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Abstracts of Articles in 2010
To request any journal reprints, please contact us.- Including Receptor Flexibility and Induced Fit Effects into the Design of MMP2 Inhibitors
- Method to Predict Crowding Effects by Postprocessing Molecular Dynamics Trajectories: Application to the Flap Dynamics of HIV-1 Protease
- The gates of ion channels and enzymes
- Identification of triazinoindol-benzimidazolones as nanomolar inhibitors of the Mycobacterium tuberculosis enzyme TDP-6-deoxy-D-xylo-4-hexopyranosid-4-ulose 3,5-epimerase (RmlC)
- Solutions to a Reduced Poisson-Nernst-Planck System and Determination of Reaction Rates
- A Multidimensional Strategy to Detect Polypharmacological Targets in the Absence of Structural and Sequence Homology
- Enhanced Conformational Space Sampling Improves the Prediction of Chemical Shifts in Proteins
- Large conformational changes in proteins: signaling and other functions
- Coupling Constant pH Molecular Dynamics with Accelerated Molecular Dynamics
- Kinetics of diffusion-controlled enzymatic reactions with charged substrates
- A Dynamic Model of HIV Integrase Inhibition and Drug Resistance
- The role of secondary sialic acid binding sites in influenza N1 neuraminidase
- AFMPB: An Adaptive Fast Multipole Poisson-Boltzmann Solver for Calculating Electrostatics in Biomolecular Systems
- Recognition of the ring-opened state of proliferating cell nuclear antigen by replication factor C promotes eukaryotic clamp-loading
- Computational Identification of Uncharacterized Cruzain Binding Sites
- Potential Drug-Like Inhibitors of Group 1 Influenza Neuraminidase Identified through Computer-Aided Drug Design
- Discovery of Small Molecule Inhibitors of the PH Domain Leucine-Rich Repeat Protein Phosphatase (PHLPP) by Chemical and Virtual Screening
- Characterization of a clinical polymer-drug conjugate using multiscale modeling
- Channeling by Proximity: The Catalytic Advantages of Active Site Colocalization Using Brownian Dynamics
- Impact of calcium on N1 influenza neuraminidase dynamics and binding free energy
- Computer-Aided Identification of Trypanosoma brucei Uridine Diphosphate Galactose 4'-Epimerase Inhibitors: Towards the Development of Novel Therapies for African Sleeping Sickness
- From Sensors to Silencers: Quinoline- and Benzimidazole-Sulfonamides as Inhibitors for Zinc Proteinases
- Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes I: Finite Element Solutions
- Mapping the druggable allosteric space of G-protein coupled receptors: A fragment-based molecular dynamics approach
- Solvation Effect on the Conformations of Alanine Dipeptide: Integral Equation Approach
- Browndye: A Software Package for Brownian Dynamics
- Water in cavity-ligand recognition
- How can hydrophobic association be enthalpy-driven?
- The distinct conformational dynamics of K-Ras and H-Ras A59G
- Numerical analysis of Ca2+ signaling in rat ventricular myocytes with realistic transverse-axial tubular geometry and inhibited sarcoplasmic reticulum
- Using Selectively Applied Accelerated Molecular Dynamics to Enhance Free Energy Calculations
- NNScore: A Neural Network Based Scoring Function for the Characterization of Protein-Ligand Complexes
- Computer-aided Drug Discovery Techniques that Account for Receptor Flexibility
- Conformational selection in G-proteins: Lessons from Ras and Rho
Including Receptor Flexibility and Induced Fit Effects into the Design of MMP2 InhibitorsJournal of Molecular Recognition, Vol. 23, pp. 173-182 (2010) [PubMed 19882751]
Matrix metalloproteinases (MMPs) comprise a class of flexible proteins required for normal tissue remodeling. Overexpression of MMPs is associated with a wide range of pathophysiological processes, including vascular disease, multiple sclerosis, Alzheimer's disease, and cancer. Nearly all MMP inhibitors have failed in clinical trials, in part due to lack of specificity. Due to the highly dynamic molecular motions of the MMP-2 binding pockets, the rational drug design of MMP inhibitors has been very challenging. To address these challenges, in the current study we combine computer docking with molecular dynamics (MD) simulations in order to incorporate receptor-flexibility and induced-fit effects into the drug-design process. Our strategy identifies molecular fragments predicted to target multiple MMP-2 binding pockets.
Matrix metalloproteinases (MMPs) comprise a class of flexible proteins required for normal tissue remodeling. Overexpression of MMPs is associated with a wide range of pathophysiological processes, including vascular disease, multiple sclerosis, Alzheimer's disease, and cancer. Nearly all MMP inhibitors have failed in clinical trials, in part due to lack of specificity. Due to the highly dynamic molecular motions of the MMP-2 binding pockets, the rational drug design of MMP inhibitors has been very challenging. To address these challenges, in the current study we combine computer docking with molecular dynamics (MD) simulations in order to incorporate receptor-flexibility and induced-fit effects into the drug-design process. Our strategy identifies molecular fragments predicted to target multiple MMP-2 binding pockets.
Method to Predict Crowding Effects by Postprocessing Molecular Dynamics Trajectories: Application to the Flap Dynamics of HIV-1 ProteaseJournal of Physical Chemistry Letters, Vol. 1, pp. 107-110 (2010) [PubMed 20228897]
The internal dynamics of proteins inside of cells may be affected by the crowded intracellular environments. Here, we test a novel approach to simulations of crowding, in which simulations in the absence of crowders are postprocessed to predict crowding effects, against the direct approach of simulations in the presence of crowders. The effects of crowding on the flap dynamics of HIV-1 protease predicted by the postprocessing approach are found to agree well with those calculated by the direct approach. The postprocessing approach presents distinct advantages over the direct approach in terms of accuracy and speed and is expected to have broad impact on atomistic simulations of macromolecular crowding.
The internal dynamics of proteins inside of cells may be affected by the crowded intracellular environments. Here, we test a novel approach to simulations of crowding, in which simulations in the absence of crowders are postprocessed to predict crowding effects, against the direct approach of simulations in the presence of crowders. The effects of crowding on the flap dynamics of HIV-1 protease predicted by the postprocessing approach are found to agree well with those calculated by the direct approach. The postprocessing approach presents distinct advantages over the direct approach in terms of accuracy and speed and is expected to have broad impact on atomistic simulations of macromolecular crowding.
The gates of ion channels and enzymesTrends in Biochemical Sciences, Vol. 35, No. 3, pp. 179-185 (2010) [PubMed 19926290]
Protein dynamics are essential for virtually all protein functions, certainly for gating mechanisms of ion channels and regulation of enzyme catalysis. Ion channels usually feature a gate in the channel pore that prevents ion permeation in the closed state. Some bifunctional enzymes with two distant active sites use a tunnel to transport intermediate products; a gate can help prevent premature leakage. Enzymes with a buried active site also require a tunnel for substrate entrance; a gate along the tunnel can contribute to selectivity. The gates in these different contexts show distinct characteristics in sequence, structure and dynamics, but they also have common features. In particular, aromatic residues often appear to serve as gates, probably because of their ability, through side chain rotation, to effect large changes in cross section.
Protein dynamics are essential for virtually all protein functions, certainly for gating mechanisms of ion channels and regulation of enzyme catalysis. Ion channels usually feature a gate in the channel pore that prevents ion permeation in the closed state. Some bifunctional enzymes with two distant active sites use a tunnel to transport intermediate products; a gate can help prevent premature leakage. Enzymes with a buried active site also require a tunnel for substrate entrance; a gate along the tunnel can contribute to selectivity. The gates in these different contexts show distinct characteristics in sequence, structure and dynamics, but they also have common features. In particular, aromatic residues often appear to serve as gates, probably because of their ability, through side chain rotation, to effect large changes in cross section.
Identification of triazinoindol-benzimidazolones as nanomolar inhibitors of the Mycobacterium tuberculosis enzyme TDP-6-deoxy-D-xylo-4-hexopyranosid-4-ulose 3,5-epimerase (RmlC)Bioorganic & Medicinal Chemistry, Vol. 18, No. 2, pp. 896-908 (2010) [PubMed 19969466]
High-throughput screening of 201,368 compounds revealed that 1-(3-(5-ethyl-5H-1,2,4triazino5,6-bindol-3-ylthio) propyl)-1H-benzodimidazol-2(3H)-one (SID 7975595) inhibited RmlC a TB cell wall biosynthetic enzyme. SID 7975595 acts as a competitive inhibitor of the enzyme’s substrate and inhibits RmlC as a fast-on rate, fully reversible inhibitor. An analog of SID 7975595 had a Ki of 62 nM. Computer modeling showed that the binding of the tethered two-ringed system into the active site occurred at the thymidine binding region for one ring system and the sugar region for the other ring system.
High-throughput screening of 201,368 compounds revealed that 1-(3-(5-ethyl-5H-1,2,4triazino5,6-bindol-3-ylthio) propyl)-1H-benzodimidazol-2(3H)-one (SID 7975595) inhibited RmlC a TB cell wall biosynthetic enzyme. SID 7975595 acts as a competitive inhibitor of the enzyme’s substrate and inhibits RmlC as a fast-on rate, fully reversible inhibitor. An analog of SID 7975595 had a Ki of 62 nM. Computer modeling showed that the binding of the tethered two-ringed system into the active site occurred at the thymidine binding region for one ring system and the sugar region for the other ring system.
Solutions to a Reduced Poisson-Nernst-Planck System and Determination of Reaction RatesPhysica A, Vol. 389, No. 7, pp. 1329-1345 (2010) [PubMed 20228879]
We study a reduced Poisson–Nernst–Planck (PNP) system for a charged spherical solute immersed in a solvent with multiple ionic or molecular species that are electrostatically neutralized in the far field. Some of these species are assumed to be in equilibrium. The concentrations of such species are described by the Boltzmann distributions that are further linearized. Others are assumed to be reactive, meaning that their concentrations vanish when in contact with the charged solute. We present both semi-analytical solutions and numerical iterative solutions to the underlying reduced PNP system, and calculate the reaction rate for the reactive species. We give a rigorous analysis on the convergence of our simple iteration algorithm. Our numerical results show the strong dependence of the reaction rates of the reactive species on the magnitude of its far field concentration as well as on the ionic strength of all the chemical species. We also find non-monotonicity of electrostatic potential in certain parameter regimes. The results for the reactive system and those for the non-reactive system are compared to show the significant differences between the two cases. Our approach provides a means of solving a PNP system which in general does not have a closed-form solution even with a special geometrical symmetry. Our findings can also be used to test other numerical methods in large-scale computational modeling of electro-diffusion in biological systems.
We study a reduced Poisson–Nernst–Planck (PNP) system for a charged spherical solute immersed in a solvent with multiple ionic or molecular species that are electrostatically neutralized in the far field. Some of these species are assumed to be in equilibrium. The concentrations of such species are described by the Boltzmann distributions that are further linearized. Others are assumed to be reactive, meaning that their concentrations vanish when in contact with the charged solute. We present both semi-analytical solutions and numerical iterative solutions to the underlying reduced PNP system, and calculate the reaction rate for the reactive species. We give a rigorous analysis on the convergence of our simple iteration algorithm. Our numerical results show the strong dependence of the reaction rates of the reactive species on the magnitude of its far field concentration as well as on the ionic strength of all the chemical species. We also find non-monotonicity of electrostatic potential in certain parameter regimes. The results for the reactive system and those for the non-reactive system are compared to show the significant differences between the two cases. Our approach provides a means of solving a PNP system which in general does not have a closed-form solution even with a special geometrical symmetry. Our findings can also be used to test other numerical methods in large-scale computational modeling of electro-diffusion in biological systems.
A Multidimensional Strategy to Detect Polypharmacological Targets in the Absence of Structural and Sequence HomologyPLoS Computational Biology, Vol. 6, Issue 1, article e1000648, 8 pages (2010) [PubMed 20098496]
Conventional drug design embraces the “one gene, one drug, one disease” philosophy. Polypharmacology, which focuses on multi-target drugs, has emerged as a new paradigm in drug discovery. The rational design of drugs that act via polypharmacological mechanisms can produce compounds that exhibit increased therapeutic potency and against which resistance is less likely to develop. Additionally, identifying multiple protein targets is also critical for side-effect prediction. One third of potential therapeutic compounds fail in clinical trials or are later removed from the market due to unacceptable side effects often caused by off-target binding. In the current work, we introduce a multidimensional strategy for the identification of secondary targets of known small-molecule inhibitors in the absence of global structural and sequence homology with the primary target protein. To demonstrate the utility of the strategy, we identify several targets of 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7?-naphthalenedisulfonic acid, a known micromolar inhibitor of Trypanosoma brucei RNA editing ligase 1. As it is capable of identifying potential secondary targets, the strategy described here may play a useful role in future efforts to reduce drug side effects and/or to increase polypharmacology.
Conventional drug design embraces the “one gene, one drug, one disease” philosophy. Polypharmacology, which focuses on multi-target drugs, has emerged as a new paradigm in drug discovery. The rational design of drugs that act via polypharmacological mechanisms can produce compounds that exhibit increased therapeutic potency and against which resistance is less likely to develop. Additionally, identifying multiple protein targets is also critical for side-effect prediction. One third of potential therapeutic compounds fail in clinical trials or are later removed from the market due to unacceptable side effects often caused by off-target binding. In the current work, we introduce a multidimensional strategy for the identification of secondary targets of known small-molecule inhibitors in the absence of global structural and sequence homology with the primary target protein. To demonstrate the utility of the strategy, we identify several targets of 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7?-naphthalenedisulfonic acid, a known micromolar inhibitor of Trypanosoma brucei RNA editing ligase 1. As it is capable of identifying potential secondary targets, the strategy described here may play a useful role in future efforts to reduce drug side effects and/or to increase polypharmacology.
Enhanced Conformational Space Sampling Improves the Prediction of Chemical Shifts in ProteinsJournal of the American Chemical Society, Vol. 132, No. 4, pp. 1220-1221 (2010) [PubMed 20063881]
A biased-potential molecular dynamics simulation method, accelerated molecular dynamics (AMD),was combined with the chemical shift prediction algorithm SHIFTX to calculate 1-H^N , 15-N, 13-Calpha, 13-Cbeta and 13-C' chemical shifts of the ankyrin repeat protein I-kappa-B-alpha (residues 67-206), the primary inhibitorof nuclear factor kappa-B. Free-energy-weighted molecular ensembles were generated over a range of acceleration levels, affording systematic enhancement of the conformational space sampling of the protein. We have found that the predicted chemical shifts, particularly for the 15-N, 13-Calpha, and 13-Cbeta nuclei, improve substantially with enhanced conformational space sampling up to an optimal acceleration level. Significant improvement in the predicted chemical shift data coincides with those regions of the protein that exhibit backbone dynamics on longer time scales. Interestingly, the optimal acceleration level for reproduction of the chemical shift data has previously been shown to best reproduce the experimental residual dipolar coupling (RDC) data for this system, as both chemical shift data and RDCs report on an ensemble and time average in the millisecond range.
A biased-potential molecular dynamics simulation method, accelerated molecular dynamics (AMD),was combined with the chemical shift prediction algorithm SHIFTX to calculate 1-H^N , 15-N, 13-Calpha, 13-Cbeta and 13-C' chemical shifts of the ankyrin repeat protein I-kappa-B-alpha (residues 67-206), the primary inhibitorof nuclear factor kappa-B. Free-energy-weighted molecular ensembles were generated over a range of acceleration levels, affording systematic enhancement of the conformational space sampling of the protein. We have found that the predicted chemical shifts, particularly for the 15-N, 13-Calpha, and 13-Cbeta nuclei, improve substantially with enhanced conformational space sampling up to an optimal acceleration level. Significant improvement in the predicted chemical shift data coincides with those regions of the protein that exhibit backbone dynamics on longer time scales. Interestingly, the optimal acceleration level for reproduction of the chemical shift data has previously been shown to best reproduce the experimental residual dipolar coupling (RDC) data for this system, as both chemical shift data and RDCs report on an ensemble and time average in the millisecond range.
Large conformational changes in proteins: signaling and other functionsCurrent Opinion in Structural Biology, Vol. 20, No. 2, pp. 142-147 (2010) [PubMed 20060708]
Guanine and adenine nucleotide triphosphatases, such as Ras proteins and protein kinases, undergo large conformational changes upon ligand binding in the course of their functions. New computer simulation methods have combined with experimental studies to deepen our understanding of these phenomena. In particular, a ‘conformational selection’ picture is emerging, where alterations in the relative populations of pre- existing conformations can best describe the conformational switching activity of these important proteins.
Guanine and adenine nucleotide triphosphatases, such as Ras proteins and protein kinases, undergo large conformational changes upon ligand binding in the course of their functions. New computer simulation methods have combined with experimental studies to deepen our understanding of these phenomena. In particular, a ‘conformational selection’ picture is emerging, where alterations in the relative populations of pre- existing conformations can best describe the conformational switching activity of these important proteins.
Coupling Constant pH Molecular Dynamics with Accelerated Molecular DynamicsJournal of Chemical Theory and Computation, Vol. 6, No. 2, pp. 560-568 (2010) [PubMed 20148176]
An extension of the constant pH method originally implemented by Mongan et al. (J. Comput. Chem. 2004, 25, 2038-2048) is proposed in this study. This adapted version of the method couples the constant pH methodology with the enhanced sampling technique of accelerated molecular dynamics, in an attempt to overcome the sampling issues encountered with current standard constant pH molecular dynamics methods. Although good results were reported by Mongan et al. on application of the standard method to the hen egg-white lysozyme (HEWL) system, residues which possess strong interactions with neighboring groups tend to converge slowly, resulting in the reported consistencies for predicted pKa values, as highlighted by the authors. The application of the coupled method described in this study to the HEWL system displays improvements over the standard version of the method, with the improved sampling leading to faster convergence and producing pKa values in closer agreement to those obtained experimentally for the more slowly converging residues.
An extension of the constant pH method originally implemented by Mongan et al. (J. Comput. Chem. 2004, 25, 2038-2048) is proposed in this study. This adapted version of the method couples the constant pH methodology with the enhanced sampling technique of accelerated molecular dynamics, in an attempt to overcome the sampling issues encountered with current standard constant pH molecular dynamics methods. Although good results were reported by Mongan et al. on application of the standard method to the hen egg-white lysozyme (HEWL) system, residues which possess strong interactions with neighboring groups tend to converge slowly, resulting in the reported consistencies for predicted pKa values, as highlighted by the authors. The application of the coupled method described in this study to the HEWL system displays improvements over the standard version of the method, with the improved sampling leading to faster convergence and producing pKa values in closer agreement to those obtained experimentally for the more slowly converging residues.
Kinetics of diffusion-controlled enzymatic reactions with charged substratesPMC Biophysics, Vol. 3, article 1, 4 pages (2010) [PubMed 20157429]
The Debye-Hückel limiting law (DHL) has often been used to estimate rate constants of diffusion-controlled reactions under different ionic strengths. Two main approximations are adopted in DHL: one is that the solution of the linearized Poisson-Boltzmann equation for a spherical cavity is used to estimate the excess electrostatic free energy of a solution; the other is that details of electrostatic interactions of the solutes are neglected. This makes DHL applicable only at low ionic strengths and dilute solutions (very low substrate/solute concentrations). We show in this work that through numerical solution of the Poisson-Nernst-Planck equations, diffusion-reaction processes can be studied at a variety of conditions including realistically concentrated solutions, high ionic strength, and certainly with non-equilibrium charge distributions. Reaction rate coefficients for the acetylcholine-acetylcholinesterase system are predicted to strongly depend on both ionic strength and substrate concentration. In particular, they increase considerably with increase of substrate concentrations at a fixed ionic strength, which is open to experimental testing. This phenomenon is also verified on a simple model, and is expected to be general for electrostatically attracting enzyme-substrate systems.
The Debye-Hückel limiting law (DHL) has often been used to estimate rate constants of diffusion-controlled reactions under different ionic strengths. Two main approximations are adopted in DHL: one is that the solution of the linearized Poisson-Boltzmann equation for a spherical cavity is used to estimate the excess electrostatic free energy of a solution; the other is that details of electrostatic interactions of the solutes are neglected. This makes DHL applicable only at low ionic strengths and dilute solutions (very low substrate/solute concentrations). We show in this work that through numerical solution of the Poisson-Nernst-Planck equations, diffusion-reaction processes can be studied at a variety of conditions including realistically concentrated solutions, high ionic strength, and certainly with non-equilibrium charge distributions. Reaction rate coefficients for the acetylcholine-acetylcholinesterase system are predicted to strongly depend on both ionic strength and substrate concentration. In particular, they increase considerably with increase of substrate concentrations at a fixed ionic strength, which is open to experimental testing. This phenomenon is also verified on a simple model, and is expected to be general for electrostatically attracting enzyme-substrate systems.
A Dynamic Model of HIV Integrase Inhibition and Drug ResistanceJournal of Molecular Biology, Vol. 397, Issue 2, pp. 600-615 (2010) [PubMed 20096702]
Human immunodeficiency virus type 1 (HIV-1) integrase is one of three virally encoded enzymes essential for replication and, therefore, a rational choice as a drug target for the treatment of HIV-1-infected individuals. In 2007, raltegravir became the first integrase inhibitor approved for use in the treatment of HIV-infected patients, more than a decade since the approval of the first protease inhibitor (saquinavir, Hoffman La-Roche, 1995) and two decades since the approval of the first reverse transcriptase inhibitor (retrovir, GlaxoSmithKline, 1987). The slow progress toward a clinically effective HIV-1 integrase inhibitor can at least in part be attributed to a poor structural understanding of this key viral protein. Here we describe the development of a restrained molecular dynamics protocol that produces a more accurate model of the active site of this drug target. This model provides an advance on previously described models as it ensures that the catalytic DDE motif makes correct, monodentate interactions with the two active-site magnesium ions. Dynamic restraints applied to this coordination state create models with the correct solvation sphere for the metal ion complex and highlight the coordination sites available for metal-binding ligands. Application of appropriate dynamic flexibility to the core domain allowed the inclusion of multiple conformational states in subsequent docking studies. These models have allowed us to (1) explore the effects of key drug resistance mutations on the dynamic flexibility and conformational preferences of HIV integrase and to (2) study raltegravir binding in the context of these dynamic models of both wild type and the G140S/Q148H drug-resistant enzyme.
Human immunodeficiency virus type 1 (HIV-1) integrase is one of three virally encoded enzymes essential for replication and, therefore, a rational choice as a drug target for the treatment of HIV-1-infected individuals. In 2007, raltegravir became the first integrase inhibitor approved for use in the treatment of HIV-infected patients, more than a decade since the approval of the first protease inhibitor (saquinavir, Hoffman La-Roche, 1995) and two decades since the approval of the first reverse transcriptase inhibitor (retrovir, GlaxoSmithKline, 1987). The slow progress toward a clinically effective HIV-1 integrase inhibitor can at least in part be attributed to a poor structural understanding of this key viral protein. Here we describe the development of a restrained molecular dynamics protocol that produces a more accurate model of the active site of this drug target. This model provides an advance on previously described models as it ensures that the catalytic DDE motif makes correct, monodentate interactions with the two active-site magnesium ions. Dynamic restraints applied to this coordination state create models with the correct solvation sphere for the metal ion complex and highlight the coordination sites available for metal-binding ligands. Application of appropriate dynamic flexibility to the core domain allowed the inclusion of multiple conformational states in subsequent docking studies. These models have allowed us to (1) explore the effects of key drug resistance mutations on the dynamic flexibility and conformational preferences of HIV integrase and to (2) study raltegravir binding in the context of these dynamic models of both wild type and the G140S/Q148H drug-resistant enzyme.
The role of secondary sialic acid binding sites in influenza N1 neuraminidaseJournal of the American Chemical Society, Vol. 132, Issue 9, pp. 2883-2885 (2010) [PubMed 20155919]
Within influenza viral particles, the intricate balance between host cell binding and sialic acid receptor destruction is carefully maintained by the hemagglutinin (HA) and neuraminidase (NA) glycoproteins, respectively. A major outstanding question in influenza biology is the function of a secondary sialic acid binding site on the NA enzyme. Through a series of Brownian dynamics (BD) simulations of the avian N1, human pandemic N2, and currently circulating pandemic (H1)N1 enzymes, we have probed the role of this secondary sialic acid binding site in the avian N1 subtype. Our results suggest that electrostatic interactions at the secondary and primary sites in avian NA may play a key role in the recognition process of the sialic acid receptors and catalytic efficiency of NA. This secondary site appears to facilitate the formation of complexes with the NA protein and the sialic acid receptors, as well as provide HA activity to a lesser extent. Moreover, this site is able to steer inhibitor binding as well, albeit with reduced capacity in N1, and may have potential implications for drug resistance or optimal inhibitor design. Although the secondary sialic acid binding site has previously been shown to be nonconserved in swine NA strains, our investigations of the currently circulating pandemic H1N1 strain of swine origin appears to have retained some of the key features of the secondary sialic acid binding site. Our results indicate possible lowered HA activity for this secondary sialic acid site, which may be an important event in the emergence of the current pandemic strain.
Within influenza viral particles, the intricate balance between host cell binding and sialic acid receptor destruction is carefully maintained by the hemagglutinin (HA) and neuraminidase (NA) glycoproteins, respectively. A major outstanding question in influenza biology is the function of a secondary sialic acid binding site on the NA enzyme. Through a series of Brownian dynamics (BD) simulations of the avian N1, human pandemic N2, and currently circulating pandemic (H1)N1 enzymes, we have probed the role of this secondary sialic acid binding site in the avian N1 subtype. Our results suggest that electrostatic interactions at the secondary and primary sites in avian NA may play a key role in the recognition process of the sialic acid receptors and catalytic efficiency of NA. This secondary site appears to facilitate the formation of complexes with the NA protein and the sialic acid receptors, as well as provide HA activity to a lesser extent. Moreover, this site is able to steer inhibitor binding as well, albeit with reduced capacity in N1, and may have potential implications for drug resistance or optimal inhibitor design. Although the secondary sialic acid binding site has previously been shown to be nonconserved in swine NA strains, our investigations of the currently circulating pandemic H1N1 strain of swine origin appears to have retained some of the key features of the secondary sialic acid binding site. Our results indicate possible lowered HA activity for this secondary sialic acid site, which may be an important event in the emergence of the current pandemic strain.
AFMPB: An Adaptive Fast Multipole Poisson-Boltzmann Solver for Calculating Electrostatics in Biomolecular SystemsComputer Physics Communications, Vol. 181, Issue 6, pp. 1150-1160 (2010) [PubMed 20532187]
A Fortran program package is introduced for the rapid evaluation of the electrostatic potential and force field in biomolecular systems modeled by the linearized Poisson- Boltzmann equation. The method utilizes a well-conditioned boundary integral equation (BIE) formulation, a node-patch discretization scheme, a Krylov subspace iterative solver package using reverse communication protocols, and an adaptive new version of fast multipole method in which the exponential expansions are used to diagonalize the multipole to local translations. The program and its full description, as well as several closely related packages are also available at http://lsec.cc.ac.cn/lubz/afmpb.html and a mirror site at http://mccammon.ucsd.edu/. This paper is a brief review of the program and its performance.
A Fortran program package is introduced for the rapid evaluation of the electrostatic potential and force field in biomolecular systems modeled by the linearized Poisson- Boltzmann equation. The method utilizes a well-conditioned boundary integral equation (BIE) formulation, a node-patch discretization scheme, a Krylov subspace iterative solver package using reverse communication protocols, and an adaptive new version of fast multipole method in which the exponential expansions are used to diagonalize the multipole to local translations. The program and its full description, as well as several closely related packages are also available at http://lsec.cc.ac.cn/lubz/afmpb.html and a mirror site at http://mccammon.ucsd.edu/. This paper is a brief review of the program and its performance.
Recognition of the ring-opened state of proliferating cell nuclear antigen by replication factor C promotes eukaryotic clamp-loadingJournal of the American Chemical Society, Vol. 132, Issue 21, pp. 7372-7378 (2010) [PubMed 20455582]
Proliferating cell nuclear antigen (PCNA, sliding clamp) is a toroidal-shaped protein that encircles DNA and plays a pivotal role in DNA replication, modification and repair. To perform its vital functions, the clamp has to be opened and resealed at primer-template junctions by a clamp loader molecular machine – replication factor C (RFC). The mechanism of this process constitutes a significant piece in the puzzle of processive DNA replication. We show that upon clamp opening the RFC/PCNA complex undergoes a large conformational rearrangement, leading to the formation of an extended interface between the clamp and RFC. Binding of ring-open PCNA to all five RFC subunits transforms the free energy landscape underlying the closed- to open state transition, trapping PCNA in an open conformation. Careful comparison of free energy profiles for clamp opening in the presence and absence of RFC allowed us to substantiate the role of RFC in the initial stage of the clamp-loading cycle. RFC does not appreciably destabilize the closed state of PCNA. Instead, the function of the clamp loader is dependent on the selective stabilization of the open conformation of the clamp.
Proliferating cell nuclear antigen (PCNA, sliding clamp) is a toroidal-shaped protein that encircles DNA and plays a pivotal role in DNA replication, modification and repair. To perform its vital functions, the clamp has to be opened and resealed at primer-template junctions by a clamp loader molecular machine – replication factor C (RFC). The mechanism of this process constitutes a significant piece in the puzzle of processive DNA replication. We show that upon clamp opening the RFC/PCNA complex undergoes a large conformational rearrangement, leading to the formation of an extended interface between the clamp and RFC. Binding of ring-open PCNA to all five RFC subunits transforms the free energy landscape underlying the closed- to open state transition, trapping PCNA in an open conformation. Careful comparison of free energy profiles for clamp opening in the presence and absence of RFC allowed us to substantiate the role of RFC in the initial stage of the clamp-loading cycle. RFC does not appreciably destabilize the closed state of PCNA. Instead, the function of the clamp loader is dependent on the selective stabilization of the open conformation of the clamp.
Computational Identification of Uncharacterized Cruzain Binding SitesPLoS Neglected Tropical Diseases, Vol. 4, Issue 5, article e676, 11 pages (2010) [PubMed 20485483]
Chagas disease, caused by the unicellular parasite Trypanosoma cruzi, claims 50,000 lives annually and is the leading cause of infectious myocarditis in the world. As current antichagastic therapies like nifurtimox and benznidazole are highly toxic, ineffective at parasite eradication, and subject to increasing resistance, novel therapeutics are urgently needed. Cruzain, the major cysteine protease of Trypanosoma cruzi, is one attractive drug target. In the current work, molecular dynamics simulations and a sequence alignment of a non-redundant, unbiased set of peptidase C1 family members are used to identify uncharacterized cruzain binding sites. The two sites identified may serve as targets for future pharmacological intervention.
Chagas disease, caused by the unicellular parasite Trypanosoma cruzi, claims 50,000 lives annually and is the leading cause of infectious myocarditis in the world. As current antichagastic therapies like nifurtimox and benznidazole are highly toxic, ineffective at parasite eradication, and subject to increasing resistance, novel therapeutics are urgently needed. Cruzain, the major cysteine protease of Trypanosoma cruzi, is one attractive drug target. In the current work, molecular dynamics simulations and a sequence alignment of a non-redundant, unbiased set of peptidase C1 family members are used to identify uncharacterized cruzain binding sites. The two sites identified may serve as targets for future pharmacological intervention.
Potential Drug-Like Inhibitors of Group 1 Influenza Neuraminidase Identified through Computer-Aided Drug DesignComputational Biology and Chemistry, Vol. 34, Issue 2, pp. 97-105 (2010) [PubMed 20427241]
Pandemic (H1N1) influenza poses an imminent threat. Nations have stockpiled inhibitors of the influenza protein neuraminidase in hopes of protecting their citizens, but drug-resistant strains have already emerged, and novel therapeutics are urgently needed. In the current work, the computer program AutoGrow is used to generate novel predicted neuraminidase inhibitors. Given the great flexibility of the neuraminidase active site, protein dynamics are also incorporated into the computer-aided drug-design process. Several potential inhibitors are identified that are predicted to bind neuraminidase better than currently approved drugs.
Pandemic (H1N1) influenza poses an imminent threat. Nations have stockpiled inhibitors of the influenza protein neuraminidase in hopes of protecting their citizens, but drug-resistant strains have already emerged, and novel therapeutics are urgently needed. In the current work, the computer program AutoGrow is used to generate novel predicted neuraminidase inhibitors. Given the great flexibility of the neuraminidase active site, protein dynamics are also incorporated into the computer-aided drug-design process. Several potential inhibitors are identified that are predicted to bind neuraminidase better than currently approved drugs.
Discovery of Small Molecule Inhibitors of the PH Domain Leucine-Rich Repeat Protein Phosphatase (PHLPP) by Chemical and Virtual ScreeningJournal of Medicinal Chemistry, Vol. 53, No. 19, pp. 6899-6911 (2010) [PubMed 20836557]
PH domain Leucine-rich repeat protein phosphatase (PHLPP) directly dephosphorylates and inactivates Akt and protein kinase C, poising it as a prime target for pharmacological intervention of two major survival pathways. Here we report on the discovery of small molecule inhibitors of the phosphatase activity of PHLPP, a member of the PP2C family of phosphatases for which there are no general pharmacological inhibitors. First, the Diversity Set of the NCI was screened for inhibition of the purified phosphatase domain of PHLPP2 in vitro. Second, selected libraries from the open NCI database were docked into a virtual model of the phosphatase domain of PHLPP2, previously trained with our experimental data set, unveiling additional inhibitors. Biochemical and cellular assays resulted in the identification of two structurally diverse compounds that selectively inhibit PHLPP in vitro, increase Akt signaling in cells, and prevent apoptosis. Thus, chemical and virtual screening has resulted in the identification of small molecules that promote Akt signaling by inhibiting its negative regulator PHLPP.
PH domain Leucine-rich repeat protein phosphatase (PHLPP) directly dephosphorylates and inactivates Akt and protein kinase C, poising it as a prime target for pharmacological intervention of two major survival pathways. Here we report on the discovery of small molecule inhibitors of the phosphatase activity of PHLPP, a member of the PP2C family of phosphatases for which there are no general pharmacological inhibitors. First, the Diversity Set of the NCI was screened for inhibition of the purified phosphatase domain of PHLPP2 in vitro. Second, selected libraries from the open NCI database were docked into a virtual model of the phosphatase domain of PHLPP2, previously trained with our experimental data set, unveiling additional inhibitors. Biochemical and cellular assays resulted in the identification of two structurally diverse compounds that selectively inhibit PHLPP in vitro, increase Akt signaling in cells, and prevent apoptosis. Thus, chemical and virtual screening has resulted in the identification of small molecules that promote Akt signaling by inhibiting its negative regulator PHLPP.
Characterization of a clinical polymer-drug conjugate using multiscale modelingBiopolymers, Vol. 93, Issue 11, pp. 936-951 (2010) [PubMed 20564048]
The molecular conformation of certain therapeutic agents has been shown to affect the ability to gain access to target cells, suggesting potential value in defining conformation of candidate molecules. This study explores how the shape and size of poly-γ-glutamyl-glutamate paclitaxel (PGG-PTX), an amphiphilic polymer-drug with potential chemotherapeutic applications, can be systematically controlled by varying hydrophobic and hydrophilic entities. Eighteen different formulations of PGG-PTX varying in three PTX loading fractions (fPTX) of 0.18, 0.24, and 0.37 and six spatial arrangements of PTX ('clusters', 'ends', 'even', 'middle', 'random', and 'side') were explored. Molecular dynamics (MD) simulations of all-atom (AA) models of PGG-PTX were run until a statistical equilibrium was reached at 100 ns and then continued as coarse-grained (CG) models until a statistical equilibrium was reached at an effective time of 800 ns. Circular dichroism spectroscopy was used to suggest initial modeling configurations. Results show that a PGG-PTX molecule has a strong tendency to form coil shapes, regardless of the PTX loading fraction and spatial PTX arrangement, although globular shapes exist at fPTX = 0.24. Also, less uniform PTX arrangements such as 'ends', 'middle', and 'side' produce coil geometries with more curvature. The prominence of coil shapes over globules suggests that PGG-PTX may confer a long circulation half-life and high propensity for accumulation to tumor endothelia. This multiscale modeling approach may be advantageous for the design of cancer therapeutic delivery systems.
The molecular conformation of certain therapeutic agents has been shown to affect the ability to gain access to target cells, suggesting potential value in defining conformation of candidate molecules. This study explores how the shape and size of poly-γ-glutamyl-glutamate paclitaxel (PGG-PTX), an amphiphilic polymer-drug with potential chemotherapeutic applications, can be systematically controlled by varying hydrophobic and hydrophilic entities. Eighteen different formulations of PGG-PTX varying in three PTX loading fractions (fPTX) of 0.18, 0.24, and 0.37 and six spatial arrangements of PTX ('clusters', 'ends', 'even', 'middle', 'random', and 'side') were explored. Molecular dynamics (MD) simulations of all-atom (AA) models of PGG-PTX were run until a statistical equilibrium was reached at 100 ns and then continued as coarse-grained (CG) models until a statistical equilibrium was reached at an effective time of 800 ns. Circular dichroism spectroscopy was used to suggest initial modeling configurations. Results show that a PGG-PTX molecule has a strong tendency to form coil shapes, regardless of the PTX loading fraction and spatial PTX arrangement, although globular shapes exist at fPTX = 0.24. Also, less uniform PTX arrangements such as 'ends', 'middle', and 'side' produce coil geometries with more curvature. The prominence of coil shapes over globules suggests that PGG-PTX may confer a long circulation half-life and high propensity for accumulation to tumor endothelia. This multiscale modeling approach may be advantageous for the design of cancer therapeutic delivery systems.
Channeling by Proximity: The Catalytic Advantages of Active Site Colocalization Using Brownian DynamicsJournal of Physical Chemistry Letters, Vol. 1, No. 9, pp. 1332-1335 (2010) [PubMed 20454551]
Nature often colocalizes successive steps in a metabolic pathway. Such organization is predicted to increase the effective concentration of pathway intermediates near their recipient active sites and to enhance catalytic efficiency. Here, the pathway of a two-step reaction is modeled using a simple spherical approximation for the enzymes and substrate particles. Brownian dynamics are used to simulate the trajectory of a substrate particle as it diffuses between the active site zones of two different enzyme spheres. The results approximate distances for the most effective reaction pathways, indicating that the most effective reaction pathway is one in which the active sites are closely aligned. However, when the active sites are too close, the ability of the substrate to react with the first enzyme was hindered, suggesting that even the most efficient orientations can be improved for a system that is allowed to rotate or change orientation to optimize the likelihood of reaction at both sites.
Nature often colocalizes successive steps in a metabolic pathway. Such organization is predicted to increase the effective concentration of pathway intermediates near their recipient active sites and to enhance catalytic efficiency. Here, the pathway of a two-step reaction is modeled using a simple spherical approximation for the enzymes and substrate particles. Brownian dynamics are used to simulate the trajectory of a substrate particle as it diffuses between the active site zones of two different enzyme spheres. The results approximate distances for the most effective reaction pathways, indicating that the most effective reaction pathway is one in which the active sites are closely aligned. However, when the active sites are too close, the ability of the substrate to react with the first enzyme was hindered, suggesting that even the most efficient orientations can be improved for a system that is allowed to rotate or change orientation to optimize the likelihood of reaction at both sites.
Impact of calcium on N1 influenza neuraminidase dynamics and binding free energyProteins, Vol. 78, Issue 11, pp. 2523-2532 (2010) [PubMed 20602360]
The highly pathogenic influenza strains H5N1 and H1N1 are currently treated with inhibitors of the viral surface protein neuraminidase (N1). Crystal structures of N1 indicate a conserved, high affinity calcium binding site located near the active site. The specific role of this calcium in the enzyme mechanism is unknown, though it has been shown to be important for enzymatic activity and thermostability. We report molecular dynamics (MD) simulations of calcium-bound and calcium-free N1 complexes with the inhibitor oseltamivir (marketed as the drug Tamiflu), independently using both the AMBER FF99SB and GROMOS96 force fields, to give structural insight into calcium stabilization of key framework residues. Y347, which demonstrates similar sampling patterns in the simulations of both force fields, is implicated as an important N1 residue that can "clamp" the ligand into a favorable binding pose. Free energy perturbation and thermodynamic integration calculations, using two different force fields, support the importance of Y347 and indicate a +3 to +5 kcal·mol-1 change in the binding free energy of oseltamivir in the absence of calcium. With the important role of structure-based drug design for neuraminidase inhibitors and the growing literature on emerging strains and subtypes, inclusion of this calcium for active site stability is particularly crucial for computational efforts such as homology modeling, virtual screening, and free energy methods.
The highly pathogenic influenza strains H5N1 and H1N1 are currently treated with inhibitors of the viral surface protein neuraminidase (N1). Crystal structures of N1 indicate a conserved, high affinity calcium binding site located near the active site. The specific role of this calcium in the enzyme mechanism is unknown, though it has been shown to be important for enzymatic activity and thermostability. We report molecular dynamics (MD) simulations of calcium-bound and calcium-free N1 complexes with the inhibitor oseltamivir (marketed as the drug Tamiflu), independently using both the AMBER FF99SB and GROMOS96 force fields, to give structural insight into calcium stabilization of key framework residues. Y347, which demonstrates similar sampling patterns in the simulations of both force fields, is implicated as an important N1 residue that can "clamp" the ligand into a favorable binding pose. Free energy perturbation and thermodynamic integration calculations, using two different force fields, support the importance of Y347 and indicate a +3 to +5 kcal·mol-1 change in the binding free energy of oseltamivir in the absence of calcium. With the important role of structure-based drug design for neuraminidase inhibitors and the growing literature on emerging strains and subtypes, inclusion of this calcium for active site stability is particularly crucial for computational efforts such as homology modeling, virtual screening, and free energy methods.
Computer-Aided Identification of Trypanosoma brucei Uridine Diphosphate Galactose 4'-Epimerase Inhibitors: Towards the Development of Novel Therapies for African Sleeping SicknessJournal of Medicinal Chemistry, Vol. 53, Issue 13, pp. 5025-5032 (2010) [PubMed 20527952]
Trypanosoma brucei, the causative agent of human African trypanosomiasis, affects tens of thousands of sub-Saharan Africans. As current therapeutics are inadequate due to toxic side effects, drug resistance, and limited effectiveness, novel therapies are urgently needed. UDP-galactose 4′-epimerase (TbGalE), an enzyme of the Leloir pathway of galactose metabolism, is one promising T. brucei drug target. We here use the relaxed complex scheme, an advanced computer-docking methodology that accounts for full protein flexibility, to identify inhibitors of TbGalE. An initial hit rate of 62% was obtained at 100 μM, ultimately leading to the identification of 14 low-micromolar inhibitors. Thirteen of these inhibitors belong to a distinct series with a conserved binding motif that may prove useful in future drug design and optimization.
Trypanosoma brucei, the causative agent of human African trypanosomiasis, affects tens of thousands of sub-Saharan Africans. As current therapeutics are inadequate due to toxic side effects, drug resistance, and limited effectiveness, novel therapies are urgently needed. UDP-galactose 4′-epimerase (TbGalE), an enzyme of the Leloir pathway of galactose metabolism, is one promising T. brucei drug target. We here use the relaxed complex scheme, an advanced computer-docking methodology that accounts for full protein flexibility, to identify inhibitors of TbGalE. An initial hit rate of 62% was obtained at 100 μM, ultimately leading to the identification of 14 low-micromolar inhibitors. Thirteen of these inhibitors belong to a distinct series with a conserved binding motif that may prove useful in future drug design and optimization.
From Sensors to Silencers: Quinoline- and Benzimidazole-Sulfonamides as Inhibitors for Zinc ProteinasesJournal of the American Chemical Society, Vol. 132, Issue 24, pp. 8232-8233 (2010) [PubMed 20507095]
Derived from the extensive work in the area of small molecule zinc(II) ion sensors, chelating fragment libraries of quinoline- and benzimidazole-sulfonamides have been prepared and screened against several different zinc(II)-dependent matrix metalloproteinases (MMPs). The fragments show impressive inhibition of these metalloenzymes and preferences for different MMPs based on the nature of the chelating group. The findings show that focused chelator libraries are a powerful strategy for the discovery of lead fragments for metalloprotein inhibition.
Derived from the extensive work in the area of small molecule zinc(II) ion sensors, chelating fragment libraries of quinoline- and benzimidazole-sulfonamides have been prepared and screened against several different zinc(II)-dependent matrix metalloproteinases (MMPs). The fragments show impressive inhibition of these metalloenzymes and preferences for different MMPs based on the nature of the chelating group. The findings show that focused chelator libraries are a powerful strategy for the discovery of lead fragments for metalloprotein inhibition.
Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes I: Finite Element SolutionsJournal of Computational Physics, Vol. 229, Issue 19, pp. 6979-6994 (2010) [PubMed 21709855]
In this paper we developed accurate finite element methods for solving 3-D Poisson–Nernst–Planck (PNP) equations with singular permanent charges for simulating electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst–Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams–Bashforth–Crank–Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst–Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.
In this paper we developed accurate finite element methods for solving 3-D Poisson–Nernst–Planck (PNP) equations with singular permanent charges for simulating electrodiffusion in solvated biomolecular systems. The electrostatic Poisson equation was defined in the biomolecules and in the solvent, while the Nernst–Planck equation was defined only in the solvent. We applied a stable regularization scheme to remove the singular component of the electrostatic potential induced by the permanent charges inside biomolecules, and formulated regular, well-posed PNP equations. An inexact-Newton method was used to solve the coupled nonlinear elliptic equations for the steady problems; while an Adams–Bashforth–Crank–Nicolson method was devised for time integration for the unsteady electrodiffusion. We numerically investigated the conditioning of the stiffness matrices for the finite element approximations of the two formulations of the Nernst–Planck equation, and theoretically proved that the transformed formulation is always associated with an ill-conditioned stiffness matrix. We also studied the electroneutrality of the solution and its relation with the boundary conditions on the molecular surface, and concluded that a large net charge concentration is always present near the molecular surface due to the presence of multiple species of charged particles in the solution. The numerical methods are shown to be accurate and stable by various test problems, and are applicable to real large-scale biophysical electrodiffusion problems.
Mapping the druggable allosteric space of G-protein coupled receptors: A fragment-based molecular dynamics approachChemical Biology & Drug Design, Vol. 76, Issue 3, pp. 201-217 (2010) [PubMed 20626410]
To address the problem of specificity in G-protein coupled receptor (GPCR) drug discovery, there has been tremendous recent interest in allosteric drugs that bind at sites topographically distinct from the orthosteric site. Unfortunately, structure-based drug design of allosteric GPCR ligands has been frustrated by the paucity of structural data for allosteric binding sites, making a strong case for predictive computational methods. In this work, we map the surfaces of the β1 (β1AR) and β2 (β2AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites. We employ the FTMAP algorithm to identify 'hot spots' with affinity for a variety of organic probe molecules corresponding to drug fragments. Our work is distinguished by an ensemble-based approach, whereby we map diverse receptor conformations taken from molecular dynamics (MD) simulations totaling approximately 0.5 mus. Our results reveal distinct pockets formed at both solvent-exposed and lipid-exposed cavities, which we interpret in light of experimental data and which may constitute novel targets for GPCR drug discovery. This mapping data can now serve to drive a combination of fragment-based and virtual screening approaches for the discovery of small molecules that bind at these sites and which may offer highly selective therapies.
To address the problem of specificity in G-protein coupled receptor (GPCR) drug discovery, there has been tremendous recent interest in allosteric drugs that bind at sites topographically distinct from the orthosteric site. Unfortunately, structure-based drug design of allosteric GPCR ligands has been frustrated by the paucity of structural data for allosteric binding sites, making a strong case for predictive computational methods. In this work, we map the surfaces of the β1 (β1AR) and β2 (β2AR) adrenergic receptor structures to detect a series of five potentially druggable allosteric sites. We employ the FTMAP algorithm to identify 'hot spots' with affinity for a variety of organic probe molecules corresponding to drug fragments. Our work is distinguished by an ensemble-based approach, whereby we map diverse receptor conformations taken from molecular dynamics (MD) simulations totaling approximately 0.5 mus. Our results reveal distinct pockets formed at both solvent-exposed and lipid-exposed cavities, which we interpret in light of experimental data and which may constitute novel targets for GPCR drug discovery. This mapping data can now serve to drive a combination of fragment-based and virtual screening approaches for the discovery of small molecules that bind at these sites and which may offer highly selective therapies.
Solvation Effect on the Conformations of Alanine Dipeptide: Integral Equation ApproachJournal of Physical Chemistry Letters, Vol. 1, No. 15, pp. 2279-2283 (2010) [PubMed 20694049]
We present an implicit solvent model based on the extended reference interaction site model (XRISM) integral equation theory, which is a molecular theory of solvation. The solvation free energy is composed of additive potentials of mean force (PMF) of various functional groups. The XRISM theory is applied to determine the PMF of each group in water and NaBr electrolyte solutions. The method has been coupled to Brownian dynamics (BD) and is illustrated here on alanine dipeptide. The results of the method are compared with those obtained by explicit water simulations and other popular implicit solvent models for detailed discussion. The comparison of our model with other methods indicates that the intramolecular correlation and the solvation structure influence the stability of the PII and αR conformers. The results of NaBr electrolyte solutions show that the concentration of electrolyte also has a substantial effect on the favored conformations.
We present an implicit solvent model based on the extended reference interaction site model (XRISM) integral equation theory, which is a molecular theory of solvation. The solvation free energy is composed of additive potentials of mean force (PMF) of various functional groups. The XRISM theory is applied to determine the PMF of each group in water and NaBr electrolyte solutions. The method has been coupled to Brownian dynamics (BD) and is illustrated here on alanine dipeptide. The results of the method are compared with those obtained by explicit water simulations and other popular implicit solvent models for detailed discussion. The comparison of our model with other methods indicates that the intramolecular correlation and the solvation structure influence the stability of the PII and αR conformers. The results of NaBr electrolyte solutions show that the concentration of electrolyte also has a substantial effect on the favored conformations.
Browndye: A Software Package for Brownian DynamicsComputer Physics Communications, Vol. 181, Issue 11, pp. 1896-1905 (2010) [PubMed 21132109]
A new software package, Browndye, is presented for simulating the diffusional encounter of two large biological molecules. It can be used to estimate second-order rate constants and encounter probabilities, and to explore reaction trajectories. Browndye builds upon previous knowledge and algorithms from software packages such as UHBD, SDA, and Macrodox, while implementing algorithms that scale to larger systems.
A new software package, Browndye, is presented for simulating the diffusional encounter of two large biological molecules. It can be used to estimate second-order rate constants and encounter probabilities, and to explore reaction trajectories. Browndye builds upon previous knowledge and algorithms from software packages such as UHBD, SDA, and Macrodox, while implementing algorithms that scale to larger systems.
Water in cavity-ligand recognitionJournal of the American Chemical Society, Vol. 132, No. 34, pp. 12091-12097 (2010) [PubMed 20695475]
We use explicit solvent molecular dynamics simulations to estimate free energy, enthalpy, and entropy changes along the cavity-ligand association coordinate for a set of seven model systems with varying physicochemical properties. Owing to the simplicity of the considered systems we can directly investigate the role of water thermodynamics in molecular recognition. A broad range of thermodynamic signatures is found in which water (rather than cavity or ligand) enthalpic or entropic contributions appear to drive cavity-ligand binding or rejection. The unprecedented, nanoscale picture of hydration thermodynamics can help the interpretation and design of protein-ligand binding experiments. Our study opens appealing perspectives to tackle the challenge of solvent entropy estimation in complex systems and for improving molecular simulation models.
We use explicit solvent molecular dynamics simulations to estimate free energy, enthalpy, and entropy changes along the cavity-ligand association coordinate for a set of seven model systems with varying physicochemical properties. Owing to the simplicity of the considered systems we can directly investigate the role of water thermodynamics in molecular recognition. A broad range of thermodynamic signatures is found in which water (rather than cavity or ligand) enthalpic or entropic contributions appear to drive cavity-ligand binding or rejection. The unprecedented, nanoscale picture of hydration thermodynamics can help the interpretation and design of protein-ligand binding experiments. Our study opens appealing perspectives to tackle the challenge of solvent entropy estimation in complex systems and for improving molecular simulation models.
How can hydrophobic association be enthalpy-driven?Journal of Chemical Theory and Computation, Vol. 6, Issue 9, pp. 2866-2871 (2010) [PubMed 20844599]
Hydrophobic association is often recognized as being driven by favorable entropic contributions. Here, using explicit solvent molecular dynamics simulations we investigate binding in a model hydrophobic receptor-ligand system which appears, instead, to be driven by enthalpy and opposed by entropy. We use the temperature dependence of the potential of mean force to analyze the thermodynamic contributions along the association coordinate. Relating such contributions to the ongoing changes in system hydration allows us to demonstrate that the overall binding thermodynamics is determined by the expulsion of disorganized water from the receptor cavity. Our model study sheds light on the solvent-induced driving forces for receptor-ligand association of general, transferable relevance for biological systems with poorly hydrated binding sites.
Hydrophobic association is often recognized as being driven by favorable entropic contributions. Here, using explicit solvent molecular dynamics simulations we investigate binding in a model hydrophobic receptor-ligand system which appears, instead, to be driven by enthalpy and opposed by entropy. We use the temperature dependence of the potential of mean force to analyze the thermodynamic contributions along the association coordinate. Relating such contributions to the ongoing changes in system hydration allows us to demonstrate that the overall binding thermodynamics is determined by the expulsion of disorganized water from the receptor cavity. Our model study sheds light on the solvent-induced driving forces for receptor-ligand association of general, transferable relevance for biological systems with poorly hydrated binding sites.
The distinct conformational dynamics of K-Ras and H-Ras A59GPLoS Computational Biology, Vol. 6, Issue 9, article e1000922, 9 pages (2010) [PubMed 20838576]
Ras proteins regulate signaling cascades crucial for cell proliferation and differentiation by switching between GTP- and GDP-bound conformations. Distinct Ras isoforms have unique physiological functions with individual isoforms associated with different cancers and developmental diseases. Given the small structural differences among isoforms and mutants, it is currently unclear how these functional differences and aberrant properties arise. Here we investigate whether the subtle differences among isoforms and mutants are associated with detectable dynamical differences. Extensive molecular dynamics simulations reveal that wild-type K-Ras and mutant H-Ras A59G are intrinsically more dynamic than wild-type H-Ras. The crucial switch 1 and switch 2 regions along with loop 3, helix 3, and loop 7 contribute to this enhanced flexibility. Removing the gamma-phosphate of the bound GTP from the structure of A59G led to a spontaneous GTP-to-GDP conformational transition in a 20-ns unbiased simulation. The switch 1 and 2 regions exhibit enhanced flexibility and correlated motion when compared to non-transitioning wild-type H-Ras over a similar timeframe. Correlated motions between loop 3 and helix 5 of wild-type H-Ras are absent in the mutant A59G reflecting the enhanced dynamics of the loop 3 region. Taken together with earlier findings, these results suggest the existence of a lower energetic barrier between GTP and GDP states of the mutant. Molecular dynamics simulations combined with principal component analysis of available Ras crystallographic structures can be used to discriminate ligand- and sequence-based dynamic perturbations with potential functional implications. Furthermore, the identification of specific conformations associated with distinct Ras isoforms and mutants provides useful information for efforts that attempt to selectively interfere with the aberrant functions of these species.
Ras proteins regulate signaling cascades crucial for cell proliferation and differentiation by switching between GTP- and GDP-bound conformations. Distinct Ras isoforms have unique physiological functions with individual isoforms associated with different cancers and developmental diseases. Given the small structural differences among isoforms and mutants, it is currently unclear how these functional differences and aberrant properties arise. Here we investigate whether the subtle differences among isoforms and mutants are associated with detectable dynamical differences. Extensive molecular dynamics simulations reveal that wild-type K-Ras and mutant H-Ras A59G are intrinsically more dynamic than wild-type H-Ras. The crucial switch 1 and switch 2 regions along with loop 3, helix 3, and loop 7 contribute to this enhanced flexibility. Removing the gamma-phosphate of the bound GTP from the structure of A59G led to a spontaneous GTP-to-GDP conformational transition in a 20-ns unbiased simulation. The switch 1 and 2 regions exhibit enhanced flexibility and correlated motion when compared to non-transitioning wild-type H-Ras over a similar timeframe. Correlated motions between loop 3 and helix 5 of wild-type H-Ras are absent in the mutant A59G reflecting the enhanced dynamics of the loop 3 region. Taken together with earlier findings, these results suggest the existence of a lower energetic barrier between GTP and GDP states of the mutant. Molecular dynamics simulations combined with principal component analysis of available Ras crystallographic structures can be used to discriminate ligand- and sequence-based dynamic perturbations with potential functional implications. Furthermore, the identification of specific conformations associated with distinct Ras isoforms and mutants provides useful information for efforts that attempt to selectively interfere with the aberrant functions of these species.
Numerical analysis of Ca2+ signaling in rat ventricular myocytes with realistic transverse-axial tubular geometry and inhibited sarcoplasmic reticulumPLoS Computational Biology, Vol. 6, Issue 10, article e1000972, 16 pages (2010) [PubMed 21060856]
The t-tubules of mammalian ventricular myocytes are invaginations of the cell membrane that occur at each Z-line. These invaginations branch within the cell to form a complex network that allows rapid propagation of the electrical signal, and hence synchronous rise of intracellular calcium (Ca2+). To investigate how the t-tubule microanatomy and the distribution of membrane Ca2+ flux affect cardiac excitation-contraction coupling we developed a 3-D continuum model of Ca2+ signaling, buffering and diffusion in rat ventricular myocytes. The transverse-axial t-tubule geometry was derived from light microscopy structural data. To solve the nonlinear reaction-diffusion system we extended SMOL software tool (http://mccammon.ucsd.edu/smol/ http://mccammon.ucsd.edu/smol/). The analysis suggests that the quantitative understanding of the Ca2+ signaling requires more accurate knowledge of the t-tubule ultra-structure and Ca2+ flux distribution along the sarcolemma. The results reveal the important role for mobile and stationary Ca2+ buffers, including the Ca2+ indicator dye. In agreement with experiment, in the presence of fluorescence dye and inhibited sarcoplasmic reticulum, the lack of detectible differences in the depolarization-evoked Ca2+ transients was found when the Ca2+ flux was heterogeneously distributed along the sarcolemma. In the absence of fluorescence dye, strongly non-uniform Ca2+ signals are predicted. Even at modest elevation of Ca2+, reached during Ca2+ influx, large and steep Ca2+ gradients are found in the narrow sub-sarcolemmal space. The model predicts that the branched t-tubule structure and changes in the normal Ca2+ flux density along the cell membrane support initiation and propagation of Ca2+ waves in rat myocytes.
The t-tubules of mammalian ventricular myocytes are invaginations of the cell membrane that occur at each Z-line. These invaginations branch within the cell to form a complex network that allows rapid propagation of the electrical signal, and hence synchronous rise of intracellular calcium (Ca2+). To investigate how the t-tubule microanatomy and the distribution of membrane Ca2+ flux affect cardiac excitation-contraction coupling we developed a 3-D continuum model of Ca2+ signaling, buffering and diffusion in rat ventricular myocytes. The transverse-axial t-tubule geometry was derived from light microscopy structural data. To solve the nonlinear reaction-diffusion system we extended SMOL software tool (http://mccammon.ucsd.edu/smol/ http://mccammon.ucsd.edu/smol/). The analysis suggests that the quantitative understanding of the Ca2+ signaling requires more accurate knowledge of the t-tubule ultra-structure and Ca2+ flux distribution along the sarcolemma. The results reveal the important role for mobile and stationary Ca2+ buffers, including the Ca2+ indicator dye. In agreement with experiment, in the presence of fluorescence dye and inhibited sarcoplasmic reticulum, the lack of detectible differences in the depolarization-evoked Ca2+ transients was found when the Ca2+ flux was heterogeneously distributed along the sarcolemma. In the absence of fluorescence dye, strongly non-uniform Ca2+ signals are predicted. Even at modest elevation of Ca2+, reached during Ca2+ influx, large and steep Ca2+ gradients are found in the narrow sub-sarcolemmal space. The model predicts that the branched t-tubule structure and changes in the normal Ca2+ flux density along the cell membrane support initiation and propagation of Ca2+ waves in rat myocytes.
Using Selectively Applied Accelerated Molecular Dynamics to Enhance Free Energy CalculationsJournal of Chemical Theory and Computation, Vol. 6, Issue 11, pp. 3285-3292 (2010) [PubMed 21072329]
Accelerated molecular dynamics (aMD) has been shown to enhance conformational space sampling relative to classical molecular dynamics; however, the exponential reweighting of aMD trajectories, which is necessary for the calculation of free energies relating to the classical system, is oftentimes problematic, especially for systems larger than small poly peptides. Here, we propose a method of accelerating only the degrees of freedom most pertinent to sampling, thereby reducing the total acceleration added to the system and improving the convergence of calculated ensemble averages, which we term selective aMD. Its application is highlighted in two biomolecular cases. First, the model system alanine dipeptide is simulated with classical MD, all-dihedral aMD, and selective aMD, and these results are compared to the infinite sampling limit as calculated with metadynamics. We show that both forms of aMD enhance the convergence of the underlying free energy landscape by 5-fold relative to classical MD; however, selective aMD can produce improved statistics over all-dihedral aMD due to the improved reweighting. Then we focus on the pharmaceutically relevant case of computing the free energy of the decoupling of oseltamivir in the active site of neuraminidase. Results show that selective aMD greatly reduces the cost of this alchemical free energy transformation, whereas all-dihedral aMD produces unreliable free energy estimates.
Accelerated molecular dynamics (aMD) has been shown to enhance conformational space sampling relative to classical molecular dynamics; however, the exponential reweighting of aMD trajectories, which is necessary for the calculation of free energies relating to the classical system, is oftentimes problematic, especially for systems larger than small poly peptides. Here, we propose a method of accelerating only the degrees of freedom most pertinent to sampling, thereby reducing the total acceleration added to the system and improving the convergence of calculated ensemble averages, which we term selective aMD. Its application is highlighted in two biomolecular cases. First, the model system alanine dipeptide is simulated with classical MD, all-dihedral aMD, and selective aMD, and these results are compared to the infinite sampling limit as calculated with metadynamics. We show that both forms of aMD enhance the convergence of the underlying free energy landscape by 5-fold relative to classical MD; however, selective aMD can produce improved statistics over all-dihedral aMD due to the improved reweighting. Then we focus on the pharmaceutically relevant case of computing the free energy of the decoupling of oseltamivir in the active site of neuraminidase. Results show that selective aMD greatly reduces the cost of this alchemical free energy transformation, whereas all-dihedral aMD produces unreliable free energy estimates.
NNScore: A Neural Network Based Scoring Function for the Characterization of Protein-Ligand ComplexesJournal of Chemical Information and Modeling, Vol. 50, No. 10, pp. 1865-1871 (2010) [PubMed 20845954]
As high-throughput biochemical screens are both expensive and labor intensive, researchers in academia and industry are turning increasingly to virtual-screening methodologies. Virtual screening relies on scoring functions to quickly assess ligand potency. Although useful for in silico ligand identification, these scoring functions generally give many false positives and negatives; indeed, a properly trained human being can often assess ligand potency by visual inspection with greater accuracy. Given the success of the human mind at protein-ligand complex characterization, we present here a scoring function based on a neural network, a computational model that attempts to simulate, albeit inadequately, the microscopic organization of the brain. Computer-aided drug design depends on fast and accurate scoring functions to aid in the identification of small-molecule ligands. The scoring function presented here, used either on its own or in conjunction with other more traditional functions, could prove useful in future drug-discovery efforts.
As high-throughput biochemical screens are both expensive and labor intensive, researchers in academia and industry are turning increasingly to virtual-screening methodologies. Virtual screening relies on scoring functions to quickly assess ligand potency. Although useful for in silico ligand identification, these scoring functions generally give many false positives and negatives; indeed, a properly trained human being can often assess ligand potency by visual inspection with greater accuracy. Given the success of the human mind at protein-ligand complex characterization, we present here a scoring function based on a neural network, a computational model that attempts to simulate, albeit inadequately, the microscopic organization of the brain. Computer-aided drug design depends on fast and accurate scoring functions to aid in the identification of small-molecule ligands. The scoring function presented here, used either on its own or in conjunction with other more traditional functions, could prove useful in future drug-discovery efforts.
Computer-aided Drug Discovery Techniques that Account for Receptor FlexibilityCurrent Opinion in Pharmacology, Vol. 10, Issue 6, pp. 770-774 (2010) [PubMed 20888294]
Protein flexibility plays a critical role in ligand binding to both orthosteric and allosteric sites. We here review some of the computer-aided drug-design techniques currently used to account for protein flexibility, ranging from methods that probe local receptor flexibility in the region of the protein immediately adjacent to the binding site, to those that account for general flexibility in all protein regions.
Protein flexibility plays a critical role in ligand binding to both orthosteric and allosteric sites. We here review some of the computer-aided drug-design techniques currently used to account for protein flexibility, ranging from methods that probe local receptor flexibility in the region of the protein immediately adjacent to the binding site, to those that account for general flexibility in all protein regions.
Conformational selection in G-proteins: Lessons from Ras and RhoBiophysical Journal, Vol. 99, Issue 11, pp. 87-89 (2010) [PubMed 21112273]
The induced fit model has traditionally been invoked to describe the activating conformational change of the monomeric G-proteins, such as Ras and Rho. With this scheme, the presence or absence of the γ-phosphate of GTP leads to an instantaneous switch in conformation. Here we describe atomistic molecular simulations that demonstrate that both Ras and Rho superfamily members harbor an intrinsic susceptibility to sample multiple conformational states in the absence of nucleotide ligand. By comparing the distribution of conformers in the presence and absence of nucleotide, we show that conformational selection is the dominant mechanism by which Ras and Rho undergo nucleotide-dependent conformational changes. Furthermore, the pattern of correlated motions revealed by these simulations predicts a preserved allosteric coupling of the nucleotide-binding site with the membrane interacting C-terminus in both Rho and Ras.
The induced fit model has traditionally been invoked to describe the activating conformational change of the monomeric G-proteins, such as Ras and Rho. With this scheme, the presence or absence of the γ-phosphate of GTP leads to an instantaneous switch in conformation. Here we describe atomistic molecular simulations that demonstrate that both Ras and Rho superfamily members harbor an intrinsic susceptibility to sample multiple conformational states in the absence of nucleotide ligand. By comparing the distribution of conformers in the presence and absence of nucleotide, we show that conformational selection is the dominant mechanism by which Ras and Rho undergo nucleotide-dependent conformational changes. Furthermore, the pattern of correlated motions revealed by these simulations predicts a preserved allosteric coupling of the nucleotide-binding site with the membrane interacting C-terminus in both Rho and Ras.
