An evaluation of Poisson-Boltzmann electrostatic free energy calculations through comparison with experimental mutagenesis data

For systems involving highly and oppositely charged proteins, electrostatic forces dominate association and contribute to biomolecular complex stability. Using experimental or theoretical alanine-scanning mutagenesis, it is possible to elucidate the contribution of individual ionizable amino acids to protein association. We evaluated our electrostatic free energy calculations by comparing calculated and experimental data for alanine mutants of five protein complexes. We calculated Poisson-Boltzmann electrostatic free energies based on a thermodynamic cycle, which incorporates association in a reference (Coulombic) and solvated (solution) state, as well as solvation effects. We observe that Coulombic and solvation free energy values correlate with experimental data in highly and oppositely charged systems, but not in systems comprised of similarly charged proteins. We also observe that correlation between solution and experimental free energies is dependent on dielectric coefficient selection for the protein interior. Free energy correlations improve as protein dielectric coefficient increases, suggesting that the protein interior experiences moderate dielectric screening, despite being shielded from solvent. We propose that higher dielectric coefficients may be necessary to more accurately predict protein-protein association. Additionally, our data suggest that Coulombic potential calculations alone may be sufficient to predict relative binding of protein mutants.     

Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes

Absolute binding free energy calculations and free energy decompositions are presented for the protein-protein complexes H-Ras/C-Raf1 and H-Ras/RalGDS. Ras is a central switch in the regulation of cell proliferation and differentiation. In our study, we investigate the capability of the molecular mechanics (MM)-generalized Born surface area (GBSA) approach to estimate absolute binding free energies for the protein-protein complexes. Averaging gas-phase energies, solvation free energies, and entropic contributions over snapshots extracted from trajectories of the unbound proteins and the complexes, calculated binding free energies (Ras-Raf: -15.0(+/-6.3)kcal mol(-1); Ras-RalGDS: -19.5(+/-5.9)kcal mol(-1)) are in fair agreement with experimentally determined values (-9.6 kcal mol(-1); -8.4 kcal mol(-1)), if appropriate ionic strength is taken into account. Structural determinants of the binding affinity of Ras-Raf and Ras-RalGDS are identified by means of free energy decomposition. For the first time, computationally inexpensive generalized Born (GB) calculations are applied in this context to partition solvation free energies along with gas-phase energies between residues of both binding partners. For selected residues, in addition, entropic contributions are estimated by classical statistical mechanics. Comparison of the decomposition results with experimentally determined binding free energy differences for alanine mutants of interface residues yielded correlations with r(2)=0.55 and 0.46 for Ras-Raf and Ras-RalGDS, respectively. Extension of the decomposition reveals residues as far apart as 25A from the binding epitope that can contribute significantly to binding free energy. These "hotspots" are found to show large atomic fluctuations in the unbound proteins, indicating that they reside in structurally less stable regions. Furthermore, hotspot residues experience a significantly larger-than-average decrease in local fluctuations upon complex formation. Finally, by calculating a pair-wise decomposition of interactions, interaction pathways originating in the binding epitope of Raf are found that protrude through the protein structure towards the loop L1. This explains the finding of a conformational change in this region upon complex formation with Ras, and it may trigger a larger structural change in Raf, which is considered to be necessary for activation of the effector by Ras.     

Molecular dynamics and free energy analysis of neuraminidase-ligand interactions

We report molecular dynamics calculations of neuraminidase in complex with an inhibitor, 4-amino-2-deoxy-2,3-didehydro-N-acetylneuraminic acid (N-DANA), with subsequent free energy analysis of binding by using a combined molecular mechanics/continuum solvent model approach. A dynamical model of the complex containing an ionized Glu119 amino acid residue is found to be consistent with experimental data. Computational analysis indicates a major van der Waals component to the inhibitor-neuraminidase binding free energy. Based on the N-DANA/neuraminidase molecular dynamics trajectory, a perturbation methodology was used to predict the binding affinity of related neuraminidase inhibitors by using a force field/Poisson-Boltzmann potential. This approach, incorporating conformational search/local minimization schemes with distance-dependent dielectric or generalized Born solvent models, correctly identifies the most potent neuraminidase inhibitor. Mutation of the key ligand four-substituent to a hydrogen atom indicates no favorable binding free energy contribution of a hydroxyl group; conversely, cationic substituents form favorable electrostatic interactions with neuraminidase. Prospects for further development of the method as an analysis and rational design tool are discussed.     

Building a foundation for structure‐based cellulosome design for cellulosic ethanol: Insight into cohesin‐dockerin complexation from computer simulation

The organization and assembly of the cellulosome, an extracellular multienzyme complex produced by anaerobic bacteria, is mediated by the high‐affinity interaction of cohesin domains from scaffolding proteins with dockerins of cellulosomal enzymes. We have performed molecular dynamics simulations and free energy calculations on both the wild type (WT) and D39N mutant of the C. thermocellum Type I cohesin‐dockerin complex in aqueous solution. The D39N mutation has been experimentally demonstrated to disrupt cohesin‐dockerin binding. The present MD simulations indicate that the substitution triggers significant protein flexibility and causes a major change of the hydrogen‐bonding network in the recognition strips—the conserved loop regions previously proposed to be involved in binding—through electrostatic and salt‐bridge interactions between β‐strands 3 and 5 of the cohesin and α‐helix 3 of the dockerin. The mutation‐induced subtle disturbance in the local hydrogen‐bond network is accompanied by conformational rearrangements of the protein side chains and bound water molecules. Additional free energy perturbation calculations of the D39N mutation provide differences in the cohesin‐dockerin binding energy, thus offering a direct, quantitative comparison with experiments. The underlying molecular mechanism of cohesin‐dockerin complexation is further investigated through the free energy profile, that is, potential of mean force (PMF) calculations of WT cohesin‐dockerin complex. The PMF shows a high‐free energy barrier against the dissociation and reveals a stepwise pattern involving both the central β‐sheet interface and its adjacent solvent‐exposed loop/turn regions clustered at both ends of the β‐barrel structure.     

On the calculation of binding free energies using continuum methods: Application to MHC class I protein-peptide interactions

This paper describes a methodology to calculate the binding free energy (ΔG) of a protein-ligand complex using a continuum model of the solvent. A formal thermodynamic cycle is used to decompose the binding free energy into electrostatic and non-electrostatic contributions. In this cycle, the reactants are discharged in water, associated as purely nonpolar entities, and the final complex is then recharged. The total electrostatic free energies of the protein, the ligand, and the complex in water are calculated with the finite difference Poisson-Boltzmann (FDPB) method. The nonpolar (hydrophobic) binding free energy is calculated using a free energy-surface area relationship, with a single alkane/water surface tension coefficient (γ_aw). The loss in backbone and side-chain configurational entropy upon binding is estimated and added to the electrostatic and the nonpolar components of ΔG. The methodology is applied to the binding of the murine MHC class I protein H-2K^b with three distinct peptides, and to the human MHC class I protein HLA-A2 in complex with five different peptides. Despite significant differences in the amino acid sequences of the different peptides, the experimental binding free energy differences (ΔΔG_exp) are quite small (<0.3 and <2.7 kcal/mol for the H-2K^b and HLA-A2 complexes, respectively). For each protein, the calculations are successful in reproducing a fairly small range of values for ΔΔG_calc (<4.4 and <5.2 kcal/mol, respectively) although the relative peptide binding affinities of H-2K^b and HLA-A2 are not reproduced. For all protein-peptide complexes that were treated, it was found that electrostatic interactions oppose binding whereas nonpolar interactions drive complex formation. The two types of interactions appear to be correlated in that larger nonpolar contributions to binding are generally opposed by increased electrostatic contributions favoring dissociation. The factors that drive the binding of peptides to MHC proteins are discussed in light of our results.     

Docking study and free energy simulation of the complex between p53 DNA-binding domain and azurin

Molecular interaction between p53 tumor suppressor and the copper protein azurin (AZ) has been demonstrated to enhance p53 stability and hence antitumoral function, opening new perspectives in cancer treatment. While some experimental work has provided evidence for AZ binding to p53, no crystal structure for the p53-AZ complex was solved thus far. In this work the association between AZ and the p53 DNA-binding domain (DBD) was investigated by computational methods. Using a combination of rigid-body protein docking, experimental mutagenesis information, and cluster analysis 10 main p53 DBD-AZ binding modes were generated. The resulting structures were further characterized by molecular dynamics (MD) simulations and free energy calculations. We found that the highest scored docking conformation for the p53 DBD-AZ complex also yielded the most favorable free energy value. This best three-dimensional model for the complex was validated by using a computational mutagenesis strategy. In this structure AZ binds to the flexible L(1) and s(7)-s(8) loops of the p53 DBD and stabilizes them through protein-protein tight packing interactions, resulting in high degree of both surface matching and electrostatic complementarity.     

Empirical free energy calculation: comparison to calorimetric data.

An effective free energy potential, developed originally for binding free energy calculation, is compared to calorimetric data on protein unfolding, described by a linear combination of changes in polar and nonpolar surface areas. The potential consists of a molecular mechanics energy term calculated for a reference medium (vapor or nonpolar liquid), and empirical terms representing solvation and entropic effects. It is shown that, under suitable conditions, the free energy function agrees well with the calorimetric expression. An additional result of the comparison is an independent estimate of the side-chain entropy loss, which is shown to agree with a structure-based entropy scale. These findings confirm that simple functions can be used to estimate the free energy change in complex systems, and that a binding free energy evaluation model can describe the thermodynamics of protein unfolding correctly. Furthermore, it is shown that folding and binding leave the sum of solute-solute and solute-solvent van der Waals interactions nearly invariant and, due to this invariance, it may be advantageous to use a nonpolar liquid rather than vacuum as the reference medium.     

Binding free energy calculations between bovine β‐lactoglobulin and four fatty acids using the MMGBSA method

The bovine dairy protein β‐lactoglobulin (βlg) is a promiscuous protein that has the ability to bind several hydrophobic ligands. In this study, based on known experimental data, the dynamic interaction mechanism between bovine βlg and four fatty acids was investigated by a protocol combining molecular dynamics (MD) simulations and molecular mechanics generalized Born surface area (MMGBSA) binding free energy calculations. Energetic analyses revealed binding free energy trends that corroborated known experimental findings; larger ligand size corresponded to greater binding affinity. Finally, binding free energy decomposition provided detailed information about the key residues stabilizing the complex. © 2014 Wiley Periodicals, Inc. Biopolymers 101: 1010–1018, 2014.     

蛋白质-蛋白质对接中打分函数的研究

通过分析蛋白质－蛋白质间的静电、疏水作用和熵效应与相对于晶体结构的蛋白质主链原子的均方根偏差（RMSD）的相关性,定量地考查了它们在蛋白质－蛋白质对接中作为打分函数评价近天然构象的能力。对7个蛋白质复合物体系的分析表明,就水化能而言,原子接触势模型（ACE）优于原子水化参数模型（ASP）,且修正的ACE模型具有更好的评价近天然构象的能力;水化能与静电能结合对评价能力有进一步的提高。最后,我们将静电和修正的ACE水化能结合作为打分函数用于36个蛋白质复合物体系的对接研究,进一步证实了这两种能量项的组合能有效地将近天然结构从分子对接模式中区分出来。     

Binding free energy calculation with QM/MM hybrid methods for Abl-Kinase inhibitor

We report a Quantum mechanics/Molecular Mechanics–Poisson-Boltzmann/ Surface Area (QM/MM-PB/SA) method to calculate the binding free energy of c-Abl human tyrosine kinase by combining the QM and MM principles where the ligand is treated quantum mechanically and the rest of the receptor by classical molecular mechanics. To study the role of entropy and the flexibility of the protein ligand complex in a solvated environment, molecular dynamics calculations are performed using a hybrid QM/MM approach. This work shows that the results of the QM/MM approach are strongly correlated with the binding affinity. The QM/MM interaction energy in our reported study confirms the importance of electronic and polarization contributions, which are often neglected in classical MM-PB/SA calculations. Moreover, a comparison of semi-empirical methods like DFTB-SCC, PM3, MNDO, MNDO-PDDG, and PDDG-PM3 is also performed. The results of the study show that the implementation of a DFTB-SCC semi-empirical Hamiltonian that is derived from DFT gives better results than other methods. We have performed such studies using the AMBER molecular dynamic package for the first time. The calculated binding free energy is also in agreement with the experimentally determined binding affinity for c-Abl tyrosine kinase complex with Imatinib.     

Virtual screening using molecular simulations

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery.     

Dynamics and assembly of the cytolethal distending toxin

The cytolethal distending toxin (CDT) is a widespread bacterial toxin that consists of an active subunit CdtB with nuclease activity and two ricin-like lectin domains, CdtA and CdtC, that are involved in the delivery of CdtB into the host cell. The three subunits form a tripartite complex that is required to achieve the fully active holotoxin. In the present study we investigate the assembly and dynamic properties of the CDT holotoxin using molecular dynamics simulations and binding free energy calculations. The results have revealed that CdtB likely adopts a different conformation in the unbound state with a closed DNA binding site. The two characterized structural elements of the aromatic patch and groove on the CdtA and CdtC protein surfaces exhibit high mobility, and free energy calculations show that the heterodimeric complex CdtA-CdtC, as well as the CdtA-CdtB and CdtB-CdtC sub-complexes are less energetically stable as compared to the binding in the tripartite complex. Analysis of the dynamical cross-correlation map reveals information on the correlated motions and long-range interplay among the CDT subunits associated with complex formation. Finally, the estimated binding free energies of subunit interactions are presented, together with the free energy decomposition to determine the contributions of residues for both binding partners, providing insight into the protein-protein interactions in the CDT holotoxin.     

Structural and energetic requirements for a second binding site at the dimeric β-lactoglobulin interface

Through experimental and theoretical approaches, it has been shown that bovine β-lactoglobulin (βlg) uses its hydrophobic cavity or calyx as the primary binding site for hydrophobic molecules, whereas the existence of a second ligand binding site at the dimeric interface has only been structurally identified for vitamin D3 (VD3). This binding exists even in the thermally denatured state, suggesting the prevalence of this secondary site. Although crystallographic experiments have suggested that VD3 can bind to both monomeric and dimeric states without significant structural differences, theoretical and experimental reports have proposed some structural requirements. Thus, in this study, based on known experimental data, the dynamic interaction of VD3 with the monomeric or dimeric forms of βlg was investigated through a protocol combining blind docking and 2 microsecond molecular dynamics simulations coupled with binding free energy and per-residue binding free energy decomposition analyses using the Molecular Mechanics Generalized Born Surface Area approach. Binding free energy calculations allowed us to estimate the energetic differences of coupling VD3 at the calyx and the dimeric interface for the monomeric or dimeric state, revealing that the dimeric structure is required to form a stable complex with VD3 at the dimeric interface. This also has an important impact on the dimerization process, whereas although the monomeric state also forms a stable complex with VD3 at the dimeric interface, the incorporation of the entropy component contributed to producing a marginally favorable binding free energy. Finally, the per-residue decomposition analysis provided energetic information about the most relevant residues in stabilizing the different systems.     

A computational analysis of pyrazole-based inhibitors binding to Hsp90 using molecular dynamics simulation and the MM-GBSA method

Owing to the key role of heat-shock protein 90 (Hsp90) in the evolution, development and disease pathogenesis of cancer, it has been an important target for anti-cancer chemotherapy over the years. A five-nanosecond molecular dynamics simulation combined with the calculation of the binding free energy was carried out to investigate the binding mechanisms of three Hsp90 inhibitors 4BH, 2E1 and 2D9 to Hsp90. The binding free energy of each complex was computed using the molecular mechanics–generalised Born surface area method. Detailed binding free energies between each inhibitor and residues of Hsp90 were calculated using a per-residue basis decomposition method. The detailed inhibitor–residue interaction provides insights into binding mechanisms and in-depth understanding of the structure–affinity relationship. This study suggests that van der Waals energy is primarily responsible for driving the binding of the inhibitors to Hsp90, and the three inhibitors bind to Hsp90 in a similar binding mode. However, a substituent in 2D9 leads to higher binding free energy than the other two inhibitors. These data may assist in designing new potent drugs to combat cancer.     

RosettaDDGPrediction for high-throughput mutational scans: From stability to binding

Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental mutational scans allow high-throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease-related variants that can benefit from analyses with structure-based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high-throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high-throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication-ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction .     

Insights into the functional role of protonation states in the HIV-1 protease-BEA369 complex: molecular dynamics simulations and free energy calculations

The molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method combined with molecular dynamics (MD) simulations were used to investigate the functional role of protonation in human immunodeficiency virus type 1 (HIV-1) protease complexed with the inhibitor BEA369. Our results demonstrate that protonation of two aspartic acids (Asp25/Asp25′) has a strong influence on the dynamics behavior of the complex, the binding free energy of BEA369, and inhibitor–residue interactions. Relative binding free energies calculated using the MM-PBSA method show that protonation of Asp25 results in the strongest binding of BEA369 to HIV-1 protease. Inhibitor–residue interactions computed by the theory of free energy decomposition also indicate that protonation of Asp25 has the most favorable effect on binding of BEA369. In addition, hydrogen-bond analysis based on the trajectories of the MD simulations shows that protonation of Asp25 strongly influences the water-mediated link of a conserved water molecule, Wat301. We expect that the results of this study will contribute significantly to binding calculations for BEA369, and to the design of high affinity inhibitors.     

Computational studies and peptidomimetic design for the human p53-MDM2 complex

The interaction between human p53 and MDM2 is a key event in controlling cell growth. Many studies have suggested that a p53 mimic would be sufficient to inhibit MDM2 to reduce cell growth in cancerous tissue. In order to design a potent p53 mimic, molecular dynamics (MD) simulations were used to examine the binding interface and the effect of mutating key residues in the human p53-MDM2 complex. The Generalized Born surface area (GBSA) method was used to estimate free energies of binding, and a computational alanine-scanning approach was used to calculate the relative effects in the free energy of binding for key mutations. Our calculations determine the free energy of binding for a model p53-MDM2 complex to be -7.4 kcal/mol, which is in very good agreement with the experimentally determined values (-6.6--8.8 kcal/mol). The alanine-scanning results are in good agreement with experimental data and calculations by other groups. We have used the information from our studies of human p53-MDM2 to design a beta-peptide mimic of p53. MD simulations of the mimic bound to MDM2 estimate a free energy of binding of -8.8 kcal/mol. We have also applied alanine scanning to the mimic-MDM2 complex and reveal which mutations are most likely to alter the binding affinity, possibly giving rise to escape mutants. The mimic was compared to nutlins, a new class of inhibitors that block the formation of the p53-MDM2 complex. There are interesting similarities between the nutlins and our mimic, and the differences point to ways that both inhibitors may be improved. Finally, an additional hydrophobic pocket is noted in the interior of MDM2. It may be possible to design new inhibitors to take advantage of that pocket.     

Evaluating the suitability of RNA intervention mechanism exerted by some flavonoid molecules against dengue virus MTase RNA capping site: a molecular docking,molecular dynamics simulation,and binding free energy study

Abstract

Dengue virus (DENV) is one of the most dangerous mosquito-borne human pathogens known to the mankind. Currently, no vaccines or standard therapy is avaliable to treate DENV infection. This makes the drug development against DENV more significant and challenging. The MTase domain of DENV RNA RdRp NS5 is a promising drug target, because this domain hosts the RNA capping process of DENV RNA to escape from human immune system. In the present study, we have analysed the RNA intervention mechanism exerted by flavoniod molecules against NS5 MTase RNA capping site by using molecular docking, molecular dynamics simulation and the binding free energy calculations. The results from the docking analysis confirmed that the RNA intervention mecanism is exerted by the quercetagetin (QGN) molecule with all necessary intermolecular interactions and high binding affinity. Notably, QGN forms strong hydrogen bonding interactions with Asn18, Leu20 and Ser150 residues and π???π stacking interaction with Phe25 residue. The apo and QGN bound NS5 MTase and QGN-NS5 MTase complex were used for MD simulation. The results of MD simulation reveal that the RMSD and RMSF values of QGN-MTase complex have increased on comparing the apo protein due to the effect of ligand binding. The binding free energy calulation includes prediction of total binding free energy of ligand-protein complex and per-residue free energy decomposition. The QGN binding to NS5 MTase affects it’s native motion, this result is found from Principal component analysis.

Communicated by Ramaswamy H. Sarma     

A computational study of binding between 3-(4-fluorophenyl)-N-((4-fluorophenyl)sulphonyl)acrylamide and tubulin

3-(4-Fluorophenyl)-N-((4-fluorophenyl)sulphonyl)acrylamide (FFSA) is a potential tubulin polymerisation inhibitor. In this article, a theoretical study of the binding between FFSA and tubulin in colchicine site was carried out by molecular docking, molecular dynamics (MD) simulation and binding free energy calculations. The docking calculations preliminarily indicate that there are three possible binding modes 1, 2 and 3; MD simulations and binding free energy calculations identify that binding mode 2 is the most favourable, with the lowest binding free energy of ? 29.54 kcal/mol. Moreover, our valuable results for the binding are as follows: the inhibitor FFSA is suitably located at the colchicine site of tubulin, where it not only interacts with residues Leu248β, Lys254β, Leu255β, Lys352β, Met259β and Val181a by hydrophilic interaction, but also interacts with Val181α and Thr179α by hydrogen bond interaction. These two factors are both essential for FFSA strongly binding to tubulin. These theoretical results help understanding the action mechanism and designing new compounds with higher affinity to tubulin.     

The Influence of Starting Coordinates in Free Energy Simulations of Ligand Binding to Dihydrofolate Reductase

Abstract

Molecular dynamics (MD) simulation combined with free energy perturbation (FEP) methods have been used to study the key structural differences and relative free energies for the binding of 6-methyl-N5-deazapterin (N8 protonated) and the 8-substituted compound, 6,8-dimethyl-N5-deazapterin (N3 protonated), to dihydrofolate reductase (DHFR). The free energy changes have been calculated using a variety of initial X-ray coordinates derived from bacterial and vertebrate (including human) DHFRs, and both with and without the reduced cofactor nicotinamide adenine dinucleotide (NADPH) bound. Given a sufficiently long simulation time for the FEP calculations (ca. 200 ps), all structures obtained after mutating 6,8-methyl-N5-deazapterin to 6-methyl-N5-deazapterin exhibited hydrogen bond formation between a backbone carbonyl group of DHFR and H(N8) of 6-methyl-N5-deazapterin, analogous to that found in the X-ray crystal structure of N5-deazafolate(N8 protonated) bound to human DHFR. However, both simulation and experiment suggest this additional H-bonding does not greatly enhance thermodynamic stability, with experiment indicating at most a factor of 2 difference in the relative affinities of the two ligand cations for vertebrate DHFR. Moreover, a binding differential of 10 in favour of the protonated 8-substituted compound is found experimentally for bacterial DHFR. The MD/FEP calculations suggest that the relative cost of ligand desolvation may largely cancel the lowering of free energy obtained in the active site, resulting in predicted binding differences within the range indicated by the vertebrate and bacterial DHFR experiments. However, the theoretical free energy changes could not be obtained with the accuracy required for the rationalization of the observed species dependence. While sampling difficulties are known to be inherent in MD simulation methodologies, these studies with several initial coordinate sets have demonstrated the contribution of coordinate choice to this problem. The results indicate that for demanding protein-ligand binding problems such as this one, the accuracy of the method may be no better than ± 2 kcal/mol.