Table of Contents
Molecular Biology International
Volume 2012, Article ID 976385, 22 pages
Review Article

Virtual Interactomics of Proteins from Biochemical Standpoint

1Department of Physiology, Second Medical School, Charles University, 150 00 Prague, Czech Republic
2Laboratory of Cell Biology, Institute of Microbiology, Academy of Sciences of the Czech Republic, 142 20 Prague, Czech Republic
3Toxicogenomics Unit, National Institute of Public Health, 100 42 Prague, Czech Republic

Received 27 March 2012; Revised 18 May 2012; Accepted 18 May 2012

Academic Editor: Alessandro Desideri

Copyright © 2012 Jaroslav Kubrycht et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations.