Research

Protein interaction atlas for prediction of genetic variations involved in drug interactions and disease development

Code:

J1-1715

Range:

01. July 2019 - 06. January 2022

Range:

0,05 FTE

Leader:

Stanislav Gobec

Field:

1.07. Natural sciences and mathematics / Computer intensive methods and applications

Abstract:

Computer intensive methods and applications is extremely propulsive area of scientific research in which the use of supercomputers and computer clusters is used to solve the most demanding computational problems in theoretical and applied research in natural and technical sciences. We deal with solving of various types of problems, such as, structure and dynamics of molecules, bulk matter research, chemical and biochemical reactions, and the development of new drugs. Development of new computational methods is closely related to the development of new algorithms and the development of modern computers. This project stands at the cutting edge of today's research trends in the field of molecular modeling. It concentrates on some of the most relevant research areas within development and application of computer simulation techniques and approaches. The current state of the art and important historical contributions are briefly sketched, and our main research goals, based on the past results and contributions of the project participants, are stated. These goals include development of new methods and new improvements for molecular modeling and the simulation of complex macromolecular systems that increase the accuracy and efficiency of present-day computation approaches. We will use and develop molecular modeling methods, especially the simulation of molecular dynamics and chemical graph theory, a branch of mathematical chemistry concerned with discrete structures in chemistry. We primarily aim to improve algorithms for combining protein binding site detection based on graph theoretical approaches, with sequence variants mapping to binding sites, and assessment of sequence variants' impact on ligand binding by incorporating protein flexibility through molecular dynamics simulations. Special emphasis will be given to development of new algorithms for protein binding sites prediction as well as to development of web tools for modeling of pharmaceutically interesting molecules. We aim to develop a free web-based protein interaction atlas for prediction of genetic variations involved in drug interactions and disease development - ProBiS-ATLAS of all available protein binding sites in the PDB with mapped ligands and sequence variants. The atlas will also contain information about sequence variants' effects on binding for each specific ligand in the PDB. This newly developed approach will be particularly useful in the context of precision medicine. Our tools will enable joining several otherwise disconnected areas of research, i.e., graph theoretical approaches, genome sequence studies, protein structures, and molecular dynamics simulation. The methodological improvements should significantly extend the scope of presently used algorithms in terms of length- and time-scales, and thus contribute to the general applicability of computer simulation algorithms. The simulation results of selected examples will facilitate the understanding of some fundamental problems in molecular biology, especially in the discovery of new biologically active compounds for the development of new drugs. In spite of large potentials for concrete use of our results in certain branches of technology and industry, the main focus of our research remains development of general, new mathematical methods and algorithms in the field of molecular modeling, and as such, represents a contribution to overall scientific knowledge. The project involves a number of researchers with excellent publishing records, currently active in Slovenia, guaranteeing research at the highest possible level. Nevertheless, collaboration with research institutions from Austria, Germany, Belgium, Japan and USA, where some of the most renowned world experts in the field of computer simulations of biological macromolecules are based, is planed too. This will further enhance our research.