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Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach

Tick-borne Babesiosis is a parasitic infection caused by Babesia microti that can infect both animals and humans and may spread by tick, blood transfusions, and organ transplantation. The current therapeutic options for B. microti are limited, and drug resistance is a concern. This study proposes us...

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Autores principales: Akash, Shopnil, Hosen, Md. Eram, Mahmood, Sajjat, Supti, Sumaiya Jahan, Kumer, Ajoy, Sultana, Shamima, Jannat, Sultana, Bayıl, Imren, Nafidi, Hiba-Allah, Jardan, Yousef A. Bin, Mekonnen, Amare Bitew, Bourhia, Mohammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469490/
https://www.ncbi.nlm.nih.gov/pubmed/37662005
http://dx.doi.org/10.3389/fcimb.2023.1222913
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author Akash, Shopnil
Hosen, Md. Eram
Mahmood, Sajjat
Supti, Sumaiya Jahan
Kumer, Ajoy
Sultana, Shamima
Jannat, Sultana
Bayıl, Imren
Nafidi, Hiba-Allah
Jardan, Yousef A. Bin
Mekonnen, Amare Bitew
Bourhia, Mohammed
author_facet Akash, Shopnil
Hosen, Md. Eram
Mahmood, Sajjat
Supti, Sumaiya Jahan
Kumer, Ajoy
Sultana, Shamima
Jannat, Sultana
Bayıl, Imren
Nafidi, Hiba-Allah
Jardan, Yousef A. Bin
Mekonnen, Amare Bitew
Bourhia, Mohammed
author_sort Akash, Shopnil
collection PubMed
description Tick-borne Babesiosis is a parasitic infection caused by Babesia microti that can infect both animals and humans and may spread by tick, blood transfusions, and organ transplantation. The current therapeutic options for B. microti are limited, and drug resistance is a concern. This study proposes using computational drug design approaches to find and design an effective drug against B. microti. The study investigated the potentiality of nine natural compounds against the pathogenic human B. microti parasite and identified Vasicinone and Evodiamine as the most promising drugs. The ligand structures were optimized using density functional theory, molecular docking, molecular dynamics simulations, quantum mechanics such as HOMO–LUMO, drug-likeness and theoretical absorption, distribution, metabolism, excretion, and toxicity (ADMET), and pharmacokinetics characteristics performed. The results showed that Vasicinone (−8.6 kcal/mol and −7.8 kcal/mol) and Evodiamine (−8.7 kcal/mol and −8.5 kcal/mol) had the highest binding energy and anti-parasitic activity against B. microti lactate dehydrogenase and B. microti lactate dehydrogenase apo form. The strongest binding energy was reported by Vasicinone and Evodiamine; the compounds were evaluated through molecular dynamics simulation at 100 ns, and their stability when they form complexes with the targeted receptors was determined. Finally, the pkCSM web server is employed to predict the ADMET qualities of specific molecules, which can help prevent negative effects that arise from taking the treatment. The SwissADME web server is used to assess the Lipinski rule of five and drug-likeness properties including topological polar surface area and bioavailability. The Lipinski rule is used to estimate significant drug-likeness. The theoretical pharmacokinetics analysis and drug-likeness of the selected compounds are confirmed to be accepted by the Lipinski rule and have better ADMET features. Thus, to confirm their experimental value, these mentioned molecules should be suggested to carry out in wet lab, pre-clinical, and clinical levels.
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spelling pubmed-104694902023-09-01 Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach Akash, Shopnil Hosen, Md. Eram Mahmood, Sajjat Supti, Sumaiya Jahan Kumer, Ajoy Sultana, Shamima Jannat, Sultana Bayıl, Imren Nafidi, Hiba-Allah Jardan, Yousef A. Bin Mekonnen, Amare Bitew Bourhia, Mohammed Front Cell Infect Microbiol Cellular and Infection Microbiology Tick-borne Babesiosis is a parasitic infection caused by Babesia microti that can infect both animals and humans and may spread by tick, blood transfusions, and organ transplantation. The current therapeutic options for B. microti are limited, and drug resistance is a concern. This study proposes using computational drug design approaches to find and design an effective drug against B. microti. The study investigated the potentiality of nine natural compounds against the pathogenic human B. microti parasite and identified Vasicinone and Evodiamine as the most promising drugs. The ligand structures were optimized using density functional theory, molecular docking, molecular dynamics simulations, quantum mechanics such as HOMO–LUMO, drug-likeness and theoretical absorption, distribution, metabolism, excretion, and toxicity (ADMET), and pharmacokinetics characteristics performed. The results showed that Vasicinone (−8.6 kcal/mol and −7.8 kcal/mol) and Evodiamine (−8.7 kcal/mol and −8.5 kcal/mol) had the highest binding energy and anti-parasitic activity against B. microti lactate dehydrogenase and B. microti lactate dehydrogenase apo form. The strongest binding energy was reported by Vasicinone and Evodiamine; the compounds were evaluated through molecular dynamics simulation at 100 ns, and their stability when they form complexes with the targeted receptors was determined. Finally, the pkCSM web server is employed to predict the ADMET qualities of specific molecules, which can help prevent negative effects that arise from taking the treatment. The SwissADME web server is used to assess the Lipinski rule of five and drug-likeness properties including topological polar surface area and bioavailability. The Lipinski rule is used to estimate significant drug-likeness. The theoretical pharmacokinetics analysis and drug-likeness of the selected compounds are confirmed to be accepted by the Lipinski rule and have better ADMET features. Thus, to confirm their experimental value, these mentioned molecules should be suggested to carry out in wet lab, pre-clinical, and clinical levels. Frontiers Media S.A. 2023-08-16 /pmc/articles/PMC10469490/ /pubmed/37662005 http://dx.doi.org/10.3389/fcimb.2023.1222913 Text en Copyright © 2023 Akash, Hosen, Mahmood, Supti, Kumer, Sultana, Jannat, Bayıl, Nafidi, Jardan, Mekonnen and Bourhia https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cellular and Infection Microbiology
Akash, Shopnil
Hosen, Md. Eram
Mahmood, Sajjat
Supti, Sumaiya Jahan
Kumer, Ajoy
Sultana, Shamima
Jannat, Sultana
Bayıl, Imren
Nafidi, Hiba-Allah
Jardan, Yousef A. Bin
Mekonnen, Amare Bitew
Bourhia, Mohammed
Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach
title Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach
title_full Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach
title_fullStr Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach
title_full_unstemmed Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach
title_short Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach
title_sort anti-parasitic drug discovery against babesia microti by natural compounds: an extensive computational drug design approach
topic Cellular and Infection Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469490/
https://www.ncbi.nlm.nih.gov/pubmed/37662005
http://dx.doi.org/10.3389/fcimb.2023.1222913
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