Evaluation of different domain-based methods in protein interaction prediction

Protein-protein interactions (PPIs) play an important role in many biological functions. PPIs typically involve binding between domains, the basic units of protein folding, evolution and function. Identifying domain-domain interactions (DDIs) would aid understanding PPI networks. Recently, many computational methods aimed to infer DDIs from databases of interacting proteins and subsequently used the inferred DDIs to predict new PPIs. We attempt to describe systematically current domain-based approaches including the association method, maximum likelihood estimation and parsimonious explanation method. The performance of these methods at inferring DDIs and predicting PPIs was evaluated comparatively. We observe that each method generates artefacts in certain situations and discuss biases in the available benchmark sets.     

A novel method for protein-protein interaction site prediction using phylogenetic substitution models

Protein-protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein-protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein-protein interaction site prediction. Here, we present a phylogenetic framework to capture critical sequence variations that favor the selection of residues essential for protein-protein binding. Through the comprehensive analysis of diverse protein families, we show that protein binding interfaces exhibit distinct amino acid substitution as compared with other surface residues. On the basis of this analysis, we have developed a novel method, BindML, which utilizes the substitution models to predict protein-protein binding sites of protein with unknown interacting partners. BindML estimates the likelihood that a phylogenetic tree of a local surface region in a query protein structure follows the substitution patterns of protein binding interface and nonbinding surfaces. BindML is shown to perform well compared to alternative methods for protein binding interface prediction. The methodology developed in this study is very versatile in the sense that it can be generally applied for predicting other types of functional sites, such as DNA, RNA, and membrane binding sites in proteins.     

计算方法在蛋白质相互作用研究中的应用

计算方法在蛋白质相互作用研究的各个阶段扮演了一个重要的角色。对此,作者将从以下几个方面对计算方法在蛋白质相互作用及相互作用网络研究中的应用做一个概述：蛋白质相互作用数据库及其发展;数据挖掘方法在蛋白质相互作用数据收集和整合中的应用;高通量方法实验结果的验证;根据蛋白质相互作用网络预测和推断未知蛋白质的功能;蛋白质相互作用的预测。     

A method for lipase co-precipitation in a biodegradable protein matrix

This article presents a novel method for immobilization of active ingredients. The method is based on CO(2) aided active ingredient co-precipitation with glycinin, a biodegradable protein matrix from edible soybean protein. Glycinin precipitates abundantly under isoelectric conditions and serves as the matrix within which the active substance is trapped during the precipitation process. The enzyme lipase from Candida rugosa was successfully co-precipitated into the protein pellet to prove the principle. It was shown that the lipase within the co-precipitate retained lipase and esterase activity under different pH conditions. In some cases the activity was even higher than the activity of crude lipase, possibly due to the protective role of the matrix protein. Due to the retained lipase activity and food-grade quality of the binary precipitate, it has potential of being used in the food or pharmaceutical industry. Additional quality of the binary precipitate is the potentially significantly reduced downstream processing due to the fact that no organic solvents or precipitants were used in the precipitation process.     

Potential of mean force for protein-protein interaction studies.

Calculating protein-protein interaction energies is crucial for understanding protein-protein associations. On the basis of the methodology of mean-field potential, we have developed an empirical approach to estimate binding free energy for protein-protein interactions. This knowledge-based approach has been used to derive distance-dependent free energies of protein complexes from a nonredundant training set in the Protein Data Bank (PDB), with a careful treatment of homology. We calculate atom pair potentials for 16 pair interactions, which can reflect the importance of hydrophobic interactions and specific hydrogen-bonding interactions. The derived potentials for hydrogen-bonding interactions show a valley of favorable interactions at a distance of approximately 3 A, corresponding to that of an established hydrogen bond. For the test set of 28 protein complexes, the calculated energies have a correlation coefficient of 0.75 compared with experimental binding free energies. The performance of the method in ranking the binding energies of different protein-protein complexes shows that the energy estimation can be applied to value binding free energies for protein-protein associations.     

Chip-based protein-protein interaction studied by atomic force microscopy

In this article, a technique for accurate direct measurement of protein‐to‐protein interactions before and after the introduction of a drug candidate is developed using atomic force microscopy (AFM). The method is applied to known immunosuppressant drug candidate Echinacea purpurea derived cynarin. T‐cell/CD28 is on‐chip immobilized and B‐cell/CD80 is immobilized on an AFM tip. The difference in unbinding force between these two proteins before and after the introduction of cynarin is measured. The method is described in detail including determination of the loading rates, maximum probability of bindings, and average unbinding forces. At an AFM loading rate of 1.44 × 10⁴ pN/s, binding events were largely reduced from 61 ± 5% to 47 ± 6% after cynarin introduction. Similarly, maximum probability of bindings reduced from 70% to 35% with a blocking effect of about 35% for a fixed contact time of 0.5 s or greater. Furthermore, average unbinding forces were reduced from 61.4 to 38.9 pN with a blocking effect of ～37% as compared with ～9% by SPR. AFM, which can provide accurate quantitative measures, is shown to be a good method for drug screening. The method could be applied to a wider variety of drug candidates with advances in bio‐chip technology and a more comprehensive AFM database of protein‐to‐protein interactions. Biotechnol. Bioeng. 2012; 109: 2460–2467. © 2012 Wiley Periodicals, Inc.     

Annexin A2/P11 interaction: new insights into annexin A2 tetramer structure by chemical crosslinking, high-resolution mass spectrometry, and computational modeling

During the past few years, the structural analysis of proteins and protein complexes by chemical crosslinking and mass spectrometry has enjoyed increasing popularity. With this approach we have investigated the quaternary structure of the complex between annexin A2 and p11, which is involved in numerous cellular processes. Although high-resolution data are available for both interaction partners as well as for the complex between two p11 subunits and two annexin A2 N-terminal peptides, the structure of the complete annexin A2/p11 heterotetramer has not yet been solved at high resolution. Thus, the quaternary structure of the biologically relevant, membrane-bound annexin A2/p11 complex is still under discussion, while the existence of a heterotetramer or a heterooctamer is the prevailing opinion. We gained further insight into the spatial organization of the annexin A2/p11 heterotetramer by employing chemical crosslinking combined with high-resolution mass spectrometry. Furthermore, tandem mass spectrometry served as a tool for an exact localization of crosslinked amino acid residues and for a confirmation of crosslinked product assignment. On the basis of distance constraints from the crosslinking data we derived structural models of the annexin A2/p11 heterotetramer by computational docking with Rosetta. We propose an octameric model for the annexin A2/p11 complex, which exerts annexin A2 function. The proposed structure of the annexin A2/p11 octamer differs from so far suggested models and sheds new light into annexin A2/p11 interaction.     

Towards the prediction of protein interaction partners using physical docking

Deciphering the whole network of protein interactions for a given proteome (‘interactome’) is the goal of many experimental and computational efforts in Systems Biology. Separately the prediction of the structure of protein complexes by docking methods is a well‐established scientific area. To date, docking programs have not been used to predict interaction partners. We provide a proof of principle for such an approach. Using a set of protein complexes representing known interactors in their unbound form, we show that a standard docking program can distinguish the true interactors from a background of 922 non‐redundant potential interactors. We additionally show that true interactions can be distinguished from non‐likely interacting proteins within the same structural family. Our approach may be put in the context of the proposed ‘funnel‐energy model’; the docking algorithm may not find the native complex, but it distinguishes binding partners because of the higher probability of favourable models compared with a collection of non‐binders. The potential exists to develop this proof of principle into new approaches for predicting interaction partners and reconstructing biological networks.     

Charged residues at protein interaction interfaces: unexpected conservation and orchestrated divergence

Protein-protein interactions play an essential role in the functioning of cell. The importance of charged residues and their diverse role in protein-protein interactions have been well studied using experimental and computational methods. Often, charged residues located in protein interaction interfaces are conserved across the families of homologous proteins and protein complexes. However, on a large scale, it has been recently shown that charged residues are significantly less conserved than other residue types in protein interaction interfaces. The goal of this work is to understand the role of charged residues in the protein interaction interfaces through their conservation patterns. Here, we propose a simple approach where the structural conservation of the charged residue pairs is analyzed among the pairs of homologous binary complexes. Specifically, we determine a large set of homologous interactions using an interaction interface similarity measure and catalog the basic types of conservation patterns among the charged residue pairs. We find an unexpected conservation pattern, which we call the correlated reappearance, occurring among the pairs of homologous interfaces more frequently than the fully conserved pairs of charged residues. Furthermore, the analysis of the conservation patterns across different superkingdoms as well as structural classes of proteins has revealed that the correlated reappearance of charged residues is by far the most prevalent conservation pattern, often occurring more frequently than the unconserved charged residues. We discuss a possible role that the new conservation pattern may play in the long-range electrostatic steering effect.     

In silico two-hybrid system for the selection of physically interacting protein pairs

Deciphering the interaction links between proteins has become one of the main tasks of experimental and bioinformatic methodologies. Reconstruction of complex networks of interactions in simple cellular systems by integrating predicted interaction networks with available experimental data is becoming one of the most demanding needs in the postgenomic era. On the basis of the study of correlated mutations in multiple sequence alignments, we propose a new method (in silico two-hybrid, i2h) that directly addresses the detection of physically interacting protein pairs and identifies the most likely sequence regions involved in the interactions. We have applied the system to several test sets, showing that it can discriminate between true and false interactions in a significant number of cases. We have also analyzed a large collection of E. coli protein pairs as a first step toward the virtual reconstruction of its complete interaction network.     

Effects of protein-protein interaction in ultrafiltration based fractionation processes

This paper discusses the use of pulsed sample injection ultrafiltration (UF) for investigating protein-protein interaction, particularly its effect on protein transmission through UF membranes. Several binary protein mixtures were investigated; the proteins in each mixture being selected such that one of the proteins in the pair would be preferentially transmitted while the other would be either totally or substantially retained. The "retained" protein either decreased or increased or did not affect the sieving coefficient of the "transmitted" protein, this depending the type of protein-protein interaction, that is, associative, repulsive, or neutral. The type of protein-protein interaction depended on the particular protein pair under investigation as well as on the operating conditions used (pH and salt concentration). The magnitude of either decrease or increase in transmission of a preferentially transmitted protein due to the presence of a retained protein was found to be independent of the manner in which the proteins were injected into the system, that is, simultaneous or sequential. These magnitudes however correlated well with the ratio of the two proteins present in the feed.     

Molecular basis of interaction between NG2 proteoglycan and galectin-3

Previous work has demonstrated the ability of the NG2 proteoglycan, a component of microvascular pericytes, to stimulate endothelial cell motility and morphogenesis. This function of NG2 depends on formation of a complex with galectin-3 and alpha3beta1 integrin to stimulate integrin-mediated transmembrane signaling. In addition, the co-expression of galectin-3 and NG2 in A375 melanoma cells suggests that the malignant properties of these cells may be affected by interaction between the two molecules. Here, we extend the theme of co-expression and interaction of NG2 and galectin-3 to human glioma cells. We also establish a molecular basis for the NG2/galectin-3 interaction. The C-terminal carbohydrate recognition domain of galectin-3 is responsible for binding to the NG2 core protein. Within the NG2 extracellular domain, the membrane-proximal D3 segment of the proteoglycan contains the primary binding site for interaction with galectin-3. The interaction between galectin-3 and NG2 is a carbohydrate-dependent one mediated by N-linked rather than O-linked oligosaccharides within the D3 domain of the NG2 core protein. These studies establish a foundation for attempts to reduce the aggressive properties of tumor cells by disrupting the NG2/galectin-3 interaction.     

Matching fusion protein systems for affinity analysis of two interacting families of proteins: the cohesin-dockerin interaction

Cellulosomes are multi-enzyme complexes that orchestrate the efficient degradation of cellulose and related plant cell wall polysaccharides. The complex is maintained by the high-affinity protein-protein interaction between two complementary modules: the cohesin and the dockerin. In order to characterize the interaction between different cohesins and dockerins, we have developed matching fusion-protein systems, which harbor either the cohesin or the dockerin component. For this purpose, corresponding plasmid cassettes were designed, which encoded for the following carrier proteins: (i) a thermostable xylanase with an appended His-tag; and (ii) a highly stable cellulose-binding module (CBM). The resultant xylanase-dockerin and CBM-cohesin fusion products exhibited high expression levels of soluble protein. The expressed, affinity-purified proteins were extremely stable, and the functionality of the cohesin or dockerin component was retained. The fusion protein system was used to establish a sensitive and reliable, semi-quantitative enzyme-linked affinity assay for determining multiple samples of cohesin-dockerin interactions in microtiter plates. A variety of cohesin-dockerin systems, which had been examined previously using other methodologies, were revisited applying the affinity-based enzyme assay, the results of which served to verify the validity of the approach.     

预测蛋白质间相互作用的生物信息学方法

后基因组时代的研究模式,已从原来的序列-结构-功能转向基因表达-系统动力学-生理功能。建立蛋白质间相互作用的完全网络,即蛋白质相互作用组(interactome),将有助于从系统角度加深对细胞结构和功能的认识,并为新药靶点的发现和药物设计提供理论基础。一系列系统分析蛋白质相互作用的实验方法已经建立,近年来,出现了多种预测蛋白质相互作用的生物信息学方法,这些方法不仅是对传统实验方法的有价值的补充,而且能够扩展实验方法的预测范围;同时,在开发这些方法的过程中建立了一些重要的分子进化和分子生物学慨念。本文综述了9种生物信息学方法的原理、方法评估、存在的问题．并分析了这个领域的发展前景。     

A matching algorithm for catalytic residue site selection in computational enzyme design

A loop closure-based sequential algorithm, PRODA_MATCH, was developed to match catalytic residues onto a scaffold for enzyme design in silico. The computational complexity of this algorithm is polynomial with respect to the number of active sites, the number of catalytic residues, and the maximal iteration number of cyclic coordinate descent steps. This matching algorithm is independent of a rotamer library that enables the catalytic residue to take any required conformation during the reaction coordinate. The catalytic geometric parameters defined between functional groups of transition state (TS) and the catalytic residues are continuously optimized to identify the accurate position of the TS. Pseudo-spheres are introduced for surrounding residues, which make the algorithm take binding into account as early as during the matching process. Recapitulation of native catalytic residue sites was used as a benchmark to evaluate the novel algorithm. The calculation results for the test set show that the native catalytic residue sites were successfully identified and ranked within the top 10 designs for 7 of the 10 chemical reactions. This indicates that the matching algorithm has the potential to be used for designing industrial enzymes for desired reactions.     

Systematic protein–protein interaction mapping for clinically relevant human GPCRs

G‐protein‐coupled receptors (GPCRs) are the largest family of integral membrane receptors with key roles in regulating signaling pathways targeted by therapeutics, but are difficult to study using existing proteomics technologies due to their complex biochemical features. To obtain a global view of GPCR‐mediated signaling and to identify novel components of their pathways, we used a modified membrane yeast two‐hybrid (MYTH) approach and identified interacting partners for 48 selected full‐length human ligand‐unoccupied GPCRs in their native membrane environment. The resulting GPCR interactome connects 686 proteins by 987 unique interactions, including 299 membrane proteins involved in a diverse range of cellular functions. To demonstrate the biological relevance of the GPCR interactome, we validated novel interactions of the GPR37, serotonin 5‐HT4d, and adenosine ADORA2A receptors. Our data represent the first large‐scale interactome mapping for human GPCRs and provide a valuable resource for the analysis of signaling pathways involving this druggable family of integral membrane proteins.     

Cis/trans isomerization in HIV-1 capsid protein catalyzed by cyclophilin A: insights from computational and theoretical studies

A network of protein vibrations has recently been identified in the enzyme cyclophilin A (CypA) that is associated with its peptidyl-prolyl cis/trans isomerization activity of small peptide substrates. It has been suggested that this network may have a role in promoting the catalytic step during the isomerization reaction. This work presents the results from the characterization of this network during the isomerization of the Gly89-Pro90 peptide bond in the N-terminal domain of the capsid protein (CA(N)) from human immunodeficiency virus type 1 (HIV-1), which is a naturally occurring, biologically relevant protein substrate for CypA. A variety of computational and theoretical studies are utilized to investigate the protein dynamics of the CypA-CA(N) complex, at multiple time scales, during the isomerization step. The results provide insights into the detailed mechanism of isomerization and confirm the presence of previously reported network of protein vibrations coupled to the reaction. Conserved CypA residues at the complex interface and at positions distal to the interface form parts of this network. There is HIV-1 related medical interest in CypA; incorporation of CypA, complexed with the capsid protein, into the virion is required for the infectious activity of HIV-1. Interaction energy and dynamical cross-correlation calculations are used for a detailed investigation of the protein-protein interactions in the CypA-CA(N) complex. The results show that CA(N) residues His87-Ala-Gly-Pro-Ile-Ala92 form the majority of the interactions with CypA residues. New protein-protein interactions distal to the active site (CypA Arg148-CA(N) Gln95 and CypA Arg148-CA(N) Asn121) are also identified.     

Refinement of unbound protein docking studies using biological knowledge

In this work we present two methods for the reranking of protein-protein docking studies. One scoring method searches the InterDom database for domains that are available in the proteins to be docked and evaluates the interaction of these domains in other complexes of known structure. The second one analyzes the interface of each proposed conformation with regard to the conservation of Phe, Met, and Trp and their polar neighbor residues. The special relevance of these residues is based on a publication by Ma et al. (Proc Natl Acad Sci USA 2003;100:5772-5777), who compared the conservation of all residues in the interface region to the conservation on the rest of the protein's surface. The scoring functions were tested on 30 unbound docking test cases. The evaluation of the methods is based on the ability to rerank the output of a Fast Fourier Transformation (FFT) docking. Both were able to improve the ranking of the docking output. The best improvement was achieved for enzyme-inhibitor examples. Especially the domain-based scoring function was successful and able to place a near-native solution on one of the first six ranks for 13 of 17 (76%) enzyme-inhibitor complexes [in 53% (nine complexes) even on the first rank]. The method evaluating residue conservation allowed us to increase the number of good solutions within the first 100 ranks out of approximately 9000 in 82% of the 17 enzyme-inhibitor test cases, and for seven (41%) out of 17 enzyme-inhibitor complexes, a near native solution was placed within the first seven ranks.     

Conformational dynamics of capping protein and interaction partners: simulation studies

Capping protein (CP) is important for the regulation of actin polymerization. CP binds to the barbed end of the actin filament and prevents actin polymerization. This interaction is modulated through competitive binding by regulatory proteins such as myotrophin (V-1) and the capping protein interacting (CPI) motif from CARMIL. The binding site of myotrophin overlaps with the region of CP that binds to the barbed end of actin filament, whereas CPI binds at a distant site. The binding of CPI to the myotrophin-CP complex dissociates myotrophin from CP. Detailed multicopy molecular dynamics simulations suggest that the binding of CPI shifts the conformational equilibria of CP away from states that favor myotrophin binding. This shift is underpinned by allosteric effects where CPI inhibits CP through suppression of flexibility and disruption of concerted motions that appear to mediate myotrophin binding. Accompanying these effects are changes in electrostatic interactions, notably those involving residue K142β, which appears to play a critical role in regulating flexibility. In addition, accessibility of the site on CP for binding the key hydrophobic residue W8 of myotrophin is modulated by CPI. These results provide insights into the modulation of CP by CPI and myotrophin and indicate the mechanism by which CPI drives the dissociation of the myotrophin-CP complex.