Lead generation of cysteine based mesenchymal epithelial transition (c-Met) kinase inhibitors: Using structure-based scaffold hopping, 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics simulation

Discovery of novel CXCR4 inhibitors for the treatment of inflammation by virtual screening and biological evaluation

C-X-C chemokine receptor type 4 (CXCR4) exerts considerable influence on the pathogenesis of inflammatory disorders and offers a potent avenue for drug intervention. This research utilizes a hybrid virtual screening methodology constructed using computer-aided drug design to discover novel CXCR4 inhibitors for the treatment of inflammation. First, a compound library was screened by Lipinski's five rules and adsorption, distribution, metabolism, excretion and toxicity properties. Second, the HypoGen algorithm was used in constructing a 3D-QSAR pharmacophore model and verify it layer by layer, and the obtained optimal pharmacophore 1 (Hypo 1) was used as a 3D query for compound screening. Then, hit compounds were obtained through molecular docking (Libdock and CDOCKER). The toxicity of the compounds to MDA-MB-231 cells was evaluated in vitro, and their binding affinity to the target was evaluated according to how they compete with 12G5 antibody for CXCR4 on the surfaces of the MDA-MB-231 cells. Compound Hit14 showed the strongest binding affinity among the hit compounds and inhibited cell migration and invasion in Matrigel invasion and wound healing assay at a concentration of 100 nM, demonstrating a better effect than AMD3100. Western Blot experiments further showed that Hit14 blocked the CXCR4/CXCL12-mediated phosphorylation of Akt. Meanwhile, cellular thermal displacement assay analysis showed that CXCR4 protein bound to Hit14 had high thermal stability. Finally, through in vivo experiments, we found that Hit14 inhibited mouse ear inflammation and reduced ear swelling and damage. Therefore, Hit14 is a promising drug for the further development of CXCR4 inhibitors for inflammation treatment.

Integration of ligand and structure-based pharmacophore screening for the identification of novel natural leads against Euchromatic histone lysine methyltransferase 2 (EHMT2/G9a)

Herein, we report a blended ligand and structure-based pharmacophore screening approach to identify new natural leads against the Protein Lysine Methyltransferase 2 (EHMT2/G9a). The EHMT2/G9a has been associated with Cancer, Alzheimer's, and aging and is considered an emerging drug target having no clinically passed inhibitor. Purposefully, we developed the ligand-based pharmacophore (Pharmacophore-L) based on the common features of known inhibitors and the structure-based pharmacophore (Pharmacophore-S) based on the interaction profile of available crystal structures. The Pharmacophore-L and Pharmacophore-S were subjected to multiple tiers of validations and utilized in combination for the screening of total 741543 compounds coming from multiple databases. Additional layers of stringency were applied in the screening process to test drug-likeness (using Lipinski's rule, Veber's rule, SMARTS and ADMET filtration), to rule out any toxicity (TOPKAT analysis). The interaction profiles, stabilities, and comparative analysis against the reference were carried out by flexible docking, MD simulation, and MM-GBSA analysis, which finally led to three leads as potential inhibitors of G9a.Communicated by Ramaswamy H. Sarma.

Identification of PLK1-PBD Inhibitors from the Library of Marine Natural Products: 3D QSAR Pharmacophore, ADMET, Scaffold Hopping, Molecular Docking, and Molecular Dynamics Study

PLK1 is found to be highly expressed in various types of cancers, but the development of inhibitors for it has been slow. Most inhibitors are still in clinical stages, and many lack the necessary selectivity and anti-tumor effects. This study aimed to create new inhibitors for the PLK1-PBD by focusing on the PBD binding domain, which has the potential for greater selectivity. A 3D QSAR model was developed using a dataset of 112 compounds to evaluate 500 molecules. ADMET prediction was then used to select three molecules with strong drug-like characteristics. Scaffold hopping was employed to reconstruct 98 new compounds with improved drug-like properties and increased activity. Molecular docking was used to compare the efficient compound abbapolin, confirming the high-activity status of [(14S)-14-hydroxy-14-(pyridin-2-yl)tetradecyl]ammonium,[(14S)-15-(2-furyl)-14-hydroxypentadecyl]ammonium and [(14S)-14-hydroxy-14-phenyltetradecyl]ammonium. Molecular dynamics simulations and MMPBSA were conducted to evaluate the stability of the compounds in the presence of proteins. An in-depth analysis of [(14S)-15-(2-furyl)-14-hydroxypentadecyl]ammonium and [(14S)-14-hydroxy-14-phenyltetradecyl]ammonium identified them as potential candidates for PLK1 inhibitors.

Lead generation of UPPS inhibitors targeting MRSA: Using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamic simulations

Undecaprenyl Pyrophosphate Synthase (UPPS) is a vital target enzyme in the early stages of bacterial cell wall biosynthesis. UPPS inhibitors have antibacterial activity against resistant strains such as MRSA and VRE. In this study, we used several consecutive computer-based protocols to identify novel UPPS inhibitors. The 3D QSAR pharmacophore model generation (HypoGen algorithm) protocol was used to generate a valid predictive pharmacophore model using a set of UPPS inhibitors with known reported activity. The developed model consists of four pharmacophoric features: one hydrogen bond acceptor, two hydrophobic, and one aromatic ring. It had a correlation coefficient of 0.86 and a null cost difference of 191.39, reflecting its high predictive power. Hypo1 was proven to be statistically significant using Fischer's randomization at a 95% confidence level. The validated pharmacophore model was used for the virtual screening of several databases. The resulting hits were filtered using SMART and Lipinski filters. The hits were docked into the binding site of the UPPS protein, affording 70 hits with higher docking affinities than the reference compound (6TC, - 21.17 kcal/mol). The top five hits were selected through extensive docking analysis and visual inspection based on docking affinities, fit values, and key residue interactions with the UPPS receptor. Moreover, molecular dynamic simulations of the top hits were performed to confirm the stability of the protein-ligand complexes, yielding five promising novel UPPS inhibitors.

3D QSAR based Virtual Screening of Flavonoids as Acetylcholinesterase Inhibitors

In an attempt to develop therapeutic agents to treat Alzheimer's disease, a series of flavonoid analogues were collected, which already had established acetylcholinesterase (AChE) enzyme inhibition activity. For each molecule we also collected biological activity data (Ki). Then, 3D-QSAR (quantitative structure-activity relationship model) was developed which showed acceptable predictive and descriptive capability as represented by standard statistical parameters r2 and q2. This SAR data can explain the key descriptors which can be related to AChE inhibitory activity. Using the QSAR model, pharmacophores were developed based on which, virtual screening was done and a dataset was obtained which loaded as a prediction set to fit the developed QSAR model. Top 10 compounds fitting the QSAR model were subjected to molecular docking. CHEMBL1718051 was found to be the lead compound. This study is offering an example of a computationally-driven tool for prioritisation and discovery of probable AChE inhibitors. Further, in vivo and in vitro testing will show its therapeutic potential.

In silico investigation of the role of vitamins in cancer therapy through inhibition of MCM7 oncoprotein

An overabundance of MCM7 protein, a component of the minichromosome maintenance complex that normally initiates DNA replication, has been reported to cause different types of cancers with aggressive malignancy. Inhibition of MCM7 may lead to a significant reduction in cancer-associated cell proliferation. Despite such significance of MCM7 in cancer, the protein structure is yet to be resolved experimentally. This significantly halts the structure-guided ligand designing for cancer therapy targeting the MCM7. The present study aims to resolve the tertiary structure of MCM7 and repurpose the FDA-approved clinically used drugs for cancer therapy by targeting MCM7 protein. The secondary and 3D structures of MCM7 were generated using multiple bioinformatics tools, including the Self-Optimized Prediction Method with Alignment (SOPMA), SWISS-MODEL, and I-TASSER. The reliability of the modeled structure was assessed using PROCHECK. Initially, a structure-guided virtual screening was performed on the approved drug library to identify potential hits against MCM7. The detailed molecular mechanism of receptor interactions of the identified hits was evaluated using extensive molecular dynamics simulation. The results from this study reveal an intriguing discovery of the potential of ergocalciferol (vitamin D2), cholecalciferol (vitamin D3), ergosterol (precursor of vitamin D2) and menaquinone (vitamin K2) as oncoprotein inhibitors for cancer therapy via inhibition of MCM7.