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Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds.

ABSTRACT: Natural chemical compounds have been widely investigated for their programmed necrosis causing characteristics. One of the conventional methods for screening such compounds is the use of concentrated plant extracts without isolation of active moieties for understanding pharmacological activity. For the last two decades, modern medicine has relied mainly on the isolation and purification of one or two complicated active and isomeric compounds. The idea of multi-target drugs has advanced rapidly and impressively from an innovative model when first proposed in the early 2000s to one of the popular trends for drug development in 2021. Alternatively, fragment-based drug discovery is also explored in identifying target-based drug discovery for potent natural anticancer agents which is based on well-defined fragments opposite to use of naturally occurring mixtures. This review summarizes the current key advancements in natural anticancer compounds; computer-assisted/fragment-based structural elucidation and a multi-target approach for the exploration of natural compounds.

SUBMITTER: Chavda VP

PROVIDER: S-EPMC8416109 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds.

Chavda Vivek P VP Ertas Yavuz Nuri YN Walhekar Vinayak V Modh Dharti D Doshi Avani A Shah Nirav N Anand Krishna K Chhabria Mahesh M

Frontiers in pharmacology 20210817

Natural chemical compounds have been widely investigated for their programmed necrosis causing characteristics. One of the conventional methods for screening such compounds is the use of concentrated plant extracts without isolation of active moieties for understanding pharmacological activity. For the last two decades, modern medicine has relied mainly on the isolation and purification of one or two complicated active and isomeric compounds. The idea of multi-target drugs has advanced rapidly a ...[more]

PMID: 34483905

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Project 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.

Dataset Information

Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds.

Publications

Advanced Computational Methodologies Used in the Discovery of New Natural Anticancer Compounds.

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