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Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents

Chemoinformatic studies were carried on some inhibitors of dopamine transporter to develop a predictive and robust QSAR model and also to elucidate binding mode and molecular interactions between the ligands (inhibitors) and the receptor targeting schizophrenia as novel Antipsychotic agents. Density...

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Autores principales: Olasupo, Sabitu Babatunde, Uzairu, Adamu, Shallangwa, Gideon Adamu, Uba, Sani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393552/
https://www.ncbi.nlm.nih.gov/pubmed/32760824
http://dx.doi.org/10.1016/j.heliyon.2020.e04464
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author Olasupo, Sabitu Babatunde
Uzairu, Adamu
Shallangwa, Gideon Adamu
Uba, Sani
author_facet Olasupo, Sabitu Babatunde
Uzairu, Adamu
Shallangwa, Gideon Adamu
Uba, Sani
author_sort Olasupo, Sabitu Babatunde
collection PubMed
description Chemoinformatic studies were carried on some inhibitors of dopamine transporter to develop a predictive and robust QSAR model and also to elucidate binding mode and molecular interactions between the ligands (inhibitors) and the receptor targeting schizophrenia as novel Antipsychotic agents. Density Functional Theory (DFT) approach was utilized to optimize the ligands at B3LYP/6-31G∗ at the ground state and Multi-linear regression of the genetic function approximation (MLR-GFA) method was employed in building Penta-parametric linear equation models. The best model with statistically significant parameters has squared correlation coefficient R(2)= 0.802, adjusted squared correlation coefficient R(2)(adj) = 0.767, Leave one out (LOO) cross-validation coefficient (Q(2)) = 0.693, lack of fit score (LOF) = 0.406, R(2)(Test) = 0.77, Y-randomization test (cR(2)p) = 0.714, Chi-squared (χ(2)) =0.026, bootstrapping (Systematic errors = 0.272) and Variance Inflation Factor (VIF) <2 . The obtained results were compared with standard validation parameters to ascertain the predictivity, reliability, and robustness of the model. Also, the mechanistic interpretation of the descriptors found in the model revealed that two out of five descriptors; MATS7s (32.3%) and RDF95m (30.4%) having pronounced influence on the observed antipsychotic property of the compounds evidenced by their highest percentage contributions. More so, the molecular docking investigation showed that the binding affinity of the selected ligands ranges from -10.05 to -9.0 kcal/mol and with ligand 21 possessed the highest binding affinity (-10.05 kcal/mol). Furthermore, all the selected ligands displayed hydrogen bonds and hydrophobic interactions with the amino acid residues of the target (4M48) which could account for their higher binding energy. Our findings revealed that the developed model passed the general requirements for an acceptable QSAR model and also satisfied the OECD principles for model development. Hence, the developed model would be practically useful as a blueprint in developing novel antipsychotic agents with improved activity for the treatment of schizophrenia mental disorder.
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spelling pubmed-73935522020-08-04 Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents Olasupo, Sabitu Babatunde Uzairu, Adamu Shallangwa, Gideon Adamu Uba, Sani Heliyon Article Chemoinformatic studies were carried on some inhibitors of dopamine transporter to develop a predictive and robust QSAR model and also to elucidate binding mode and molecular interactions between the ligands (inhibitors) and the receptor targeting schizophrenia as novel Antipsychotic agents. Density Functional Theory (DFT) approach was utilized to optimize the ligands at B3LYP/6-31G∗ at the ground state and Multi-linear regression of the genetic function approximation (MLR-GFA) method was employed in building Penta-parametric linear equation models. The best model with statistically significant parameters has squared correlation coefficient R(2)= 0.802, adjusted squared correlation coefficient R(2)(adj) = 0.767, Leave one out (LOO) cross-validation coefficient (Q(2)) = 0.693, lack of fit score (LOF) = 0.406, R(2)(Test) = 0.77, Y-randomization test (cR(2)p) = 0.714, Chi-squared (χ(2)) =0.026, bootstrapping (Systematic errors = 0.272) and Variance Inflation Factor (VIF) <2 . The obtained results were compared with standard validation parameters to ascertain the predictivity, reliability, and robustness of the model. Also, the mechanistic interpretation of the descriptors found in the model revealed that two out of five descriptors; MATS7s (32.3%) and RDF95m (30.4%) having pronounced influence on the observed antipsychotic property of the compounds evidenced by their highest percentage contributions. More so, the molecular docking investigation showed that the binding affinity of the selected ligands ranges from -10.05 to -9.0 kcal/mol and with ligand 21 possessed the highest binding affinity (-10.05 kcal/mol). Furthermore, all the selected ligands displayed hydrogen bonds and hydrophobic interactions with the amino acid residues of the target (4M48) which could account for their higher binding energy. Our findings revealed that the developed model passed the general requirements for an acceptable QSAR model and also satisfied the OECD principles for model development. Hence, the developed model would be practically useful as a blueprint in developing novel antipsychotic agents with improved activity for the treatment of schizophrenia mental disorder. Elsevier 2020-07-28 /pmc/articles/PMC7393552/ /pubmed/32760824 http://dx.doi.org/10.1016/j.heliyon.2020.e04464 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Olasupo, Sabitu Babatunde
Uzairu, Adamu
Shallangwa, Gideon Adamu
Uba, Sani
Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
title Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
title_full Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
title_fullStr Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
title_full_unstemmed Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
title_short Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
title_sort chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393552/
https://www.ncbi.nlm.nih.gov/pubmed/32760824
http://dx.doi.org/10.1016/j.heliyon.2020.e04464
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