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Fragment-based screening with natural products for novel anti-parasitic disease drug discovery.

ABSTRACT: Introduction: Fragment-based drug discovery can identify relatively simple compounds with low binding affinity due to fewer binding interactions with protein targets. FBDD reduces the library size and provides simpler starting points for subsequent chemical optimization of initial hits. A much greater proportion of chemical space can be sampled in fragment-based screening compared to larger molecules with typical molecular weights (MWs) of 250-500 g mol^-1 used in high-throughput screening (HTS) libraries. Areas covered: The authors cover the role of natural products in fragment-based drug discovery against parasitic disease targets. They review the approaches to develop fragment-based libraries either using natural products or natural product-like compounds. The authors present approaches to fragment-based drug discovery against parasitic diseases and compare these libraries with the 3D attributes of natural products. Expert opinion: To effectively use the three-dimensional properties and the chemical diversity of natural products in fragment-based drug discovery against parasitic diseases, there needs to be a mind-shift. Library design, in the medicinal chemistry area, has acknowledged that escaping flat-land is very important to increase the chances of clinical success. Attempts to increase sp³ richness in fragment libraries are acknowledged. Sufficient low molecular weight natural products are known to create true natural product fragment libraries.

SUBMITTER: Liu M

PROVIDER: S-EPMC6816479 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Fragment-based screening with natural products for novel anti-parasitic disease drug discovery.

Liu Miaomiao M Quinn Ronald J RJ

Expert opinion on drug discovery 20190912 12

<b>Introduction</b>: Fragment-based drug discovery can identify relatively simple compounds with low binding affinity due to fewer binding interactions with protein targets. FBDD reduces the library size and provides simpler starting points for subsequent chemical optimization of initial hits. A much greater proportion of chemical space can be sampled in fragment-based screening compared to larger molecules with typical molecular weights (MWs) of 250-500 g mol<sup>-1</sup> used in high-throughpu ...[more]

PMID: 31512943

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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

Fragment-based screening with natural products for novel anti-parasitic disease drug discovery.

Publications

Fragment-based screening with natural products for novel anti-parasitic disease drug discovery.

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