Biological units and their effect upon the properties and prediction of protein-protein interactions

Structural data as collated in the Protein Data Bank (PDB) have been widely applied in the study and prediction of protein-protein interactions. However, since the basic PDB Entries contain only the contents of the asymmetric unit rather than the biological unit, some key interactions may be missed by analysing only the PDB Entry. A total of 69,054 SCOP (Structural Classification of Proteins) domains were examined systematically to identify the number of additional novel interacting domain pairs and interfaces found by considering the biological unit as stored in the PQS (Protein Quaternary Structure) database. The PQS data adds 25,965 interacting domain pairs to those seen in the PDB Entries to give a total of 61,783 redundant interacting domain pairs. Redundancy filtering at the level of the SCOP family shows PQS to increase the number of novel interacting domain-family pairs by 302 (13.3%) from 2277, but only 16/302 (1.4%) of the interacting domain pairs have the two domains in different SCOP families. This suggests the biological units add little to the elucidation of novel biological interaction networks. However, when the orientation of the domain pairs is considered, the PQS data increases the number of novel domain-domain interfaces observed by 1455 (34.5%) to give 5677 non-redundant domain-domain interfaces. In all, 162/1455 novel domain-domain interfaces are between domains from different families, an increase of 8.9% over the PDB Entries. Overall, the PQS biological units provide a rich source of novel domain-domain interfaces that are not seen in the studied PDB Entries, and so PQS domain-domain interaction data should be exploited wherever possible in the analysis and prediction of protein-protein interactions.     

Identification of protein interaction partners and protein-protein interaction sites

Rigid-body docking has become quite successful in predicting the correct conformations of binary protein complexes, at least when the constituent proteins do not undergo large conformational changes upon binding. However, determining whether two given proteins interact is a more difficult problem. Successful docking procedures often give equally good scores for proteins that do not interact experimentally. This is the case for the multiple minimization approach we use here. An analysis of the results where all proteins within a set are docked with all other proteins (complete cross-docking) shows that the predictions can be greatly improved if the location of the correct binding interface on each protein is known, since the experimental complexes are much more likely to bring these two interfaces into contact, at the same time as yielding good interaction energy scores. While various methods exist for identifying binding interfaces, it is shown that simply studying the interaction of all potential protein pairs within a data set can itself help to identify the correct interfaces.     

The tryptophan switch: changing ligand-binding specificity from type I to type II in SH3 domains

The ability of certain Src homology 3 (SH3) domains to bind specifically both type I and type II polyproline ligands is perhaps the best characterized, but also the worst understood, example in the family of protein-interaction modules. A detailed analysis of the structural variations in SH3 domains, with respect to ligand-binding specificity, together with mutagenesis of SH3 Fyn tyrosine kinase, reveal the structural basis for types I and II binding specificity by SH3 domains. The conserved Trp in the SH3 binding pocket can adopt two different orientations that, in turn, determine the type of ligand (I or II) able to bind to the domain. The only exceptions are ligands with Leu at positions P(-1) and P(2), that deviate from standard poly-Pro angles. The motion of the conserved Trp depends on the presence of certain residues located in a key position (132 for Fyn), near the binding pocket. SH3 domains placing aromatic residues in this key position are promiscuous. By contrast, those presenting beta-branched or long aliphatic residues block the conserved Trp in one of the two possible orientations, preventing binding in a type I orientation. This is experimentally demonstrated by a single mutation in Fyn SH3 (Y132I) that abolishes type I ligand binding, while preserving binding to type II ligands. Thus, simple conformational changes, governed by simple rules, can have profound effects on protein-protein interactions, highlighting the importance of structural details to predict protein-protein interactions.     

A dissection of specific and non-specific protein-protein interfaces

We compare the geometric and physical-chemical properties of interfaces involved in specific and non-specific protein-protein interactions in crystal structures reported in the Protein Data Bank. Specific interactions are illustrated by 70 protein-protein complexes and by subunit contacts in 122 homodimeric proteins; non-specific interactions are illustrated by 188 pairs of monomeric proteins making crystal-packing contacts selected to bury more than 800 A2 of protein surface. A majority of these pairs have 2-fold symmetry and form crystal dimers that cannot be distinguished from real dimers on the basis of the interface size or symmetry. The chemical and amino acid compositions of the large crystal-packing interfaces resemble the protein solvent-accessible surface. These interfaces are less hydrophobic than in homodimers and contain much fewer fully buried atoms. We develop a residue propensity score and a hydrophobic interaction score to assess preferences seen in the chemical and amino acid compositions of the different types of interfaces, and we derive indexes to evaluate the atomic packing, which we find to be less compact at non-specific than at specific interfaces. We test the capacity of these parameters to identify homodimeric proteins in crystal structures, and show that a simple combination of the non-polar interface area and the fraction of buried interface atoms assigns the quaternary structure of 88% of the homodimers and 77% of the monomers in our data set correctly. These success rates increase to 93-95% when the residue propensity score of the interfaces is taken into consideration.     

A family of evolution-entropy hybrid methods for ranking protein residues by importance

In order to identify the amino acids that determine protein structure and function it is useful to rank them by their relative importance. Previous approaches belong to two groups; those that rely on statistical inference, and those that focus on phylogenetic analysis. Here, we introduce a class of hybrid methods that combine evolutionary and entropic information from multiple sequence alignments. A detailed analysis in insulin receptor kinase domain and tests on proteins that are well-characterized experimentally show the hybrids' greater robustness with respect to the input choice of sequences, as well as improved sensitivity and specificity of prediction. This is a further step toward proteome scale analysis of protein structure and function.     

蛋白质-蛋白质相互作用及其抑制剂研究进展

蛋白质-蛋白质相互作用在细胞活动和生命过程中扮演着非常重要的角色。基因调节、免疫应答、信号转导、细胞组装等等都离不开蛋白质-蛋白质的相互作用。近几年,靶向蛋白质-蛋白质相互作用及其抑制剂研究也逐渐成为研究的热点;但是蛋白质复合物相互作用界面的一些特点和性质,如相互作用界面较大、结合界面较为平坦等,使蛋白质-蛋白质相互作用及其抑制剂研究充满了挑战。本文主要总结了蛋白质-蛋白质相互作用界面的一些性质和特点,分析了界面特性与其抑制剂设计的关系,并讨论了蛋白质-蛋白质相互作用的理论预测方法及其抑制剂的类型和特点,最后又通过实例说明了如何进行蛋白质-蛋白质相互作用抑制剂的设计。     

Prediction of protein-mannose binding sites using random forest

Mannose is an abundant cell surface monosaccharide and has an important role in many biochemical processes. It binds to a greatdiversity of receptor proteins. In this study we have employed Random Forest for prediction of mannose binding sites. Mannosebindingsite is taken to be a sphere around the centroid of the ligand and the sphere is subdivided into different layers and atomwise and residue wise features were extracted for each layer. The method achieves 95.59 % of accuracy using Random Forest with10 fold cross validation. Prediction of mannose binding site analysis will be quite useful in drug design.     

Interaction modes at protein hetero-dimer interfaces

Hetero dimer (different monomers) interfaces are involved in catalysis and regulation through the formation of interface active sites. This is critical in cell and molecular biology events. The physical and chemical factors determining the formation of the interface active sites is often large in numbers. The combined role of interacting features is frequently combinatorial and additive in nature. Therefore, it is important to determine the physical and chemical features of such interactions. A number of such features have been documented in literature since 1975. However, the use of such interaction features in the prediction of interaction partners and sites given their sequences is still a challenge. In a non-redundant dataset of 156 hetero-dimer structures determined by X-ray crystallography, the interacting partners are often varying in size and thus, size variation between subunits is an important factor in determining the mode of interface formation. The size of protein subunits interacting are either small-small, largelarge, medium-medium, large-small, large-medium and small-medium. It should also be noted that the interface formed between subunits have physical interactions at N terminal (N), C terminal (C) and middle (M) region of the protein with reference to their sequences in one dimension. These features are believed to have application in the prediction of interaction partners and sites from sequences. However, the use of such features for interaction prediction from sequence is not currently clear.