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

Computational Alanine Scanning Reveals Common Features of TCR/pMHC Recognition in HLA-DQ8-Associated Celiac Disease

In HLA-DQ8-associated celiac disease, Gliadin-γ1 or Gliadin-α1 peptide is presented to the cell surface and recognized by several types of T-cell receptor (TCR), but it is still unclear how the TCR, peptide, and the major histocompatibility complex (MHC) act together to trigger celiac disease. For now, most of the analysis is based on static crystal structures. And the detailed information about these structures based on energetic interaction is still lacking. Here, we took four types of celiac disease-related MHC-peptide-TCR structures from three patients to perform computational alanine scanning calculations using the molecular mechanics generalized born surface area (MM/GBSA) approach combined with a recently developed interaction entropy (IE) method to identify the key residues on TCR, peptide, and MHC. Our study aims to shed some light on the interaction mechanism of this complex protein interaction system. Based on detailed computational analysis and mutational calculations, important binding interactions in these triple-interaction complexes are analyzed, and critical residues responsible for TCR/pMHC recognition pattern in HLA-DQ8-associated celiac disease are presented. These detailed analysis and computational result should help shed light on our understanding of the celiac disease and the development of the medical treatment.

Conformational selection of allergen-antibody complexes-surface plasticity of paratopes and epitopes

Antibodies have the ability to bind various types of antigens and to recognize different antibody-binding sites (epitopes) of the same antigen with different binding affinities. Due to the conserved structural framework of antibodies, their specificity to antigens is mainly determined by their antigen-binding site (paratope). Therefore, characterization of epitopes in combination with describing the involved conformational changes of the paratope upon binding is crucial in understanding and predicting antibody-antigen binding. Using molecular dynamics simulations complemented with strong experimental structural information, we investigated the underlying binding mechanism and the resulting local and global surface plasticity in the binding interfaces of distinct antibody-antigen complexes. In all studied allergen-antibody complexes, we clearly observe that experimentally suggested epitopes reveal less plasticity, while non-epitope regions show high surface plasticity. Surprisingly, the paratope shows higher conformational diversity reflected in substantially higher surface plasticity, compared to the epitope. This work allows a visualization and characterization of antibody-antigen interfaces and might have strong implications for antibody-antigen docking and in the area of epitope prediction.

Pushing the accuracy limit of shape complementarity for protein-protein docking

Background

Protein-protein docking is a valuable computational approach for investigating protein-protein interactions. Shape complementarity is the most basic component of a scoring function and plays an important role in protein-protein docking. Despite significant progresses, shape representation remains an open question in the development of protein-protein docking algorithms, especially for grid-based docking approaches.

Results

We have proposed a new pairwise shape-based scoring function (LSC) for protein-protein docking which adopts an exponential form to take into account long-range interactions between protein atoms. The LSC scoring function was incorporated into our FFT-based docking program and evaluated for both bound and unbound docking on the protein docking benchmark 4.0. It was shown that our LSC achieved a significantly better performance than four other similar docking methods, ZDOCK 2.1, MolFit/G, GRAMM, and FTDock/G, in both success rate and number of hits. When considering the top 10 predictions, LSC obtained a success rate of 51.71% and 6.82% for bound and unbound docking, respectively, compared to 42.61% and 4.55% for the second-best program ZDOCK 2.1. LSC also yielded an average of 8.38 and 3.94 hits per complex in the top 1000 predictions for bound and unbound docking, respectively, followed by 6.38 and 2.96 hits for the second-best ZDOCK 2.1.

Conclusions

The present LSC method will not only provide an initial-stage docking approach for post-docking processes but also have a general implementation for accurate representation of other energy terms on grids in protein-protein docking. The software has been implemented in our HDOCK web server at http://hdock.phys.hust.edu.cn/.

Engineered Dengue Virus Domain III Proteins Elicit Cross-Neutralizing Antibody Responses in Mice

Dengue virus is the most globally prevalent mosquito-transmitted virus. Primary infection with one of four cocirculating serotypes (DENV-1 to -4) causes a febrile illness, but secondary infection with a heterologous serotype can result in severe disease, due in part to antibody-dependent enhancement of infection (ADE). In ADE, cross-reactive but nonneutralizing antibodies, or subprotective levels of neutralizing antibodies, promote uptake of antibody-opsonized virus in Fc-γ receptor-positive cells. Thus, elicitation of broadly neutralizing antibodies (bNAbs), but not nonneutralizing antibodies, is desirable for dengue vaccine development. Domain III of the envelope glycoprotein (EDIII) is targeted by bNAbs and thus is an attractive immunogen. However, immunization with EDIII results in sera with limited neutralization breadth. We developed "resurfaced" EDIII immunogens (rsDIIIs) in which the A/G strand epitope that is targeted by bNAb 4E11 is maintained but less desirable epitopes are masked. RsDIIIs bound 4E11, but not serotype-specific or nonneutralizing antibodies. One rsDIII and, unexpectedly, wild-type (WT) DENV-2 EDIII elicited cross-neutralizing antibody responses against DENV-1 to -3 in mice. While these sera were cross-neutralizing, they were not sufficiently potent to protect AG129 immunocompromised mice at a dose of 200 μl (50% focus reduction neutralization titer [FRNT₅₀], ∼1:60 to 1:130) against mouse-adapted DENV-2. Our results provide insight into immunogen design strategies based on EDIII.IMPORTANCE Dengue virus causes approximately 390 million infections per year. Primary infection by one serotype causes a self-limiting febrile illness, but secondary infection by a heterologous serotype can result in severe dengue syndrome, which is characterized by hemorrhagic fever and shock syndrome. This severe disease is thought to arise because of cross-reactive, non- or poorly neutralizing antibodies from the primary infection that are present in serum at the time of secondary infection. These cross-reactive antibodies enhance the infection rather than controlling it. Therefore, induction of a broadly and potently neutralizing antibody response is desirable for dengue vaccine development. Here, we explore a novel strategy for developing immunogens based on domain III of the E glycoprotein, where undesirable epitopes (nonneutralizing or nonconserved) are masked by mutation. This work provides fundamental insight into the immune response to domain III that can be leveraged for future immunogen design.

Rapid Detection of Avian Influenza Virus by Fluorescent Diagnostic Assay using an Epitope-Derived Peptide

Currently, the point of care testing (POCT) is not fully developed for subtype-specific avian influenza virus detection. In this study, an H5N1 hemaglutinin 1 (HA1) epitope (P0: KPNDAINF) and three modified peptides (P1: KPNTAINF, P2: KPNGAINF, P3: KPNDAINDAINF) were evaluated as POCT elements for rapid detection of avian influenza virus. Based on modeling predictions by Autodock Vina, binding affinity varied depending on alteration of one amino acid in these peptides. The binding energy of P2 indicated its potential for a strong interaction with HA. Fluorescence-linked immunosorbent assay experimentally demonstrated the interaction between these peptides and virus. The four peptides interacted with HA1 of H5N3 with different binding affinities with P2 showing the strongest binding affinity. When P0 and P2 peptides were used in rapid fluorescent immunochromatographic test (FICT) as detection elements, the inter-assay coefficients of variation (CV) indicated that P2-linked FICT was more acceptable than the P0-linked FICT in the presence of human specimens. Antibody pair-linked FICT was influenced by clinical samples more than the P2-linked FICT assay, which showed a 4-fold improvement in the detection limit of H5N3 and maintained H5 subtype-specificity. Compared to the rapid diagnostic test (RDT) which is not specific for influenza subtypes, P2-linked FICT could increase virus detection. In conclusion, results of this study suggest that HA epitope-derived peptides can be used as alternatives to antibodies for a rapid fluorescent diagnostic assay to detect avian influenza virus.

Great interactions: How binding incorrect partners can teach us about protein recognition and function

Protein–protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross‐docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross‐docking predictions using the area under the specificity‐sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding‐site predictions resulting from the cross‐docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408–1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Evaluation of the coarse-grained OPEP force field for protein-protein docking

Background

Knowing the binding site of protein–protein complexes helps understand their function and shows possible regulation sites. The ultimate goal of protein–protein docking is the prediction of the three-dimensional structure of a protein–protein complex. Docking itself only produces plausible candidate structures, which must be ranked using scoring functions to identify the structures that are most likely to occur in nature.

Methods

In this work, we rescore rigid body protein–protein predictions using the optimized potential for efficient structure prediction (OPEP), which is a coarse-grained force field. Using a force field based on continuous functions rather than a grid-based scoring function allows the introduction of protein flexibility during the docking procedure. First, we produce protein–protein predictions using ZDOCK, and after energy minimization via OPEP we rank them using an OPEP-based soft rescoring function. We also train the rescoring function for different complex classes and demonstrate its improved performance for an independent dataset.

Results

The trained rescoring function produces a better ranking than ZDOCK for more than 50 % of targets, rising to over 70 % when considering only enzyme/inhibitor complexes.

Conclusions

This study demonstrates for the first time that energy functions derived from the coarse-grained OPEP force field can be employed to rescore predictions for protein–protein complexes.

Shape complementarity and hydrogen bond preferences in protein-protein interfaces: implications for antibody modeling and protein-protein docking

MOTIVATIONS

Characterizing protein-protein interfaces and the hydrogen bonds is a first step to better understand proteins' structures and functions toward high-resolution protein design. However, there are few large-scale surveys of hydrogen bonds of interfaces. In addition, previous work of shape complementarity of protein complexes suggested that lower shape complementarity in antibody-antigen interfaces is related to their evolutionary origin.

RESULTS

Using 6637 non-redundant protein-protein interfaces, we revealed peculiar features of various protein complex types. In contrast to previous findings, the shape complementarity of antibody-antigen interfaces resembles that of the other interface types. These results highlight the importance of hydrogen bonds during evolution of protein interfaces and rectify the prevailing belief that antibodies have lower shape complementarity.

CONTACT

jgray@jhu.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bovine milk proteome in the first 9 days: protein interactions in maturation of the immune and digestive system of the newborn

In order to better understand the milk proteome and its changes from colostrum to mature milk, samples taken at seven time points in the first 9 days from 4 individual cows were analyzed using proteomic techniques. Both the similarity in changes from day 0 to day 9 in the quantitative milk proteome, and the differences in specific protein abundance, were observed among four cows. One third of the quantified proteins showed a significant decrease in concentration over the first 9 days after calving, especially in the immune proteins (as much as 40 fold). Three relative high abundant enzymes (XDH, LPL, and RNASE1) and cell division and proliferation protein (CREG1) may be involved in the maturation of the gastro-intestinal tract. In addition, high correlations between proteins involved in complement and blood coagulation cascades illustrates the complex nature of biological interrelationships between milk proteins. The linear decrease of protease inhibitors and proteins involved in innate and adaptive immune system implies a protective role for protease inhibitor against degradation. In conclusion, the results found in this study not only improve our understanding of the role of colostrum in both host defense and development of the newborn calf but also provides guidance for the improvement of infant formula through better understanding of the complex interactions between milk proteins.

Structural studies of the sBBI/trypsin non-covalent complex using covalent modification and mass spectrometry

RATIONALE

The study of protein recognition sites is crucial for understanding the mechanisms of protein interaction. Mass spectrometry can be a method of choice for the investigation of the contact surface within the protein non-covalent complexes.

METHODS

Probing the reactivity of essential amino acid residues of soybean Bowman-Birk inhibitor (sBBI) within the non-covalent sBBI/bovine trypsin complex was performed using covalent labeling by the BS3 cross-linker and charge tag with a quaternary ammonium group in combination with matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analysis.

RESULTS

Significant modulation of the reactivity of essential K16 and S17 residues in the sBBI molecule upon binding to trypsin was established. The studies of sBBI proteolytic peptides with the same structure but carrying different labels using metastable dissociation in LIFT mode demonstrated that fragmentation pathways were oriented by used modification (BS3 cross-linker or charge tag).

CONCLUSIONS

The effectiveness of the mass spectrometric approach including covalent modification for exploring protein-protein interaction sites has been demonstrated. The alteration of the reactivity of functionally important amino acid residues in the sBBI molecule is most likely related to changes in their microenvironment. It has been suggested that in the presence of charge tags fragmentation in LIFT mode proceeds through the formation of salt bridges between quaternary ammonium groups and acidic residues due to the occurrence of zwitterions (including basic and acidic residues). Despite the presence of one or several charge tags, fragmentation takes place yielding modulated bi /yj ion series depending on the positions of the tags.

DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking

The distance-dependent knowledge-based DrugScore^PPI potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking “unbound perturbation” (“unbound docking”) decoys generated by Baker and coworkers a 4-fold (1.5-fold) enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScore^PPI/FRODOCK finds up to 10% (15%) more high accuracy solutions in the top 1 (top 10) predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ∼2-fold to 18% (58%) for an at least acceptable solution in the top 10 (top 100) predictions when performing knowledge-driven unbound docking. This suggests that DrugScore^PPI balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScore^PPI/FRODOCK will be successful.

Molecular characterization of monoclonal antibodies that inhibit acetylcholinesterase by targeting the peripheral site and backdoor region

The inhibition properties and target sites of monoclonal antibodies (mAbs) Elec403, Elec408 and Elec410, generated against Electrophorus electricus acetylcholinesterase (AChE), have been defined previously using biochemical and mutagenesis approaches. Elec403 and Elec410, which bind competitively with each other and with the peptidic toxin inhibitor fasciculin, are directed toward distinctive albeit overlapping epitopes located at the AChE peripheral anionic site, which surrounds the entrance of the active site gorge. Elec408, which is not competitive with the other two mAbs nor fasciculin, targets a second epitope located in the backdoor region, distant from the gorge entrance. To characterize the molecular determinants dictating their binding site specificity, we cloned and sequenced the mAbs; generated antigen-binding fragments (Fab) retaining the parental inhibition properties; and explored their structure-function relationships using complementary x-ray crystallography, homology modeling and flexible docking approaches. Hypermutation of one Elec403 complementarity-determining region suggests occurrence of antigen-driven selection towards recognition of the AChE peripheral site. Comparative analysis of the 1.9Å-resolution structure of Fab408 and of theoretical models of its Fab403 and Fab410 congeners evidences distinctive surface topographies and anisotropic repartitions of charges, consistent with their respective target sites and inhibition properties. Finally, a validated, data-driven docking model of the Fab403-AChE complex suggests a mode of binding at the PAS that fully correlates with the functional data. This comprehensive study documents the molecular peculiarities of Fab403 and Fab410, as the largest peptidic inhibitors directed towards the peripheral site, and those of Fab408, as the first inhibitor directed toward the backdoor region of an AChE and a unique template for the design of new, specific modulators of AChE catalysis.

Immunogenicity of membrane-bound HIV-1 gp41 membrane-proximal external region (MPER) segments is dominated by residue accessibility and modulated by stereochemistry

Structural characterization of epitope-paratope pairs has contributed to the understanding of antigenicity. By contrast, few structural studies relate to immunogenicity, the process of antigen-induced immune responses in vivo. Using a lipid-arrayed membrane-proximal external region (MPER) of HIV-1 glycoprotein 41 as a model antigen, we investigated the influence of physicochemical properties on immunogenicity in relation to structural modifications of MPER/liposome vaccines. Anchoring the MPER to the membrane via an alkyl tail or transmembrane domain retained the MPER on liposomes in vivo, while preserving MPER secondary structure. However, structural modifications that affected MPER membrane orientation and antigenic residue accessibility strongly impacted induced antibody responses. The solvent-exposed MPER tryptophan residue (Trp-680) was immunodominant, focusing immune responses, despite sequence variability elsewhere. Nonetheless, immunogenicity could be readily manipulated using site-directed mutagenesis or structural constraints to modulate amino acid surface display. These studies provide fundamental insights for immunogen design aimed at targeting B cell antibody responses.

GalaxyDock: protein-ligand docking with flexible protein side-chains

An important issue in developing protein-ligand docking methods is how to incorporate receptor flexibility. Consideration of receptor flexibility using an ensemble of precompiled receptor conformations or by employing an effectively enlarged binding pocket has been reported to be useful. However, direct consideration of receptor flexibility during energy optimization of the docked conformation has been less popular because of the large increase in computational complexity. In this paper, we present a new docking program called GalaxyDock that accounts for the flexibility of preselected receptor side-chains by global optimization of an AutoDock-based energy function trained for flexible side-chain docking. This method was tested on 3 sets of protein-ligand complexes (HIV-PR, LXRβ, cAPK) and a diverse set of 16 proteins that involve side-chain conformational changes upon ligand binding. The cross-docking tests show that the performance of GalaxyDock is higher or comparable to previous flexible docking methods tested on the same sets, increasing the binding conformation prediction accuracy by 10%-60% compared to rigid-receptor docking. This encouraging result suggests that this powerful global energy optimization method may be further extended to incorporate larger magnitudes of receptor flexibility in the future. The program is available at http://galaxy.seoklab.org/softwares/galaxydock.html .

An analysis of B-cell epitope discontinuity

Although it is widely acknowledged that most B-cell epitopes are discontinuous, the degree of discontinuity is poorly understood. For example, given that an antigen having a single epitope that has been chopped into peptides of a specific length, what is the likelihood that one of the peptides will span all the residues belonging to that epitope? Or, alternatively, what is the largest proportion of the epitope's residues that any peptide is likely to contain? These and similar questions are of direct relevance both to computational methods that aim to predict the location of epitopes from sequence (linear B-cell epitope prediction methods) and window-based experimental methods that aim to locate epitopes by assessing the strength of antibody binding to synthetic peptides on a chip.

In this paper we present an analysis of the degree of B-cell epitope discontinuity, both in terms of the structural epitopes defined by a set of antigen–antibody complexes in the Protein Data Bank, and with respect to the distribution of key residues that form functional epitopes. We show that, taking a strict definition of discontinuity, all the epitopes in our data set are discontinuous. More significantly, we provide explicit guidance about the choice of peptide length when using window-based B-cell epitope prediction and mapping techniques based on a detailed analysis of the likely effectiveness of different lengths.

Possible conformational change within the desolvated and cationized sBBI/trypsin non-covalent complex during the collision-induced dissociation process

Electrospray ionization mass spectrometry (ESI-MS) has become an analytical technique widely used for the investigation of non-covalent protein-protein and protein-ligand complexes due to the soft desolvation conditions that preserve the stoichiometry of the interacting partners. Dissociation studies of solvated or desolvated complexes (in the source and in the collision cell, respectively) allow access to information on protein conformation and localization of the metal ions involved in protein structure stabilization and biological activity. The complex of bovine trypsin and small soybean Bowman-Birk inhibitor (sBBI) was studied by ESI-MS to determine changes occurring within the complex during its transfer from droplets to the gas phase independently of the ion polarity. Under collision-induced dissociation (CID) conditions, unexpected binding of the Ca(2+) ion (cofactor of native trypsin) to the inhibitor molecule was observed within the desolvated sBBI/trypsin/Ca(2+) complex (with a 1:1:1 stoichiometry). This formal gas-phase migration of the calcium ion from trypsin to the inhibitor may be related to conformational rearrangements in the solvent-free and likely collapsed complex. However, under conditions leading to the increase in complex charge state, the appearance of the cationized trypsin molecule was detected during complex dissociation, thus reflecting different pathways of the evolution of complex conformation.

Design of Deinococcus radiodurans thioredoxin reductase with altered thioredoxin specificity using computational alanine mutagenesis

In this study, the X-ray crystal structure of the complex between Escherichia coli thioredoxin reductase (EC TrxR) and its substrate thioredoxin (Trx) was used as a guide to design a Deinococcus radiodurans TrxR (DR TrxR) mutant with altered Trx specificity. Previous studies have shown that TrxRs have higher affinity for cognate Trxs (same species) than that for Trxs from different species. Computational alanine scanning mutagenesis and visual inspection of the EC TrxR-Trx interface suggested that only four residues (F81, R130, F141, and F142) account for the majority of the EC TrxR-Trx interface stability. Individual replacement of equivalent residues in DR TrxR (M84, K137, F148, and F149) with alanine resulted in drastic changes in binding affinity, confirming that the four residues account for most of TrxR-Trx interface stability. When M84 and K137 were changed to match equivalent EC TrxR residues (K137R and M84F), the DR TrxR substrate specificity was altered from its own Trx to that of EC Trx. The results suggest that a small subset of the TrxR-Trx interface residues is responsible for the majority of Trx binding affinity and species-specific recognition.

Functional mapping of the anti-idiotypic antibody anti-TS1 scFv using site-directed mutagenesis and kinetic analysis

Recombinant antibodies may be engineered to obtain improved functional properties. Functional mapping of the residues in the binding surfaces is of importance for predicting alterations needed to yield the desired properties. In this investigation, 17 single mutation mutant single-chain variable fragments (scFvs) of the anti-idiotypic antibody anti-TS1 were generated in order to functionally map amino acid residues important for the interaction with its idiotype TS1. Residues in anti-TS1 determined to be very important for the interaction were identified, Y32L, K50L, K33H, and Y52H, and they were distributed adjacent to a centrally located hydrophobic area, and contributed extensively to the interaction energy (≥2.5 kcal/mol) in the interaction. Quantitative ELISA assays, BIAcore technologies and three-dimensional surface analysis by modeling were employed to visualize the consequences of the mutations. The expression levels varied between 2 - 1,800 nM as determined by ELISA. All the 17 scFvs displayed higher dissociation rates (60 - 1,300 times) and all but two of them also faster association rates (1.3 - 56 times). The decrease in affinity was determined to be 1.6 - 12,200 times. Two of the mutants displayed almost identical affinity with the wild type anti-TS1, but with a change in both association and dissociation rates. The present investigation demonstrates that it is possible to generate a large panorama of anti-idiotypic antibodies, and single out a few that might be of potential use for future clearing and pre-targeting purposes of idiotypic-anti-idiotypic interactions.

Parallel synthesis of an oligomeric imidazole-4,5-dicarboxamide library

A library of oligomeric compounds was synthesized based on the imidazole-4,5-dicarboxylic acid scaffold along with amino acid esters and chiral diamines derived from amino acids. The final compounds incorporate nonpolar amino acids (Leu, Phe, Trp), polar amino acids (Ser, Asp, Arg), and neutral amino acids (Gly, Ala), and were designed to be useful in screening for inhibitors of protein-protein interactions. Many of the protected and deprotected oligomers show evidence of conformational isomers persistent at room temperature in aqueous solution. A total of 317 final oligomers, out of 441 targeted compounds, were obtained in high analytical purity and of sufficient quantity to submit them for high-throughput screening as part of the NIH Roadmap.

Mining for the antibody-antigen interacting associations that predict the B cell epitopes

Background

Predicting B-cell epitopes is very important for designing vaccines and drugs to fight against the infectious agents. However, due to the high complexity of this problem, previous prediction methods that focus on linear and conformational epitope prediction are both unsatisfactory. In addition, antigen interacting with antibody is context dependent and the coarse binary classification of antigen residues into epitope and non-epitope without the corresponding antibody may not reveal the biological reality. Therefore, we take a novel way to identify epitopes by using associations between antibodies and antigens.

Results

Given a pair of antibody-antigen sequences, the epitope residues can be identified by two types of associations: paratope-epitope interacting biclique and cooccurrent pattern of interacting residue pairs. As the association itself does not include the neighborhood information on the primary sequence, residues' cooperativity and relative composition are then used to enhance our method. Evaluation carried out on a benchmark data set shows that the proposed method produces very good performance in terms of accuracy. After compared with other two structure-based B-cell epitope prediction methods, results show that the proposed method is competitive to, sometimes even better than, the structure-based methods which have much smaller applicability scope.

Conclusions

The proposed method leads to a new way of identifying B-cell epitopes. Besides, this antibody-specified epitope prediction can provide more precise and helpful information for wet-lab experiments.

Potential aggregation-prone regions in complementarity-determining regions of antibodies and their contribution towards antigen recognition: a computational analysis

PURPOSE

To analyze contribution of short aggregation-prone regions (APRs), which may self-associate via cross-beta motif and were earlier identified in therapeutic mAbs, towards antigen recognition via structural analyses of antibody-antigen complexes.

METHODS

A dataset of 29 publically available high-resolution crystal structures of Fab-antigen complexes was collected. Contribution of APRs towards the surface areas of the Fabs buried by the cognate antigens was computed. Propensities of amino acids to occur in APRs and to be involved in antigen binding were compared. Coincidence between APRs and individual CDR loops was examined.

RESULTS

All Fabs in the dataset contain at least one APR in CDR loops and adjacent framework beta-strands. The average contribution of APRs towards buried surface area of Fabs is 16.0 +/- 10.7%. Aggregation and antigen recognition may be coupled via aromatic residues (Tyr, Trp), which occur with high propensities in both APRs and antigen binding sites. APRs are infrequent in the heavy chain CDR 3 (H3) loops (7%), but are frequent in H2 loops (45%).

CONCLUSIONS

Co-incidence of APRs with antigen recognition sites can potentially lead to the loss of function upon aggregation. Rational structure-based design or selection strategies are suggested for biotherapeutics with improved druggability while maintaining potency.

Contribution of asparagine residues to the stabilization of a proteinaceous antigen-antibody complex, HyHEL-10-hen egg white lysozyme

Many germ line antibodies have asparagine residues at specific sites to achieve specific antigen recognition. To study the role of asparagine residues in the stabilization of antigen-antibody complexes, we examined the interaction between hen egg white lysozyme (HEL) and the corresponding HyHEL-10 variable domain fragment (Fv). We introduced Ala and Asp substitutions into the Fv side chains of L-Asn-31, L-Asn-32, and L-Asn-92, which interact directly with residues in HEL via hydrogen bonding in the wild-type Fv-HEL complex, and we investigated the interactions between these mutant antibodies and HEL. Isothermal titration calorimetric analysis showed that all the mutations decreased the negative enthalpy change and decreased the association constants of the interaction. Structural analyses showed that the effects of the mutations on the structure of the complex could be compensated for by conformational changes and/or by gains in other interactions. Consequently, the contribution of two hydrogen bonds was minor, and their abolition by mutation resulted in only a slight decrease in the affinity of the antibody for its antigen. By comparison, the other two hydrogen bonds buried at the interfacial area had large enthalpic advantage, despite entropic loss that was perhaps due to stiffening of the interface by the bonds, and were crucial to the strength of the interaction. Deletion of these strong hydrogen bonds could not be compensated for by other structural changes. Our results suggest that asparagine can provide the two functional groups for strong hydrogen bond formation, and their contribution to the antigen-antibody interaction can be attributed to their limited flexibility and accessibility at the complex interface.

Improving the species cross-reactivity of an antibody using computational design

The high degree of specificity displayed by antibodies often results in varying potencies against antigen orthologs, which can affect the efficacy of these molecules in different animal models of disease. We have used a computational design strategy to improve the species cross-reactivity of an antibody-based inhibitor of the cancer-associated serine protease MT-SP1. In silico predictions were tested in vitro, and the most effective mutation, T98R, was shown to improve antibody affinity for the mouse ortholog of the enzyme 14-fold, resulting in an inhibitor with a K(I) of 340 pM. This improved affinity will be valuable when exploring the role of MT-SP1 in mouse models of cancer, and the strategy outlined here could be useful in fine-tuning antibody specificity.

DARS (Decoys As the Reference State) potentials for protein-protein docking

Decoys As the Reference State (DARS) is a simple and natural approach to the construction of structure-based intermolecular potentials. The idea is generating a large set of docked conformations with good shape complementarity but without accounting for atom types, and using the frequency of interactions extracted from these decoys as the reference state. In principle, the resulting potential is ideal for finding near-native conformations among structures obtained by docking, and can be combined with other energy terms to be used directly in docking calculations. We investigated the performance of various DARS versions for docking enzyme-inhibitor, antigen-antibody, and other type of complexes. For enzyme-inhibitor pairs, DARS provides both excellent discrimination and docking results, even with very small decoy sets. For antigen-antibody complexes, DARS is slightly better than a number of interaction potentials tested, but results are worse than for enzyme-inhibitor complexes. With a few exceptions, the DARS docking results are also good for the other complexes, despite poor discrimination, and we show that the latter is not a correct test for docking accuracy. The analysis of interactions in antigen-antibody pairs reveals that, in constructing pairwise potentials for such complexes, one should account for the asymmetry of hydrophobic patches on the two sides of the interface. Similar asymmetry does occur in the few other complexes with poor DARS docking results.

Efficient comprehensive scoring of docked protein complexes using probabilistic support vector machines

Biological systems and processes rely on a complex network of molecular interactions. While the association of biological macromolecules is a fundamental biochemical phenomenon crucial for the understanding of complex living systems, protein-protein docking methods aim for the computational prediction of protein complexes from individual subunits. Docking algorithms generally produce large numbers of putative protein complexes with only few of these conformations resembling the native complex structure within an acceptable degree of structural similarity. A major challenge in the field of docking is to extract near-native structure(s) out of the large pool of solutions, the so called scoring or ranking problem. A series of structural, chemical, biological and physical properties are used in this work to classify docked protein-protein complexes. These properties include specialized energy functions, evolutionary relationship, class specific residue interface propensities, gap volume, buried surface area, empiric pair potentials on residue and atom level as well as measures for the tightness of fit. Efficient comprehensive scoring functions have been developed using probabilistic Support Vector Machines in combination with this array of properties on the largest currently available protein-protein docking benchmark. The established classifiers are shown to be specific for certain types of protein-protein complexes and are able to detect near-native complex conformations from large sets of decoys with high sensitivity. Using classification probabilities the ranking of near-native structures was drastically improved, leading to a significant enrichment of near-native complex conformations within the top ranks. It could be shown that the developed schemes outperform five other previously published scoring functions.

SOFTDOCK application to protein-protein interaction benchmark and CAPRI

The success of molecular docking requires cooperation of sampling and scoring of various conformations. The SOFTDOCK package uses a coarse-grained docking method to sample all possible conformations of complexes. SOFTDOCK uses a new Voronoi molecular surface and calculates several grid-based scores. It is shown by the leave-one-out test that three geometry scores and an FTDOCK-like electrostatics score contribute the most to the discrimination of near-native conformations. However, an atom-based solvation score is shown to be ineffective. It is also found that an increased Voronoi surface thickness greatly increases the accuracy of docking results. Finally, the clustering procedure is shown to improve the overall ranking, but leads to less accurate docking results. The application of SOFTDOCK in Critical Assessment of PRedicted Interactions involves four steps: (i) sampling with INTELEF; (ii) clustering; (iii) AMBER energy minimization; and (iv) manual inspection. Biological information from literature is used as filters in some of the sampling and manual inspection according to different targets. Two of our submissions have L_rmsd around 10 A. Although they are not classified as acceptable solutions, they are considered successful because they are comparable to the accuracy of our method.

AVAILABILITY

SOFTDOCK is open source code and can be downloaded at http://bio.iphy.ac.cn

Enhanced function annotations for Drosophila serine proteases: a case study for systematic annotation of multi-member gene families

Systematically annotating function of enzymes that belong to large protein families encoded in a single eukaryotic genome is a very challenging task. We carried out such an exercise to annotate function for serine-protease family of the trypsin fold in Drosophila melanogaster, with an emphasis on annotating serine-protease homologues (SPHs) that may have lost their catalytic function. Our approach involves data mining and data integration to provide function annotations for 190 Drosophila gene products containing serine-protease-like domains, of which 35 are SPHs. This was accomplished by analysis of structure-function relationships, gene-expression profiles, large-scale protein-protein interaction data, literature mining and bioinformatic tools. We introduce functional residue clustering (FRC), a method that performs hierarchical clustering of sequences using properties of functionally important residues and utilizes correlation co-efficient as a quantitative similarity measure to transfer in vivo substrate specificities to proteases. We show that the efficiency of transfer of substrate-specificity information using this method is generally high. FRC was also applied on Drosophila proteases to assign putative competitive inhibitor relationships (CIRs). Microarray gene-expression data were utilized to uncover a large-scale and dual involvement of proteases in development and in immune response. We found specific recruitment of SPHs and proteases with CLIP domains in immune response, suggesting evolution of a new function for SPHs. We also suggest existence of separate downstream protease cascades for immune response against bacterial/fungal infections and parasite/parasitoid infections. We verify quality of our annotations using information from RNAi screens and other evidence types. Utilization of such multi-fold approaches results in 10-fold increase of function annotation for Drosophila serine proteases and demonstrates value in increasing annotations in multiple genomes.

Complex-type-dependent scoring functions in protein–protein docking

A major challenge in the field of protein-protein docking is to discriminate between the many wrong and few near-native conformations, i.e. scoring. Here, we introduce combinatorial complex-type-dependent scoring functions for different types of protein-protein complexes, protease/inhibitor, antibody/antigen, enzyme/inhibitor and others. The scoring functions incorporate both physical and knowledge-based potentials, i.e. atomic contact energy (ACE), the residue pair potential (RP), electrostatic and van der Waals' interactions. For different type complexes, the weights of the scoring functions were optimized by the multiple linear regression method, in which only top 300 structures with ligand root mean square deviation (L_RMSD) less than 20 A from the bound (co-crystallized) docking of 57 complexes were used to construct a training set. We employed the bound docking studies to examine the quality of the scoring function, and also extend to the unbound (separately crystallized) docking studies and extra 8 protein-protein complexes. In bound docking of the 57 cases, the first hits of protease/inhibitor cases are all ranked in the top 5. For the cases of antibody/antigen, enzyme/inhibitor and others, there are 17/19, 5/6 and 13/15 cases with the first hits ranked in the top 10, respectively. In unbound docking studies, the first hits of 9/17 protease/inhibitor, 6/19 antibody/antigen, 1/6 enzyme/inhibitor and 6/15 others' complexes are ranked in the top 10. Additionally, for the extra 8 cases, the first hits of the two protease/inhibitor cases are ranked in the top for the bound and unbound test. For the two enzyme/inhibitor cases, the first hits are ranked 1st for bound test, and the 119th and 17th for the unbound test. For the others, the ranks of the first hits are the 1st for the bound test and the 12th for the 1WQ1 unbound test. To some extent, the results validated our divide-and-conquer strategy in the docking study, which might hopefully shed light on the prediction of protein-protein interactions.

Combination of scoring schemes for protein docking

Background

Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function.

Results

The scoring with the atom specific weighting factors yields better results than the amino acid specific scoring. In combination with SVM-based scoring functions the percentage of complexes for which a near native structure can be predicted within the top 100 ranks increased from 14% with the geometric scoring to 54% with the combination of all scoring functions. Especially for the enzyme-inhibitor complexes the results of the ranking are excellent. For half of these complexes a near-native structure can be predicted within the first 10 proposed structures and for more than 86% of all enzyme-inhibitor complexes within the first 50 predicted structures.

Conclusion

We were able to develop a combination of different scoring schemes which considers a series of previously described and some new scoring criteria yielding a remarkable improvement of prediction quality.

Design of multi-specificity in protein interfaces

Interactions in protein networks may place constraints on protein interface sequences to maintain correct and avoid unwanted interactions. Here we describe a "multi-constraint" protein design protocol to predict sequences optimized for multiple criteria, such as maintaining sets of interactions, and apply it to characterize the mechanism and extent to which 20 multi-specific proteins are constrained by binding to multiple partners. We find that multi-specific binding is accommodated by at least two distinct patterns. In the simplest case, all partners share key interactions, and sequences optimized for binding to either single or multiple partners recover only a subset of native amino acid residues as optimal. More interestingly, for signaling interfaces functioning as network "hubs," we identify a different, "multi-faceted" mode, where each binding partner prefers its own subset of wild-type residues within the promiscuous binding site. Here, integration of preferences across all partners results in sequences much more "native-like" than seen in optimization for any single binding partner alone, suggesting these interfaces are substantially optimized for multi-specificity. The two strategies make distinct predictions for interface evolution and design. Shared interfaces may be better small molecule targets, whereas multi-faceted interactions may be more "designable" for altered specificity patterns. The computational methodology presented here is generalizable for examining how naturally occurring protein sequences have been selected to satisfy a variety of positive and negative constraints, as well as for rationally designing proteins to have desired patterns of altered specificity.

Affilin-novel binding molecules based on human gamma-B-crystallin, an all beta-sheet protein

The concept of novel binding proteins as an alternative to antibodies has undergone rapid development and is now ready for practical use in a wide range of applications. Alternative binding proteins, based on suitable scaffolds with desirable properties, are selected from combinatorial libraries in vitro. Here, we describe an approach using a beta-sheet of human gamma-B-crystallin to generate a universal binding site through randomization of eight solvent-exposed amino acid residues selected according to structural and sequence analyses. Specific variants, so-called Affilin, have been isolated from a phage display library against a variety of targets that differ considerably in size and structure. The isolated Affilin variants can be produced in Escherichia coli as soluble proteins and have a high level of thermodynamic stability. The crystal structures of the human wild-type gamma-B-crystallin and a selected Affilin variant have been determined to 1.7 A and 2.0 A resolution, respectively. Comparison of the two molecules indicates that the human gamma-B-crystallin tolerates amino acid exchanges with no major structural change. We conclude that the intrinsically stable and easily expressed gamma-B-crystallin provides a suitable framework for the generation of novel binding molecules.

Prediction of physical protein-protein interactions

Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.

PIPER: an FFT-based protein docking program with pairwise potentials

The Fast Fourier Transform (FFT) correlation approach to protein-protein docking can evaluate the energies of billions of docked conformations on a grid if the energy is described in the form of a correlation function. Here, this restriction is removed, and the approach is efficiently used with pairwise interaction potentials that substantially improve the docking results. The basic idea is approximating the interaction matrix by its eigenvectors corresponding to the few dominant eigenvalues, resulting in an energy expression written as the sum of a few correlation functions, and solving the problem by repeated FFT calculations. In addition to describing how the method is implemented, we present a novel class of structure-based pairwise intermolecular potentials. The DARS (Decoys As the Reference State) potentials are extracted from structures of protein-protein complexes and use large sets of docked conformations as decoys to derive atom pair distributions in the reference state. The current version of the DARS potential works well for enzyme-inhibitor complexes. With the new FFT-based program, DARS provides much better docking results than the earlier approaches, in many cases generating 50% more near-native docked conformations. Although the potential is far from optimal for antibody-antigen pairs, the results are still slightly better than those given by an earlier FFT method. The docking program PIPER is freely available for noncommercial applications.

Statistical analysis of predominantly transient protein-protein interfaces

A non-redundant set of 170 protein-protein interfaces of known structure was statistically analyzed for residue and secondary-structure compositions, pairing preferences and side-chain-backbone interaction frequencies. By focussing mainly on transient protein-protein interfaces, the results underline previous findings for protein-protein interfaces but also show some new interesting aspects of transient interfaces. The residue compositions at interfaces found in this study correlate well with the results of other studies. On average, contacts between pairs of hydrophobic and polar residues were unfavorable, and the charged residues tended to pair subject to charge complementarity. Secondary structure composition analysis shows that neither helices nor beta-sheets are dominantly populated at interfaces. Analyzing the pairing preferences of the secondary structure elements revealed a higher affinity within the same elements and alludes to tight packings. In addition, the results for the side-chain and backbone interaction frequencies, which were measured under more stringent conditions, showed a high occurrence of side-chain-backbone interactions. Taking a closer look at the helix and beta-sheet binding frequencies for a given side-chain and backbone interaction underlined the relevance of tight packings. The polarity of interfaces increased with decreasing interface size. These types of information may be useful for scoring complexes in protein-protein docking studies or for prediction of protein-protein interfaces from the sequences alone.

Hot Regions in Protein–Protein Interactions: The Organization and Contribution of Structurally Conserved Hot Spot Residues

Structurally conserved residues at protein-protein interfaces correlate with the experimental alanine-scanning hot spots. Here, we investigate the organization of these conserved, computational hot spots and their contribution to the stability of protein associations. We find that computational hot spots are not homogeneously distributed along the protein interfaces; rather they are clustered within locally tightly packed regions. Within the dense clusters, they form a network of interactions and consequently their contributions to the stability of the complex are cooperative; however the contributions of independent clusters are additive. This suggests that the binding free energy is not a simple summation of the single hot spot residue contributions. As expected, around the hot spot residues we observe moderately conserved residues, further highlighting the crucial role of the conserved interactions in the local densely packed environment. The conserved occurrence of these organizations suggests that they are advantageous for protein-protein associations. Interestingly, the total number of hydrogen bonds and salt bridges contributed by hot spots is as expected. Thus, H-bond forming residues may use a "hot spot for water exclusion" mechanism. Since conserved residues are located within highly packed regions, water molecules are easily removed upon binding, strengthening electrostatic contributions of charge-charge interactions. Hence, the picture that emerges is that protein-protein associations are optimized locally, with the clustered, networked, highly packed structurally conserved residues contributing dominantly and cooperatively to the stability of the complex. When addressing the crucial question of "what are the preferred ways of proteins to associate", these findings point toward a critical involvement of hot regions in protein-protein interactions.

A soft docking algorithm for predicting the structure of antibody-antigen complexes

An efficient soft docking algorithm is described for predicting the mode of binding between an antibody and its antigen based on the three-dimensional structures of the molecules. The basic tools are the "simplified protein" model and the docking algorithm of Wodak and Janin. The side-chain flexibility of Arg, Lys, Asp, Glu, and Met residues on the protein surface is taken into account. A combined filtering technique is used to select candidate binding modes. After energy minimization, we calculate a scoring function, which includes electrostatic and desolvation energy terms. This procedure was applied to targets 04, 05, and 06 of CAPRI, which are complexes of three different camelid antibody VHH variable domains with pig alpha-amylase. For target 06, two native-like structures with a root-mean-square deviation < 4.0 A relative to the X-ray structure were found within the five top ranking structures. For targets 04 and 05, our procedure produced models where more than half of the antigen residues forming the epitope were correctly predicted, albeit with a wrong VHH domain orientation. Thus, our soft docking algorithm is a promising tool for predicting antibody-antigen recognition.

Protein-protein docking with a reduced protein model accounting for side-chain flexibility

A protein-protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking minima on the protein surfaces within. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chemical character. Energy minimization of protein test complexes in the reduced representation results in geometries close to experiment with backbone root mean square deviations (RMSDs) of approximately 1 to 3 A for the mobile protein partner from the experimental geometry. For most test cases, the energy-minimized experimental structure scores among the top five energy minima in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound (apo) binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a solution within approximately 2 to 3.5 A RMSD of the full mobile partner from the experimental geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.

A protein-protein docking algorithm dependent on the type of complexes

An efficient 'soft docking' algorithm is described to assist the prediction of protein-protein association using three-dimensional structures of molecules. The basic tools are the 'simplified protein' model and the docking algorithm of Wodak and Janin. The side chain flexibility of Arg, Lys, Asp, Glu and Met residues at the protein surface is taken into account. The complex type-dependent filtering technique on the basis of the geometric matching, hydrophobicity and electrostatic complementarity is used to select candidate binding modes. Subsequently, we calculate a scoring function which includes electrostatic and desolvation energy terms. In the 44 complexes tested including enzyme-inhibitor, antibody-antigen and other complexes, native-like structures were all found, of which 30 were ranked in the top 20. Thus, our soft docking algorithm has the potential to predict protein-protein recognition.

Small molecule antagonists of proteins

The identification of small molecule antagonists of protein function is at the core of the pharmaceutical industry. Successful approaches to this problem, including screening and rational design, have been developed over the years to identify antagonists of enzymes and cellular receptors. These methods have been extended to the search for inhibitors of protein-protein interactions. While the very possibility of designing a small molecule inhibitor for such interactions was once doubted, there are examples of such inhibitors that are currently marketed products and many more inhibitors in various stages of research and development. Here we review the progress in identifying and designing small molecule protein inhibitors, with particular attention to those that block protein-protein interactions. We also discuss the physical character of protein-protein interfaces, and the resulting implications for small molecule lead discovery and design.

Differences in electrostatic properties at antibody-antigen binding sites: implications for specificity and cross-reactivity

Antibodies HyHEL8, HyHEL10, and HyHEL26 (HH8, HH10, and HH26, respectively) recognize highly overlapping epitopes on hen egg-white lysozyme (HEL) with similar affinities, but with different specificities. HH8 binding to HEL is least sensitive toward mutations in the epitope and thus is most cross-reactive, HH26 is most sensitive, whereas the sensitivity of HH10 lies in between HH8 and HH26. Here we have investigated intra- and intermolecular interactions in three antibody-protein complexes: theoretical models of HH8-HEL and HH26-HEL complexes, and the x-ray crystal structure of HH10-HEL complex. Our results show that HH8-HEL has the lowest number and HH26-HEL has the highest number of intra- and intermolecular hydrogen bonds. The number of salt bridges is lowest in HH8-HEL and highest in HH26-HEL. The binding site salt bridges in HH8-HEL are not networked, and are weak, whereas, in HH26-HEL, an intramolecular salt-bridge triad at the binding site is networked to an intermolecular triad to form a pentad. The pentad and each salt bridge of this pentad are exceptionally stabilizing. The number of binding-site salt bridges and their strengths are intermediate in HH10-HEL, with an intramolecular triad. Our further calculations show that the electrostatic component contributes the most to binding energy of HH26-HEL, whereas the hydrophobic component contributes the most in the case of HH8-HEL. A "hot-spot" epitope residue Lys-97 forms an intermolecular salt bridge in HH8-HEL, and participates in the intermolecular pentad in the HH26-HEL complex. Mutant modeling and surface plasmon resonance (SPR) studies show that this hot-spot epitope residue contributes significantly more to the binding than an adjacent epitope residue, Lys-96, which does not form a salt bridge in any of the three HH-HEL complexes. Furthermore, the effect of mutating Lys-97 is most severe in HH26-HEL. Lys-96, being a charged residue, also contributes the most in HH26-HEL among the three complexes. The SPR results on these mutants also highlight that the apparent "electrostatic steering" on net on rates actually act at post-collision level stabilization of the complex. The significance of this work is the observed variations in electrostatic interactions among the three complexes. Our work demonstrates that higher electrostatics, both as a number of short-range electrostatic interactions and their contributions, leads to higher binding specificity. Strong salt bridges, their networking, and electrostatically driven binding, limit flexibilities through geometric constrains. In contrast, hydrophobic driven binding and low levels of electrostatic interactions are associated with conformational flexibility and cross-reactivity.

Protein-protein interactions: mechanisms and modification by drugs

Protein-protein interactions form the proteinaceous network, which plays a central role in numerous processes in the cell. This review highlights the main structures, properties of contact surfaces, and forces involved in protein-protein interactions. The properties of protein contact surfaces depend on their functions. The characteristics of contact surfaces of short-lived protein complexes share some similarities with the active sites of enzymes. The contact surfaces of permanent complexes resemble domain contacts or the protein core. It is reasonable to consider protein-protein complex formation as a continuation of protein folding. The contact surfaces of the protein complexes have unique structure and properties, so they represent prospective targets for a new generation of drugs. During the last decade, numerous investigations have been undertaken to find or design small molecules that block protein dimerization or protein(peptide)-receptor interaction, or on the other hand, induce protein dimerization.