Computational study to discover potent phytochemical inhibitors against drug target, squalene synthase from Leishmania donovani

Abstract

Aims The parasite, Leishmania donovani is responsible for lethal visceral leishmaniasis (VL) in humans. There is a need to investigate novel medicines as antileishmanial drugs, as medication currently introduced for leishmaniasis may cause resistance, serious side-effects, chemical instability and high cost. Therefore, this computational study was designed to explore potential phytochemical inhibitors against Leishmania donovani squalene synthase (LdSQS) enzyme, a drug target. Main methods Multiple sequence alignment was carried to detect conserved regions across squalene synthases from different Leishmania spp. Their evolutionary relationships were studied by generating phylogenetic tree. Homology modeling method was used to build a three dimensional model of the protein. The validated model was explored by docking simulation with the phytochemicals of interest to identify the most potent inhibitors. Two reported inhibitors were used as references in the virtual screening. The top hit compounds (binding energy less than -9 kcal/mol) were further subjected to intermolecular interaction analysis, pharmacophore modeling, pharmacokinetic and toxicity prediction. Key findings Seven phytochemicals displayed binding energies less than -9 kcal/mol hence demonstrating ability to be strongly bound to the active site of LdSQS to inhibit the enzymatic activity. Ancistrotanzanine B demonstrated the lowest binding affinity of -9.83 kcal/mol superior to reported inhibitors in literature. Conserved two aspartate rich regions and two signatory motifs were found in the L. donovani squalene synthase by multiple sequence alignment. In addition, study of pharmacophore modeling confirmed that top hit phytochemicals and the reported inhibitor (E5700) share common chemical features for their biochemical interaction with LdSQS. Among seven phytochemicals, 3-O-methyldiplacol showed admissible physicochemical, pharmacokinetic and toxicity predictions compared to the reported inhibitors. All seven phytochemicals satisfied in silico prediction criteria for oral bioavailability. Significance Based on the current study, these hits can be further structurally optimized and validated under laboratory conditions to develop antileishmanial drugs.

In Silico Analysis of the Apoptotic and HPV Inhibitory Roles of Some Selected Phytochemicals Detected from the Rhizomes of Greater Cardamom

“…Pharmacophore-based models were screened based on the descriptors of the identified phytochemicals. For phytochemicals, applications of such techniques are common in the literature [ 58 , 59 ]. Based on pharmacophore-based screening, Sharma et al (2020) [ 60 ] filtered ten compounds and identified the phytochemical schinilenol as the best lead compound against the protein cyclin-dependent kinase 2 (CDK2).…”

Challenges and Tools for In Vitro Leishmania Exploratory Screening in the Drug Development Process: An Updated Review

“…In this way, a growing body of work was published on structure-based computational approaches and pharmacophore-based virtual screenings, such as the in silico high throughput screening and the molecular docking published by Saki et al in 2019 [140]: this work identified five potent antileishmanial ligands for lipophosphoglycan (LPS) receptor, and two for γ-glutamylcystein synthase (γ-GCS) receptor in L. infantum among 20,000 FDA approved drugs. In 2021, similar computational approaches notably led to identifying phytochemical inhibitors of squalene synthase [141] and selective inhibitors of dihydrofolate reductase [142] in L. donovani. Allosteric modulators of superoxide dismutase in L. chagasi were also identified [143].…”