimerization. Here, the predominant coevolution sector lies along the observed dimer interface, suggesting functional relevance. Furthermore, coevolution scoring provides a basis for determining significant nodes, termed hubs, in the network formed by residues found along the interface of the homodimer. These node residues coincide with hotspots indicating potential druggability. Drug design efforts targeting such key residues could potentially result in modulation of binding and therapeutic benefits for disease states, such as lung cancers, lymphomas and latent HIV-1 infection. Furthermore, this method may be applied to any protein-protein interaction.
Farnesyl diphosphate synthase inhibitors from in silico screeningChem. Biol. Drug Des. 81(6): 742-748 (2013) [PubMed PMC3671582]
The relaxed complex scheme is an in silico drug screening method that accounts for receptor flexibility by using molecular dynamics simulations. Here, we used this approach combined with similarity searches and experimental inhibition assays to identify several low micro-molar, non-bisphosphonate inhibitors, bisamidines, of farnesyl diphosphate synthase (FPPS), an enzyme targeted by some anti-cancer and anti-microbial agents and for the treatment of bone resorption diseases. This novel class of FPPS inhibitors have more drug-like properties than existing bisphosphonate inhibitors, making them interesting pharmaceutical leads.
The relaxed complex scheme is an in silico drug screening method that accounts for receptor flexibility by using molecular dynamics simulations. Here, we used this approach combined with similarity searches and experimental inhibition assays to identify several low micro-molar, non-bisphosphonate inhibitors, bisamidines, of farnesyl diphosphate synthase (FPPS), an enzyme targeted by some anti-cancer and anti-microbial agents and for the treatment of bone resorption diseases. This novel class of FPPS inhibitors have more drug-like properties than existing bisphosphonate inhibitors, making them interesting pharmaceutical leads.
Effect of histidine protonation and rotameric states on virtual screening of M. tuberculosis RmlCJ. Comp. Aid. Mol. Des., Vol. 27, Issue 3, pp. 235−246 (2013) [PubMed 23579613]
While it is well established that protonation and tautomeric states of ligands can significantly affect the results of virtual screening, such effects of ionizable residues of protein receptors are less well understood. In this study, we focus on histidine protonation and rotameric states and their impact on virtual screening of Mycobacterium tuberculosis enzyme RmlC. Depending on the net charge and the location of proton(s), a histidine can adopt three states: HIP (+1 charged, both δ- and ε-nitrogens protonated), HID (neutral, δ-nitrogen protonated), and HIE (neutral, ε-nitrogen protonated). Due to common ambiguities in X-ray crystal structures, a histidine may also be resolved as three additional states with its imidazole ring flipped. Here, we systematically investigate the predictive power of 36 receptor models with different protonation and rotameric states of two histidines in the RmlC active site by using results from a previous high-throughput screening. By measuring enrichment factors and area under the receiver operating characteristic curves, we show that virtual screening results vary depending on hydrogen bonding networks provided by the histidines, even in the cases where the ligand does not obviously interact with the side chain. Our results also suggest that, even with the help of widely used pKa prediction software, assigning histidine protonation and rotameric states for virtual screening can still be challenging and requires further examination and systematic characterization of the receptor-ligand complex.
While it is well established that protonation and tautomeric states of ligands can significantly affect the results of virtual screening, such effects of ionizable residues of protein receptors are less well understood. In this study, we focus on histidine protonation and rotameric states and their impact on virtual screening of Mycobacterium tuberculosis enzyme RmlC. Depending on the net charge and the location of proton(s), a histidine can adopt three states: HIP (+1 charged, both δ- and ε-nitrogens protonated), HID (neutral, δ-nitrogen protonated), and HIE (neutral, ε-nitrogen protonated). Due to common ambiguities in X-ray crystal structures, a histidine may also be resolved as three additional states with its imidazole ring flipped. Here, we systematically investigate the predictive power of 36 receptor models with different protonation and rotameric states of two histidines in the RmlC active site by using results from a previous high-throughput screening. By measuring enrichment factors and area under the receiver operating characteristic curves, we show that virtual screening results vary depending on hydrogen bonding networks provided by the histidines, even in the cases where the ligand does not obviously interact with the side chain. Our results also suggest that, even with the help of widely used pKa prediction software, assigning histidine protonation and rotameric states for virtual screening can still be challenging and requires further examination and systematic characterization of the receptor-ligand complex.
AutoGrow 3.0: An Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor DesignJournal of Molecular Graphics and Model., Volume 44, 104-112 (2013) [PubMed PMC3842281]
We here present an improved version of AutoGrow (version 3.0), an evolutionary algorithm that works in conjunction with existing open-source software to automatically optimize candidate ligands for predicted binding affinity and other druglike properties. Though no substitute for the medicinal chemist, AutoGrow 3.0, unlike its predecessors, attempts to introduce some chemical intuition into the automated optimization process. AutoGrow 3.0 uses the rules of click chemistry to guide optimization, greatly enhancing synthesizability. Additionally, the program discards any growing ligand whose physical and chemical properties are not druglike. By carefully crafting chemically feasible druglike molecules, we hope that AutoGrow 3.0 will help supplement the chemist's efforts.
To demonstrate the utility of the program, we used AutoGrow 3.0 to generate predicted inhibitors of three important drug targets: T. brucei RNA editing ligase 1, peroxisome proliferator-activated receptor γ, and dihydrofolate reductase. In all cases, AutoGrow generated druglike molecules with high predicted binding affinities.
AutoGrow 3.0 is available free of charge (autogrow.ucsd.edu) under the terms of the GNU General Public License and has been tested on Linux and Mac OS X
We here present an improved version of AutoGrow (version 3.0), an evolutionary algorithm that works in conjunction with existing open-source software to automatically optimize candidate ligands for predicted binding affinity and other druglike properties. Though no substitute for the medicinal chemist, AutoGrow 3.0, unlike its predecessors, attempts to introduce some chemical intuition into the automated optimization process. AutoGrow 3.0 uses the rules of click chemistry to guide optimization, greatly enhancing synthesizability. Additionally, the program discards any growing ligand whose physical and chemical properties are not druglike. By carefully crafting chemically feasible druglike molecules, we hope that AutoGrow 3.0 will help supplement the chemist's efforts.
To demonstrate the utility of the program, we used AutoGrow 3.0 to generate predicted inhibitors of three important drug targets: T. brucei RNA editing ligase 1, peroxisome proliferator-activated receptor γ, and dihydrofolate reductase. In all cases, AutoGrow generated druglike molecules with high predicted binding affinities.
AutoGrow 3.0 is available free of charge (autogrow.ucsd.edu) under the terms of the GNU General Public License and has been tested on Linux and Mac OS X
Correlated Motions and Residual Frustration in ThrombinJ Phys Chem B. (Peter Wolynes Festschrift) 117(42):12857-63 (2013) [PubMed 23621631]
Thrombin is the central protease in the cascade of blood coagulation proteases. The structure of thrombin consists of a double β-barrel core surrounded by connecting loops and helices. Compared to chymotrypsin, thrombin has more extended loops that are thought to have arisen from insertions in the serine protease that evolved to impart greater specificity. Previous experiments showed thermodynamic coupling between ligand binding at the active site and distal exosites. We present a combined approach of molecular dynamics (MD), accelerated molecular dynamics (AMD), and analysis of the residual local frustration of apo-thrombin and active site-bound (PPACK-thrombin). Community analysis of the MD ensembles identified changes upon active site occupation in groups of residues linked through correlated motions and physical contacts. AMD simulations, calibrated on measured residual dipolar couplings, reveal that upon active site ligation correlated loop motions are quenched, but new ones connecting the active site with distal sites where allosteric regulators bind, emerge. Residual local frustration analysis reveals a striking correlation between frustrated contacts and regions undergoing slow timescale dynamics. The results elucidate a motional network that probably evolved through retention of frustrated contacts to provide facile conversion between ensembles of states.
Thrombin is the central protease in the cascade of blood coagulation proteases. The structure of thrombin consists of a double β-barrel core surrounded by connecting loops and helices. Compared to chymotrypsin, thrombin has more extended loops that are thought to have arisen from insertions in the serine protease that evolved to impart greater specificity. Previous experiments showed thermodynamic coupling between ligand binding at the active site and distal exosites. We present a combined approach of molecular dynamics (MD), accelerated molecular dynamics (AMD), and analysis of the residual local frustration of apo-thrombin and active site-bound (PPACK-thrombin). Community analysis of the MD ensembles identified changes upon active site occupation in groups of residues linked through correlated motions and physical contacts. AMD simulations, calibrated on measured residual dipolar couplings, reveal that upon active site ligation correlated loop motions are quenched, but new ones connecting the active site with distal sites where allosteric regulators bind, emerge. Residual local frustration analysis reveals a striking correlation between frustrated contacts and regions undergoing slow timescale dynamics. The results elucidate a motional network that probably evolved through retention of frustrated contacts to provide facile conversion between ensembles of states.
Discovery of Staphylococcus aureus Sortase A Inhibitors Using Virtual Screening and the Relaxed Complex Scheme.Chem. Biol. Drug Disc. 82, 418-428 (2013) [PubMed 23701677]
Staphylococcus aureus is the leading cause of hospital-acquired infections in the United States. The emergence of multidrug-resistant strains of S. aureus has created an urgent need for new antibiotics. Staphylococcus aureus uses the sortase A enzyme to display surface virulence factors suggesting that compounds that inhibit its activity will function as potent anti-infective agents. Here, we report the identification of several inhibitors of sortase A using virtual screening methods that employ the relaxed complex scheme, an advanced computer-docking methodology that accounts for protein receptor flexibility. Experimental testing validates that several compounds identified in the screen inhibit the activity of sortase A. A lead compound based on the 2-phenyl-2,3-dihydro-1H-perimidine scaffold is particularly promising, and its binding mechanism was further investigated using molecular dynamics simulations and conducting preliminary structure–activity relationship studies.
Staphylococcus aureus is the leading cause of hospital-acquired infections in the United States. The emergence of multidrug-resistant strains of S. aureus has created an urgent need for new antibiotics. Staphylococcus aureus uses the sortase A enzyme to display surface virulence factors suggesting that compounds that inhibit its activity will function as potent anti-infective agents. Here, we report the identification of several inhibitors of sortase A using virtual screening methods that employ the relaxed complex scheme, an advanced computer-docking methodology that accounts for protein receptor flexibility. Experimental testing validates that several compounds identified in the screen inhibit the activity of sortase A. A lead compound based on the 2-phenyl-2,3-dihydro-1H-perimidine scaffold is particularly promising, and its binding mechanism was further investigated using molecular dynamics simulations and conducting preliminary structure–activity relationship studies.
Assessing the Two-body Diffusion Tensor Calculated by Bead ModelsJ. Chem. Phys. 138(20), article 204117 (2013) [PubMed PMC3683057]
The diffusion tensor of complex macromolecules in Stokes flow is often approximated by the bead models. The bead models are known to reproduce the experimental diffusion coefficients of a single macromolecule, but the accuracy of their calculation of the whole multi-body diffusion tensor, which is important for Brownian dynamics simulations, has not been closely investigated. As a first step, we assess the accuracy of the bead model calculated diffusion tensor of two spheres. Our results show that the bead models produce very accurate diffusion tensors for two spheres where a reasonable number of beads are used and there is no bead overlap.
The diffusion tensor of complex macromolecules in Stokes flow is often approximated by the bead models. The bead models are known to reproduce the experimental diffusion coefficients of a single macromolecule, but the accuracy of their calculation of the whole multi-body diffusion tensor, which is important for Brownian dynamics simulations, has not been closely investigated. As a first step, we assess the accuracy of the bead model calculated diffusion tensor of two spheres. Our results show that the bead models produce very accurate diffusion tensors for two spheres where a reasonable number of beads are used and there is no bead overlap.
Population Based Reweighting of Scaled Molecular DynamicsJ. Phys. Chem. B, 117(42): 12759-12768 (2013) [PubMed PMC3808002]
Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting.
Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting.
Phase-Field Approach to Implicit Solvation of Biomolecules with Coulomb-Field Approximation.J. Chem. Phys. 139, article 024111 (2013). [PubMed PMC3724799]
A phase-field variational implicit-solvent approach is developed for the solvation of charged molecules. The starting point of such an approach is the representation of a solute-solvent interface by a phase field that takes one value in the solute region and another in the solvent region, with a smooth transition from one to the other on a small transition layer. The minimization of an effective free-energy functional of all possible phase fields determines the equilibrium conformations and free energies of an underlying molecular system. All the surface energy, the solute-solvent van der Waals interaction, and the electrostatic interaction are coupled together self-consistently through a phase field. The surface energy results from the minimization of a double-well potential and the gradient of a field. The electrostatic interaction is described by the Coulomb-field approximation. Accurate and efficient methods are designed and implemented to numerically relax an underlying charged molecular system. Applications to single ions, a two-plate system, and a two-domain protein reveal that the new theory and methods can capture capillary evaporation in hydrophobic confinement and corresponding multiple equilibrium states as found in molecular dynamics simulations. Comparisons of the phase-field and the original sharp-interface variational approaches are discussed.
A phase-field variational implicit-solvent approach is developed for the solvation of charged molecules. The starting point of such an approach is the representation of a solute-solvent interface by a phase field that takes one value in the solute region and another in the solvent region, with a smooth transition from one to the other on a small transition layer. The minimization of an effective free-energy functional of all possible phase fields determines the equilibrium conformations and free energies of an underlying molecular system. All the surface energy, the solute-solvent van der Waals interaction, and the electrostatic interaction are coupled together self-consistently through a phase field. The surface energy results from the minimization of a double-well potential and the gradient of a field. The electrostatic interaction is described by the Coulomb-field approximation. Accurate and efficient methods are designed and implemented to numerically relax an underlying charged molecular system. Applications to single ions, a two-plate system, and a two-domain protein reveal that the new theory and methods can capture capillary evaporation in hydrophobic confinement and corresponding multiple equilibrium states as found in molecular dynamics simulations. Comparisons of the phase-field and the original sharp-interface variational approaches are discussed.
Comparing Neural-Network Scoring Functions and the State of the Art: Applications to Common Library Screening.J. Chem. Info. Model. 53, 1726–1735 (2013). [PubMed PMC3735370]
We compare established docking programs, AutoDock Vina and Schrödinger’s Glide, to the recently published NNScore scoring functions. As expected, the best protocol to use in a virtual-screening project is highly dependent on the target receptor being studied. However, the mean screening performance obtained when candidate ligands are docked with Vina and rescored with NNScore 1.0 is not statistically different than the mean performance obtained when docking and scoring with Glide. We further demonstrate that the Vina and NNScore docking scores both correlate with chemical properties like small-molecule size and polarizability. Compensating for these potential biases leads to improvements in virtual screen performance. Composite NNScore-based scoring functions suited to a specific receptor further improve performance. We are hopeful that the current study will prove useful for those interested in computer-aided drug design.
We compare established docking programs, AutoDock Vina and Schrödinger’s Glide, to the recently published NNScore scoring functions. As expected, the best protocol to use in a virtual-screening project is highly dependent on the target receptor being studied. However, the mean screening performance obtained when candidate ligands are docked with Vina and rescored with NNScore 1.0 is not statistically different than the mean performance obtained when docking and scoring with Glide. We further demonstrate that the Vina and NNScore docking scores both correlate with chemical properties like small-molecule size and polarizability. Compensating for these potential biases leads to improvements in virtual screen performance. Composite NNScore-based scoring functions suited to a specific receptor further improve performance. We are hopeful that the current study will prove useful for those interested in computer-aided drug design.
Activation and dynamic network of the M2 muscarinic receptor.Proc. Natl. Acad. Sci. USA 110, 10982–10987 (2013). [PubMed PMC3703993]
G-protein-coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases. Although significant advances have been made in structural studies of GPCRs, details of their activation mechanism remain unclear. The X-ray crystal structure of the M2 muscarinic receptor, a key GPCR that regulates human heart rate and contractile forces of cardiomyocytes, was determined recently in an inactive antagonist-bound state. Here, activation of the M2 receptor is directly observed via accelerated molecular dynamics simulation, in contrast to previous microsecond-timescale conventional molecular dynamics simulations in which the receptor remained inactive. Receptor activation is characterized by formation of a Tyr206(5.58)-Tyr440(7.53) hydrogen bond and ∼6-Å outward tilting of the cytoplasmic end of transmembrane α-helix 6, preceded by relocation of Trp400(6.48) toward Phe195(5.47) and Val199(5.51) and flipping of Tyr430(7.43) away from the ligand-binding cavity. Network analysis reveals that communication in the intracellular domains is greatly weakened during activation of the receptor. Together with the finding that residue motions in the ligand-binding and G-protein-coupling sites of the apo receptor are correlated, this result highlights a dynamic network for allosteric regulation of the M2 receptor activation.
G-protein-coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases. Although significant advances have been made in structural studies of GPCRs, details of their activation mechanism remain unclear. The X-ray crystal structure of the M2 muscarinic receptor, a key GPCR that regulates human heart rate and contractile forces of cardiomyocytes, was determined recently in an inactive antagonist-bound state. Here, activation of the M2 receptor is directly observed via accelerated molecular dynamics simulation, in contrast to previous microsecond-timescale conventional molecular dynamics simulations in which the receptor remained inactive. Receptor activation is characterized by formation of a Tyr206(5.58)-Tyr440(7.53) hydrogen bond and ∼6-Å outward tilting of the cytoplasmic end of transmembrane α-helix 6, preceded by relocation of Trp400(6.48) toward Phe195(5.47) and Val199(5.51) and flipping of Tyr430(7.43) away from the ligand-binding cavity. Network analysis reveals that communication in the intracellular domains is greatly weakened during activation of the receptor. Together with the finding that residue motions in the ligand-binding and G-protein-coupling sites of the apo receptor are correlated, this result highlights a dynamic network for allosteric regulation of the M2 receptor activation.
Iterative Molecular Dynamics – Rosetta Protein Structure Refinement Protocol to Improve Model Quality.J. Chem. Theory Comp. 9, 3843−3847 (2013). [PubMed PMC3744128]
Rosetta is one of the prime tools for high resolution protein structure refinement. While its scoring function can distinguish native-like from non-native-like conformations in many cases, the method is limited by conformational sampling for larger proteins, that is, leaving a local energy minimum in which the search algorithm may get stuck. Here, we test the hypothesis that iteration of Rosetta with an orthogonal sampling and scoring strategy might facilitate exploration of conformational space. Specifically, we run short molecular dynamics (MD) simulations on models created by de novo folding of large proteins into cryoEM density maps to enable sampling of conformational space not directly accessible to Rosetta and thus provide an escape route from the conformational traps. We present a combined MD–Rosetta protein structure refinement protocol that can overcome some of these sampling limitations. Two of four benchmark proteins showed incremental improvement through all three rounds of the iterative refinement protocol. Molecular dynamics is most efficient in applying subtle but important rearrangements within secondary structure elements and is thus highly complementary to the Rosetta refinement, which focuses on side chains and loop regions.
Rosetta is one of the prime tools for high resolution protein structure refinement. While its scoring function can distinguish native-like from non-native-like conformations in many cases, the method is limited by conformational sampling for larger proteins, that is, leaving a local energy minimum in which the search algorithm may get stuck. Here, we test the hypothesis that iteration of Rosetta with an orthogonal sampling and scoring strategy might facilitate exploration of conformational space. Specifically, we run short molecular dynamics (MD) simulations on models created by de novo folding of large proteins into cryoEM density maps to enable sampling of conformational space not directly accessible to Rosetta and thus provide an escape route from the conformational traps. We present a combined MD–Rosetta protein structure refinement protocol that can overcome some of these sampling limitations. Two of four benchmark proteins showed incremental improvement through all three rounds of the iterative refinement protocol. Molecular dynamics is most efficient in applying subtle but important rearrangements within secondary structure elements and is thus highly complementary to the Rosetta refinement, which focuses on side chains and loop regions.
Insertion of the Ca2+-Independent Phospholipase A2 into a Phospholipid Bilayer via Coarse-Grained and Atomistic Molecular Dynamics Simulations.PLoS Comp. Biol. 9, article e1003156 (2013). [PubMed PMC3723492]
Group VI Ca2+-independent phospholipase A2 (iPLA2) is a water-soluble enzyme that is active when associated with phospholipid membranes. Despite its clear pharmaceutical relevance, no X-ray or NMR structural information is currently available for the iPLA2 or its membrane complex. In this paper, we combine homology modeling with coarse-grained (CG) and all-atom (AA) molecular dynamics (MD) simulations to build structural models of iPLA2 in association with a phospholipid bilayer. CG-MD simulations of the membrane insertion process were employed to provide a starting point for an atomistic description. Six AA-MD simulations were then conducted for 60 ns, starting from different initial CG structures, to refine the membrane complex. The resulting structures are shown to be consistent with each other and with deuterium exchange mass spectrometry (DXMS) experiments, suggesting that our approach is suitable for the modeling of iPLA2 at the membrane surface. The models show that an anchoring region (residues 710–724) forms an amphipathic helix that is stabilized by the membrane. In future studies, the proposed iPLA2 models should provide a structural basis for understanding the mechanisms of lipid extraction and drug-inhibition. In addition, the dual-resolution approach discussed here should provide the means for the future exploration of the impact of lipid diversity and sequence mutations on the activity of iPLA2 and related enzymes.
Group VI Ca2+-independent phospholipase A2 (iPLA2) is a water-soluble enzyme that is active when associated with phospholipid membranes. Despite its clear pharmaceutical relevance, no X-ray or NMR structural information is currently available for the iPLA2 or its membrane complex. In this paper, we combine homology modeling with coarse-grained (CG) and all-atom (AA) molecular dynamics (MD) simulations to build structural models of iPLA2 in association with a phospholipid bilayer. CG-MD simulations of the membrane insertion process were employed to provide a starting point for an atomistic description. Six AA-MD simulations were then conducted for 60 ns, starting from different initial CG structures, to refine the membrane complex. The resulting structures are shown to be consistent with each other and with deuterium exchange mass spectrometry (DXMS) experiments, suggesting that our approach is suitable for the modeling of iPLA2 at the membrane surface. The models show that an anchoring region (residues 710–724) forms an amphipathic helix that is stabilized by the membrane. In future studies, the proposed iPLA2 models should provide a structural basis for understanding the mechanisms of lipid extraction and drug-inhibition. In addition, the dual-resolution approach discussed here should provide the means for the future exploration of the impact of lipid diversity and sequence mutations on the activity of iPLA2 and related enzymes.
Influence of neighboring reactive particles on diffusion-limited reactions.J. Chem. Phys. 139, article number 044117 (2013). [PubMed PMC3745503]
Competition between reactive species is commonplace in typical chemical reactions. Specifically the primary reaction between a substrate and its target enzyme may be altered when interactions with secondary species in the system are substantial. We explore this competition phenomenon for diffusion-limited reactions in the presence of neighboring particles through numerical solution of the diffusion equation. As a general model for globular proteins and small molecules, we consider spherical representations of the reactants and neighboring particles; these neighbors vary in local density, size, distribution, and relative distance from the primary target reaction, as well as their surface reactivity. Modulations of these model variables permit inquiry into the influence of excluded volume and competition on the primary reaction due to the presence of neighboring particles. We find that the surface reactivity effect is long-ranged and a strong determinant of reaction kinetics, whereas the excluded volume effect is relatively short-ranged and less influential in comparison. As a consequence, the effect of the excluded volume is only modestly dependent on the neighbor distribution and is approximately additive; this additivity permits a linear approximation to the many-body effect on the reaction kinetics. In contrast, the surface reactivity effect is non-additive, and thus it may require higher-order approximations to describe the reaction kinetics. Our model study has broad implications in the general understanding of competition and local crowding on diffusion-limited chemical reactions.
Competition between reactive species is commonplace in typical chemical reactions. Specifically the primary reaction between a substrate and its target enzyme may be altered when interactions with secondary species in the system are substantial. We explore this competition phenomenon for diffusion-limited reactions in the presence of neighboring particles through numerical solution of the diffusion equation. As a general model for globular proteins and small molecules, we consider spherical representations of the reactants and neighboring particles; these neighbors vary in local density, size, distribution, and relative distance from the primary target reaction, as well as their surface reactivity. Modulations of these model variables permit inquiry into the influence of excluded volume and competition on the primary reaction due to the presence of neighboring particles. We find that the surface reactivity effect is long-ranged and a strong determinant of reaction kinetics, whereas the excluded volume effect is relatively short-ranged and less influential in comparison. As a consequence, the effect of the excluded volume is only modestly dependent on the neighbor distribution and is approximately additive; this additivity permits a linear approximation to the many-body effect on the reaction kinetics. In contrast, the surface reactivity effect is non-additive, and thus it may require higher-order approximations to describe the reaction kinetics. Our model study has broad implications in the general understanding of competition and local crowding on diffusion-limited chemical reactions.
Multi-core CPU or GPU-accelerated Multiscale Modeling for Biomolecular Complexes.Molecular Based Mathematical Biology 1, 164-179 (2013). [PubMed PMC3858848]
Multi-scale modeling plays an important role in understanding the structure and biological functionalities of large biomolecular complexes. In this paper, we present an efficient computational framework to construct multi-scale models from atomic resolution data in the Protein Data Bank (PDB), which is accelerated by multi-core CPU and programmable Graphics Processing Units (GPU). A multi-level summation of Gaus-sian kernel functions is employed to generate implicit models for biomolecules. The coefficients in the summation are designed as functions of the structure indices, which specify the structures at a certain level and enable a local resolution control on the biomolecular surface. A method called neighboring search is adopted to locate the grid points close to the expected biomolecular surface, and reduce the number of grids to be analyzed. For a specific grid point, a KD-tree or bounding volume hierarchy is applied to search for the atoms contributing to its density computation, and faraway atoms are ignored due to the decay of Gaussian kernel functions. In addition to density map construction, three modes are also employed and compared during mesh generation and quality improvement to generate high quality tetrahedral meshes: CPU sequential, multi-core CPU parallel and GPU parallel. We have applied our algorithm to several large proteins and obtained good results.
Multi-scale modeling plays an important role in understanding the structure and biological functionalities of large biomolecular complexes. In this paper, we present an efficient computational framework to construct multi-scale models from atomic resolution data in the Protein Data Bank (PDB), which is accelerated by multi-core CPU and programmable Graphics Processing Units (GPU). A multi-level summation of Gaus-sian kernel functions is employed to generate implicit models for biomolecules. The coefficients in the summation are designed as functions of the structure indices, which specify the structures at a certain level and enable a local resolution control on the biomolecular surface. A method called neighboring search is adopted to locate the grid points close to the expected biomolecular surface, and reduce the number of grids to be analyzed. For a specific grid point, a KD-tree or bounding volume hierarchy is applied to search for the atoms contributing to its density computation, and faraway atoms are ignored due to the decay of Gaussian kernel functions. In addition to density map construction, three modes are also employed and compared during mesh generation and quality improvement to generate high quality tetrahedral meshes: CPU sequential, multi-core CPU parallel and GPU parallel. We have applied our algorithm to several large proteins and obtained good results.
Inactivating mutation in Histone deacetylase 3 stabilizes its active conformation.Protein Science 22,1306-1312 (2013) [PubMed 23904210]
Histone deacetylases (HDACs), together with histone acetyltransferases (HATs), regulate gene expression by modulating the acetylation level of chromatin. HDAC3 is implicated in many important cellular processes, particularly in cancer cell proliferation and metastasis, making inhibition of HDAC3 a promising epigenetic treatment for certain cancers. HDAC3 is activated upon complex formation with both inositol tetraphosphate (IP4) and the deacetylase-activating domain (DAD) of multi-protein nuclear receptor corepressor complexes. In previous studies, we have shown that binding of DAD and IP4 to HDAC3 significantly restricts its conformational space towards its stable ternary complex conformation, and suggest this to be the active conformation. Here, we report a single mutation of HDAC3 that is capable of mimicking the stabilizing effects of DAD and IP4, without the presence of either. This mutation, however, results in a total loss of deacetylase activity, prompting a closer evaluation of our understanding of the activation of HDAC3.
Histone deacetylases (HDACs), together with histone acetyltransferases (HATs), regulate gene expression by modulating the acetylation level of chromatin. HDAC3 is implicated in many important cellular processes, particularly in cancer cell proliferation and metastasis, making inhibition of HDAC3 a promising epigenetic treatment for certain cancers. HDAC3 is activated upon complex formation with both inositol tetraphosphate (IP4) and the deacetylase-activating domain (DAD) of multi-protein nuclear receptor corepressor complexes. In previous studies, we have shown that binding of DAD and IP4 to HDAC3 significantly restricts its conformational space towards its stable ternary complex conformation, and suggest this to be the active conformation. Here, we report a single mutation of HDAC3 that is capable of mimicking the stabilizing effects of DAD and IP4, without the presence of either. This mutation, however, results in a total loss of deacetylase activity, prompting a closer evaluation of our understanding of the activation of HDAC3.
Simulations of Biased Agonists in the β2 Adrenergic Receptor with Accelerated Molecular Dynamics.Biochemistry 52 (33), pp 5593-5603 (2013) [PubMed 23879802]
The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signaling pathway a GPCR promotes intracellular signals though β-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that aGPCR forms a distinct ensemble of conformations signaling through the G protein and β-arrestin. Here we report on the dynamics of the β2 adrenergic receptor bound to the β-arrestin and G protein-biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring of the transition within the nanosecond time scale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the β-arrestin-biased agonist N-cyclopentylbutanepherine, we observe a different pattern of motions in helix 7 when compared to simulations with the G protein-biased agonist salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs.
The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signaling pathway a GPCR promotes intracellular signals though β-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that aGPCR forms a distinct ensemble of conformations signaling through the G protein and β-arrestin. Here we report on the dynamics of the β2 adrenergic receptor bound to the β-arrestin and G protein-biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring of the transition within the nanosecond time scale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the β-arrestin-biased agonist N-cyclopentylbutanepherine, we observe a different pattern of motions in helix 7 when compared to simulations with the G protein-biased agonist salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs.
Variational Implicit-Solvent Modeling of Host-Guest Binding: A Case Study on Cucurbit[7]uril.J. Chem. Theory Comput. 9(9): 4195–4204 (2013) [PubMed PMC3770055]
The synthetic host cucurbit[7]uril (CB[7]) binds aromatic guests or metal complexes with ultrahigh affinity compared with that typically displayed in protein–ligand binding. Due to its small size, CB[7] serves as an ideal receptor–ligand system for developing computational methods for molecular recognition. Here, we apply the recently developed variational implicit-solvent model (VISM), numerically evaluated by the level-set method, to study hydration effects in the high-affinity binding of the B2 bicyclo[2.2.2]octane derivative to CB[7]. For the unbound host, we find that the host cavity favors the hydrated state over the dry state due to electrostatic effects. For the guest binding, we find reasonable agreement to experimental binding affinities. Dissection of the individual VISM free-energy contributions shows that the major driving forces are water-mediated hydrophobic interactions and the intrinsic (vacuum) host–guest van der Waals interactions. These findings are in line with recent experiments and molecular dynamics simulations with explicit solvent. It is expected that the level-set VISM, with further refinement on the electrostatic descriptions, can efficiently predict molecular binding and recognition in a wide range of future applications.
The synthetic host cucurbit[7]uril (CB[7]) binds aromatic guests or metal complexes with ultrahigh affinity compared with that typically displayed in protein–ligand binding. Due to its small size, CB[7] serves as an ideal receptor–ligand system for developing computational methods for molecular recognition. Here, we apply the recently developed variational implicit-solvent model (VISM), numerically evaluated by the level-set method, to study hydration effects in the high-affinity binding of the B2 bicyclo[2.2.2]octane derivative to CB[7]. For the unbound host, we find that the host cavity favors the hydrated state over the dry state due to electrostatic effects. For the guest binding, we find reasonable agreement to experimental binding affinities. Dissection of the individual VISM free-energy contributions shows that the major driving forces are water-mediated hydrophobic interactions and the intrinsic (vacuum) host–guest van der Waals interactions. These findings are in line with recent experiments and molecular dynamics simulations with explicit solvent. It is expected that the level-set VISM, with further refinement on the electrostatic descriptions, can efficiently predict molecular binding and recognition in a wide range of future applications.
Substrate-dependent dynamics of UDP-galactopyranose mutase: implications for drug design.Protein Science Vol. 22, Issue 11, 14901-1501 (2013). [PubMed 23934860]
Trypanosoma cruzi is the causative agent of Chagas disease, a neglected tropical disease that represents one of the major health challenges of the Latin American countries. Successful efforts were made during the last few decades to control the transmission of this disease, but there is still no treatment for the 10 million adults in the chronic phase of the disease. In T. cruzi, as well as in other pathogens, the flavoenzyme UDP-galactopyranose mutase (UGM) catalyzes the conversion of UDP-galactopyranose to UDP-galactofuranose, a precursor of the cell surface β-galactofuranose that is involved in the virulence of the pathogen. The fact that UGM is not present in humans makes inhibition of this enzyme a good approach in the design of new Chagas therapeutics. By performing a series of computer simulations of T. cruzi UGM in the presence or absence of an active site ligand, we address the molecular details of the mechanism that controls the uptake and retention of the substrate. The simulations suggest a modular mechanism in which each moiety of the substrate controls the flexibility of a different protein loop. Furthermore, the calculations indicate that interactions with the substrate diphosphate moiety are especially important for stabilizing the closed active site. This hypothesis is supported with kinetics measurements of site-directed mutants of T. cruzi UGM. Our results extend our knowledge of UGM dynamics and offer new alternatives for the prospective design of drugs.
Trypanosoma cruzi is the causative agent of Chagas disease, a neglected tropical disease that represents one of the major health challenges of the Latin American countries. Successful efforts were made during the last few decades to control the transmission of this disease, but there is still no treatment for the 10 million adults in the chronic phase of the disease. In T. cruzi, as well as in other pathogens, the flavoenzyme UDP-galactopyranose mutase (UGM) catalyzes the conversion of UDP-galactopyranose to UDP-galactofuranose, a precursor of the cell surface β-galactofuranose that is involved in the virulence of the pathogen. The fact that UGM is not present in humans makes inhibition of this enzyme a good approach in the design of new Chagas therapeutics. By performing a series of computer simulations of T. cruzi UGM in the presence or absence of an active site ligand, we address the molecular details of the mechanism that controls the uptake and retention of the substrate. The simulations suggest a modular mechanism in which each moiety of the substrate controls the flexibility of a different protein loop. Furthermore, the calculations indicate that interactions with the substrate diphosphate moiety are especially important for stabilizing the closed active site. This hypothesis is supported with kinetics measurements of site-directed mutants of T. cruzi UGM. Our results extend our knowledge of UGM dynamics and offer new alternatives for the prospective design of drugs.
Improving the Efficiency of Free Energy Calculations in the Amber Molecular Dynamics Package.J. Chem. Theory Comp. 9, 4131−4139 (2013).
Alchemical transformations are widely used methods to calculate free energies. Amber has traditionally included support for alchemical transformations as part of the sander molecular dynamics (MD) engine. Here, we describe the implementation of a more efficient approach to alchemical transformations in the Amber MD package. Specifically, we have implemented this new approach within the more computationally efficient and scalable pmemd MD engine that is included with the Amber MD package. The majority of the gain in efficiency comes from the improved design of the calculation, which includes better parallel scaling and reduction in the calculation of redundant terms. This new implementation is able to reproduce results from equivalent simulations run with the existing functionality but at 2.5 times greater computational efficiency. This new implementation is also able to run softcore simulations at the λ end states making direct calculation of free energies more accurate, compared to the extrapolation required in the existing implementation. The updated alchemical transformation functionality is planned to be included in the next major release of Amber (scheduled for release in Q1 2014), available at http://ambermd.org, under the Amber license.
Alchemical transformations are widely used methods to calculate free energies. Amber has traditionally included support for alchemical transformations as part of the sander molecular dynamics (MD) engine. Here, we describe the implementation of a more efficient approach to alchemical transformations in the Amber MD package. Specifically, we have implemented this new approach within the more computationally efficient and scalable pmemd MD engine that is included with the Amber MD package. The majority of the gain in efficiency comes from the improved design of the calculation, which includes better parallel scaling and reduction in the calculation of redundant terms. This new implementation is able to reproduce results from equivalent simulations run with the existing functionality but at 2.5 times greater computational efficiency. This new implementation is also able to run softcore simulations at the λ end states making direct calculation of free energies more accurate, compared to the extrapolation required in the existing implementation. The updated alchemical transformation functionality is planned to be included in the next major release of Amber (scheduled for release in Q1 2014), available at http://ambermd.org, under the Amber license.
Mapping of Allosteric Druggable Sites in Activation-Associated Conformers of the M2 Muscarinic Receptor.Chem. Biol. Drug Design 83, 237-246 (2014). [PubMed PMC2918726]
G-protein coupled receptors (GPCRs) are key cellular signaling proteins and have been targeted by ~30-40% of marketed drugs for treating many human diseases including cancer and heart failure. Recently, we directly observed activation of the M2 muscarinic receptor through long-timescale accelerated molecular dynamics (aMD) simulation, which revealed distinct inactive, intermediate and active conformers of the receptor. Here, FTMAP is applied to search for “hot spots” in these activation-associated conformers using a library of 16 organic probe molecules that represent fragments of potential drugs. Seven allosteric (non-orthosteric) binding sites are identified in the M2 receptor through the FTMAP analysis. These sites are distributed in the solvent-exposed extracellular and intracellular mouth regions, as well as the lipid-exposed pockets formed by the transmembrane α helices TM3-TM4, TM5-TM6 and TM7-TM1/TM2. They serve as promising target sites for designing novel allosteric modulators as receptor-selective drugs.
G-protein coupled receptors (GPCRs) are key cellular signaling proteins and have been targeted by ~30-40% of marketed drugs for treating many human diseases including cancer and heart failure. Recently, we directly observed activation of the M2 muscarinic receptor through long-timescale accelerated molecular dynamics (aMD) simulation, which revealed distinct inactive, intermediate and active conformers of the receptor. Here, FTMAP is applied to search for “hot spots” in these activation-associated conformers using a library of 16 organic probe molecules that represent fragments of potential drugs. Seven allosteric (non-orthosteric) binding sites are identified in the M2 receptor through the FTMAP analysis. These sites are distributed in the solvent-exposed extracellular and intracellular mouth regions, as well as the lipid-exposed pockets formed by the transmembrane α helices TM3-TM4, TM5-TM6 and TM7-TM1/TM2. They serve as promising target sites for designing novel allosteric modulators as receptor-selective drugs.
Molecular and Subcellular-Scale Modeling of Nucleotide Diffusion in the Cardiac Myofilament LatticeBiophys. J 105,2130-2140 (2013) [PubMed PMC3835335]
Contractile function of cardiac cells is driven by the sliding displacement of myofilaments powered by the cycling myosin crossbridges. Critical to this process is the availability of ATP, which myosin hydrolyzes during the cross-bridge cycle. The diffusion of adenine nucleotides through the myofilament lattice has been shown to be anisotropic, with slower radial diffu- sion perpendicular to the filament axis relative to parallel, and is attributed to the periodic hexagonal arrangement of the thin (actin) and thick (myosin) filaments. We investigated whether atomistic-resolution details of myofilament proteins can refine coarse-grain estimates of diffusional anisotropy for adenine nucleotides in the cardiac myofibril, using homogenization theory and atomistic thin filament models from the Protein Data Bank. Our results demonstrate considerable anisotropy in ATP and ADP diffusion constants that is consistent with experimental measurements and dependent on lattice spacing and myofilament overlap. A reaction-diffusion model of the half-sarcomere further suggests that diffusional anisotropy may lead to modest adenine nucleotide gradients in the myoplasm under physiological conditions.
Contractile function of cardiac cells is driven by the sliding displacement of myofilaments powered by the cycling myosin crossbridges. Critical to this process is the availability of ATP, which myosin hydrolyzes during the cross-bridge cycle. The diffusion of adenine nucleotides through the myofilament lattice has been shown to be anisotropic, with slower radial diffu- sion perpendicular to the filament axis relative to parallel, and is attributed to the periodic hexagonal arrangement of the thin (actin) and thick (myosin) filaments. We investigated whether atomistic-resolution details of myofilament proteins can refine coarse-grain estimates of diffusional anisotropy for adenine nucleotides in the cardiac myofibril, using homogenization theory and atomistic thin filament models from the Protein Data Bank. Our results demonstrate considerable anisotropy in ATP and ADP diffusion constants that is consistent with experimental measurements and dependent on lattice spacing and myofilament overlap. A reaction-diffusion model of the half-sarcomere further suggests that diffusional anisotropy may lead to modest adenine nucleotide gradients in the myoplasm under physiological conditions.
Structure, mechanism, and dynamics of UDP-galactopyranose mutase.Archives of Biochemistry and Biophysics, Vol. 544, 128-141 (2014) [PubMed 24096172]
The flavoenzyme UDP-galactopyranose mutase (UGM) is a key enzyme in galactofuranose biosynthesis. The enzyme catalyzes the 6-to-5 ring contraction of UDP-galactopyranose to UDP-galactofuranose. Galactofuranose is absent in humans yet is an essential component of bacterial and fungal cell walls and a cell surface virulence factor in protozoan parasites. Thus, inhibition of galactofuranose biosynthesis is a valid strategy for developing new antimicrobials. UGM is an excellent target in this effort because the product of the UGM reaction represents the first appearance of galactofuranose in the biosynthetic pathway. The UGM reaction is redox neutral, which is atypical for flavoenzymes, motivating intense examination of the chemical mechanism and structural features that tune the flavin for its unique role in catalysis. These studies show that the flavin functions as nucleophile, forming a flavin-sugar adduct that facilitates galactose-ring opening and contraction. The 3-dimensional fold is novel and conserved among all UGMs, however the larger eukaryotic enzymes have additional secondary structure elements that lead to significant differences in quaternary structure, substrate conformation, and conformational flexibility. Here we present a comprehensive review of UGM three-dimensional structure, provide an update on recent developments in understanding the mechanism of the enzyme, and summarize computational studies of active site flexibility.
The flavoenzyme UDP-galactopyranose mutase (UGM) is a key enzyme in galactofuranose biosynthesis. The enzyme catalyzes the 6-to-5 ring contraction of UDP-galactopyranose to UDP-galactofuranose. Galactofuranose is absent in humans yet is an essential component of bacterial and fungal cell walls and a cell surface virulence factor in protozoan parasites. Thus, inhibition of galactofuranose biosynthesis is a valid strategy for developing new antimicrobials. UGM is an excellent target in this effort because the product of the UGM reaction represents the first appearance of galactofuranose in the biosynthetic pathway. The UGM reaction is redox neutral, which is atypical for flavoenzymes, motivating intense examination of the chemical mechanism and structural features that tune the flavin for its unique role in catalysis. These studies show that the flavin functions as nucleophile, forming a flavin-sugar adduct that facilitates galactose-ring opening and contraction. The 3-dimensional fold is novel and conserved among all UGMs, however the larger eukaryotic enzymes have additional secondary structure elements that lead to significant differences in quaternary structure, substrate conformation, and conformational flexibility. Here we present a comprehensive review of UGM three-dimensional structure, provide an update on recent developments in understanding the mechanism of the enzyme, and summarize computational studies of active site flexibility.
Accelerated Molecular Dynamics Simulations with the AMOEBA Polarizable Force Field on graphics processing units.J. Chem. Theory Comp. 9 (11), pp 4684-4691 (2013) [PubMed PMC3948463]
The accelerated molecular dynamics (aMD) method has recently been shown to enhance the sampling of biomolecules in molecular dynamics (MD) simulations, often by several orders of magnitude. Here, we describe an implementation of the aMD method for the OpenMM application layer that takes full advantage of graphics processing units (GPUs) computing. The aMD method is shown to work in combination with the AMOEBA polarizable force field (AMOEBA-aMD), allowing the simulation of long timescale events with a polarizable force field. Benchmarks are provided to show that the AMOEBA-aMD method is efficiently implemented and produces accurate results in its standard parametrization. For the BPTI protein, we demonstrate that the protein structure described with AMOEBA remains stable even on the extended time scales accessed at high levels of accelerations. For the DNA repair metalloenzyme endonuclease IV, we show that the use of the AMOEBA force field is a significant improvement over fixed charged models for describing the enzyme active-site. The new AMOEBA-aMD method is publicly available (http://wiki.simtk. org/openmm/VirtualRepository) and promises to be interesting for studying complex systems that can benefit from both the use of a polarizable force field and enhanced sampling.
The accelerated molecular dynamics (aMD) method has recently been shown to enhance the sampling of biomolecules in molecular dynamics (MD) simulations, often by several orders of magnitude. Here, we describe an implementation of the aMD method for the OpenMM application layer that takes full advantage of graphics processing units (GPUs) computing. The aMD method is shown to work in combination with the AMOEBA polarizable force field (AMOEBA-aMD), allowing the simulation of long timescale events with a polarizable force field. Benchmarks are provided to show that the AMOEBA-aMD method is efficiently implemented and produces accurate results in its standard parametrization. For the BPTI protein, we demonstrate that the protein structure described with AMOEBA remains stable even on the extended time scales accessed at high levels of accelerations. For the DNA repair metalloenzyme endonuclease IV, we show that the use of the AMOEBA force field is a significant improvement over fixed charged models for describing the enzyme active-site. The new AMOEBA-aMD method is publicly available (http://wiki.simtk. org/openmm/VirtualRepository) and promises to be interesting for studying complex systems that can benefit from both the use of a polarizable force field and enhanced sampling.
Utilizing a dynamical description of IspH to aid in the development of novel antimicrobial drugs.PLoS Comp. Biol. v.9(12) (2013). [PubMed PMC3868525]
The nonmevalonate pathway is responsible for isoprenoid production in microbes, including H. pylori, M. tuberculosis and P. falciparum, but is nonexistent in humans, thus providing a desirable route for antibacterial and antimalarial drug discovery. We coordinate a structural study of IspH, a [4Fe-4S] protein responsible for converting HMBPP to IPP and DMAPP in the ultimate step in the nonmevalonate pathway. By performing accelerated molecular dynamics simulations on both substrate-free and HMBPP-bound [Fe4S4]2+ IspH, we elucidate how substrate binding alters the dynamics of the protein. Using principal component analysis, we note that while substrate-free IspH samples various open and closed conformations, the closed conformation observed experimentally for HMBPP-bound IspH is inaccessible in the absence of HMBPP. In contrast, simulations with HMBPP bound are restricted from accessing the open states sampled by the substrate-free simulations. Further investigation of the substrate-free simulations reveals large fluctuations in the HMBPP binding pocket, as well as allosteric pocket openings – both of which are achieved through the hinge motions of the individual domains in IspH. Coupling these findings with solvent mapping and various structural analyses reveals alternative druggable sites that may be exploited in future drug design efforts.
The nonmevalonate pathway is responsible for isoprenoid production in microbes, including H. pylori, M. tuberculosis and P. falciparum, but is nonexistent in humans, thus providing a desirable route for antibacterial and antimalarial drug discovery. We coordinate a structural study of IspH, a [4Fe-4S] protein responsible for converting HMBPP to IPP and DMAPP in the ultimate step in the nonmevalonate pathway. By performing accelerated molecular dynamics simulations on both substrate-free and HMBPP-bound [Fe4S4]2+ IspH, we elucidate how substrate binding alters the dynamics of the protein. Using principal component analysis, we note that while substrate-free IspH samples various open and closed conformations, the closed conformation observed experimentally for HMBPP-bound IspH is inaccessible in the absence of HMBPP. In contrast, simulations with HMBPP bound are restricted from accessing the open states sampled by the substrate-free simulations. Further investigation of the substrate-free simulations reveals large fluctuations in the HMBPP binding pocket, as well as allosteric pocket openings – both of which are achieved through the hinge motions of the individual domains in IspH. Coupling these findings with solvent mapping and various structural analyses reveals alternative druggable sites that may be exploited in future drug design efforts.
