Search

Group VIA calcium-independent phospholipase A 2 (iPLA 2 ) is a member of the PLA 2 superfamily that exhibits calcium-independent activity in contrast to the other two major types, secreted phospholipase A 2 (sPLA 2 ) and cytosolic phospholipase A 2 (cPLA 2 ), which both require calcium for their enzymatic activity. Adenosine triphosphate (ATP) has been reported to allosterically activate iPLA 2 , and this has now been verified with a lipidomics-based mixed-micelle assay, but its mechanism of action has been unknown. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) was employed to identify ATP interaction peptide regions located within the ankyrin repeat domain at which ATP interacts. Molecular dynamics simulations revealed the mechanism by which ATP binds to its site and the main residues that interact. Site-directed mutagenesis was used to verify the importance of these residues in the role of ATP in regulating iPLA 2 activity. Importantly, calcium was found to abolish the enhancing regulatory function of ATP and to promote the inhibitory activity by calmodulin. Given previous evidence that calcium does not bind directly to iPLA 2 , its effect appears to be indirect via association with ATP and/or calmodulin. Using HDX-MS, we found that calmodulin interacts with the N terminus peptide region of iPLA 2 consisting of residues 20 to 28. These two regulatory iPLA 2 sites open the road to the development of potential targets for therapeutic intervention., Competing Interests: Competing interests statement:The authors declare no competing interest.

We present the NetSci program-an open-source scientific software package designed for estimating mutual information (MI) between data sets using GPU acceleration and a k-nearest-neighbor algorithm. This approach significantly enhances calculation speed, achieving improvements of several orders of magnitude over traditional CPU-based methods, with data set size limits dictated only by available hardware. To validate NetSci, we accurately compute MI for an analytically verifiable two-dimensional Gaussian distribution and replicate the generalized correlation (GC) analysis previously conducted on the B1 domain of protein G. We also apply NetSci to molecular dynamics simulations of the Sarcoendoplasmic Reticulum Calcium-ATPase (SERCA) pump, exploring the allosteric mechanisms and pathways influenced by ATP and 2'-deoxy-ATP (dATP) binding. Our analysis reveals distinct allosteric effects induced by ATP compared to dATP, with predicted information pathways from the bound nucleotide to the calcium-binding domain differing based on the nucleotide involved. NetSci proves to be a valuable tool for estimating MI and GC in various data sets and is particularly effective for analyzing intraprotein communication and information transfer.

We develop a hybrid approach that combines the Monte Carlo (MC) method, a variational implicit-solvent model (VISM), and a binary level-set method for the simulation of biomolecular binding in an aqueous solvent. The solvation free energy for the biomolecular complex is estimated by minimizing the VISM free-energy functional of all possible solute-solvent interfaces that are used as dielectric boundaries. This functional consists of the solute volumetric, solute-solvent interfacial, solute-solvent van der Waals interaction, and electrostatic free energy. A technique of shifting the dielectric boundary is used to accurately predict the electrostatic part of the solvation free energy. Minimizing such a functional in each MC move is made possible by our new and fast binary level-set method. This method is based on the approximation of surface area by the convolution of an indicator function with a compactly supported kernel and is implemented by simple flips of numerical grid cells locally around the solute-solvent interface. We apply our approach to the p53-MDM2 system for which the two molecules are approximated by rigid bodies. Our efficient approach captures some of the poses before the final bound state. All-atom molecular dynamics simulations with most of such poses quickly reach the final bound state. Our work is a new step toward realistic simulations of biomolecular interactions. With further improvement of coarse graining and MC sampling, and combined with other models, our hybrid approach can be used to study the free-energy landscape and kinetic pathways of ligand binding to proteins.

Ligand-receptor binding and unbinding are fundamental biomolecular processes and particularly essential to drug efficacy. Environmental water fluctuations, however, impact the corresponding thermodynamics and kinetics and thereby challenge theoretical descriptions. Here, we devise a holistic, implicit-solvent, multimethod approach to predict the (un)binding kinetics for a generic ligand-pocket model. We use the variational implicit-solvent model (VISM) to calculate the solute-solvent interfacial structures and the corresponding free energies, and combine the VISM with the string method to obtain the minimum energy paths and transition states between the various metastable ("dry" and "wet") hydration states. The resulting dry-wet transition rates are then used in a spatially dependent multistate continuous-time Markov chain Brownian dynamics simulation and the related Fokker-Planck equation calculations of the ligand stochastic motion, providing the mean first-passage times for binding and unbinding. We find the hydration transitions to significantly slow down the binding process, in semiquantitative agreement with existing explicit-water simulations, but significantly accelerate the unbinding process. Moreover, our methods allow the characterization of nonequilibrium hydration states of pocket and ligand during the ligand movement, for which we find substantial memory and hysteresis effects for binding vs. unbinding. Our study thus provides a significant step forward toward efficient, physics-based interpretation and predictions of the complex kinetics in realistic ligand-receptor systems.

Fatty acid biosynthesis in α- and γ-proteobacteria requires two functionally distinct dehydratases, FabA and FabZ. Here, mechanistic cross-linking facilitates the structural characterization of a stable hexameric complex of six Escherichia coli FabZ dehydratase subunits with six AcpP acyl carrier proteins. The crystal structure sheds light on the divergent substrate selectivity of FabA and FabZ by revealing distinct architectures of the binding pocket. Molecular dynamics simulations demonstrate differential biasing of substrate orientations and conformations within the active sites of FabA and FabZ such that FabZ is preorganized to catalyze only dehydration, while FabA is primed for both dehydration and isomerization., Competing Interests: The authors declare no conflict of interest.

The atomic-level mechanisms that coordinate ligand release from protein pockets are only known for a handful of proteins. Here, we report results from accelerated molecular dynamics simulations for benzene dissociation from the buried cavity of the T4 lysozyme Leu99Ala mutant (L99A). In these simulations, benzene is released through a previously characterized, sparsely populated room-temperature excited state of the mutant, explaining the coincidence for experimentally measured benzene off rate and apo protein slow-timescale NMR relaxation rates between ground and excited states. The path observed for benzene egress is a multistep ligand migration from the buried cavity to ultimate release through an opening between the F/G-, H-, and I-helices and requires a number of cooperative multiresidue and secondary-structure rearrangements within the C-terminal domain of L99A. These rearrangements are identical to those observed along the ground state to excited state transitions characterized by molecular dynamic simulations run on the Anton supercomputer. Analyses of the molecular properties of the residues lining the egress path suggest that protein surface electrostatic potential may play a role in the release mechanism. Simulations of wild-type T4 lysozyme also reveal that benzene-egress-associated dynamics in the L99A mutant are potentially exaggerations of the substrate-processivity-related dynamics of the wild type., (Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

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 5.6-7.6 Å. 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.

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 harmonic force constants 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. 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.

Understanding the conformational dynamics of CRISPR (clustered regularly interspaced short palindromic repeat)-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., Competing Interests: Conflict of interest. None.

CRISPR-Cas9 is a genome editing technology with major impact in life sciences. In this system, the endonuclease Cas9 generates double strand breaks in DNA upon RNA-guided recognition of a complementary DNA sequence, which strictly requires the presence of a protospacer adjacent motif (PAM) next to the target site. Although PAM recognition is essential for cleavage, it is unknown whether and how PAM binding activates Cas9 for DNA cleavage at spatially distant sites. Here, we find evidence of a PAM-induced allosteric mechanism revealed by microsecond molecular dynamics simulations. PAM acts as an allosteric effector and triggers the interdependent conformational dynamics of the Cas9 catalytic domains (HNH and RuvC), responsible for concerted cleavage of the two DNA strands. Targeting such an allosteric mechanism should enable control of CRISPR-Cas9 functionality.

CRISPR-Cas9 has become a facile genome editing technology, yet the structural and mechanistic features underlying its function are unclear. Here, we perform extensive molecular simulations in an enhanced sampling regime, using a Gaussian-accelerated molecular dynamics (GaMD) methodology, which probes displacements over hundreds of microseconds to milliseconds, to reveal the conformational dynamics of the endonuclease Cas9 during its activation toward catalysis. We disclose the conformational transition of Cas9 from its apo form to the RNA-bound form, suggesting a mechanism for RNA recruitment in which the domain relocations cause the formation of a positively charged cavity for nucleic acid binding. GaMD also reveals the conformation of a catalytically competent Cas9, which is prone for catalysis and whose experimental characterization is still limited. We show that, upon DNA binding, the conformational dynamics of the HNH domain triggers the formation of the active state, explaining how the HNH domain exerts a conformational control domain over DNA cleavage [Sternberg SH et al. (2015) Nature , 527 , 110-113]. These results provide atomic-level information on the molecular mechanism of CRISPR-Cas9 that will inspire future experimental investigations aimed at fully clarifying the biophysics of this unique genome editing machinery and at developing new tools for nucleic acid manipulation based on CRISPR-Cas9., Competing Interests: Conflict of interest statement: R.C.W. became a full-time employee of GlaxoSmithKline (GSK) in November 2016. This research was conducted prior to R.C.W. joining GSK and was not funded by GSK.

Activation of the first sphingosine-1-phosphate receptor (S1PR 1 ) promotes permeability of the blood brain barrier, astrocyte and neuronal protection, and lymphocyte egress from secondary lymphoid tissues. Although an agonist often activates the S1PR 1 , the receptor exhibits high levels of basal activity. In this study, we performed long-timescale molecular dynamics and accelerated molecular dynamics (aMD) simulations to investigate activation mechanisms of the ligand-free (apo) S1PR 1 . In the aMD enhanced sampling simulations, we observed four independent events of activation, which is characterized by close interaction between Y311 7.53 and Y221 5.58 and increased distance between the intracellular ends of transmembrane (TM) helices 3 and 6. Although TM helices TM3, TM6, TM5 and, TM7 are associated with GPCR activation, we discovered that their movements are not necessarily correlated during activation. Instead, TM5 showed a decreased correlation with each of these regions during activation. During activation of the apo receptor, Y221 5.58 and Y311 7.53 became more solvated, because a water channel formed in the intracellular pocket. Additionally, a lipid molecule repeatedly entered the receptor between the extracellular ends of TM1 and TM7, providing important insights into the pathway of ligand entry into the S1PR 1 ., (© 2017 The Protein Society.)

Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that provides efficient free energy calculations of biomolecules. Like the previous accelerated molecular dynamics (aMD), GaMD allows for "unconstrained" enhanced sampling without the need to set predefined collective variables and so is useful for studying complex biomolecular conformational changes such as protein folding and ligand binding. Furthermore, because the boost potential is constructed using a harmonic function that follows Gaussian distribution in GaMD, cumulant expansion to the second order can be applied to recover the original free energy profiles of proteins and other large biomolecules, which solves a long-standing energetic reweighting problem of the previous aMD method. Taken together, GaMD offers major advantages for both unconstrained enhanced sampling and free energy calculations of large biomolecules. Here, we have implemented GaMD in the NAMD package on top of the existing aMD feature and validated it on three model systems: alanine dipeptide, the chignolin fast-folding protein, and the M 3 muscarinic G protein-coupled receptor (GPCR). For alanine dipeptide, while conventional molecular dynamics (cMD) simulations performed for 30 ns are poorly converged, GaMD simulations of the same length yield free energy profiles that agree quantitatively with those of 1000 ns cMD simulation. Further GaMD simulations have captured folding of the chignolin and binding of the acetylcholine (ACh) endogenous agonist to the M 3 muscarinic receptor. The reweighted free energy profiles are used to characterize the protein folding and ligand binding pathways quantitatively. GaMD implemented in the scalable NAMD is widely applicable to enhanced sampling and free energy calculations of large biomolecules.

G-protein coupled receptors (GPCRs), the largest family of human membrane proteins, mediate cellular signaling and represent primary targets of about one third of currently marketed drugs. GPCRs undergo highly dynamic structural transitions during signal transduction, from binding of extracellular ligands to coupling with intracellular effector proteins. Molecular dynamics (MD) simulations have been utilized to investigate GPCR signaling mechanisms (such as pathways of ligand binding and receptor activation/deactivation) and to design novel small-molecule drug candidates. Future research directions point towards modeling cooperative binding of multiple orthosteric and allosteric ligands to GPCRs, GPCR oligomerization and interactions of GPCRs with different intracellular signaling proteins. Through methodological and supercomputing advances, MD simulations will continue to provide important insights into GPCR signaling mechanisms and further facilitate structure-based drug design., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Folding of four fast-folding proteins, including chignolin, Trp-cage, villin headpiece and WW domain, was simulated via accelerated molecular dynamics (aMD). In comparison with hundred-of-microsecond timescale conventional molecular dynamics (cMD) simulations performed on the Anton supercomputer, aMD captured complete folding of the four proteins in significantly shorter simulation time. The folded protein conformations were found within 0.2-2.1 Å of the native NMR or X-ray crystal structures. Free energy profiles calculated through improved reweighting of the aMD simulations using cumulant expansion to the second-order are in good agreement with those obtained from cMD simulations. This allows us to identify distinct conformational states (e.g., unfolded and intermediate) other than the native structure and the protein folding energy barriers. Detailed analysis of protein secondary structures and local key residue interactions provided important insights into the protein folding pathways. Furthermore, the selections of force fields and aMD simulation parameters are discussed in detail. Our work shows usefulness and accuracy of aMD in studying protein folding, providing basic references in using aMD in future protein-folding studies., (© 2015 Wiley Periodicals, Inc.)

Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges.

Many excellent methods exist that incorporate cryo-electron microscopy (cryoEM) data to constrain computational protein structure prediction and refinement. Previously, it was shown that iteration of two such orthogonal sampling and scoring methods – Rosetta and molecular dynamics (MD) simulations – facilitated exploration of conformational space in principle. Here, we go beyond a proof-of-concept study and address significant remaining limitations of the iterative MD–Rosetta protein structure refinement protocol. Specifically, all parts of the iterative refinement protocol are now guided by medium-resolution cryoEM density maps, and previous knowledge about the native structure of the protein is no longer necessary. Models are identified solely based on score or simulation time. All four benchmark proteins showed substantial improvement through three rounds of the iterative refinement protocol. The best-scoring final models of two proteins had sub-Ångstrom RMSD to the native structure over residues in secondary structure elements. Molecular dynamics was most efficient in refining secondary structure elements and was thus highly complementary to the Rosetta refinement which is most powerful in refining side chains and loop regions.

In protein-ligand binding, the electrostatic environments of the two binding partners may vary significantly in bound and unbound states, which may lead to protonation changes upon binding. In cases where ligand binding results in a net uptake or release of protons, the free energy of binding is pH-dependent. Nevertheless, conventional free energy calculations and molecular docking protocols typically do not rigorously account for changes in protonation that may occur upon ligand binding. To address these shortcomings, we present a simple methodology based on Wyman's binding polynomial formalism to account for the pH dependence of binding free energies and demonstrate its use on cucurbit[7]uril (CB[7]) host-guest systems. Using constant pH molecular dynamics and a reference binding free energy that is taken either from experiment or from thermodynamic integration computations, the pH-dependent binding free energy is determined. This computational protocol accurately captures the large pKa shifts observed experimentally upon CB[7]:guest association and reproduces experimental binding free energies at different levels of pH. We show that incorrect assignment of fixed protonation states in free energy computations can give errors of >2 kcal/mol in these host-guest systems. Use of the methods presented here avoids such errors, thus suggesting their utility in computing proton-linked binding free energies for protein-ligand complexes.

Cardiac troponin (cTn) is a key molecule in the regulation of human cardiac muscle contraction. The N-terminal cardiac-specific peptide of the inhibitory subunit of troponin, cTnI (cTnI(1-39)), is a target for phosphorylation by protein kinase A (PKA) during β-adrenergic stimulation. We recently presented evidence indicating that this peptide interacts with the inhibitory peptide (cTnl(137-147)) when S23 and S24 are phosphorylated. The inhibitory peptide is also the target of the point mutation cTnI-R145G, which is associated with hypertrophic cardiomyopathy (HCM), a disease associated with sudden death in apparently healthy young adults. It has been shown that both phosphorylation and this mutation alter the cTnC-cTnI (C-I) interaction, which plays a crucial role in modulating contractile activation. However, little is known about the molecular-level events underlying this modulation. Here, we computationally investigated the effects of the cTnI-R145G mutation on the dynamics of cTn, cTnC Ca(2+) handling, and the C-I interaction. Comparisons were made with the cTnI-R145G/S23D/S24D phosphomimic mutation, which has been used both experimentally and computationally to study the cTnI N-terminal specific effects of PKA phosphorylation. Additional comparisons between the phosphomimic mutations and the real phosphorylations were made. For this purpose, we ran triplicate 150 ns molecular dynamics simulations of cTnI-R145G Ca(2+)-bound cTnC(1-161)-cTnI(1-172)-cTnT(236-285), cTnI-R145G/S23D/S24D Ca(2+)-bound cTnC(1-161)-cTnI(1-172)-cTnT(236-285), and cTnI-R145G/PS23/PS24 Ca(2+)-bound cTnC(1-161)-cTnI(1-172)-cTnT(236-285), respectively. We found that the cTnI-R145G mutation did not impact the overall dynamics of cTn, but stabilized crucial Ca(2+)-coordinating interactions. However, the phosphomimic mutations increased overall cTn fluctuations and destabilized Ca(2+) coordination. Interestingly, cTnI-R145G blunted the intrasubunit interactions between the cTnI N-terminal extension and the cTnI inhibitory peptide, which have been suggested to play a crucial role in modulating troponin function during β-adrenergic stimulation. These findings offer a molecular-level explanation for how the HCM mutation cTnI-R145G reduces the modulation of cTn by phosphorylation of S23/S24 during β-adrenergic stimulation., (Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Serine proteases are involved in many fundamental physiological processes, and control of their activity mainly results from the fact that they are synthetized in an inactive form that becomes active upon cleavage. Three decades ago Martin Karplus's group performed the first molecular dynamics simulations of trypsin, the most studied member of the serine protease family, to address the transition from the zymogen to its active form. Based on the computational power available at the time, only high frequency fluctuations, but not the transition steps, could be observed. By performing accelerated molecular dynamics (aMD) simulations, an interesting approach that increases the configurational sampling of atomistic simulations, we were able to observe the N-terminal tail insertion, a crucial step of the transition mechanism. Our results also support the hypothesis that the hydrophobic effect is the main force guiding the insertion step, although substantial enthalpic contributions are important in the activation mechanism. As the N-terminal tail insertion is a conserved step in the activation of serine proteases, these results afford new perspective on the underlying thermodynamics of the transition from the zymogen to the active enzyme., (© 2014 The Protein Society.)

During β-adrenergic stimulation, cardiac troponin I (cTnI) is phosphorylated by protein kinase A (PKA) at sites S23/S24, located at the N-terminus of cTnI. This phosphorylation has been shown to decrease KCa and pCa50, and weaken the cTnC-cTnI (C-I) interaction. We recently reported that phosphorylation results in an increase in the rate of early, slow phase of relaxation (kREL,slow) and a decrease in its duration (tREL,slow), which speeds up the overall relaxation. However, as the N-terminus of cTnI (residues 1-40) has not been resolved in the whole cardiac troponin (cTn) structure, little is known about the molecular-level behavior within the whole cTn complex upon phosphorylation of the S23/S24 residues of cTnI that results in these changes in function. In this study, we built up the cTn complex structure (including residues cTnC 1-161, cTnI 1-172, and cTnT 236-285) with the N-terminus of cTnI. We performed molecular-dynamics (MD) simulations to elucidate the structural basis of PKA phosphorylation-induced changes in cTn structure and Ca(2+) binding. We found that introducing two phosphomimic mutations into sites S23/S24 had no significant effect on the coordinating residues of Ca(2+) binding site II. However, the overall fluctuation of cTn was increased and the C-I interaction was altered relative to the wild-type model. The most significant changes involved interactions with the N-terminus of cTnI. Interestingly, the phosphomimic mutations led to the formation of intrasubunit interactions between the N-terminus and the inhibitory peptide of cTnI. This may result in altered interactions with cTnC and could explain the increased rate and decreased duration of slow-phase relaxation seen in myofibrils., (Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Transcription factor IIS (TFIIS) is a protein known for catalyzing the cleavage reaction of the 3'-end of backtracked RNA transcript, allowing RNA polymerase II (Pol II) to reactivate the transcription process from the arrested state. Recent structural studies have provided a molecular basis of protein-protein interaction between TFIIS and Pol II. However, the detailed dynamic conformational changes of TFIIS upon binding to Pol II and the related thermodynamic information are largely unknown. Here we use computational approaches to investigate the conformational space of TFIIS in the Pol II-bound and Pol II-free (unbound) states. Our results reveal two distinct conformations of TFIIS: the closed and the open forms. The closed form is dominant in the Pol II-free (unbound) state of TFIIS, whereas the open form is favorable in the Pol II-bound state. Furthermore, we discuss the free energy difference involved in the conformational changes between the two forms in the presence or absence of Pol II. Additionally, our analysis indicates that hydrophobic interactions and the protein-protein interactions between TFIIS and Pol II are crucial for inducing the conformational changes of TFIIS. Our results provide novel insights into the functional interplay between Pol II and TFIIS as well as mechanism of reactivation of Pol II transcription by TFIIS.

Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value of λ seed the conformational space sampled at another λ value. Adapting the value of λ throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the λ value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of λ, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors.

Sortase cysteine transpeptidases covalently attach proteins to the bacterial cell wall or assemble fiber-like pili that promote bacterial adhesion. Members of this enzyme superfamily are widely distributed in Gram-positive bacteria that frequently utilize multiple sortases to elaborate their peptidoglycan. Sortases catalyze transpeptidation using a conserved active site His-Cys-Arg triad that joins a sorting signal located at the C terminus of their protein substrate to an amino nucleophile located on the cell surface. However, despite extensive study, the catalytic mechanism and molecular basis of substrate recognition remains poorly understood. Here we report the crystal structure of the Staphylococcus aureus sortase B enzyme in a covalent complex with an analog of its NPQTN sorting signal substrate, revealing the structural basis through which it displays the IsdC protein involved in heme-iron scavenging from human hemoglobin. The results of computational modeling, molecular dynamics simulations, and targeted amino acid mutagenesis indicate that the backbone amide of Glu(224) and the side chain of Arg(233) form an oxyanion hole in sortase B that stabilizes high energy tetrahedral catalytic intermediates. Surprisingly, a highly conserved threonine residue within the bound sorting signal substrate facilitates construction of the oxyanion hole by stabilizing the position of the active site arginine residue via hydrogen bonding. Molecular dynamics simulations and primary sequence conservation suggest that the sorting signal-stabilized oxyanion hole is a universal feature of enzymes within the sortase superfamily.

Thrombin is the central protease in the cascade of blood coagulation proteases. The structure of thrombin consists of a double β-barrel core surrounded by connecting loops and helices. Compared to chymotrypsin, thrombin has more extended loops that are thought to have arisen from insertions in the serine protease that evolved to impart greater specificity. Previous experiments showed thermodynamic coupling between ligand binding at the active site and distal exosites. We present a combined approach of molecular dynamics (MD), accelerated molecular dynamics (AMD), and analysis of the residual local frustration of apo-thrombin and active-site-bound (PPACK-thrombin). Community analysis of the MD ensembles identified changes upon active site occupation in groups of residues linked through correlated motions and physical contacts. AMD simulations, calibrated on measured residual dipolar couplings, reveal that upon active site ligation, correlated loop motions are quenched, but new ones connecting the active site with distal sites where allosteric regulators bind emerge. Residual local frustration analysis reveals a striking correlation between frustrated contacts and regions undergoing slow time scale dynamics. The results elucidate a motional network that probably evolved through retention of frustrated contacts to provide facile conversion between ensembles of states.

Molecular dynamics simulation using enhanced sampling methods is one of the powerful computational tools used to explore protein conformations and free energy landscapes. Enhanced sampling methods often employ either an increase in temperature or a flattening of the potential energy surface to rapidly sample phase space, and a corresponding reweighting algorithm is used to recover the Boltzmann statistics. However, potential energies of complex biomolecules usually involve large fluctuations on a magnitude of hundreds of kcal/mol despite minimal structural changes during simulation. This leads to noisy reweighting statistics and complicates the obtainment of accurate final results. To overcome this common issue in enhanced conformational sampling, we propose a scaled molecular dynamics method, which modifies the biomolecular potential energy surface and employs a reweighting scheme based on configurational populations. Statistical mechanical theory is applied to derive the reweighting formula, and the canonical ensemble of simulated structures is recovered accordingly. Test simulations on alanine dipeptide and the fast folding polypeptide Chignolin exhibit sufficiently enhanced conformational sampling and accurate recovery of free energy surfaces and thermodynamic properties. The results are comparable to long conventional molecular dynamics simulations and exhibit better recovery of canonical statistics over methods which employ a potential energy term in reweighting.

The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signaling pathway a GPCR promotes intracellular signals though β-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that a GPCR forms a distinct ensemble of conformations signaling through the G protein and β-arrestin. Here we report on the dynamics of the β2 adrenergic receptor bound to the β-arrestin and G protein-biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring of the transition within the nanosecond time scale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the β-arrestin-biased agonist N-cyclopentylbutanepherine, we observe a different pattern of motions in helix 7 when compared to simulations with the G protein-biased agonist salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs.

The mechanism of inhibition of group VIA Ca(2+)-independent phospholipase A(2) (iPLA(2)) by fluoroketone (FK) ligands is examined by a combination of deuterium exchange mass spectrometry (DXMS) and molecular dynamics (MD). Models for iPLA(2) were built by homology with the known structure of patatin and equilibrated by extensive MD simulations. Empty pockets were identified during the simulations and studied for their ability to accommodate FK inhibitors. Ligand docking techniques showed that the potent inhibitor 1,1,1,3-tetrafluoro-7-phenylheptan-2-one (PHFK) forms favorable interactions inside an active-site pocket, where it blocks the entrance of phospholipid substrates. The polar fluoroketone headgroup is stabilized by hydrogen bonds with residues Gly486, Gly487, and Ser519. The nonpolar aliphatic chain and aromatic group are stabilized by hydrophobic contacts with Met544, Val548, Phe549, Leu560, and Ala640. The binding mode is supported by DXMS experiments showing an important decrease of deuteration in the contact regions in the presence of the inhibitor. The discovery of the precise binding mode of FK ligands to the iPLA(2) should greatly improve our ability to design new inhibitors with higher potency and selectivity.

Group VI Ca²⁺-independent phospholipase A₂ (iPLA₂) is a water-soluble enzyme that is active when associated with phospholipid membranes. Despite its clear pharmaceutical relevance, no X-ray or NMR structural information is currently available for the iPLA₂ or its membrane complex. In this paper, we combine homology modeling with coarse-grained (CG) and all-atom (AA) molecular dynamics (MD) simulations to build structural models of iPLA₂ in association with a phospholipid bilayer. CG-MD simulations of the membrane insertion process were employed to provide a starting point for an atomistic description. Six AA-MD simulations were then conducted for 60 ns, starting from different initial CG structures, to refine the membrane complex. The resulting structures are shown to be consistent with each other and with deuterium exchange mass spectrometry (DXMS) experiments, suggesting that our approach is suitable for the modeling of iPLA₂ at the membrane surface. The models show that an anchoring region (residues 710-724) forms an amphipathic helix that is stabilized by the membrane. In future studies, the proposed iPLA₂ models should provide a structural basis for understanding the mechanisms of lipid extraction and drug-inhibition. In addition, the dual-resolution approach discussed here should provide the means for the future exploration of the impact of lipid diversity and sequence mutations on the activity of iPLA₂ and related enzymes.

Sortase enzymes are vitally important for the virulence of gram-positive bacteria as they play a key role in the attachment of surface proteins to the cell wall. These enzymes recognize a specific sorting sequence in proteins destined to be displayed on the surface of the bacteria and catalyze the transpeptidation reaction that links it to a cell wall precursor molecule. Because of their role in establishing pathogenicity, and in light of the recent rise of antibiotic-resistant bacterial strains, sortase enzymes are novel drug targets. Here, we present a study of the prototypical sortase protein Staphylococcus aureus Sortase A (SrtA). Both conventional and accelerated molecular dynamics simulations of S. aureus SrtA in its apo state and when bound to an LPATG sorting signal (SS) were performed. Results support a binding mechanism that may be characterized as conformational selection followed by induced fit. Additionally, the SS was found to adopt multiple metastable states, thus resolving discrepancies between binding conformations in previously reported experimental structures. Finally, correlation analysis reveals that the SS actively affects allosteric pathways throughout the protein that connect the first and the second substrate binding sites, which are proposed to be located on opposing faces of the protein. Overall, these calculations shed new light on the role of dynamics in the binding mechanism and function of sortase enzymes., (Copyright © 2012 The Protein Society.)

Enoyl-acyl carrier protein reductase (ENR) is a crucial enzyme in the type II fatty acid synthesis pathway of many pathogens such as Plasmodium falciparum, the etiological agent of the most severe form of malaria. Because of its essential function of fatty acid double bond reduction and the absence of a human homologue, PfENR is an interesting drug target. Although extensive knowledge of the protein structure has been gathered over the last decade, comparatively little remains known about the dynamics of this crucial enzyme. Here, we perform extensive molecular dynamics simulations of tetrameric PfENR in different states of cofactor and ligand binding, and with a variety of different ligands bound. A pocket-volume analysis is also performed, and virtual screening is used to identify potential druggable hotspots. The implications of the results for future drug-discovery projects are discussed., (Copyright © 2012 The Protein Society.)

Troponin (Tn) is an important regulatory protein in the thin-filament complex of cardiomyocytes. Calcium binding to the troponin C (TnC) subunit causes a change in its dynamics that leads to the transient opening of a hydrophobic patch on TnC's surface, to which a helix of another subunit, troponin I (TnI), binds. This process initiates contraction, making it an important target for studies investigating the detailed molecular processes that underlie contraction. Here we use microsecond-timescale Anton molecular dynamics simulations to investigate the dynamics and kinetics of the opening transition of the TnC hydrophobic patch. Free-energy differences for opening are calculated for wild-type Ca(2+)-bound TnC (∼8 kcal/mol), V44Q Ca(2+)-bound TnC (3.2 kcal/mol), E40A Ca(2+)-bound TnC (∼12 kcal/mol), and wild-type apo TnC (∼20 kcal/mol). These results suggest that the mutations have a profound impact on the frequency with which the hydrophobic patch presents to TnI. In addition, these simulations corroborate that cardiac wild-type TnC does not open on timescales relevant to contraction without calcium being bound., (Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

During the past century, several epidemics of human African trypanosomiasis, a deadly disease caused by the protist Trypanosoma brucei, have afflicted sub-Saharan Africa. Over 10 000 new victims are reported each year, with hundreds of thousands more at risk. As current drug treatments are either highly toxic or ineffective, novel trypanocides are urgently needed. The T. brucei galactose synthesis pathway is one potential therapeutic target. Although galactose is essential for T. brucei survival, the parasite lacks the transporters required to intake galactose from the environment. UDP-galactose 4'-epimerase (TbGalE) is responsible for the epimerization of UDP-glucose to UDP-galactose and is therefore of great interest to medicinal chemists. Using molecular dynamics simulations, we investigate the atomistic motions of TbGalE in both the apo and holo states. The sampled conformations and protein dynamics depend not only on the presence of a UDP-sugar ligand, but also on the chirality of the UDP-sugar C4 atom. This dependence provides important insights into TbGalE function and may help guide future computer-aided drug discovery efforts targeting this protein., (© 2012 John Wiley & Sons A/S.)

Troponin C (TnC) is an important regulatory molecule in cardiomyocytes. Calcium binding to site II in TnC initiates a series of molecular events that result in muscle contraction. The most direct change upon Ca(2+) binding is an opening motion of the molecule that exposes a hydrophobic patch on the surface allowing for Troponin I to bind. Molecular dynamics simulations were used to elucidate the dynamics of this crucial protein in three different states: apo, Ca(2+)-bound, and Ca(2+)-TnI-bound. Dynamics between the states are compared, and the Ca(2+)-bound system is investigated for opening motions. On the basis of the simulations, NMR chemical shifts and order parameters are calculated and compared with experimental observables. Agreement indicates that the simulations sample the relevant dynamics of the system. Brownian dynamics simulations are used to investigate the calcium association of TnC. We find that calcium binding gives rise to correlative motions involving the EF hand and collective motions conducive of formation of the TnI-binding interface. We furthermore indicate the essential role of electrostatic steering in facilitating diffusion-limited binding of Ca(2+).

The backbone dynamics of human α-thrombin inhibited at the active site serine were analyzed using R(1), R(2), and heteronuclear NOE experiments, variable temperature TROSY 2D [(1)H-(15)N] correlation spectra, and R(ex) measurements. The N-terminus of the heavy chain, which is formed upon zymogen activation and inserts into the protein core, is highly ordered, as is much of the double beta-barrel core. Some of the surface loops, by contrast, remain very dynamic with order parameters as low as 0.5 indicating significant motions on the ps-ns timescale. Regions of the protein that were thought to be dynamic in the zymogen and to become rigid upon activation, in particular the γ-loop, the 180s loop, and the Na(+) binding site have order parameters below 0.8. Significant R(ex) was observed in most of the γ-loop, in regions proximal to the light chain, and in the β-sheet core. Accelerated molecular dynamics simulations yielded a molecular ensemble consistent with measured residual dipolar couplings that revealed dynamic motions up to milliseconds. Several regions, including the light chain and two proximal loops, did not appear highly dynamic on the ps-ns timescale, but had significant motions on slower timescales., (Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

An alchemical free energy method with explicit solvent molecular dynamics simulations was applied as part of the blind prediction contest SAMPL3 to calculate binding free energies for seven guests to an acyclic cucurbit-[n]uril host. The predictions included determination of protonation states for both host and guests, docking pose generation, and binding free energy calculations using thermodynamic integration. We found a root mean square error (RMSE) of 3.6 kcal mol(-1) from the reference experimental results, with an R(2) correlation of 0.51. The agreement with experiment for the largest contributor to this error, guest 6, is improved by 1.7 kcal mol(-1) when a periodicity-induced free energy correction is applied. The corrections for the other ligands were significantly smaller, and altogether the RMSE was reduced by 0.4 kcal mol(-1). We link properties of the host-guest systems during simulation to errors in the computed free energies. Overall, we show that charged host-guest systems studied here, initialized in unconfirmed docking poses, present a challenge to accurate alchemical simulation methods.

We report altogether 3-μs molecular dynamics (MD) simulations of the antimicrobial peptide CM15 to systematically investigate its interaction with two model lipid bilayers, pure POPC and mixed POPG:POPC (1:2). Starting with either an α-helical or a random-coil conformation, CM15 is found to insert into both bilayers. Peptide-lipid interaction is stronger with the anionic POPG:POPC than the zwitterionic POPC, which is largely attributed to the electrostatic attraction between CM15 and the negatively charged POPG. Simulations initiated with CM15 as a random coil allowed us to study peptide folding at the lipid-water interface. Interestingly, CM15 folding appears to be faster in POPC than POPG:POPC, which may be explained by a lower activation energy barrier of structural rearrangement in the former system. Our data also suggest that compared with the random-coil conformation, CM15 in a pre-folded α-helix has significantly reduced interactions with the lipids, indicating that peptide initial structures may bias the simulation results considerably on the 100-ns timescale. The implications of this result should be considered when preparing and interpreting future AMP simulations., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Diffusion is often the rate determining step in many biological processes. Currently, the two main computational methods for studying diffusion are stochastic methods, such as Brownian dynamics, and continuum methods, such as the finite element method. This paper proposes a new hybrid diffusion method that couples the strengths of each of these two methods. The method is derived for a general multidimensional system, and is presented using a basic test case for 1D linear and radially symmetric diffusion systems.

The vitally important AAA (ATPases associated with various cellular activities) protein p97 is involved in cellular functions ranging from replication to degradation of misfolded proteins and has recently been proposed as a novel chemotherapeutic target. p97 is a large molecular machine that has been shown to hexamerize in vitro, with each monomer consisting of an N domain responsible for binding to effector proteins and two AAA repeats (D1 and D2). However, structural studies are inconclusive or in disagreement with one another on several important features such as the locations of the N domains, the relative orientations of the D1 and D2 rings, and the dimensions of the central pore. Here, we present atomic-scale simulations of the p97 hexamer in the prehydrolysis, transition, and post-hydrolysis states. To improve the agreement between low- and high-resolution experimental studies, we first use a biased simulation technique, molecular dynamics flexible fitting (MDFF), to improve the correlation between the structures described in these experiments. We follow this with extended, classical molecular dynamics simulations, which not only show that structures generated in the MDFF phase are stable, but reveal insights into the dynamics important to each state. Simulation results suggest a hybrid model for hydrolysis, in which the N and D2 domains are dynamic while the D1 domains are relatively static, salt bridges stabilize the position of the N domains in the pre-hydrolysis state, and the rings formed by D1 and D2 rotate relative to one another., (Copyright © 2012 The Protein Society.)

Molecular recognition plays a central role in biochemical processes. Although well studied, understanding the mechanisms of recognition is inherently difficult due to the range of potential interactions, the molecular rearrangement associated with binding, and the time and length scales involved. Computational methods have the potential for not only complementing experiments that have been performed, but also in guiding future ones through their predictive abilities. In this review, we discuss how molecular dynamics (MD) simulations may be used in advancing our understanding of the thermodynamics that drive biomolecular recognition. We begin with a brief review of the statistical mechanics that form a basis for these methods. This is followed by a description of some of the most commonly used methods: thermodynamic pathways employing alchemical transformations and potential of mean force calculations, along with end-point calculations for free energy differences, and harmonic and quasi-harmonic analysis for entropic calculations. Finally, a few of the fundamental findings that have resulted from these methods are discussed, such as the role of configurational entropy and solvent in intermolecular interactions, along with selected results of the model system T4 lysozyme to illustrate potential and current limitations of these methods.

An expanding repertoire of "allosteric" drugs is revealing that structure-based drug design (SBDD) is not restricted to the "active site" of the target protein. Such compounds have been shown to bind distant regions of the protein topography, potentially providing higher levels of target specificity, reduced toxicity and access to new regions of chemical space. Unfortunately, the location of such allosteric pockets is not obvious in the absence of a bound crystal structure and the ability to predict their presence would be useful in the discovery of novel therapies. Here, we describe a method for the prediction of "druggable" binding sites that takes protein flexibility into account through the use of molecular dynamics (MD) simulation. By using a dynamic representation of the target, we are able to sample multiple protein conformations that may expose new drug-binding surfaces. We perform a fragment-based mapping analysis of individual structures in the MD ensemble using the FTMAP algorithm and then rank the most prolific probe-binding protein residues to determine potential "hot-spots" for further examination. This approach has recently been applied to a pair of human G-protein-coupled receptors (GPCRs), resulting in the detection of five potential allosteric sites.

The method of accelerated molecular dynamics (aMD) has been shown to increase the rate of phase-space sampling in biomolecular simulations. In this chapter, we discuss the theory behind aMD and describe the implementation of two versions: dual-boost and selective aMD. Each method has its practical advantages: dual-boost aMD is useful for increasing sampling of global conformational motions while selective aMD can improve the rate of convergence of free energy calculations. Special emphasis is placed on the use of these methods in computer-aided drug design, and the example of oseltamivir binding to neuraminidase is highlighted for both cases.

Receptors are inherently dynamic and this flexibility is important to consider when constructing a model of molecular association. Conformations from molecular dynamics simulations, a well-established method for examining protein dynamics, can be used in virtual screening to account for flexibility in structure-based drug discovery. Different receptor configurations influence docking results. Molecular dynamics simulations can provide snapshots that improve virtual screening predictive power over known crystal structures, most likely as a result of sampling more relevant receptor conformations. Here we highlight some details and nuances of using such snapshots and evaluating them for predictive performance.

Many biologically important processes such as enzyme catalysis, signal transduction, ligand binding and allosteric regulation occur on the micro- to millisecond time-scale. Despite the sustained and rapid increase in available computational power and the development of efficient simulation algorithms, molecular dynamics (MD) simulations of proteins and bio-machines are generally limited to time-scales of tens to hundreds of nano-seconds. In this perspective article we present a comprehensive review of Accelerated Molecular Dynamics (AMD), an extended biased potential molecular dynamics approach that allows for the efficient study of bio-molecular systems up to time-scales several orders of magnitude greater than those accessible using standard classical MD methods, whilst still maintaining a fully atomistic representation of the system. Compared to many other approaches, AMD affords efficient enhanced conformational space sampling without any a priori understanding of the underlying free energy surface, nor does it require the specific prior definition of a reaction coordinate or a set of collective variables. Successful applications of the AMD method, including the study of slow time-scale functional dynamics in folded proteins and the conformational behavior of natively unstructured proteins are discussed and an outline of the different variants and extensions to the standard AMD approach is presented.

This review discusses the many roles atomistic computer simulations of macromolecular (for example, protein) receptors and their associated small-molecule ligands can play in drug discovery, including the identification of cryptic or allosteric binding sites, the enhancement of traditional virtual-screening methodologies, and the direct prediction of small-molecule binding energies. The limitations of current simulation methodologies, including the high computational costs and approximations of molecular forces required, are also discussed. With constant improvements in both computer power and algorithm design, the future of computer-aided drug design is promising; molecular dynamics simulations are likely to play an increasingly important role.

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life-threatening illness affecting 11-18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR) as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery.

Matrix metalloproteinases are zinc-containing enzymes capable of degrading all components of the extracellular matrix. Owing to their role in human disease, matrix metalloproteinase have been the subject of extensive study. A bioinorganic approach was recently used to identify novel inhibitors based on a maltol zinc-binding group, but accompanying molecular-docking studies failed to explain why one of these inhibitors, AM-6, had approximately 2500-fold selectivity for MMP-3 over MMP-2. A number of studies have suggested that the matrix-metalloproteinase active site is highly flexible, leading some to speculate that differences in active-site flexibility may explain inhibitor selectivity. To extend the bioinorganic approach in a way that accounts for MMP-2 and MMP-3 dynamics, we here investigate the predicted binding modes and energies of AM-6 docked into multiple structures extracted from matrix-metalloproteinase molecular dynamics simulations. Our findings suggest that accounting for protein dynamics is essential for the accurate prediction of binding affinity and selectivity. Additionally, AM-6 and other similar inhibitors likely select for and stabilize only a subpopulation of all matrix-metalloproteinase conformations sampled by the apo protein. Consequently, when attempting to predict ligand affinity and selectivity using an ensemble of protein structures, it may be wise to disregard protein conformations that cannot accommodate the ligand., (© 2011 John Wiley & Sons A/S.)

Molecular dynamics (MD) simulation is a well-established method for understanding protein dynamics. Conformations from unrestrained MD simulations have yet to be assessed for blind virtual screening (VS) by docking. This study presents a critical analysis of the predictive power of MD snapshots to this regard, evaluating two well-characterized systems of varying flexibility in ligand-bound and unbound configurations. Results from such VS predictions are discussed with respect to experimentally determined structures. In all cases, MD simulations provide snapshots that improve VS predictive power over known crystal structures, possibly due to sampling more relevant receptor conformations. Additionally, MD can move conformations previously not amenable to docking into the predictive range.