Comparison of protein-protein interactions in serine protease-inhibitor and antibody-antigen complexes: implications for the protein docking problem

The protein-protein interaction energy of 12 nonhomologous serine protease-inhibitor and 15 antibody-antigen complexes is calculated using a molecular mechanics formalism and dissected in terms of the main-chain vs. side-chain contribution, nonrotameric side-chain contributions, and amino acid residue type involvement in the interface interaction. There are major differences in the interactions of the two types of protein-protein complex. Protease-inhibitor complexes interact predominantly through a main-chain-main-chain mechanism while antibody-antigen complexes interact predominantly through a side-chain-side-chain or a side-chain-main-chain mechanism. However, there is no simple correlation between the main-chain-main-chain interaction energy and the percentage of main-chain surface area buried on binding. The interaction energy is equally effected by the presence of nonrotameric side-chain conformations, which constitute approximately 20% of the interaction energy. The ability to reproduce the interface interaction energy of the crystal structure if original side-chain conformations are removed from the calculation is much greater in the protease-inhibitor complexes than the antibody-antigen complexes. The success of a rotameric model for protein-protein docking appears dependent on the extent of the main-chain-main-chain contribution to binding. Analysis of (1) residue type and (2) residue pair interactions at the interface show that antibody-antigen interactions are very restricted with over 70% of the antibody energy attributable to just six residue types (Tyr > Asp > Asn > Ser > Glu > Trp) in agreement with previous studies on residue propensity. However, it is found here that 50% of the antigen energy is attributable to just four residue types (Arg = Lys > Asn > Asp). On average just 12 residue pair interactions (6%) contribute over 40% of the favorable interaction energy in the antibody-antigen complexes, with charge-charge and charge/polar-tyrosine interactions being prominent. In contrast protease inhibitors use a diverse set of residue types and residue pair interactions.     

Calculating proton uptake/release and binding free energy taking into account ionization and conformation changes induced by protein-inhibitor association: application to plasmepsin, cathepsin D and endothiapepsin-pepstatin complexes

The protein-inhibitor binding energies of enzymes are often pH dependent, and binding induces either proton uptake or proton release. The proton uptake/release and the binding energy for three complexes with available experimental data were numerically studied: pepstatin-cathepsin D, pepstatin-plasmepsin II and pepstatin-endothiapepsin. Very good agreement with the experimental data was achieved when conformational changes were taken into account. The role of the desolvation energy and the conformational changes was revealed by modeling the complex, the separated molecules in the complex conformation and the free molecules. It was shown that the conformational changes induced by the complex formation are as important for the proton transfer as the loss of solvation energy caused by the burial of interface residues. The residues responsible for the proton transfer were identified and their contribution to the proton uptake/release calculated. These residues were found to be scattered along the whole protein rather than being localized only at the active site. In the case of cathepsin D, these residues were found to be highly conserved among the cathepsin D sequences of other species. It was shown that conformation and ionization changes induced by the complex formation are critical for the correct calculation of the binding energy. Taking into account the electrostatics and the van der Waals (vdW) energies within the Boltzmann distribution of energies and allowing ionization and conformation changes to occur makes the calculated binding energy more realistic and closer to the experimental value. The interplay between electrostatic and vdW forces makes the pH dependence of the binding energy smoother, because the vdW force acts in reaction to the changes of the electrostatic energy. It was found that a small fraction of the ionizable groups remain uncharged in both the free and complexed molecules. The sequence and structural position of these groups aligns well within the three proteases, suggesting that these may have specific role.     

Calculations of antibody-antigen interactions: microscopic and semi-microscopic evaluation of the free energies of binding of phosphorylcholine analogs to McPC603.

The study of antibody-antigen interactions should greatly benefit from the development of quantitative models for the evaluation of binding free energies in proteins. The present work addresses this challenge by considering the test case of the binding free energies of phosphorylcholine analogs to the murine myeloma protein McPC603. This includes the evaluation of the differential binding energy as well as the absolute binding energies and their corresponding electrostatic contributions. Four different approaches are examined: the Protein Dipoles Langevin Dipoles (PDLD) method, the semi-microscopic PDLD (PDLD/S) method, a free energy perturbation (FEP) method based on an adiabatic charging procedure and a linear response approximation that accelerates the FEP calculation. The PDLD electrostatic calculations are augmented by estimates of the relevant hydrophobic and steric contributions. The determination of the hydrophobic energy involves an approach which considers the modification of the effective surface area of the solute by local field effects. The steric contributions are analyzed in terms of the corresponding reorganization energies. This treatment, which considers the protein as a harmonic system, views the steric forces as the restoring forces for the electrostatic interactions. The FEP method is found to give unreliable results with regular cut-off radii and starts to give quantitative results only in very expensive treatment with very large cut-off radii. The PDLD and PDLD/S methods are much faster than the FEP approach and give reasonable results for both the relative and absolute binding energies. The speed and simplicity of the PDLD/S method make it an effective strategy for interactive docking studies and indeed such an option is incorporated in the program MOLARIS. A component analysis of the different energy contributions of the FEP treatment and a similar PDLD analysis indicate that electrostatic effects provide the largest contribution to the differential binding energy, while the hydrophobic and steric contributions are much smaller. This finding lends further support to the idea that electrostatic interactions play a major role in determining the antigen specificity of McPC603.     

Optimization of binding electrostatics: charge complementarity in the barnase-barstar protein complex

Theoretical and experimental studies have shown that the large desolvation penalty required for polar and charged groups frequently precludes their involvement in electrostatic interactions that contribute strongly to net stability in the folding or binding of proteins in aqueous solution near room temperature. We have previously developed a theoretical framework for computing optimized electrostatic interactions and illustrated use of the algorithm with simplified geometries. Given a receptor and model assumptions, the method computes the ligand-charge distribution that provides the most favorable balance of desolvation and interaction effects on binding. In this paper the method has been extended to treat complexes using actual molecular shapes. The barnase-barstar protein complex was investigated with barnase treated as a target receptor. The atomic point charges of barstar were varied to optimize the electrostatic binding free energy. Barnase and natural barstar form a tight complex (K(d) approximately 10(-14) M) with many charged and polar groups near the interface that make this a particularly relevant system for investigating the role of electrostatic effects on binding. The results show that sets of barstar charges (resulting from optimization with different constraints) can be found that give rise to relatively large predicted improvements in electrostatic binding free energy. Principles for enhancing the effect of electrostatic interactions in molecular binding in aqueous environments are discussed in light of the optima. Our findings suggest that, in general, the enhancements in electrostatic binding free energy resulting from modification of polar and charged groups can be substantial. Moreover, a recently proposed definition of electrostatic complementarity is shown to be a useful tool for examining binding interfaces. Finally, calculational results suggest that wild-type barstar is closer to being affinity optimized than is barnase for their mutual binding, consistent with the known roles of these proteins.     

Do electrostatic interactions destabilize protein–nucleic acid binding?

The negatively charged phosphates of nucleic acids are often paired with positively charged residues upon binding proteins. It was thus counter-intuitive when previous Poisson-Boltzmann (PB) calculations gave positive energies from electrostatic interactions, meaning that they destabilize protein-nucleic acid binding. Our own PB calculations on protein-protein binding have shown that the sign and the magnitude of the electrostatic component are sensitive to the specification of the dielectric boundary in PB calculations. A popular choice for the boundary between the solute low dielectric and the solvent high dielectric is the molecular surface; an alternative is the van der Waals (vdW) surface. In line with results for protein-protein binding, in this article, we found that PB calculations with the molecular surface gave positive electrostatic interaction energies for two protein-RNA complexes, but the signs are reversed when the vdW surface was used. Therefore, whether destabilizing or stabilizing effects are predicted depends on the choice of the dielectric boundary. The two calculation protocols, however, yielded similar salt effects on the binding affinity. Effects of charge mutations differentiated the two calculation protocols; PB calculations with the vdW surface had smaller deviations overall from experimental data.     

What determines the van der Waals coefficient beta in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations?

Recently a semiempirical method has been proposed by Aqvist et al. to calculate absolute and relative binding free energies. In this method, the absolute binding free energy of a ligand is estimated as deltaGbind = alpha + beta, where Vel(bound) and Vvdw(bound) are the electrostatic and van der Waals interaction energies between the ligand and the solvated protein from an molecular dynamics (MD) trajectory with ligand bound to protein and Vel(free) and Vel(free) and Vvdw(free) are the electrostatic and van der Waals interaction energies between the ligand and the water from an MD trajectory with the ligand in water. A set of values, alpha = 0.5 and beta = 0.16, was found to give results in good agreement with experimental data. Later, however, different optimal values of beta were found in studies of compounds binding to P450cam and avidin. The present work investigates how the optimal value of beta depends on the nature of binding sites for different protein-ligand interactions. By examining seven ligands interacting with five proteins, we have discovered a linear correlation between the value of beta and the weighted non-polar desolvation ratio (WNDR), with a correlation coefficient of 0.96. We have also examined the ability of this correlation to predict optimal values of beta for different ligands binding to a single protein. We studied twelve neutral compounds bound to avidin. In this case, the WNDR approach gave a better estimate of the absolute binding free energies than results obtained using the fixed value of beta found for biotin-avidin. In terms of reproducing the relative binding free energy to biotin, the fixed-beta value gave better results for compounds similar to biotin, but for compounds less similar to biotin, the WNDR approach led to better relative binding free energies.     

Electrostatic contributions to protein-protein interactions: fast energetic filters for docking and their physical basis

The methods of continuum electrostatics are used to calculate the binding free energies of a set of protein-protein complexes including experimentally determined structures as well as other orientations generated by a fast docking algorithm. In the native structures, charged groups that are deeply buried were often found to favor complex formation (relative to isosteric nonpolar groups), whereas in nonnative complexes generated by a geometric docking algorithm, they were equally likely to be stabilizing as destabilizing. These observations were used to design a new filter for screening docked conformations that was applied, in conjunction with a number of geometric filters that assess shape complementarity, to 15 antibody-antigen complexes and 14 enzyme-inhibitor complexes. For the bound docking problem, which is the major focus of this paper, native and near-native solutions were ranked first or second in all but two enzyme-inhibitor complexes. Less success was encountered for antibody-antigen complexes, but in all cases studied, the more complete free energy evaluation was able to identify native and near-native structures. A filter based on the enrichment of tyrosines and tryptophans in antibody binding sites was applied to the antibody-antigen complexes and resulted in a native and near-native solution being ranked first and second in all cases. A clear improvement over previously reported results was obtained for the unbound antibody-antigen examples as well. The algorithm and various filters used in this work are quite efficient and are able to reduce the number of plausible docking orientations to a size small enough so that a final more complete free energy evaluation on the reduced set becomes computationally feasible.     

Electrostatic contribution to the binding stability of protein-protein complexes

To investigate roles of electrostatic interactions in protein binding stability, electrostatic calculations were carried out on a set of 64 mutations over six protein-protein complexes. These mutations alter polar interactions across the interface and were selected for putative dominance of electrostatic contributions to the binding stability. Three protocols of implementing the Poisson-Boltzmann model were tested. In vdW4 the dielectric boundary between the protein low dielectric and the solvent high dielectric is defined as the protein van der Waals surface and the protein dielectric constant is set to 4. In SE4 and SE20, the dielectric boundary is defined as the surface of the protein interior inaccessible to a 1.4-A solvent probe, and the protein dielectric constant is set to 4 and 20, respectively. In line with earlier studies on the barnase-barstar complex, the vdW4 results on the large set of mutations showed the closest agreement with experimental data. The agreement between vdW4 and experiment supports the contention of dominant electrostatic contributions for the mutations, but their differences also suggest van der Waals and hydrophobic contributions. The results presented here will serve as a guide for future refinement in electrostatic calculation and inclusion of nonelectrostatic effects.     

All-Atom Monte Carlo Approach to Protein-Peptide Binding

We develop a procedure for exploring the free energy landscape of protein-peptide binding at atomic detail and apply it to PDZ domain-peptide interactions. The procedure involves soft constraints on receptor proteins providing limited chain flexibility, including backbone motions. Peptide chains are left fully flexible and kept in spatial proximity of the protein through periodic boundary conditions. By extensive Monte Carlo simulations, full representative conformational ensembles at temperatures where bound and unbound states coexist are obtained. To make this approach computationally feasible, we develop an effective all-atom energy function centering on hydrophobicity, hydrogen bonding, and electrostatic interactions. Our initial focus is a set of 11 PDZ domain-peptide pairs with experimentally determined complex structures. Minimum-energy conformations are found to be highly similar to the respective native structures in eight of the cases (all-atom peptide RMSDs < 6 Å). Having achieved that, we turn to a more complete characterization of the bound peptide state through a clustering scheme applied on the full ensembles of peptide structures. We find a significant diversity among bound peptide conformations for several PDZ domains, in particular involving the N terminal side of the peptide chains. Our computational model is then tested further on a set of nine PDZ domain-peptide pairs where the peptides are not originally present in the experimentally determined structures. We find a similar success rate in terms of the nativeness of minimum-energy conformations. Finally, we investigate the ability of our approach to capture variations in binding affinities for different peptide sequences. This is done in particular for a set of related sequences binding to the third PDZ domain of PSD-95 with encouraging results.     

Energetic analysis of binding of progesterone and 5 beta-androstane-3,17-dione to anti-progesterone antibody DB3 using molecular dynamics and free energy calculations.

Molecular dynamics simulations and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) free energy calculations were used to study the energetics of the binding of progesterone (PRG) and 5 beta-androstane-3,17-dione (5AD) to anti-PRG antibody DB3. Although the two steroids bind to DB3 in different orientations, their binding affinities are of the same magnitude, 1 nM for PRG and 8 nM for 5AD. The calculated relative binding free energy of the steroids, 8.8 kJ/mol, is in fair agreement with the experimental energy, 5.4 kJ/mol. In addition, computational alanine scanning was applied to study the role of selected amino acid residues of the ligand-binding site on the steroid cross-reactivity. The electrostatic and van der Waals components of the total binding free energies were found to favour more the binding of PRG, whereas solvation energies were more favourable for the binding of 5AD. The differences in the free energy components are due to the binding of the A rings of the steroids to different binding pockets: PRG is bound to a pocket in which electrostatic antibody-steroid interactions are dominating, whereas 5AD is bound to a pocket in which van der Waals and hydrophobic interactions dominate.     

Reducing CDK4/6-p16(INK4a) interface. Computational alanine scanning of a peptide bound to CDK6 protein

The tumor suppressor gene p16INK4a is commonly found altered in numerous and different types of cancer. The encoded protein arrests cell cycle in G1 phase by binding to CDK4 and CDK6, inhibiting their kinase function. In 1995, a 20-residue peptide, extracted from p16INK4a protein sequence, was discovered that retains the cell cycle inhibition properties of the endogenous tumor suppressor. However, its structure has not been determined yet. In this article, the features of a theoretical structure of the peptide bound to CDK6 are reported. The complex was modeled from CDK6-p16INK4a X-ray crystal structure and through molecular dynamics. Final structure was assessed by comparing computed binding free energy changes, when single-alanine substitutions were brought about on the peptide, to experimental data. Better concordance was obtained when including a high level of solvation effects. Solute-solvent vdW energy and electrostatic energy between solute and first shells of water, computed through a force field and considering explicit waters, were also to be included to achieve reasonably good concordance between theoretical and experimental data.     

Free energy calculations for the relative binding affinity between DNA and lambda-repressor

The change in the binding free energy between DNA and lambda-repressor resulting from a base substitution, thymine (T)-->deoxyuracil (abbreviated as U), was evaluated by the free energy perturbation method on the basis of molecular dynamics simulations for the DNA-lambda-repressor complex in water with all degrees of freedom and including long-range Coulomb interactions. The binding free energy change that we calculated (1.47 +/- 0.40 kcal/mol) was in good agreement with an experimental value (1.8 kcal/mol). We clarified why the small difference between T and U (CH(3) in T is replaced with H in U) caused such a significant change in the binding free energy: The substitution of CH(3) in T with H in U lowered the dissociated-state free energy level due to the gain of the hydration free energy. Furthermore, the T-->U substitution raised the free energy level in the associated state due to the loss of the favored van der Waals (vdW) interactions with the lambda-repressor amino acid residues. In other words, the amino acid residues of lambda-repressor can recognize the CH(3) in T through the vdW interactions with the CH(3). This recognition is enhanced in a water environment, because the hydrophobic CH(3) prefers the amino acid residues of lambda-repressor to water molecules.     

An insight into the inhibitory selectivity of 4-(Pyrazol- 4-yl)-pyrimidines to CDK4 over CDK2

Revealing selectivity mechanism of cyclin-dependent kinases (CDK) and their inhibitors is an important issue to develop potential anticancer drugs. The substituted 4-(Pyrazol-4-yl)-pyrimidines are potent inhibitors of CDK4 but not of the highly homologous CDK2. In order to reveal the inhibitory selectivity of these inhibitors to CDK4 over CDK2, we select one of substituted 4-(Pyrazol-4-yl)-pyrimidines as a representative (marked as A1 hereunder) and perform molecular docking, molecular dynamics simulations and binding free energy analysis for CDK4/A1 and CDK2/A1, respectively. The electrostatic and van der Waals (vdW) interactions of the A1 inhibitor with CDK4/CDK2 are discussed. The computed binding free energies based on the MM-PBSA method are consistent with experimental bioactivity ranking of A1 inhibitor to CDK4/CDK2. On the other hand, the conformational characteristics of CDK2 and CDK4 induced by A1 inhibitor are analysed and revealed. Results demonstrate that the vdW interactions considerably contribute to binding of CDK4/CDK2 with A1 inhibitor and are similar in size. The hydrogen bonding between A1 inhibitor and CDK4/CDK2 is considerably favourable to the binding, in which the hydrogen bond between the NH group of the pyrazole group of A1 and the residue Asp158 of CDK4 plays a crucial role in inhibitory selectivity of A1 inhibitor to CDK4 over CDK2. The electrostatic interaction energy differences between the corresponding residues of CDK4/A1 and CDK2/A1 confirm the above inference. The conformational changes of CDK2 and CDK4 induced by A1 inhibitor influence the selectivity of A1 inhibitor to CDK4/CDK2.     

Interactions of calmodulin with death-associated protein kinase peptides: experimental and modeling studies

We have studied the interactions between calmodulin (CaM) and three target peptides from the death-associated protein kinase (DAPK) protein family using both experimental and modeling methods, aimed at determining the details of the underlying biological regulation mechanisms. Experimentally, calorimetric binding free energies were determined for the complexes of CaM with peptides representing the DAPK2 wild-type and S308D mutant, as well as DAPK1. The observed affinity of CaM was very similar for all three studied peptides. The DAPK2 and DAPK1 peptides differ significantly in sequence and total charge, while the DAPK2 S308D mutant is designed to model the effects of DAPK2 Ser308 phosphorylation. The crystal structure of the CaM-DAPK2 S308D mutant peptide is also reported. The structures of CaM-DAPK peptide complexes present a mode of CaM-kinase interaction, in which bulky hydrophobic residues at positions 10 and 14 are both bound to the same hydrophobic cleft. To explain the microscopic effects underlying these interactions, we performed free energy calculations based on the approximate MM-PBSA approach. For these highly charged systems, standard MM-PBSA calculations did not yield satisfactory results. We proposed a rational modification of the approach which led to reasonable predictions of binding free energies. All three complexes are strongly stabilized by two effects: electrostatic interactions and buried surface area. The strong favorable interactions are to a large part compensated by unfavorable entropic terms, in which vibrational entropy is the largest contributor. The electrostatic component of the binding free energy followed the trend of the overall peptide charge, with strongest interactions for DAPK1 and weakest for the DAPK2 mutant. The electrostatics was dominated by interactions of the positively charged residues of the peptide with the negatively charged residues of CaM. The nonpolar binding free energy was comparable for all three peptides, the largest contribution coming from the Trp305. About two-thirds of the buried surface area corresponds to nonpolar residues, showing that hydrophobic interactions play an important role in these CaM-peptide complexes. The simulation results agree with the experimental data in predicting a small effect of the S308D mutation on CaM interactions with DAPK2, suggesting that this mutation is not a good model for the S308 phosphorylation.     

Simulation of the different biological activities of diethylstilbestrol (DES) on estrogen receptor alpha and estrogen-related receptor gamma

We describe the application of the molecular dynamics (MD) and molecular mechanics-generalized Born/surface area (MM-GB/SA) approaches to the simulation of the different biological activity of diethylstilbestrol (DES) on two highly homologous nuclear receptors-estrogen receptor alpha (ER-alpha) and estrogen-related receptor gamma (ERR-gamma). DES exerts an agonistic effect against ER-alpha and an antagonistic effect against ERR-gamma. Using the x-ray crystal structures of ER-alpha in the canonical agonist bound form (PDB code: 3ERD) and antagonist bound form (PDB code: 3ERT), ERR-gamma homology models have been constructed for the receptor in two different conformations. MM-GB/SA binding free energy calculations of DES in the ER-alpha and ERR-gamma structures suggest that DES exhibits a greater free energy of binding in the agonist bound conformation of ER-alpha, while the antagonist bound conformation is preferred for ERR-gamma. Further dissection of the free energy contributions coupled with calculation of the ligand binding pocket volume suggests that the van der Waals interactions for DES within the smaller binding pocket volume of ERR-gamma are less favorable and this is the main factor for DES antagonism in ERR-gamma. This approach has potential general applicability to the prediction of the biological activity of nuclear receptor ligands.     

Stereochemistry of binding of the tetrapeptide acetyl-Pro-Ala-Pro-Tyr-NH2 to porcine pancreatic elastase. Combined use of two-dimensional transferred nuclear Overhauser enhancement measurements, restrained molecular dynamics, X-ray crystallography and molecular modelling

A nuclear magnetic resonance study of the conformation of the tetrapeptide acetyl-Pro-Ala-Pro-Tyr-NH2 bound to porcine pancreatic elastase is presented. From two-dimensional transferred nuclear Overhauser enhancement measurements, a set of 23 approximate distance restraints between pairs of bound ligand protons, indicative of an extended type structure, is derived. The structure of the bound tetrapeptide is then refined from two different starting structures (an extended beta-strand and a polyproline helix) by restrained molecular dynamics, in which the interproton distances are incorporated into the total energy of the system in the form of effective potentials. Convergence to essentially the same average restrained dynamics structures is achieved. The refined structures are then modelled into the active site of elastase by interactive molecular graphics. The determination of the anchor point of the bound tetrapeptide on the enzyme was aided by a simultaneous crystallographic study which, despite the fact that only electron density for a Pro-X dipeptide fragment was visible, enabled both the approximate position and orientation of binding to be determined. It is found that the tetrapeptide is bound in the S' binding site in the reverse orientation found in other serine protease-inhibitor complexes and is stabilized both by hydrogen-bonding and by van der Waals' interactions.     

Protein clefts in molecular recognition and function.

One of the primary factors determining how proteins interact with other molecules is the size of clefts in the protein's surface. In enzymes, for example, the active site is often characterized by a particularly large and deep cleft, while interactions between the molecules of a protein dimer tend to involve approximately planar surfaces. Here we present an analysis of how cleft volumes in proteins relate to their molecular interactions and functions. Three separate datasets are used, representing enzyme-ligand binding, protein-protein dimerization and antibody-antigen complexes. We find that, in single-chain enzymes, the ligand is bound in the largest cleft in over 83% of the proteins. Usually the largest cleft is considerably larger than the others, suggesting that size is a functional requirement. Thus, in many cases, the likely active sites of an enzyme can be identified using purely geometrical criteria alone. In other cases, where there is no predominantly large cleft, chemical interactions are required for pinpointing the correct location. In antibody-antigen interactions the antibody usually presents a large cleft for antigen binding. In contrast, protein-protein interactions in homodimers are characterized by approximately planar interfaces with several clefts involved. However, the largest cleft in each subunit still tends to be involved.     

Rationalization and design of the complementarity determining region sequences in an antibody-antigen recognition interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes.     

On the contribution of water-mediated interactions to protein-complex stability

Protein-water interactions have long been recognized as a major determinant of chain folding, conformational stability, binding specificity and catalysis. However, the detailed effects of water on stabilizing protein-protein interactions remain elusive. A way to test experimentally the contribution of water-mediated interactions is by applying double mutant cycle analysis on pairs of residues that do not form direct interactions, but are bridged by water. Seven such interactions within the interface between TEM1 and BLIP proteins were evaluated. No significant interaction free energy was found between either of them. Water can bridge interactions, but also stabilize the structure of the monomer. To distinguish between these, we performed a bioinformatic analysis using AQUAPROT (http://bioinfo.weizmann.ac.il/aquaprot) to determine the degree of water conservation between the bound and unbound states. 29 structures of twelve complexes and 20 related monomers were analyzed. Of the 262 water molecules located within the interfaces, 145 were conserved between the unbound and bound structures. Strikingly, all 50 buried or partially buried waters in the monomer structures were conserved at the same location in the bound structures. Thus, buried waters have an important role in stabilizing the monomer fold rather than contributing to protein-protein binding, and are not replaced by residues from the incoming protein. Taking together the experimental and bioinformatics evidence suggests that exposed waters within the interface may be good sites for protein engineering, while buried or mostly buried waters should be left unchanged.