AMBER ff99SB-ILDN Research Articles

PEGylation of Insulin and Lysozyme To Stabilize against Thermal Denaturation: A Molecular Dynamics Simulation Study.

Biologic drugs or "biologics" (proteins derived from living organisms) are one of the fastest-growing classes of FDA-approved therapeutics. These compounds are often fragile and require conjugation to polymers for stabilization, with many proteins too ephemeral for therapeutic use. During storage or administration, proteins tend to unravel and lose their secondary structure due to changes in solution temperature, pH, and other external stressors. To enhance their lifetime, protein drugs currently in the market are conjugated with polyethylene glycol (PEG), owing to its ability to increase the stability, solubility, and pharmacokinetics of protein drugs. Here, we perform all-atom molecular dynamics simulations to study the unfolding process of egg-white lysozyme and insulin at elevated temperatures. We test the validity of two force fields─CHARMM36 and Amber ff99SB-ILDN─in the unfolding process. By calculating global and local properties, we capture residues that deteriorate first─these are the "weak links" in the proteins. Next, we conjugate both proteins with PEG and find that PEG preserves the native structure of the proteins at elevated temperatures by blocking water molecules from entering the hydrophobic core, thereby causing the secondary structure to stabilize.

Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison.

Phosphorylation is a common post-translational modification among intrinsically disordered proteins and regions, which helps regulate function by changing the protein conformations, dynamics, and interactions with binding partners. To fully comprehend the effects of phosphorylation, computer simulations are a helpful tool, although they are dependent on the accuracy of the force field used. Here, we compared the conformational ensembles produced by Amber ff99SB-ILDN+TIP4P-D and CHARMM36m, for four phosphorylated disordered peptides ranging in length from 14–43 residues. CHARMM36m consistently produced more compact conformations with a higher content of bends, mainly due to more stable salt bridges. Based on comparisons with experimental size estimates for the shortest and longest peptide, CHARMM36m appeared to overestimate the compactness. The difference between the force fields was largest for the peptide showing the greatest separation between positively charged and phosphorylated residues, in line with the importance of charge distribution. For this peptide, the conformational ensemble did not change significantly upon increasing the ionic strength from 0 mM to 150 mM, despite a reduction of the salt-bridging probability in the CHARMM36m simulations, implying that salt concentration has negligible effects in this study.

Force Field Effects in Simulations of Flexible Peptides with Varying Polyproline II Propensity.

Five peptides previously suggested to possess polyproline II (PPII) structure have here been investigated by using atomistic molecular dynamics simulations to compare how well four different force fields known for simulating intrinsically disordered proteins relatively well (Amber ff99SB-disp, Amber ff99SB-ILDN, CHARM36IDPSFF, and CHARMM36m) can capture this secondary structure element. The results revealed that all force fields sample PPII structures but to different extents and with different propensities toward other secondary structure elements, in particular, the β-sheet and “random coils”. A cluster analysis of the simulations of histatin 5 also revealed that the conformational ensembles of the force fields are quite different. We compared the simulations to circular dichroism and nuclear magnetic resonance spectroscopy experiments and conclude that further experiments and methods for interpreting them are needed to assess the accuracy of force fields in determining PPII structure.

Phosphorylation of a Disordered Peptide-Structural Effects and Force Field Inconsistencies.

Phosphorylation is one of the most abundant types of post-translational modifications of intrinsically disordered proteins (IDPs). This study examines the conformational changes in the 15-residue-long N-terminal fragment of the IDP statherin upon phosphorylation, using computer simulations with two different force fields: AMBER ff99SB-ILDN and CHARMM36m. The results from the simulations are compared with experimental small-angle X-ray scattering (SAXS) and circular dichroism data. In the unphosphorylated state, the two force fields are in excellent agreement regarding global structural properties such as size and shape. However, they exhibit some differences in the extent and type of the secondary structure. In the phosphorylated state, neither of the force fields performs well compared to the experimental data. Both force fields show a compaction of the peptide upon phosphorylation, greater than what is seen in SAXS experiments, although they differ in the local structure. While the CHARMM force field increases the fraction of bends in the peptide as a response to strong interactions between the phosphorylated residues and arginines, the AMBER force field shows an increase of the helical content in the N-terminal part of the peptide, where the phosphorylated residues reside, in better agreement with circular dichroism results.

Force Field Benchmark of Amino Acids: I. Hydration and Diffusion in Different Water Models.

Thermodynamic and kinetic properties are of critical importance for the applicability of computational models to biomolecules such as proteins. Here we present an extensive evaluation of the Amber ff99SB-ILDN force field for modeling of hydration and diffusion of amino acids with three-site (SPC, SPC/E, SPC/Eb, and TIP3P), four-site (TIP4P, TIP4P-Ew, and TIP4P/2005), and five-site (TIP5P and TIP5P-Ew) water models. Hydration free energies (HFEs) of neutral amino acid side chain analogues have little dependence on the water model, with a root-mean-square error (RMSE) of ∼1 kcal/mol from experimental observations. On the basis of the number of interacting sites in the water model, HFEs of charged side chains can be putatively classified into three groups, of which the group of three-site models lies between those of four- and five-site water models; for each group, the water model dependence is greatly eliminated when the solvent Galvani potential is considered. Some discrepancies in the location of the first hydration peak ( RRDF) in the ion-water radial distribution function between experimental and calculated observations were detected, such as a systematic underestimation of the acetate (Asp side chain) ion. The RMSE of calculated diffusion coefficients of amino acids from experiment increases linearly with the increasing diffusion coefficients of the solvent water models at infinite dilution. TIP3P has the fastest diffusivity, in line with literature findings, while the "FB" and "OPC" water model families as well as TIP4P/2005 perform well, within a relative error of 5%, and TIP4P/2005 yields the most accurate estimate for the water diffusion coefficient. All of the tested water models overestimate amino acid diffusion coefficients by approximately 40% (TIP4P/2005) to 200% (TIP3P). Scaling of protein-water interactions with TIP4P/2005 in the Amber ff99SBws and ff03ws force fields leads to more negative HFEs but has little influence on the diffusion of amino acids. The most recent FF/water combinations of ff14SB/OPC3, ff15ipq/SPC/Eb, and fb15/TIP3P-FB do not show obvious improvements in accuracy for the tested quantities. These findings here establish a benchmark that may aid in the development and improvement of classical force fields to accurately model protein dynamics and thermodynamics.

Permeability and ammonia selectivity in aquaporin TIP2;1: linking structure to function

Aquaporin TIP2;1 is a protein channel permeable to both water and ammonia. The structural origin of ammonia selectivity remains obscure, but experiments have revealed that a double mutation renders it impermeable to ammonia without affecting water permeability. Here, we aim to reproduce and explain these observations by performing an extensive mutational study using microsecond long molecular dynamics simulations, applying the two popular force fields CHARMM36 and Amber ff99SB-ILDN. We calculate permeabilities and free energies along the channel axis for ammonia and water. For one force field, the permeability of the double mutant decreases by a factor of 2.5 for water and 4 for ammonia, increasing water selectivity by a factor of 1.6. We attribute this effect to decreased entropy of water in the pore, due to the observed increase in pore–water interactions and narrower pore. Additionally, we observe spontaneous opening and closing of the pore on the cytosolic side, which suggests a gating mechanism for the pore. Our results show that sampling methods and simulation times are sufficient to delineate even subtle effects of mutations on structure and function and to capture important long-timescale events, but also underline the importance of improving models further.

Transfer Learning from Markov Models Leads to Efficient Sampling of Related Systems.

We recently showed that the time-structure-based independent component analysis method from Markov state model literature provided a set of variationally optimal slow collective variables for metadynamics (tICA-metadynamics). In this paper, we extend the methodology toward efficient sampling of related mutants by borrowing ideas from transfer learning methods in machine learning. Our method explicitly assumes that a similar set of slow modes and metastable states is found in both the wild type (baseline) and its mutants. Under this assumption, we describe a few simple techniques using sequence mapping for transferring the slow modes and structural information contained in the wild type simulation to a mutant model for performing enhanced sampling. The resulting simulations can then be reweighted onto the full-phase space using the multistate Bennett acceptance ratio, allowing for thermodynamic comparison against the wild type. We first benchmark our methodology by recapturing alanine dipeptide dynamics across a range of different atomistic force fields, including the polarizable Amoeba force field, after learning a set of slow modes using Amber ff99sb-ILDN. We next extend the method by including structural data from the wild type simulation and apply the technique to recapturing the effects of the GTT mutation on the FIP35 WW domain.

Modeling the mechanism of CLN025 beta-hairpin formation.

Beta-hairpins are substructures found in proteins that can lend insight into more complex systems. Furthermore, the folding of beta-hairpins is a valuable test case for benchmarking experimental and theoretical methods. Here, we simulate the folding of CLN025, a miniprotein with a beta-hairpin structure, at its experimental melting temperature using a range of state-of-the-art protein force fields. We construct Markov state models in order to examine the thermodynamics, kinetics, mechanism, and rate-determining step of folding. Mechanistically, we find the folding process is rate-limited by the formation of the turn region hydrogen bonds, which occurs following the downhill hydrophobic collapse of the extended denatured protein. These results are presented in the context of established and contradictory theories of the beta-hairpin folding process. Furthermore, our analysis suggests that the AMBER-FB15 force field, at this temperature, best describes the characteristics of the full experimental CLN025 conformational ensemble, while the AMBER ff99SB-ILDN and CHARMM22* force fields display a tendency to overstabilize the native state.

Prediction of Bond Vector Autocorrelation Functions from Larmor Frequency-Selective Order Parameter Analysis of NMR Relaxation Data.

Protein molecular dynamics interpretation of the standard R1, R2, and heteronuclear NOE relaxation measurements has typically been limited to a single S2 order parameter which is often insufficient to characterize the rich content of these NMR experiments. In the absence of exchange linebroadening, an optimized reduced spectral density analysis of these measurements can yield spectral density values at three distinct frequencies. Surprisingly, these three discrete spectral density values have proven to be sufficient for a Larmor frequency-selective order parameter analysis of the 223 methine and methylene H-C bonds of the B3 domain of Protein G (GB3) to accurately back-calculate the entire curve of the corresponding bond vector autocorrelation functions upon which the NMR relaxation behavior depends. The 13C relaxation values calculated from 2 μs of CHARMM36 simulation trajectories yielded the corresponding autocorrelation functions to an average rmsd of 0.44% with only three bond vectors having rmsd errors slightly greater than 1.0%. Similar quality predictions were obtained using the CHARMM22/CMAP, AMBER ff99SB, and AMBER ff99SB-ILDN force fields. Analogous predictions for the backbone 15N relaxation values were 3-fold more accurate. Excluding seven residues for which either experimental data is lacking or previous MD studies have indicated markedly divergent dynamics predictions, the CHARMM36-derived and experimentally derived 15N relaxation values for the remaining 48 amides of GB3 agree to an average of 0.016, 0.010, and 0.020 for the fast limit (Sf2) and Larmor frequency-selective (SH2 and SN2) order parameters, respectively. In contrast, for a substantial fraction of side chain positions, the statistical uncertainties obtained in the relaxation value predictions from each force field were appreciably less than the much larger differences predicted among these force fields, indicating a significant opportunity for experimental NMR relaxation measurements to provide structurally interpretable guidance for further optimizing the prediction of protein dynamics.

Reparametrization of Protein Force Field Nonbonded Interactions Guided by Osmotic Coefficient Measurements from Molecular Dynamics Simulations.

There is a small, but growing, body of literature describing the use of osmotic coefficient measurements to validate and reparametrize simulation force fields. Here we have investigated the ability of five very commonly used force field and water model combinations to reproduce the osmotic coefficients of seven neutral amino acids and five small molecules. The force fields tested include AMBER ff99SB-ILDN, CHARMM36, GROMOS54a7, and OPLS-AA, with the first of these tested in conjunction with the TIP3P and TIP4P-Ew water models. In general, for both the amino acids and the small molecules, the tested force fields produce computed osmotic coefficients that are lower than experiment; this is indicative of excessively favorable solute-solute interactions. The sole exception to this general trend is provided by GROMOS54a7 when applied to amino acids: in this case, the computed osmotic coefficients are consistently too high. Importantly, we show that all of the force fields tested can be made to accurately reproduce the experimental osmotic coefficients of the amino acids when minor modifications-some previously reported by others and some that are new to this study-are made to the van der Waals interactions of the charged terminal groups. Special care is required, however, when simulating Proline with a number of the force fields, and a hydroxyl-group specific modification is required in order to correct Serine and Threonine when simulated with AMBER ff99SB-ILDN. Interestingly, an alternative parametrization of the van der Waals interactions in the latter force field, proposed by the Nerenberg and Head-Gordon groups, is shown to immediately produce osmotic coefficients that are in excellent agreement with experiment. Overall, this study reinforces the idea that osmotic coefficient measurements can be used to identify general shortcomings in commonly used force fields' descriptions of solute-solute interactions and further demonstrates that modifications to van der Waals parameters provide a simple route to optimizing agreement with experiment.

Molecular Dynamics Simulations of Intrinsically Disordered Proteins: On the Accuracy of the TIP4P-D Water Model and the Representativeness of Protein Disorder Models.

Here, we first present a follow-up to a previous work by our group on the problematic of molecular dynamics simulations of intrinsically disordered proteins (IDPs) [ Henriques et al. J. Chem. Theory Comput. 2015 , 11 , 3420 - 3431 ], using the recently developed TIP4P-D water model. When used in conjunction with the standard AMBER ff99SB-ILDN force field and applied to the simulation of Histatin 5, our IDP model, we obtain results which are in excellent agreement with the best performing IDP-suitable force field from the earlier study and with experiment. We then assess the representativeness of the IDP models used in these and similar studies, finding that most are too short in comparison to the average IDP and contain a bias toward hydrophilic amino acid residues. Moreover, several key order- and disorder-promoting residues are also found to be misrepresented. It seems appropriate for future studies to address these issues.

Osmotic Pressure Simulations of Amino Acids and Peptides Highlight Potential Routes to Protein Force Field Parameterization.

Recent molecular dynamics (MD) simulations of proteins have suggested that common force fields overestimate the strength of amino acid interactions in aqueous solution. In an attempt to determine the causes of these effects, we have measured the osmotic coefficients of a number of amino acids using the AMBER ff99SB-ILDN force field with two popular water models, and compared the results with available experimental data. With TIP4P-Ew water, interactions between aliphatic residues agree well with experiment, but interactions of the polar residues serine and threonine are found to be excessively attractive. For all tested amino acids, the osmotic coefficients are lower when the TIP3P water model is used. Additional simulations performed on charged amino acids indicate that the osmotic coefficients are strongly dependent on the parameters assigned to the salt ions, with a reparameterization of the sodium/carboxylate interaction reported by the Aksimentiev group significantly improving description of the osmotic coefficient for glutamate. For five neutral amino acids, we also demonstrate a decrease in solute-solute attractions using the recently reported TIP4P-D water model and using the KBFF force field. Finally, we show that for four two-residue peptides improved agreement with experiment can be achieved by rederiving the partial charges for each peptide.

Molecular dynamics simulations data of the twenty encoded amino acids in different force fields.

We present extensive all-atom Molecular Dynamics (MD) simulation data of the twenty encoded amino acids in explicit water, simulated with different force fields. The termini of the amino acids have been capped to ensure that the dynamics of the Φ and ψ torsion angles are analogues to the dynamics within a peptide chain. We use representatives of each of the four major force field families: AMBER ff-99SBILDN [1], AMBER ff-03 [2], OPLS-AA/L [3], CHARMM27 [4] and GROMOS43a1 [5], [6]. Our data represents a library and test bed for method development for MD simulations and for force fields development. Part of the data set has been previously used for comparison of the dynamic properties of force fields (Vitalini et al., 2015) [7] and for the construction of peptide basis functions for the variational approach to molecular kinetics [8].

Microsecond simulations of mdm2 and its complex with p53 yield insight into force field accuracy and conformational dynamics.

The p53-MDM2 complex is both a major target for cancer drug development and a valuable model system for computational predictions of protein-ligand binding. To investigate the accuracy of molecular simulations of MDM2 and its complex with p53, we performed a number of long (200 ns to 1 µs) explicit-solvent simulations using a range of force fields. We systematically compared nine popular force fields (AMBER ff03, ff12sb, ff14sb, ff99sb, ff99sb-ildn, ff99sb-ildn-nmr, ff99sb-ildn-phi, CHARMM22*, and CHARMM36) against experimental chemical shift data, and found similarly accurate results, with microsecond simulations achieving better agreement compared to 200-ns trajectories. Although the experimentally determined apo structure has a closed binding cleft, simulations in all force fields suggest the apo state of MDM2 is highly flexible, and able to sample holo-like conformations, consistent with a conformational selection model. Initial structuring of the MDM2 lid region, known to competitively bind the binding cleft, is also observed in long simulations. Taken together, these results show molecular simulations can accurately sample conformations relevant for ligand binding. We expect this study to inform future computational work on folding and binding of MDM2 ligands.

The structure and IR signatures of the arginine-glutamate salt bridge. Insights from the classical MD simulations.

Salt bridges and ionic interactions play an important role in protein stability, protein-protein interactions, and protein folding. Here, we provide the classical MD simulations of the structure and IR signatures of the arginine (Arg)-glutamate (Glu) salt bridge. The Arg-Glu model is based on the infinite polyalanine antiparallel two-stranded β-sheet structure. The 1 μs NPT simulations show that it preferably exists as a salt bridge (a contact ion pair). Bidentate (the end-on and side-on structures) and monodentate (the backside structure) configurations are localized [Donald et al., Proteins 79, 898-915 (2011)]. These structures are stabilized by the short (+)N-H⋯O(-) bonds. Their relative stability depends on a force field used in the MD simulations. The side-on structure is the most stable in terms of the OPLS-AA force field. If AMBER ff99SB-ILDN is used, the backside structure is the most stable. Compared with experimental data, simulations using the OPLS all-atom (OPLS-AA) force field describe the stability of the salt bridge structures quite realistically. It decreases in the following order: side-on > end-on > backside. The most stable side-on structure lives several nanoseconds. The less stable backside structure exists a few tenth of a nanosecond. Several short-living species (solvent shared, completely separately solvated ionic groups ion pairs, etc.) are also localized. Their lifetime is a few tens of picoseconds or less. Conformational flexibility of amino acids forming the salt bridge is investigated. The spectral signature of the Arg-Glu salt bridge is the IR-intensive band around 2200 cm(-1). It is caused by the asymmetric stretching vibrations of the (+)N-H⋯O(-) fragment. Result of the present paper suggests that infrared spectroscopy in the 2000-2800 frequency region may be a rapid and quantitative method for the study of salt bridges in peptides and ionic interactions between proteins. This region is usually not considered in spectroscopic studies of peptides and proteins.

Dynamic properties of force fields.

Molecular-dynamics simulations are increasingly used to study dynamic properties of biological systems. With this development, the ability of force fields to successfully predict relaxation timescales and the associated conformational exchange processes moves into focus. We assess to what extent the dynamic properties of model peptides (Ac-A-NHMe, Ac-V-NHMe, AVAVA, A10) differ when simulated with different force fields (AMBER ff99SB-ILDN, AMBER ff03, OPLS-AA/L, CHARMM27, and GROMOS43a1). The dynamic properties are extracted using Markov state models. For single-residue models (Ac-A-NHMe, Ac-V-NHMe), the slow conformational exchange processes are similar in all force fields, but the associated relaxation timescales differ by up to an order of magnitude. For the peptide systems, not only the relaxation timescales, but also the conformational exchange processes differ considerably across force fields. This finding calls the significance of dynamic interpretations of molecular-dynamics simulations into question.

New Force Field on Modeling Intrinsically Disordered Proteins

Intrinsically disordered proteins or intrinsically disordered protein regions comprise a large portion of eukaryotic proteomes (between 35% and 51%). These intrinsically disordered proteins were found to link with cancer and various other diseases. However, widely used additive force field parameter sets are insufficient in quantifying the structural properties of intrinsically disordered proteins. Therefore, we explored to a systematic correction of a base additive force field parameter set (chosen as Amber ff99SBildn) to correct the biases that was first demonstrated in simulations with the base parameter set. Specifically, the φ/ψ distributions of disorder-promoting residues were systematically corrected with the CMAP method. Our simulations show that the CMAP corrected Amber parameter set, termed ff99IDPs, improves the φ/ψ distributions of the disorder-promoting residues with respect to the benchmark data of intrinsically disordered protein structures, with root mean-squared percentage deviation less than 0.15% between the simulation and the benchmark. Our further validation shows that the chemical shifts from the ff99IDPs simulations are in quantitative agreement with those from reported NMR measurements for two tested IDPs, MeV NTAIL , and p53. The predicted residue dipolar couplings also show high correlation with experimental data. Interestingly, our simulations show that ff99IDPs can still be used to model the ordered state when the intrinsically disordered proteins are in complex, in contrast to ff99SBildn that can be applied well only to the ordered complex structures. These findings confirm that the newly proposed Amber ff99IDPs parameter set provides a reasonable tool in further studies of intrinsically disordered protein structures. In addition, our study also shows the importance of considering intrinsically disordered protein structures in general-purposed force field developments for both additive and non-additive models.

Effects of force fields for refining protein NMR structures with atomistic force fields and generalized-Born implicit solvent model

Atomistic molecular dynamics (MD) simulation has become mature enabling close approximation of the real behaviors of biomolecules. In biomolecular NMR field, atomistic MD simulation coupled with generalized implicit solvent model (GBIS) has contributed to improving the qualities of NMR structures in the refinement stage with experimental restraints. Here all-atom force fields play important roles in defining the optimal positions between atoms and angles, resulting in more precise and accurate structures. Despite successful applications in refining NMR structure, however, the research that has studied the influence of force fields in GBIS is limited. In this study, we compared the qualities of NMR structures of two model proteins, ubiquitin and GB1, under a series of AMBER force fields-ff99SB, ff99SB-ILDN, ff99SB-NMR, ff12SB, and ff13-with experimental restraints. The root mean square deviations of backbone atoms and packing scores that reflect the apparent structural qualities were almost indistinguishable except ff13. Qualitative comparison of parameters, however, indicates that ff99SB-ILDN is more recommendable, at least in the cases of ubiquitin and GB1.

Flexibility of the Bacterial Chaperone Trigger Factor in Microsecond-Timescale Molecular Dynamics Simulations

The bacterial chaperone trigger factor (TF) is the first chaperone to be encountered by a nascent protein chain as it emerges from the ribosome exit tunnel. Experimental results suggest that TF possesses considerable conformational flexibility, and in an attempt to provide an atomic-level view of this flexibility, we have performed independent 1.5-μs molecular dynamics simulations of TF in explicit solvent using two different simulation force fields (OPLS-AA/L and AMBER ff99SB-ILDN). Both simulations indicate that TF possesses tremendous flexibility, with huge excursions from the crystallographic conformation caused by reorientations of the protein’s constituent domains; both simulations also predict the formation of extensive contacts between TF’s PPIase domain and the Arm 1 domain that is involved in nascent-chain binding. In the OPLS simulation, however, TF rapidly settles into a very compact conformation that persists for at least 1 μs, whereas in the AMBER simulation, it remains highly dynamic; additional simulations in which the two force fields were swapped suggest that these differences are at least partly attributable to sampling issues. The simulation results provide potential rationalizations of a number of experimental observations regarding TF’s conformational behavior and have implications for using simulations to model TF’s function on translating ribosomes.

Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study.

A major current challenge for drug design efforts focused on protein kinases is the development of drug resistance caused by spontaneous mutations in the kinase catalytic domain. The ubiquity of this problem means that it would be advantageous to develop fast, effective computational methods that could be used to determine the effects of potential resistance-causing mutations before they arise in a clinical setting. With this long-term goal in mind, we have conducted a combined experimental and computational study of the thermodynamic effects of active-site mutations on a well-characterized and high-affinity interaction between a protein kinase and a small-molecule inhibitor. Specifically, we developed a fluorescence-based assay to measure the binding free energy of the small-molecule inhibitor, SB203580, to the p38α MAP kinase and used it measure the inhibitor's affinity for five different kinase mutants involving two residues (Val38 and Ala51) that contact the inhibitor in the crystal structure of the inhibitor-kinase complex. We then conducted long, explicit-solvent thermodynamic integration (TI) simulations in an attempt to reproduce the experimental relative binding affinities of the inhibitor for the five mutants; in total, a combined simulation time of 18.5 μs was obtained. Two widely used force fields - OPLS-AA/L and Amber ff99SB-ILDN - were tested in the TI simulations. Both force fields produced excellent agreement with experiment for three of the five mutants; simulations performed with the OPLS-AA/L force field, however, produced qualitatively incorrect results for the constructs that contained an A51V mutation. Interestingly, the discrepancies with the OPLS-AA/L force field could be rectified by the imposition of position restraints on the atoms of the protein backbone and the inhibitor without destroying the agreement for other mutations; the ability to reproduce experiment depended, however, upon the strength of the restraints' force constant. Imposition of position restraints in corresponding simulations that used the Amber ff99SB-ILDN force field had little effect on their ability to match experiment. Overall, the study shows that both force fields can work well for predicting the effects of active-site mutations on small molecule binding affinities and demonstrates how a direct combination of experiment and computation can be a powerful strategy for developing an understanding of protein-inhibitor interactions.