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The proposed project aims at developing a new approach to supporting the decision making process in in silico studies of complex biomolecular systems using intercriteria analysis (ICrA). Molecular, and in particular drug design, is a time-consuming and costly process that motivates intensive development and use of computer-aided (in silico) approaches. These approaches are strongly interdisciplinary and integrate knowledge from basic disciplines such as chemistry, biology, physics, pharmacology, toxicology, mathematical modeling, and informatics. A key element in the algorithms for docking and virtual screening of bioactive molecules is the scoring function, the purpose of which is to quickly and accurately calculate the energy of the interaction of the protein ligand complex. Despite the large number of comparative studies of various scoring functions, the question of which docking programs and protocols are performing better is still unresolved and the results are often contradictory. ICrA, developed as a new multi-criterion decision-making approach, has the necessary prerequisites to assist in choosing the most appropriate scoring functions in order to guide the selection of the most appropriate drug candidates. The proposed project aims to conduct theoretical research, combining ICrA-based techniques of artificial intelligence (intuitionistic fuzzy logic and indexed matrices) and in silico methods for molecular design.

The working hypothesis of the project is based on the assumption that inter-criteria analysis can support decision-making in structure-based in silico studies of complex biomolecular systems, offering a new approach to assessing the results of using different scoring functions in docking protocols. The hypothesis will be proved by fulfilling the following main objectives:

  1. To investigate the applicability of ICrA to scoring functions of different types and from different software implementations for molecular modelling (commercial and free) on a set of experimental data on structures and activities of various protein-ligand complexes.
  2. To investigate the applicability of ICrA with respect to different indicators (interaction energies and binding poses) for evaluation of the results of docking and post-dock optimization of protein-ligand complexes.
  3. Based on objectives 1 and 2, to develop a prototype of a software environment, implementing the ICrA capabilities.
  4. Based on objectives 1, 2 and 3, to estimate the potential of ICrA to assist decision making in in silico studies of complex biomolecular systems, and to stimulate its further development.

The results obtained for evaluation, comparison and selection of molecular dock assessment functions are expected to support decision making in in silico molecular design and be useful for researchers in choosing the most appropriate compounds for drug candidates.