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Projects / Programmes source: ARIS

New computational tools at the PDB scale for drug discovery

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Research activity

Code Science Field Subfield
1.07.00  Natural sciences and mathematics  Computer intensive methods and applications   

Code Science Field
P000  Natural sciences and mathematics   

Code Science Field
1.01  Natural Sciences  Mathematics 
Keywords
Molecular Modeling, Algorithms, Computer Simulations, Graph Theory, Protein Binding Sites, Pharmaceutically Interesting Molecules, Drug Design
Evaluation (rules)
source: COBISS
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (11)
no. Code Name and surname Research area Role Period No. of publications
1.  29452  PhD Barbara Boldin  Interdisciplinary research  Researcher  2018 - 2021  79 
2.  25434  PhD Urban Bren  Natural sciences and mathematics  Researcher  2018 - 2021  339 
3.  31774  PhD Klen Čopič Pucihar  Engineering sciences and technologies  Researcher  2018 - 2021  135 
4.  34384  PhD Karla Ferjančič  Natural sciences and mathematics  Researcher  2018 - 2021  20 
5.  06734  PhD Dušanka Janežič  Natural sciences and mathematics  Head  2018 - 2021  495 
6.  32587  PhD Marko Jukič  Natural sciences and mathematics  Researcher  2019 - 2021  157 
7.  24897  PhD Matjaž Kljun  Engineering sciences and technologies  Researcher  2018 - 2021  160 
8.  25435  PhD Janez Konc  Natural sciences and mathematics  Researcher  2018 - 2020  228 
9.  24997  PhD Klavdija Kutnar  Natural sciences and mathematics  Researcher  2018 - 2021  248 
10.  50720  PhD Žiga Velkavrh  Natural sciences and mathematics  Junior researcher  2018  14 
11.  27559  PhD Vito Vitrih  Natural sciences and mathematics  Researcher  2018 - 2021  109 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  2790  University of Primorska, Faculty of mathematics, Natural Sciences and Information Technologies  Koper  1810014009  16,821 
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 integration of classical and quantum equations of motion by further developing symplectic algorithms based on analytical treatment of high frequency motions. 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. The proposed 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, a 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.
Significance for science
The development of algorithms for binding sites detection on protein structures could provide new insights into mode of action of these molecular machines and is fundamental to our understanding of the processes that govern binding of small ligands and biomolecules such as proteins or nucleic acids. Newly developed methods that allow the prediction of protein binding sites, are particularly promising because they explore the interactions between proteins due to the rapidly expanding progress of structural genomics. This work is also important for the development of modern methods of systems biology, through which it will be possible to explain cooperation between the hitherto seemingly unrelated proteins. The result of the proposed project will be a new tool for pharmaceutical modeling, free to researchers worldwide, available from our web server ProBiS (Protein Binding Sites) at http://insilab.org, distinguished for its comprehensible graphical interface. The developed tool will enable researchers to predict binding of molecules to proteins, and to evaluate their binding affinity using molecular dynamics. The research carried out following this proposal is of great importance to the development of modern simulation techniques, which hold the promise to greatly increase our ability to simulate large macromolecular systems with a reasonable amount of computational effort. It is expected that the product of this research effort will be added to the CHARMM (Chemistry at HARvard for Macromolecular Mechanics) program and distributed for use by others throughout the world.
Significance for the country
The development of algorithms for binding sites detection on protein structures could provide new insights into mode of action of these molecular machines and is fundamental to our understanding of the processes that govern binding of small ligands and biomolecules such as proteins or nucleic acids. Newly developed methods that allow the prediction of protein binding sites, are particularly promising because they explore the interactions between proteins due to the rapidly expanding progress of structural genomics. This work is also important for the development of modern methods of systems biology, through which it will be possible to explain cooperation between the hitherto seemingly unrelated proteins. The result of the proposed project will be a new tool for pharmaceutical modeling, free to researchers worldwide, available from our web server ProBiS (Protein Binding Sites) at http://insilab.org, distinguished for its comprehensible graphical interface. The developed tool will enable researchers to predict binding of molecules to proteins, and to evaluate their binding affinity using molecular dynamics. The research carried out following this proposal is of great importance to the development of modern simulation techniques, which hold the promise to greatly increase our ability to simulate large macromolecular systems with a reasonable amount of computational effort. It is expected that the product of this research effort will be added to the CHARMM (Chemistry at HARvard for Macromolecular Mechanics) program and distributed for use by others throughout the world.
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