Binding Free Energy Change Research Articles

BindProfX: Assessing Mutation-Induced Binding Affinity Change by Protein Interface Profiles with Pseudo-Counts

Understanding how gene-level mutations affect the binding affinity of protein–protein interactions is a key issue of protein engineering. Due to the complexity of the problem, using physical force field to predict the mutation-induced binding free-energy change remains challenging. In this work, we present a renewed approach to calculate the impact of gene mutations on the binding affinity through the structure-based profiling of protein–protein interfaces, where the binding free-energy change (ΔΔG) is counted as the logarithm of relative probability of mutant amino acids over wild-type ones in the interface alignment matrix; three pseudo-counts are introduced to alleviate the limit of the current interface library. Compared with a previous profile score that was based on the log-odds likelihood calculation, the correlation between predicted and experimental ΔΔG of single-site mutations is increased in this approach from 0.33 to 0.68. The structure-based profile score is found complementary to the physical potentials, where a linear combination of the profile score with the FoldX potential could increase the ΔΔG correlation from 0.46 to 0.74. It is also shown that the profile score is robust for counting the coupling effect of multiple individual mutations. For the mutations involving more than two mutation sites where the correlation between FoldX and experimental data vanishes, the profile-based calculation retains a strong correlation with the experimental measurements.

SAAMBE: Webserver to Predict the Charge of Binding Free Energy Caused by Amino Acids Mutations.

Predicting the effect of amino acid substitutions on protein–protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.

Mutations in the KDM5C ARID Domain and Their Plausible Association with Syndromic Claes-Jensen-Type Disease.

Mutations in KDM5C gene are linked to X-linked mental retardation, the syndromic Claes-Jensen-type disease. This study focuses on non-synonymous mutations in the KDM5C ARID domain and evaluates the effects of two disease-associated missense mutations (A77T and D87G) and three not-yet-classified missense mutations (R108W, N142S, and R179H). We predict the ARID domain’s folding and binding free energy changes due to mutations, and also study the effects of mutations on protein dynamics. Our computational results indicate that A77T and D87G mutants have minimal effect on the KDM5C ARID domain stability and DNA binding. In parallel, the change in the free energy unfolding caused by the mutants A77T and D87G were experimentally measured by urea-induced unfolding experiments and were shown to be similar to the in silico predictions. The evolutionary conservation analysis shows that the disease-associated mutations are located in a highly-conserved part of the ARID structure (N-terminal domain), indicating their importance for the KDM5C function. N-terminal residues’ high conservation suggests that either the ARID domain utilizes the N-terminal to interact with other KDM5C domains or the N-terminal is involved in some yet unknown function. The analysis indicates that, among the non-classified mutations, R108W is possibly a disease-associated mutation, while N142S and R179H are probably harmless.

Characterization of the interaction between bovine serum albumin and doxycycline by chemiluminescence and molecular docking

ABSTRACTThe interaction of bovine serum albumin with doxycycline was investigated using chemiluminescence and molecular docking. Doxycycline at concentrations from 1.0 to 2.5 × 103 pmol · L−1 quenched the chemiluminescence from the luminol–bovine serum albumin system. The data were analyzed using a chemiluminescence mathematic model for protein–ligand interaction, log[(I0 – I)/I] = logK + nlog[D]. The binding constant of bovine serum albumin with doxycycline was 3.36 × 105 L · mol−1 at 298 K with one binding site. The binding constant, enthalpy change, entropy change, and binding free energy change showed that the bonding of doxycycline to bovine serum albumin was spontaneous and enthalpy driven via hydrogen bonding and van der Waals forces. Further molecular docking analysis substantiated that doxycycline was well positioned in the pocket at the subdomain IIA (site I) of bovine serum albumin with a binding constant of 3.31 × 105 L · mol−1. Doxycycline served as both a hydrogen acceptor and donor and mainly interacted with the Arg217 residue through four hydrogen bonds with an average length of 2.55 Å. The chemiluminescence mechanism of doxycycline on luminol–bovine serum albumin system was evaluated, showing that a ternary complex of luminol–bovine serum albumin–doxycycline was formed with luminol and doxycycline at sites III and I of bovine serum albumin.

Accurate Binding Free Energy Predictions in Fragment Optimization.

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Design, synthesis and anti-HIV-1 evaluation of a series of 5-hydroxypyridine-4-one derivatives as possible integrase inhibitors

A series of 5-hydroxypyridine-4-one derivatives were synthesized and subjected to HIV-1 replication inhibition assay. Docking studies provide a detailed molecular binding model for this class of compounds interacting with integrase enzyme. All of the derivatives were recognized potent in the docking studies in terms of both the estimated free energy change of binding and interactions with integrase key elements. 5a, 5c, 5d, 5h and 5n exhibited good anti-HIV-1 activities in cell-based assay. Compound 5d was the most potent derivative not only in vitro but also in silico. 5c and 5h offered the highest therapeutic indices. Suboptimal lipophilicity of 6b, 6g, 6i, 6j, 6l and 5m made them inactive in assays, despite the high activity in the docking studies.

Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method

A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624) while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation).

Cooperative DNA Recognition Modulated by an Interplay between Protein-Protein Interactions and DNA-Mediated Allostery.

Highly specific transcriptional regulation depends on the cooperative association of transcription factors into enhanceosomes. Usually, their DNA-binding cooperativity originates from either direct interactions or DNA-mediated allostery. Here, we performed unbiased molecular simulations followed by simulations of protein-DNA unbinding and free energy profiling to study the cooperative DNA recognition by OCT4 and SOX2, key components of enhanceosomes in pluripotent cells. We found that SOX2 influences the orientation and dynamics of the DNA-bound configuration of OCT4. In addition SOX2 modifies the unbinding free energy profiles of both DNA-binding domains of OCT4, the POU specific and POU homeodomain, despite interacting directly only with the first. Thus, we demonstrate that the OCT4-SOX2 cooperativity is modulated by an interplay between protein-protein interactions and DNA-mediated allostery. Further, we estimated the change in OCT4-DNA binding free energy due to the cooperativity with SOX2, observed a good agreement with experimental measurements, and found that SOX2 affects the relative DNA-binding strength of the two OCT4 domains. Based on these findings, we propose that available interaction partners in different biological contexts modulate the DNA exploration routes of multi-domain transcription factors such as OCT4. We consider the OCT4-SOX2 cooperativity as a paradigm of how specificity of transcriptional regulation is achieved through concerted modulation of protein-DNA recognition by different types of interactions.

Using Enhanced Sampling Molecular Dynamics Techniques to Probe the Thermodynamics of pHLIP Peptide Insertion into a Model Lipid Bilayer

The molecular mechanism of spontaneous polypeptide folding and insertion into a membrane, as well as its exit and unfolding, is of interest from several perspectives, including the action of antimicrobial peptides, the folding and degradation of membrane proteins, and medical applications of pH-triggered insertion peptides. A notable example is pH (Low) Insertion Peptide (pHLIP), which is a water-soluble polypeptide derived from helix C of bacteriorhodopsin that has the ability to insert into a membrane at acidic pH to form a stable transmembrane α-helix. The insertion process takes place in three stages: pHLIP is unstructured and soluble in water at neutral pH(state I), unstructured and bound to the surface of a membrane at neutral pH(state II), and inserted into the membrane as an α-helix at low pH(state III). Our hypothesis is that, there is a connection between the free energy change of binding /insertion and pKa of insertion. To test this hypothesis, we used enhanced sampling molecular dynamics (MD) techniques (steered MD and umbrella sampling) to investigate the molecular interactions of a C-terminal-truncated pHLIP variant, pHLIP-1, with a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer. The goal is to characterize the free energy of binding from state I to state II and the free energy of insertion from state II to state III (α-helical peptide insertion) and to identify key structural aspects that govern these processes. Our results agree well with the previous experiments, providing the first steps in establishing a direct relationship between the thermodynamics and pKa of pHLIP peptide insertion.

Computational design of protein-based inhibitors of Plasmodium vivax subtilisin-like 1 protease.

BackgroundMalaria remains a major global health concern. The development of novel therapeutic strategies is critical to overcome the selection of multiresistant parasites. The subtilisin-like protease (SUB1) involved in the egress of daughter Plasmodium parasites from infected erythrocytes and in their subsequent invasion into fresh erythrocytes has emerged as an interesting new drug target.FindingsUsing a computational approach based on homology modeling, protein–protein docking and mutation scoring, we designed protein–based inhibitors of Plasmodium vivax SUB1 (PvSUB1) and experimentally evaluated their inhibitory activity. The small peptidic trypsin inhibitor EETI-II was used as scaffold. We mutated residues at specific positions (P4 and P1) and calculated the change in free-energy of binding with PvSUB1. In agreement with our predictions, we identified a mutant of EETI-II (EETI-II-P4LP1W) with a Ki in the medium micromolar range.ConclusionsDespite the challenges related to the lack of an experimental structure of PvSUB1, the computational protocol we developed in this study led to the design of protein-based inhibitors of PvSUB1. The approach we describe in this paper, together with other examples, demonstrates the capabilities of computational procedures to accelerate and guide the design of novel proteins with interesting therapeutic applications.

Influence of microheterogeneity on the solution phase photophysics of a newly synthesised, environment sensitive fluorophore 2-((7,8-dimethyl-1-oxo-2,3,4,9-tetrahydro-1H-carbazol-6-yl)oxy)acetic acid and its tagged derivative

Abstract Excited state spectral properties like fluorescence quantum yield, emission maxima and lifetime of 2-((7,8-dimethyl-1-oxo-2,3,4,9-tetrahydro-1H-carbazol-6-yl)oxy) acetic acid (DOTHCA) are markedly sensitive to polarity and the H-bonding ability of its immediate local environment. Inspired by the excited state properties of the molecule in homogeneous solvents, attempt has been made to investigate its sensitivity of heterogeneity at the “microscopic” level in bio-mimicking environments like micelles (neutral, cationic, anionic) and β-cyclodextrins. DOTHCA interacts differently as the nature of aqueous micelles alters and prominent deviations are encountered only around critical micellar concentrations (CMCs) of each concerned medium. A quantitative assessment of the emission intensity data yields the binding constant (K) and free energy change (ΔG) for the interaction of DOTHCA with the micelles and β-CD. Use of Benesi–Hildebrand equation reveals a 1:1 stoichiometry for DOTHCA:β-CD complex. Micropolarities of the binding sites of the probe in those above mentioned systems have been determined for all micellar systems from a comparison of the variation of fluorescence properties in water–1,4-dioxane solvent mixtures and with the aid of that information probable location of the probe inside the micelles has also been proposed. DOTHCA has the COOH functionality that has been modified to tag an amino acid derivative of biological significance, benzocaine by forming ethyl 4-(2-((7,8-dimethyl-1-oxo-2,3,4,9-tetrahydro-1H-carbazol-6-yl)oxy)acetamido)benzoate (EDOTHCAB). Spectroscopic properties of EDOTHCAB in microheterogeneous environment behave differently than that of DOTHCA.

Targeting human secretory phospholipase A2 with designed peptide inhibitors for inflammatory therapy

Phospholipase A2 (PLA2) is potentially an important target for anti-inflammatory therapeutics. Here, we described a systematic scheme that integrated protein docking and peptide redocking, molecular dynamics simulation, and binding affinity analysis to rationally design PLA2 inhibitory peptides based on a solved PLA2 crystal structure. The scheme employed protein docking to sample the interaction modes of PLA2 with its natural inhibitor Clara cell protein, from which a number of peptide fragments, including a pentapeptide LLLGS, were cut off and redocked to serve as the lead entities of PLA2 inhibitory peptides. In addition, a systematic mutation energy map that characterized the binding free energy changes ΔG upon mutations of each position of the putative pentapeptide to 20 amino acids was also profiled, which was subsequently used to guide peptide structure optimization. In order to solidify the computational findings, we performed kinetic and inhibition studies of few designed peptides against human secretory PLA2. Consequently, eight peptides were successfully identified to have potent inhibition potency, in which the LLAYK and AVFRS were found to suppress enzymatic activity significantly (Ki = 0.75 ± 0.06 and 4.2 ± 0.3 μM, respectively). A further structure examination revealed that the designed peptides can form intensive nonpolar networks of van der Waals contacts and hydrophobic interactions at their complex interfaces with PLA2, conferring considerable stability and affinity for the formed complex systems.

Explicit spectral response of an intramolecular charge transfer molecule within microheterogeneous micellar environments

Photophysical properties of a potent intramolecular charge transfer probe viz., 5-(4-dimethylamino-phenyl)-penta-2,4-dienoic acid methyl ester (DPDAME) have been investigated in aqueous micellar environments using spectroscopic techniques. The intramolecular charge transfer (ICT) fluorescence of DPDAME is found to display remarkable hypsochromic shift coupled with intensity enhancement within the microheterogeneous micellar environments. This is also associated with discernible increase in fluorescence anisotropy whereby indicating the impartation of considerable motional restrictions on the fluorophore within the micellar systems. The fluorescence anisotropy results are also processed to delve into an estimate of the microviscosity of the probe environment at the binding site on the micellar aggregates. Quantitative evaluation of the probe–micelle binding strength has been achieved from fluorescence data in terms of binding constant and free energy change of the interaction process. The extensive polarity-sensitive fluorescence behavior of DPDAME has been exploited to cast light on assessing the micropolarity at the interaction site of the probe within the micelles. This information has in turn been efficiently employed as the actuating avenue to argue on complex issues like probable location, distribution and orientation of the probe within the micellar aggregates. The pattern of variation of emission intensity of DPDAME as a function of surfactant concentrations is found to reveal the existence of multiple critical micellar concentration (CMC). Overall, the present results have been argued to reflect the commendable efficiency of DPDAME to function as a prospective molecular reporter for complex microheterogeneous micellar environments.

Binding free-energy calculation is a powerful tool for drug optimization: calculation and measurement of binding free energy for 7-azaindole derivatives to glycogen synthase kinase-3β.

Present computational lead (drug)-optimization is lacking in thermodynamic tactics. To examine whether calculation of binding free-energy change (ΔG) is effective for the lead-optimization process, binding ΔGs of 7-azaindole derivatives to the ATP binding site of glycogen synthase kinase-3β (GSK-3β) were calculated. The result was a significant correlation coefficient of r = 0.895 between calculated and observed ΔGs. This indicates that calculated ΔG reflects the inhibitory activities of 7-azaindole derivatives. In addition to quantitative estimation of activity, ΔG calculation characterizes the thermodynamic behavior of 7-azaindole derivatives, providing also useful information for inhibitor optimization on affinity to water molecules.

Spectroscopic and molecular docking studies on the charge transfer complex of bovine serum albumin with quinone in aqueous medium and its influence on the ligand binding property of the protein

The spectral techniques such as UV–Vis, 1H NMR and fluorescence and electrochemical experiments have been employed to investigate the interaction between 2-methoxy-3,5,6-trichloro-1,4-benzoquinone (MQ; a water soluble quinone) and bovine serum albumin (BSA) in aqueous medium. The fluorescence of BSA was quenched by MQ via formation of a 1:1 BSA–MQ charge transfer adduct with a formation constant of 3.3×108Lmol−1. Based on the Forster’s theory the binding distance between them is calculated as 2.65nm indicating high probability of binding. For the first time, influence of quinone on the binding property of various types of ligands such as aspirin, ascorbic acid, nicotinimide and sodium stearate has also been investigated. The results indicated that the strong and spontaneous binding existing between BSA and MQ, decreased the intensity of binding of these ligands with BSA. Since Tryptophan (Trp) is the basic residue present in BSA, a comparison between binding property of Trp-MQ adduct with that of BSA–MQ with these ligands has also been attempted. 1H NMR titration study indicated that the Trp forms a charge transfer complex with MQ, which reduces the interaction of Trp with the ligands. Molecular docking study supported the fact that the quinone interacts with the Trp212 unit of the BSA and the free energy change of binding (ΔG) for the BSA–MQ complex was found to be −46kJmol−1, which is comparable to our experimental free energy of binding (−49kJmol−1) obtained from fluorescence study.

Integrating water exclusion theory into β contacts to predict binding free energy changes and binding hot spots.

BackgroundBinding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss.ResultsThis work proposes a new method, βACV ASA , to predict the change of binding free energy after alanine mutations. βACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector (ACV). A β contact between two atoms is a direct contact without being interrupted by any other atom between them. A β contact’s potential contribution to protein binding is also supposed to be inversely proportional to its ASA to follow the water exclusion hypothesis of binding hot spots. Tested on a dataset of 396 alanine mutations, our method is found to be superior in classification performance to many other methods, including Robetta, FoldX, HotPOINT, an ACV method of β contacts without ASA integration, and ACV ASA methods (similar to βACV ASA but based on distance-cutoff contacts). Based on our data analysis and results, we can draw conclusions that: (i) our method is powerful in the prediction of binding free energy change after alanine mutation; (ii) β contacts are better than distance-cutoff contacts for modeling the well-organized protein-binding interfaces; (iii) β contacts usually are only a small fraction number of the distance-based contacts; and (iv) water exclusion is a necessary condition for a residue to become a binding hot spot.ConclusionsβACV ASA is designed using the advantages of both β contacts and water exclusion. It is an excellent tool to predict binding free energy changes and binding hot spots after alanine mutation.

A Thermodynamic Discrimination of Efficacy of GPCR Ligands using Absolute Binding Free Energy Calculations

G-protein-coupled receptors (GPCRs) play fundamental roles in most physiological processes by modulating diverse signaling pathways and thus have become one of the most important drug targets. Based on the fact that a variety of the extracellular signals are mediated in a ligand-specific manner such as inverse agonist, neutral antagonist and agonist, quantitative characterization of the ligand efficacy is essential for rational design of selective modulators for GPCR targets. As experimental methods used for this purpose are time-, cost- and labor-intensive, computational tools, if they were systematically able to predict the efficacy of GPCR ligands, would make a big impact on GPCR drug design. To tackle this issue, in this study we apply free energy perturbation molecular dynamics (FEP/MD) simulations to calculating absolute ligand binding free energy for β2-adrenergic receptor (β2AR)/ligand systems. Based on the characterization of binding free energy change with respect to simulation time and free energy decomposition, we present that computationally measured thermodynamic properties can be used as promising descriptors for discriminating the efficacy of GPCR ligands. In addition, the simulation results also provide further insights into β2AR activation dynamics and ligand binding affinity.

Efficient Computation of Small-Molecule Configurational Binding Entropy and Free Energy Changes by Ensemble Enumeration

Here we present a novel, end-point method using the dead-end-elimination and A* algorithms to efficiently and accurately calculate the change in free energy, enthalpy, and configurational entropy of binding for ligand–receptor association reactions. We apply the new approach to the binding of a series of human immunodeficiency virus (HIV-1) protease inhibitors to examine the effect ensemble reranking has on relative accuracy as well as to evaluate the role of the absolute and relative ligand configurational entropy losses upon binding in affinity differences for structurally related inhibitors. Our results suggest that most thermodynamic parameters can be estimated using only a small fraction of the full configurational space, and we see significant improvement in relative accuracy when using an ensemble versus single-conformer approach to ligand ranking. We also find that using approximate metrics based on the single-conformation enthalpy differences between the global minimum energy configuration in the bound as well as unbound states also correlates well with experiment. Using a novel, additive entropy expansion based on conditional mutual information, we also analyze the source of ligand configurational entropy loss upon binding in terms of both uncoupled per degree of freedom losses as well as changes in coupling between inhibitor degrees of freedom. We estimate entropic free energy losses of approximately +24 kcal/mol, 12 kcal/mol of which stems from loss of translational and rotational entropy. Coupling effects contribute only a small fraction to the overall entropy change (1–2 kcal/mol) but suggest differences in how inhibitor dihedral angles couple to each other in the bound versus unbound states. The importance of accounting for flexibility in drug optimization and design is also discussed.

Intermolecular Contact Potentials for Protein-Protein Interactions Extracted from Binding Free Energy Changes upon Mutation.

Understanding and predicting the energetics of protein-protein interactions is fundamental to the structural modeling of protein complexes. Binding free energy can be approximated as a sum of pairwise atomic or residue contact energies, which are commonly inferred from contact frequencies observed in experimental protein structures. However, such statistically inferred potentials require certain assumptions and approximation. Here, we explore the possibility of deriving atomic and residue contact potentials directly from experimental binding free energy changes following mutation and present a number of such potentials. The first set of potentials is obtained by unweighted least-squares fitting and bootsrap aggregating. The second set is calculated using a weighting scheme optimized against absolute binding affinity data, so as to account for the over-representation of certain complexes, residues, and families of interactions. The congruence of the potentials with known physical chemistry is investigated. The potentials are further validated by ranking and clustering protein-protein docking poses.

Role of tyrosine hot‐spot residues at the interface of colicin E9 and immunity protein 9: A comparative free energy simulation study

The endonuclease activity of the bacterial colicin 9 enzyme is controlled by the specific and high-affinity binding of immunity protein 9 (Im9). Molecular dynamics simulation studies in explicit solvent were used to investigate the free energy change associated with the mutation of two hot-spot interface residues [tyrosine (Tyr): Tyr54 and Tyr55] of Im9 to Ala. In addition, the effect of several other mutations (Leu33Ala, Leu52Ala, Val34Ala, Val37Ala, Ser48Ala, and Ile53Ala) with smaller influence on binding affinity was also studied. Good qualitative agreement of calculated free energy changes and experimental data on binding affinity of the mutations was observed. The simulation studies can help to elucidate the molecular details on how the mutations influence protein-protein binding affinity. The role of solvent and conformational flexibility of the partner proteins was studied by comparing the results in the presence or absence of solvent and with or without positional restraints. Restriction of the conformational mobility of protein partners resulted in significant changes of the calculated free energies but of similar magnitude for isolated Im9 and for the complex and therefore in only modest changes of binding free energy differences. Although the overall binding free energy change was similar for the two Tyr-Ala mutations, the physical origin appeared to be different with solvation changes contributing significantly to the Tyr55Ala mutation and to a loss of direct protein-protein interactions dominating the free energy change due to the Tyr54Ala mutation.