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

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,...

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Main Authors: A.S. Kozlova, A.R. Mukhametgalieva, A.N. Fattakhova, N.I. Akberova
Format: Article
Language:English
Published: Kazan Federal University 2022-03-01
Series:Учёные записки Казанского университета. Серия Физико-математические науки
Subjects:
Online Access:https://kpfu.ru/uz-eng-phm-2022-1-7.html
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author A.S. Kozlova
A.R. Mukhametgalieva
A.N. Fattakhova
N.I. Akberova
author_facet A.S. Kozlova
A.R. Mukhametgalieva
A.N. Fattakhova
N.I. Akberova
author_sort A.S. Kozlova
collection DOAJ
description 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).
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spelling doaj.art-68001da7eaca4021bd2e70c3d7f7f2962023-01-03T08:10:11ZengKazan Federal UniversityУчёные записки Казанского университета. Серия Физико-математические науки2541-77462500-21982022-03-01164112213610.26907/2541-7746.2022.1.122-136Software pipeline for predicting and analyzing the structure of the receptor–ligandA.S. Kozlova0A.R. Mukhametgalieva1A.N. Fattakhova2N.I. Akberova3Kazan Federal University, Kazan, 420008 RussiaKazan Federal University, Kazan, 420008 RussiaKazan Federal University, Kazan, 420008 RussiaKazan Federal University, Kazan, 420008 RussiaIt 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).https://kpfu.ru/uz-eng-phm-2022-1-7.htmlmolecular dockingmolecular dynamicsglobular proteinligand–receptor complexsoftware pipelineacetylcholinesteraseautodockvmdnamd
spellingShingle A.S. Kozlova
A.R. Mukhametgalieva
A.N. Fattakhova
N.I. Akberova
Software pipeline for predicting and analyzing the structure of the receptor–ligand
Учёные записки Казанского университета. Серия Физико-математические науки
molecular docking
molecular dynamics
globular protein
ligand–receptor complex
software pipeline
acetylcholinesterase
autodock
vmd
namd
title Software pipeline for predicting and analyzing the structure of the receptor–ligand
title_full Software pipeline for predicting and analyzing the structure of the receptor–ligand
title_fullStr Software pipeline for predicting and analyzing the structure of the receptor–ligand
title_full_unstemmed Software pipeline for predicting and analyzing the structure of the receptor–ligand
title_short Software pipeline for predicting and analyzing the structure of the receptor–ligand
title_sort software pipeline for predicting and analyzing the structure of the receptor ligand
topic molecular docking
molecular dynamics
globular protein
ligand–receptor complex
software pipeline
acetylcholinesterase
autodock
vmd
namd
url https://kpfu.ru/uz-eng-phm-2022-1-7.html
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AT armukhametgalieva softwarepipelineforpredictingandanalyzingthestructureofthereceptorligand
AT anfattakhova softwarepipelineforpredictingandanalyzingthestructureofthereceptorligand
AT niakberova softwarepipelineforpredictingandanalyzingthestructureofthereceptorligand