Editorial [ Protein-Protein Interactions Guest Editor: Emil Alexov ]

The ultimate goal of pharmacology and biotechnology is to develop drugs that could prevent or cure human diseases. Despite of the enormous progress made in experimental techniques, still discovering a new drug is an expensive and lengthy procedure. Structure-based drug discovery techniques offer fast and efficient alternative to the experimental approaches. Since protein-protein interactions are essential for the function of the living cell, they are one of the primary subjects of pharmaceutical investigations. However, the success of structure-based drug discovery depends on the availability of 3D structures of the proteins and protein-protein complexes being targeted. Apparently vast majority of these structures have to be modeled in silico. This special issue describes the current state-of-art and the progress made in developing computational approaches in two major directions: (A) Predicting structural features such as 3D structures and interfaces of protein-protein complexes and the conformational changes induced by the binding; and (B) Using the 3D structures to calculate biophysical characteristics such as the binding affinity and the effect of pH and salt concentration, to design inhibitors and to evaluate the effect of disease-associated single nucleoside polymorphism. (A). Predicting Structural Features Such as 3D Structures and Interfaces of Protein-Protein Complexes and the Conformational Changes Induced by the Binding The recent success of the human genome project and the progress in sequencing other genomes has enormously increased the universe of known proteins at amino acid sequences level. However, the biological function and the molecular basis of protein-protein interactions cannot easily be revealed from the sequence alone. Specifically, for the aims of structure-based drug design, 3D structures of the proteins and their complexes are needed. It is unlikely that all these structures will be determined experimentally. To bridge this gap, Structural Genomics Initiatives (SGI) are intended to experimentally determine the 3D structures of carefully selected targets so they can later serve as templates for the maximum number of protein sequences with unknown 3D structures. Currently SGIs are in stage 2, the production phase, and it has been projected that the 3D structures of all monomeric proteins of interest will be predicted in feasible time. The next level of these initiatives is naturally extended toward predicting the 3D structure of the corresponding protein-protein complexes. There are two distinctive approaches of predicting the 3D structures of protein-protein complexes: ab-initio docking and template-based docking. The first one uses physical methods to dock the experimentally determined 3D structures or high quality models of the monomers. The second one, that does not require a priori knowledge of the monomeric structures, predicts the 3D structure of a complex based on the homology relations to another complex with known 3D structure. The last approach, perhaps will require Structural Proteomic Initiatives (SPI), such that significant carefully selected number of representative 3D structures of protein complexes will be experimentally determined and will be further used as templates to generate models for maximal number of complexes with unknown 3D structures. The achievements and perspectives in this important area are outlined in the manuscript “Predicting 3D structures of protein-protein complexes” by Ilya A. Vakser and Petras Kundrotas. The performance of both ab-initio and template-based docking methods can be significantly improved if the binding interfaces are successfully predicted. With respect to the ab-initio docking, this will reduce the sampling and will avoid wrong binding modes. With regard to template-based docking, especially if the interfaces are predicted on sequence level, this will allow for applying profile-to-profile alignment methods that emphasize on the alignment of interfacial residues and thus will contribute to better detection of appropriate templates. From point of view of drug discovery, the ability to predict putative binding interfaces on the 3D structures of monomeric proteins is of special interest. It has the potential to reveal protein-protein interaction networks and the interfacial residues, which can be targeted by inhibitors to alter the corresponding protein-protein interactions. The progress made in developing computational methods to predict protein-protein interfaces and corresponding interaction networks is reviewed in the manuscript “Characterization and prediction of protein interfaces to infer proteinprotein interaction networks”by Ozlem Keskin, Nurcan Tuncbag and Attila Gursoy.