Molecular interaction of investigational ligands with human brain acetylcholinesterase

Target-based virtual screening, computational multiscoring docking and molecular dynamics simulation of small molecules as promising drug candidate affecting kinesin-like protein KIFC1

The kinesin family member C1 (KIFC1) is an essential protein that facilitates the bipolar division of neoplastic cells. Inhibiting KIFC1 by small molecules is a lucrative strategy to impede bipolar mitosis leading to the apoptosis of cancerous cells. The research aims to envisage small-molecule inhibitors targeting KIFC1. The Mcule database, a comprehensive online digital platform containing more than five million chemical compounds, was used for structure-based virtual screening (SBVS). Druglikeness filtration sifted 2,293,282 chemical hits that further narrowed down to 49 molecules after toxicity profiling. Finally, 39 compounds that comply with the BOILED-Egg permeation predictive model of the ADME rules were carried forward for multiscoring docking using the AutoDock Vina inbuilt to Mcule drug discovery platform, DockThor and SwissDock tools. The mean of ΔG terms produced by docking tools was computed to find consensus top ligand hits. AZ82 exhibited stronger binding (Consensus ΔG: -7.99 kcal mol^-1 ) with KIFC1 among reference inhibitors, for example, CW069 (-7.57 kcal mol^-1 ) and SR31527 (-7.01 kcal mol^-1 ). Ten ligand hits namely, Mcule-4895338547 (Consensus ΔG: -8.69 kcal mol^-1 ), Mcule-7035674888 (-8.42 kcal mol^-1 ), Mcule-5531166845 (-8.53 kcal mol^-1 ), Mcule-3248415882 (-8.55 kcal mol^-1 ), Mcule-291881733 (-8.41 kcal mol^-1 ), Mcule-5918624394 (-8.44), Mcule-3470115427 (-8.47), Mcule-3686193135 (-8.18 kcal mol^-1 ), Mcule-3955355291 (8.09 kcal mol^-1 ) and Mcule-9534899193 (-8.01 kcal mol^-1 ) depicted strong binding interactions with KIFC1 in comparison to potential reference inhibitor AZ82. The top four ligands and AZ82 were considered for molecular dynamics simulation of 50 ns duration. Toxicity profiling, physicochemical properties, lipophilicity, solubility, pharmacokinetics, druglikeness, medicinal chemistry attributes, average potential energy, RMSD, RMSF, SASA, ΔGsolv and Rg analyses forecast the ligand mcule-4895338547 as a promising inhibitor of KIFC1.

Molecular interaction of inhibitors with human brain butyrylcholinesterase

Alzheimer's disease is a topic of deep research interest across the global scientific community. Butyrylcholinesterase (BuChE) is an important enzyme, and an interesting anti-Alzheimer's target. Identification or fresh design of promising BuChE-inhibitors is warranted. Virtual screening supported by molecular dynamics simulations has emerged as a key component of present drug-discovery cascades. The research piece aimed at identification of a putative BuChE-inhibitor as a fresh molecular frame that might aid drug design in the context of Alzheimer's disease. The study utilized 'MCULE' to screen a set of 5 million ligands to test their ability to bind to human BuChE. Pharmacokinetic profiling was achieved by the 'SWISS ADME' program. Toxicities were duly assessed. YASARA STRUCTURE version 20.10.4.W.64 was employed to run 133 ns molecular dynamics (MD) simulation for the complex of 'the top screened out inhibitor' and 'the human BuChE enzyme'. The simulation was executed for approx. 4 days (~93 hrs) on an HP ZR30w workstation. YANACONDA, a special language contained in YASARA STRUCTURE was employed to perform complex tasks. Fine resolution figures (notably the RMSD vs time plot) were created. Snapshots were extracted at every 250 ps. The selected ligand, (3-Bromophenyl)[5-(4-chlorophenyl)-5-hydroxy-3-(trifluoromethyl)-4,5-dihydro-1H-pyrazol-1-yl]methanone, exhibited the best overall binding with human BuChE. It interacted with human BuChE through 19 residues. Markedly, 9 of the 19 residues were confirmed to be matching to those of the reference complex (PDB ID 5DYW). Trajectory analysis returned 533 snapshots. The RMSD versus time plot indicated that around 22 ns, equilibrium was achieved and, from then on, the 'BuChE-Top inhibitor' complex remained predominantly stable. From 22 ns and onwards till 133 ns, the backbone RMSD fluctuations were observed to remain limited within a range of 1.2-1.9 Å. The molecule, (3-Bromophenyl)[5-(4-chlorophenyl)-5-hydroxy-3-(trifluoromethyl)-4,5-dihydro-1H-pyrazol-1-yl]methanone, satisfied ADMET requirements. Additionally, the feasibility of the proposed enzyme-inhibitor complex was supported by an adequately extended MD simulation of 133 ns. Hence, the proposed molecule could be a likely lead for designing inhibitor(s) against human BuChE. Scope remains for validatory wet laboratory investigation.

In silico screening of glycogen synthase kinase-3β targeted ligands against acetylcholinesterase and its probable relevance to Alzheimer's disease

Alzheimer's disease (AD) is a growing global health concern that affects 10% of the population aged above 65 years. A growing body of evidence indicates that multi-targeted drugs might be useful therapeutic options owing to the heterogeneity of AD pathology. The current study exploited advanced computational biology tools to identify ligands that might display effective binding to two protein targets in the context of AD. The present study used in silico virtual screening of small molecules library to identify effectiveness against two AD targets viz. acetyl cholinesterase (AChE) and glycogen synthase kinase-3β (GSK-3β). PyRX-Python prescription with AutodockVina was used to generate binding energy profiles. Further screening was accomplished using SwissADME and molecular interaction studies. The present study obtained 48 ligands (absolute binding energy >8 kcal/mol), by virtual screening of 100 ligands. Among those, 13 ligands (BRW, 6VK, 6Z5, SMH, X37, 55E, 65 A, IQ6, 6VL, 6VM, F1B, 6Z2 and GVP) were selected based on blood brain barrier (BBB) permeability, acceptable ADME properties as well as their molecular interaction profiles with the aforementioned AD-targets. The present study has predicted certain molecules that appear worthy to be tested for effectiveness against two AD targets, namely AChE and GSK-3β. However, the results warrant further wet laboratory validation, as computational studies are merely predictive in nature. This approach might be useful for future treatment of AD.Communicated by Ramaswamy H. Sarma.