Software pipeline for predicting and analyzing the structure of the receptor–ligand

A.S. Kozlova^∗ , A.R. Mukhametgalieva^∗∗ , A.N. Fattakhova^∗∗∗ , N.I. Akberova^∗∗∗∗

Kazan Federal University, Kazan, 420008 Russia

E-mail: ^∗kozlovanastasiaser@gmail.com, ^∗∗aliyara_fikovna@mail.ru, ^∗∗∗afattakh57@gmail.com, ^∗∗∗∗nakberova@mail.ru

Received August 31, 2021

ORIGINAL ARTICLE

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DOI: 10.26907/2541-7746.2022.1.122-136

For citation: Kozlova A.S., Mukhametgalieva A.R., Fattakhova A.N., Akberova N.I. Software pipeline for predicting and analyzing the structure of the receptor–ligand complex. Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 2022, vol. 164, no. 1, pp. 122–136. doi: 10.26907/2541-7746.2022.1.122-136. (In Russian)

Abstract

It is of fundamental importance in pharmacology and theoretical biology to analyze the binding of ligands to receptors. A better understanding of this process and its outcomes can help predict the following: how the protein interacts with ligands; whether the ligand acts as an activator, inhibitor, or substrate; in which areas the ligand interacts best with the receptor. This article describes the potential of using a software pipeline for finding the most probable position of the ligand in the receptor. Such a pipeline involves a complex algorithm, from predicting the structure of the receptor to searching and analyzing the interaction of ligands with the receptor. The advantage of the software pipeline is that it allows numerous combinations of ligands and receptors to be analyzed at once. Possible interactions of the receptor–ligand complex are studied based on certain parameters: the energy of the affinity of the ligand for the receptor; the length and energy of the bond between the receptor and the ligand, both in the whole complex and between individual atoms. All characteristics can be automatically calculated by default under the specified optimal parameters. Alternatively, they can be set by the user, depending on the task. To illustrate how the software pipeline works, we analyzed the interaction of ligands with human acetylcholinesterase, a protein with the most studied active center. We confirmed that the software pipeline works correctly by comparing the obtained results with the experimental data on the binding of various ligands to human acetylcholinesterase. The pipeline code was published on GitHub (https://github.com/NastiaKozlova/stabilisation complex-receptor-ligand).

Keywords: molecular docking, molecular dynamics, globular protein, ligand–receptor complex, software pipeline, acetylcholinesterase, AutoDock, VMD, NAMD

Acknowledgments. The study was supported by the Russian Foundation for Basic Research (project no. 19-34-90120) and by the Kazan Federal University Strategic Academic Leadership Program (“PRIORITY-2030”).

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