Abstract. In this study we examine the possibility of using evolutionary optimization algorithms in protein-peptide docking. We present the main assumptions that reduce the docking problem to a continuous global optimization problem and provide a way of using evolutionary optimization algorithms. The Rosetta all-atom force field was used for structural representation and energy scoring. We describe the parallelization scheme and MPI/OpenMP realization of the considered algorithms. We demonstrate the efficiency and the performance for some algorithms which were applied to a set of benchmark tests.
In this paper we study features of the multivariate empirical quantum function implementation for which sample is distributed at the mesh points of the regular grid. We present an algorithm for continuous and discrete quantile transform based on recursive definition of the multivariate quantile function. We perform numerical study of the presented algorithm and demonstrate it computational complexity according to representation of the sample. We present the results of using evolutionary optimization algorithm with quantile transform for solving the problems in structural bioinformatics: protein structure prediction from amino acid sequence and protein-peptide docking with known binding site and linear peptide structure.
In this paper presented problem-oriented software package for performing computational experiments in structural bioinformatics problems: protein structure prediction and peptide-protein docking. These problemsare formulated as continuous global optimization tasks. The primary purpose of the presented software package is to provide functionality for performing computational experiments using various stochastic optimization methods. To perform experiments for the selected task the objective function and search space are provided for user. In this work the software packagefunctionality, implementation features and the results of various experimentsare presented. The software is written in C++ and provides the possibility ofusing parallel computing using OpenMP technology. The presented package is open source software that stored in the GitHub repositories.
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