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Computational Research in Molecular Chemistry

Abstracts of Articles in 2018

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  1. Mapping the Allosteric Sites of the A2A Adenosine Receptor
  2. Improvements to the APBS biomolecular solvation software suite.
  3. Brownian dynamic study of an enzyme metabolon in the TCA cycle: Substrate kinetics and channeling
  4. Membrane Allostery and Unique Hydrophobic Sites Promote Enzyme Substrate Specificity
  5. Remarkable similarity in P. falciparum and P. vivax Geranylgeranyl Diphosphate Synthase (GGPPS) dynamics and its implication for anti-malarial drug design.
  6. Hierarchical Orthogonal Matrix Generation and Matrix-Vector Multiplications in Rigid Body Simulations
  7. Tailoring the Variational Implicit Solvent Method for New Challenges: Biomolecular Recognition and Assembly
  8. Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics Package
  9. Ligand Binding Pathways and Conformational Transitions of the HIV Protease
  10. RPYFMM: Parallel Adaptive Fast Multipole Method for Rotne-Prager-Yamakawa Tensor in Biomolecular Hydrodynamics Simulations
  11. Ensemble Docking in Drug Discovery
  12. Mechanism of the G-Protein Mimetic Nanobody Binding to a Muscarinic G-Protein-Coupled Receptor
  13. Replica exchange Gaussian accelerated molecular dynamics: Improved enhanced sampling and free energy calculation
  14. Key role of the REC lobe during CRISPR-Cas9 activation by “sensing”, “regulating” and “locking” the catalytic HNH domain
  15. A computational modelling approach predicts interaction of the antifungal protein AFP from Aspergillus giganteus with fungal membranes via its γ-core motif.
  16. Identification of SLAC1 anion channel residues required for CO2 signaling in Arabidopsis guard cells
  17. Heterogeneous solvation in distinctive protein-protein interfaces revealed by molecular dynamics simulations.
Mapping the Allosteric Sites of the A2A Adenosine ReceptorCaliman, A.D., Y. Miao, J.A. McCammonChem. Biol. Drug Disc., Volume 91, (1), pp 5-16 (2018)    
The A2A adenosine receptor (A2AAR) is a G protein-coupled receptor that is pharmacologically targeted for the treatment of inflammation, sepsis, cancer, neuro-degeneration, and Parkinson’s disease. Recently, we applied long-timescale molecular dynamics simulations on two ligand-free receptor conformations, starting from the agonist-bound (PDB ID:3QAK) and antagonist-bound (PDB ID:3EML) X-ray structures. This analysis revealed four distinct conformers of the A2AAR: the active, intermediate 1, intermediate 2, and inactive. In this study, we apply the fragment-based mapping algorithm, FTMap, on these receptor conformations to uncover five non-orthosteric sites on the A2AAR. Two sites that are identified in the active conformation are located in the intracellular region of the transmembrane helices (TM) 3/TM4 and the G protein-binding site in the intracellular region between TM2/TM3/TM6/TM7. Three sites are identified in the intermediate 1 and intermediate 2 conformations, annexing a site in the lipid interface of TM5/TM6. Five sites are identified in the inactive conformation, comprising of a site in the intracellular region of TM1/TM7, and in the extracellular region of TM3/TM4 of the A2AAR.  We postulate that these sites on the A2AAR be screened for allosteric modulators for the treatment of inflammatory and neurological diseases.
Improvements to the APBS biomolecular solvation software suite.Jurrus, E., D. Engel, K. Star, K. Monson, J. Brandi, L.E. Felbergy, D. Brookesy, L. Wilson, J. Chen, K. Liles, M. Chun, P. Li, T. Dolinsky, R. Konecny, D.R. Koes, J.E. Nielsen, T. Head-Gordon, W. Geng, R. Krasny, G.W. Weir, M.J. Holst, J.A. McCammon, N.A. Baker.Protein Sci. Vol. 27 (1) pp 112-128 (2018)    
The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.
Brownian dynamic study of an enzyme metabolon in the TCA cycle: Substrate kinetics and channelingHuang, Y.M., G.A. Huber, N. Wang, S.D. Minteer, J.A. McCammonProtein Sci., Volume 27, (2) pp 463-471 (2018)    
Malate dehydrogenase (MDH) and citrate synthase (CS) are two pacemaking enzymes involved in the tricarboxylic acid (TCA) cycle. Oxaloacetate (OAA) molecules are the intermediate substrates that are transferred from the MDH to CS to carry out sequential catalysis. It is known that, to achieve a high flux of intermediate transport and reduce the probability of substrate leaking, a MDH-CS metabolon forms to enhance the OAA substrate channeling. In this study, we aim to understand the OAA channeling within possible MDH-CS metabolons that have different structural orientations in their complexes. Three MDH-CS metabolons from native bovine, wild-type porcine and recombinant sources, published in recent work, were selected to calculate OAA transfer efficiency by Brownian dynamics (BD) simulations and to study, through electrostatic potential calculations, a possible role of charges that drive the substrate channeling. Our results show that an electrostatic channel is formed in the metabolons of native bovine and recombinant porcine enzymes, which guides the oppositely-charged OAA molecules passing through the channel and enhances the transfer efficiency. However, the channeling probability in a suggested wild-type porcine metabolon conformation is reduced due to an extended diffusion length between the MDH and CS active sites, implying that the corresponding arrangements of MDH and CS result in the decrease of electrostatic steering between substrates and protein surface and then reduce the substrate transfer efficiency from one active site to another. This article is protected by copyright. All rights reserved.
Membrane Allostery and Unique Hydrophobic Sites Promote Enzyme Substrate SpecificityMouchlis, V.D., Y. Chen, J.A. McCammon, E.A. DennisJ. Amer. Chem. Soc., 140 (9), pp 3285-3291 (2018)    
We demonstrate that lipidomics coupled with molecular dynamics reveals unique phospholipase A2 specificity toward membrane phospholipid substrates. We discovered unexpected head-group and acyl-chain specificity for three-major human phospholipases A2. These differences between each enzyme’s specificity coupled with molecular dynamicsbased structural and binding studies revealed unique active site and interfacial surface binding moieties for each enzyme that explains the observed specificity at a hitherto inaccessible structural level. Surprisingly, we discovered that a unique hydrophobic binding site for the cleaved fatty acid dominates each enzyme’s specificity, rather than its catalytic residues and polar head-group binding site. Molecular dynamics simulations revealed the optimal phospholipid binding mode leading to a detailed understanding of the preference of cytosolic phospholipase A2 for cleavage of pro-inflammatory arachidonic acid, calcium-independent phospholipase A2 which is involved in membrane remodeling for cleavage of linoleic acid, and for anti-bacterial secreted phospholipase A2 favoring linoleate, saturated fatty acids, and phosphatidylglycerol.
Remarkable similarity in P. falciparum and P. vivax Geranylgeranyl Diphosphate Synthase (GGPPS) dynamics and its implication for anti-malarial drug design.Venkatramani, A., C.G. Ricci, E. Oldfield, J.A. McCammon.Chem. Biol. Drug Disc., Volume 91, (6), pp1068-1077 (2018)    
Malaria, mainly caused by Plasmodium falciparum and Plasmodium vivax, has been a growing cause of morbidity and mortality. P. falciparum is more lethal than is P. vivax, but there is a vital need for effective drugs against both species. Geranylgeranyl diphosphate synthase (GGPPS) is an enzyme involved in the biosynthesis of quinones and in protein prenylation and has been proposed to be a malaria drug target. However, the structure of P. falciparumGGPPS (PfGGPPS) has not been determined, due to difficulties in crystallization. Here, we created a PfGGPPS model using the homologous P.vivaxGGPPS X‐ray structure as a template. We simulated the modeled PfGGPPS as well as PvGGPPS using conventional and Gaussian accelerated molecular dynamics in both apo‐ and GGPP‐bound states. The MD simulations revealed a striking similarity in the dynamics of both enzymes with loop 9‐10 controlling access to the active site. We also found that GGPP stabilizes PfGGPPS and PvGGPPS into closed conformations and via similar mechanisms. Shape‐based analysis of the binding sites throughout the simulations suggests that the two enzymes will be readily targeted by the same inhibitors. Finally, we produced three MD‐validated conformations of PfGGPPS to be used in future virtual screenings for potential new antimalarial drugs acting on both PvGGPPS and PfGGPPS.
Hierarchical Orthogonal Matrix Generation and Matrix-Vector Multiplications in Rigid Body SimulationsFang, F., J. Huang, G. Huber, J.A. McCammon, B. ZhangSIAM J. Sci. Comp. Vol. 40 (3) A1345-A1361 (2018)    
In this paper, we apply the hierarchical modeling technique and study some numerical linear algebra problems arising from the Brownian dynamics simulations of biomolecular systems where molecules are modeled as ensembles of rigid bodies. Given a rigid body p consisting of n beads, the 6×3n transformation matrix Z that maps the force on each bead to p's translational and rotational forces (a 6×1 vector), and V the row space of Z, we show how to explicitly construct the (3n−6)×3n matrix Q~ consisting of (3n−6) orthonormal basis vectors of V⊥ (orthogonal complement of V) using only O(nlogn) operations and storage. For applications where only the matrix-vector multiplications Q~v and Q~Tv are needed, we introduce asymptotically optimal O(n) hierarchical algorithms without explicitly forming Q~. Preliminary numerical results are presented to demonstrate the performance and accuracy of the numerical algorithms.
Tailoring the Variational Implicit Solvent Method for New Challenges: Biomolecular Recognition and AssemblyRicci, C.G., B. Li, L.T. Cheng, J. Dzubiella, J.A. McCammonFrontiers Molec. Biosci., Volume 5, Article 13 (2018)    
Predicting solvation free energies and describing the complex water behavior that plays an important role in essentially all biological processes is a major challenge from the computational standpoint. While an atomistic, explicit description of the solvent can turn out to be too expensive in large biomolecular systems, most implicit solvent methods fail to capture ‘dewetting’ effects and heterogeneous hydration by relying on a pre-established (i.e. guessed) solvation interface. Here we focus on the Variational Implicit Solvent Method, an implicit solvent method that adds water ‘plasticity’ back to the picture by formulating the solvation free energy as a functional of all possible solvation interfaces. We survey VISM’s applications to the problem of molecular recognition and report some of the most recent efforts to tailor VISM for more challenging scenarios, with the ultimate goal of including thermal fluctuations into the framework. The advances reported herein pave the way to make VISM a uniquely successful approach to characterize complex solvation properties in the recognition and binding of large-scale biomolecular complexes.
Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics PackageMermelstein, D.J., C. Lin, G. Nelson, R. Kretsch,, J.A. McCammon, R.C. WalkerJ. Comp. Chem., Volume 39 (19), pp 1354-1358 (2018)    
Alchemical free energy calculations (AFE) based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability, and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER
Ligand Binding Pathways and Conformational Transitions of the HIV ProteaseMiao, Y., Y-m. M. Huang, R. Walker, J.A. McCammon. C-e.A. ChangBiochemistry, 57 (9), pp 1533-1541 (2018)    
It is important to determine the binding pathways and mechanisms of ligand molecules to target proteins in order to effectively design therapeutic drugs. Molecular dynamics (MD) is a promising computational tool that allows us to simulate protein-drug binding at an atomistic level. However, the gap between timescales of current simulations and those of many drug binding processes has limited the usage of conventional MD, which has been reflected in studies of the HIV protease. Here, we have applied a robust enhanced simulation method, Gaussian accelerated molecular dynamics (GaMD), to sample binding pathways of the XK263 ligand and associated protein conformational changes in the HIV protease. During two of ten independent GaMD simulations performed over 500 – 2,500 ns, the ligand was observed to successfully bind to the protein active site. Although GaMD-derived free energy profiles were not fully converged due to insufficient sampling of the complex system, the simulations still allowed us to identify relatively low-energy intermediate conformational states during ligand binding to the HIV protease. Relative to the X-ray crystal structure, the XK263 ligand reached a minimum RMSD of 2.26 Å during 2.5 us of GaMD simulation. In comparison, the ligand RMSD reached a minimum RMSD of only ~5.73 Å during an earlier 14 us conventional MD simulation. This work highlights the enhanced sampling power of the GaMD approach and demonstrates its wide applicability to studies of drug-receptor interactions for the HIV protease and by extension many other target proteins.
RPYFMM: Parallel Adaptive Fast Multipole Method for Rotne-Prager-Yamakawa Tensor in Biomolecular Hydrodynamics SimulationsGuan, W., X. Cheng, J. Huang, G. Huber, W. Li, J. A. McCammon, B. ZhangComp. Physics Comm., Vol. 227, pp99-108 (2018).    
RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) [1] where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library [2, 3]. Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.
Ensemble Docking in Drug DiscoveryAmaro, R.E., J. Baudry, J. Chodera, O. Demir, J.A. McCammon, Y. Miao, J.C. SmithBiophys. J., Vol. 114 (10), pp 2271-2278 (2018)    
Ensemble docking corresponds to the generation of an “ensemble” of drug target conformations in computational structure-based drug discovery, often obtained by using molecular dynamics simulation, that is used in docking candidate ligands. This approach is now well established in the field of early-stage drug discovery. This review gives a historical account of the development of ensemble docking and discusses some pertinent methodological advances in conformational sampling.
Mechanism of the G-Protein Mimetic Nanobody Binding to a Muscarinic G-Protein-Coupled ReceptorMiao, Y., J.A. McCammonProc. Natl. Acad. Sci. USA, 115, (12), pp 3036-3041 (2018)    
Protein–protein binding is key in cellular signaling processes. Molecular dynamics (MD) simulations of protein–protein binding, however, are challenging due to limited timescales. In particular, binding of the medically important G-protein-coupled receptors (GPCRs) with intracellular signaling proteins has not been simulated with MD to date. Here, we report a successful simulation of the binding of a G-protein mimetic nanobody to the M2muscarinic GPCR using the robust Gaussian accelerated MD (GaMD) method. Through long-timescale GaMD simulations over 4,500 ns, the nanobody was observed to bind the receptor intracellular G-protein-coupling site, with a minimum rmsd of 2.48 Å in the nanobody core domain compared with the X-ray structure. Binding of the nanobody allosterically closed the orthosteric ligand-binding pocket, being consistent with the recent experimental finding. In the absence of nanobody binding, the receptor orthosteric pocket sampled open and fully open conformations. The GaMD simulations revealed two low-energy intermediate states during nanobody binding to the M2 receptor. The flexible receptor intracellular loops contribute remarkable electrostatic, polar, and hydrophobic residue interactions in recognition and binding of the nanobody. These simulations provided important insights into the mechanism of GPCR–nanobody binding and demonstrated the applicability of GaMD in modeling dynamic protein–protein interactions.
Replica exchange Gaussian accelerated molecular dynamics: Improved enhanced sampling and free energy calculationHuang, Y-m. M, J.A. McCammon, Y. MiaoJ. Chem. Theory Comp., 14, 4, pp 1853-18645 (2018).    
Through adding a harmonic boost potential to smooth the system potential energy surface, Gaussian accelerated molecular dynamics (GaMD) provides enhanced sampling and free energy calculation of biomolecules without the need of predefined reaction coordinates. This work continues to improve the acceleration power and energy reweighting of the GaMD by combining the GaMD with replica exchange algorithms. Two versions of replica exchange GaMD (rex-GaMD) are presented: force constant rex-GaMD and threshold energy rex-GaMD. During simulations of force constant rex-GaMD, the boost potential can be exchanged between replicas of different user-defined standard deviations with fixed threshold energy. However, the algorithm of threshold energy rex-GaMD tends to switch the threshold energy between lower and upper bounds for generating different levels of boost potential with a fixed value of standard deviation. Testing simulations on three model systems, including the alanine dipeptide, chignolin and HIV protease, demonstrate that through continuous exchanges of the boost potential, the rex-GaMD simulations not only enhance the conformational transitions of the systems, but also narrow down the distribution width of the applied boost potential for accurate energetic reweighting to recover biomolecular free energy profiles.
Key role of the REC lobe during CRISPR-Cas9 activation by “sensing”, “regulating” and “locking” the catalytic HNH domainPalermo, G., J.S. Chen, C.G. Ricci, I. Rivalta, M. Jinek, V.S. Batista, J.A. Doudna, J.A. McCammonQuart. Revs. Biophys., 51, e9, 1–11 (2018).    
Understanding the conformational dynamics of CRISPR-Cas9 is of the utmost importance for improving its genome editing capability. Here, molecular dynamics simulations performed using Anton-2 – a specialized supercomputer capturing micro-to-millisecond biophysical events in real time and at atomic level resolution – reveal the activation process of the endonuclease Cas9 toward DNA cleavage. Over the unbiased simulation, we observe that the spontaneous approach of the catalytic domain HNH to the DNA cleavage site is accompanied by a remarkable structural remodeling of the recognition (REC) lobe, which exerts a key role for DNA cleavage. Specifically, the significant conformational changes and the collective conformational dynamics of the REC lobe indicate a mechanism by which the REC1-3 regions “sense” nucleic acids, “regulate” the HNH conformational transition, and ultimately “lock” the HNH domain at the cleavage site, contributing to its catalytic competence. By integrating additional independent simulations and existing experimental data, we provide a solid validation of the activated HNH conformation, which had been so far poorly characterized, and we deliver a comprehensive understanding of the role of REC1-3 in the activation process. Considering the importance of the REC lobe in the specificity of Cas9, this study poses the basis for fully understanding how the REC components control the cleavage of off-target sequences, laying the foundation for future engineering efforts toward improved genome editing.
A computational modelling approach predicts interaction of the antifungal protein AFP from Aspergillus giganteus with fungal membranes via its γ-core motif.Utesch, T., Miguel Catalina, C. Schattenberg, N. Paege, P. Schmieder, E. Krause, Y. Miao, J.A. McCammon, V. Meyer, S. Jung, M.A. Mroginski.mSphere (Amer. Soc. Microbiol.) September/October 2018, Volume 3) Issue 5 e00377-18 (2018)    
Fungal pathogens kill more people per year globally than malaria or tuberculosis and threaten international food security through crop destruction. New sophisticated strategies to inhibit fungal growth are thus urgently needed. Among potential candidate molecules that strongly inhibit fungal spore germination are small cationic, cysteine-stabilized proteins of the AFP family secreted by a group of filamentous Ascomycetes. Its founding member, AFP from Aspergillus giganteus, is of particular interest since it selectively inhibits the growth of filamentous fungi without affecting the viability of mammalian, plant or bacterial cells. AFPs are also characterized by their high efficacy and stability. Thus, AFP can serve as a lead compound for the development of novel antifungals. Notably, all members of the AFP family comprise a γ-core motif which is conserved in all antimicrobial proteins from pro- and eukaryotes and known to interfere with the integrity of cytoplasmic plasma membranes. In this study, we used classical molecular dynamics simulations combined with wet lab experiments and NMR spectroscopy to characterize the structure and dynamical behavior of AFP isomers in solution and their interaction with fungal model membranes. We demonstrate that the γ-core motif of structurally conserved AFP is the key for its membrane interaction, thus verifying for the first time that the conserved γ-core motif of antimicrobial proteins is directly involved in protein-membrane interaction. Furthermore, molecular dynamic simulations suggested that AFP does not destroy the fungal membrane by pore formation but covers its surface in a well-defined manner executing multi-step mechanism to destroy the membranes integrity
Identification of SLAC1 anion channel residues required for CO2 signaling in Arabidopsis guard cellsZhang, J., N. Wang, Y. Miao, F. Hauser, J.A. McCammon, W.-J. Rappel, J. SchroederProc. Natl. Acad. Sci. USA, 115, (44), 11129-11137 (2018)    
Increases in CO2 concentration in plant leaves due to respiration in the dark and the continuing atmospheric [CO2] rise cause closing of stomatal pores, thus affecting plantÐwater relations globally. However, the underlying CO2/bicarbonate (CO2/HCO3_) sensing mechanisms remain unknown. [CO2] elevation in leaves triggers stomatal closure by anion efflux mediated via the SLAC1 anion channel localized in the plasma membrane of guard cells. Previous reconstitution analysis has suggested that intracellular bicarbonate ions might directly up-regulate SLAC1 channel activity. However, whether such a CO2/HCO3_ regulation of SLAC1 is relevant for CO2 control of stomatal movements in planta remains unknown. Here, we computationally probe for candidate bicarbonate-interacting sites within the SLAC1 anion channel via long-timescale Gaussian accelerated molecular dynamics (GaMD) simulations. Mutations of two putative bicarbonate-interacting residues, R256 and R321, impaired the enhancement of the SLAC1 anion channel activity by CO2/HCO3_ in Xenopus oocytes. Mutations of the neighboring charged amino acid K255 and residue R432 and the predicted gate residue F450 did not affect HCO3_ regulation of SLAC1. Notably, gas-exchange experiments with slac1-transformed plants expressing mutated SLAC1 proteins revealed that the SLAC1 residue R256 is required for CO2regulation of stomatal movements in planta, but not for abscisic acid (ABA)-induced stomatal closing. Patch clamp analyses of guard cells show that activation of S-type anion channels by CO2/HCO3_, but not by ABA, was impaired, indicating the relevance of R256 for CO2 signal transduction. Together, these analyses suggest that the SLAC1 anion channel is one of the physiologically relevant CO2/HCO3_sensors in guard cells.
Heterogeneous solvation in distinctive protein-protein interfaces revealed by molecular dynamics simulations.Ricci, C., J.A. McCammonJ. Phys. Chem. B (Bill Eaton Festschrift), 122, 49, 11695-11701 (2018)    
Water, despite being a driving force in biochemical processes, has an elusively complex microscopic behavior. While water can increase its local density near amphiphilic protein surfaces, water is also thought to evaporate from hydrophobic surfaces and cavities, an effect known as “dewetting”. The existence and extent of dewetting effects remains elusive due to the difficulty in observing clear “drying” transitions in experiments or simulations. Here, we use explicit solvent molecular dynamics (MD) simulations to study the molecular solvation at the binding interfaces of two distinctive molecular complexes: the highly hydrophilic barnase-barstar and the highly hydrophobic MDM2-p53. Our simulations, in conjunction with simple volumetric analyses, reveal a strikingly different water behavior at the binding interfaces of these two molecular complexes. In both complexes, we observe significant changes in the water local density as the two proteins approach, supporting the existence of a clear dewetting transition in the case of MDM2-p53, with an onset distance of 5.6-7.6Å. Furthermore, the solvation analysis reported herein is a valuable tool to capture and quantify persistent or transient dewetting events in future explicit solvent MD simulations.
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