QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors

Abstract Malaria, a disease caused by one of the world’s fatal parasites Plasmodium falciparum, is responsible for over a million death annually. P. falciparum dihydroorotate dehydrogenase (PfDHODH) is a validated target of this deadly parasite. Quantitative structure–activity relationship and molec...

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Main Authors: Zakari Ya’u Ibrahim, Adamu Uzairu, Gideon Shallangwa, Stephen Abechi
Format: Article
Language:English
Published: Springer 2020-06-01
Series:SN Applied Sciences
Subjects:
Online Access:https://doi.org/10.1007/s42452-020-2955-1
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spelling doaj-c790ce540d974da2ba325dd5f210c7fa2021-06-06T11:21:19ZengSpringerSN Applied Sciences2523-39632523-39712020-06-012711210.1007/s42452-020-2955-1QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitorsZakari Ya’u Ibrahim0Adamu Uzairu1Gideon Shallangwa2Stephen Abechi3Department of Chemistry, Faculty of Physical Sciences, Ahmadu Bello UniversityDepartment of Chemistry, Faculty of Physical Sciences, Ahmadu Bello UniversityDepartment of Chemistry, Faculty of Physical Sciences, Ahmadu Bello UniversityDepartment of Chemistry, Faculty of Physical Sciences, Ahmadu Bello UniversityAbstract Malaria, a disease caused by one of the world’s fatal parasites Plasmodium falciparum, is responsible for over a million death annually. P. falciparum dihydroorotate dehydrogenase (PfDHODH) is a validated target of this deadly parasite. Quantitative structure–activity relationship and molecular docking in silico methods were employed in the discovery of unique PfDHODH inhibitors from the computational design derivatives of indolyl-3-ethanone-α-thioethers through models generation via a genetic function algorithm methods. The best model indicates good power of prediction with coefficient of determination, R2 = 0.9482, adjusted coefficient of determination ($${\text{R}}_{\text{adj}}^{2}$$ Radj2 ) = 0.9288, Leave one out cross-validation coefficient (Q2) = 0.9201 and the external validation ($${\text{R}}_{\text{pred}}^{2}$$ Rpred2 ) = 0.6467. The contribution of every descriptor in the model was investigated through finding their mean effect to (pIC50) the activities of the compounds. With MATS5m (− 0.11725), RDF75m (− 0.12097), VE3_Dzp (0.14697), and MLFER_BH (1.08528) contributing more to the model, while AATSC8p (− 0.04833) and minHBa (0.05430) contributed the least to the model. Hence, the mean effect indicated MLFER_BH to be the most relevant descriptor, which aided the design of five derivatives of indolyl-3-ethanone-α-thioethers. All the designed antimalarial compounds were deeply docked within the binding region thereby forming several hydrogens and hydrophobic bonds leading to the generation of better binding affinity and high binding scores (− 156.181 kcal/mol) compared to the design template (− 138.201 kcal/mol) and the standard drug (− 128.467 kcal/mol). Furthermore, all the five designed antimalarial compounds were found to be better bonded to the binding pocket of PfDHODH than other compounds reported by other researchers.https://doi.org/10.1007/s42452-020-2955-1QSARMolecular dockingMolecular designAntimalarialIndolyl-3-ethanone-α-thioethersDescriptors
collection DOAJ
language English
format Article
sources DOAJ
author Zakari Ya’u Ibrahim
Adamu Uzairu
Gideon Shallangwa
Stephen Abechi
spellingShingle Zakari Ya’u Ibrahim
Adamu Uzairu
Gideon Shallangwa
Stephen Abechi
QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors
SN Applied Sciences
QSAR
Molecular docking
Molecular design
Antimalarial
Indolyl-3-ethanone-α-thioethers
Descriptors
author_facet Zakari Ya’u Ibrahim
Adamu Uzairu
Gideon Shallangwa
Stephen Abechi
author_sort Zakari Ya’u Ibrahim
title QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors
title_short QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors
title_full QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors
title_fullStr QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors
title_full_unstemmed QSAR and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors
title_sort qsar and molecular docking based design of some indolyl-3-ethanone-α-thioethers derivatives as plasmodium falciparum dihydroorotate dehydrogenase (pfdhodh) inhibitors
publisher Springer
series SN Applied Sciences
issn 2523-3963
2523-3971
publishDate 2020-06-01
description Abstract Malaria, a disease caused by one of the world’s fatal parasites Plasmodium falciparum, is responsible for over a million death annually. P. falciparum dihydroorotate dehydrogenase (PfDHODH) is a validated target of this deadly parasite. Quantitative structure–activity relationship and molecular docking in silico methods were employed in the discovery of unique PfDHODH inhibitors from the computational design derivatives of indolyl-3-ethanone-α-thioethers through models generation via a genetic function algorithm methods. The best model indicates good power of prediction with coefficient of determination, R2 = 0.9482, adjusted coefficient of determination ($${\text{R}}_{\text{adj}}^{2}$$ Radj2 ) = 0.9288, Leave one out cross-validation coefficient (Q2) = 0.9201 and the external validation ($${\text{R}}_{\text{pred}}^{2}$$ Rpred2 ) = 0.6467. The contribution of every descriptor in the model was investigated through finding their mean effect to (pIC50) the activities of the compounds. With MATS5m (− 0.11725), RDF75m (− 0.12097), VE3_Dzp (0.14697), and MLFER_BH (1.08528) contributing more to the model, while AATSC8p (− 0.04833) and minHBa (0.05430) contributed the least to the model. Hence, the mean effect indicated MLFER_BH to be the most relevant descriptor, which aided the design of five derivatives of indolyl-3-ethanone-α-thioethers. All the designed antimalarial compounds were deeply docked within the binding region thereby forming several hydrogens and hydrophobic bonds leading to the generation of better binding affinity and high binding scores (− 156.181 kcal/mol) compared to the design template (− 138.201 kcal/mol) and the standard drug (− 128.467 kcal/mol). Furthermore, all the five designed antimalarial compounds were found to be better bonded to the binding pocket of PfDHODH than other compounds reported by other researchers.
topic QSAR
Molecular docking
Molecular design
Antimalarial
Indolyl-3-ethanone-α-thioethers
Descriptors
url https://doi.org/10.1007/s42452-020-2955-1
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