Theoretical studies on benzimidazole and imidazo[1,2-a]pyridine derivatives as Polo-like kinase 1 (Plk1) inhibitors: Pharmacophore modeling, atom-based 3D-QSAR and molecular docking approach

Anthelmintic activity of Calotropis gigantea: in silico investigation on novel target site nematode kinases

Over one billion peoples are currently infected with a parasitic nematode, particularly in tropical regions. Helminthiasis is a medical condition characterized by an infection of parasitic worms in the human body. Calotropis gigantea Linn. Belongs to the Asclepiadaceae family, commonly known as "Gaint milkweed" or "Crown flower" and recognized as a traditional medicinal plant. In this study, anthelminthic potential of Calotropis gigantea phytoconstituents were determined. Nematode kinases EGFR, MEK1, and PLK1 have diverged from their vertebrate counterparts in their drug-binding pockets. The development of novel anthelmintics targets Kinases that hold potential as targets. This pipeline revealed three potential anthelmintic targets that include epidermal growth factor tyrosine kinase transmembrane receptor [EGFR], the Mitogen-activate protein kinase [MEK1], and polo-like kinase [PLK1]. The software used in the in silico study investigation is the pyRx virtual screening tool, Biovia Discovery Studio, mol-inspiration, and RCSB [Protein Data Bank (PDB)]. The various phytoconstituents of Calotropis gigantea were docked Stigmasterol, beta-sitosterol, Desmosterol, alpha-amyrin, asclepin, and others showed high binding energies in EGFR, MEK1, and PLK1 receptors. This investigational study research highlights the potential of phytoconstituents from Calotropis gigantea as anthelmintic activity.

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QSAR study of tetrahydropteridin derivatives as polo-like kinase 1(PLK1) Inhibitors with molecular docking and dynamics study

PLK1 is the key target for dealing with different cancer because it plays an important role in cell proliferation. According to the regulation of OECD, a QSAR model was developed from a dataset of 68 tetrahydropteridin derivatives. Three descriptors (maxHaaCH, ATSC7i, AATS7m) were considered for the development of the QSAR model. The reliability and predictability of the developed QSAR model were evaluated by various statistical parameters (r² = 0.8213, r²_ext = 0.8771 and CCC_ext = 0.9364). The maxHaaCH descriptor is positively correlated to pIC₅₀ whereas, the ATSC7i and AATS7m are negatively correlated with pIC₅₀. The QSAR model explains all the structural features and shows a good correlation with the activity. Based on molecular modelling techniques, five compounds (D1-D5) were designed. Molecular docking and dynamics studies of the most active compound were performed with PDB ID: 2RKU. The results of the present investigation may be employed to identify and develop effective inhibitors for the treatment of PLK1-related pathophysiological disorders.

Virtual screening of natural compounds as selective inhibitors of polo-like kinase-1 at C-terminal polo box and N-terminal catalytic domain

The over-expression of Polo-like kinase-1 (PLK1) is associated with cancer prognosis due to its pivotal role in cell proliferation. The N-terminal catalytic domain (NCD) and C-terminal polo box domain (PBD) of PLK1 are critical for the activity of the protein. Drugs that inhibit PLK1 by targeting these domains are on clinical trials, but so far, none has been approved by FDA. Thus, this study targets the two domains of PLK1 to identify compounds with inhibitory potential. Four validated e-pharmacophore models from NCD (PDB ID: 2OU7 and 4J52) and PBD (PDB ID: 5NEI and 5NN2) were used to screen over 26,000 natural compounds from NPASS database. Hits were identified after the well-fitted compounds were subjected to molecular docking study and ADME prediction. The pIC50 and electronic behaviour of the identified hits selectively targeting NCD and PBD of PLK1 were predicted via an externally validated QSAR model and quantum mechanics. The results showed that CAA180504, CAA197326, CAA74619, CAA328856 modulating PLK1 at NCD, and CBB130581, CBB230713, CBB206123, CBB12656 and CBB267117 modulating PLK1 at PBD had better molecular docking scores, pharmacokinetics and drug-like properties than NCD (volasertib) and PBD (purpurogallin) reference inhibitors. The compounds all had satisfactory inhibitory (pIC50) values which range from 6.187 to 7.157. The electronic behaviours of understudied compounds using HOMO/LUMO and global descriptive parameters revealed the atomic portion of the compounds prone to donating and accepting electrons. In conclusion, the hit compounds identified from the library of natural compounds are worthy of further experimental validation.Communicated by Ramaswamy H. Sarma.

Computational identification of 2,4-disubstituted amino-pyrimidines as L858R/T790M-EGFR double mutant inhibitors using pharmacophore mapping, molecular docking, binding free energy calculation, DFT study and molecular dynamic simulation

Pharmacophore modelling studies have been performed for a series of 2,4-disubstituted-pyrimidines derivatives as EGFR L858R/T790M tyrosine kinase inhibitors. The high scoring AARR.15 hypothesis was selected as the best pharmacophore model with the highest survival score of 3.436 having two hydrogen bond acceptors and two aromatic ring features. Pharmacophore-based virtual screening followed by structure-based yielded the six molecules (ZINC17013227, ZINC17013215, ZINC9573324, ZINC9573445, ZINC24023331 and ZINC17013503) from the ZINC database with significant in silico predicted activity and strong binding affinity towords the EGFR L858R/T790M tyrosine kinase. In silico toxicity and cytochrome profiling indicates that all the 06 virtually screened compounds were substrate/inhibitors of the CYP-3A4 metabolizing enzyme and were non-carcinogenic and devoid of Ames mutagenesis. Density functional theory (DFT) and molecular dynamic (MD) simulation further validated the obtained hits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00113-x.

Recent Progress of Benzimidazole Hybrids for Anticancer Potential

This review presents the detailed account of factors leading to cancer and design strategy for the synthesis of benzimidazole derivatives as anticancer agents. The recent survey for cancer treatment in Cancer facts and figures 2017 American Chemical Society has shown progressive development in fighting cancer. Researchers all over the world in both developed and developing countries are in a continuous effort to tackle this serious concern. Benzimidazole and its derivatives showed a broad range of biological activities due to their resemblance with naturally occurring nitrogenous base i.e. purine. The review discussed benzimidazole derivatives showing anticancer properties through a different mechanism viz. intercalation, alkylating agents, topoisomerases, DHFR enzymes, and tubulin inhibitors. Benzimidazole derivatives act through a different mechanism and the substituents reported from the earlier and recent research articles are prerequisites for the synthesis of targeted based benzimidazole derivatives as anticancer agents. The review focuses on an easy comparison of the substituent essential for potency and selectivity through SAR presented in figures. This will further provide a better outlook or fulfills the challenges faced in the development of novel benzimidazole derivatives as anticancer.

Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r²_ncv) value of 0.974, leave one out (q²) value of 0.662 and predicted correlation coefficient (r²_pred) value of 0.560 was used for the analysis of QSAR. For the MDS study, A-chain of telomerase was stabilised for 50 ns with respect to 1-atm pressure, with an average temperature of 299.98 k and with potential energy of 1,145,336 kJ/m converged in 997 steps. Furthermore, the behaviour study of variants towards the target revealed that active variable gave better affinity without affecting amino acid sequences and dimensions of protein which was accomplished through RMSD, RMSF and Rg analysis. Results of molecular docking study supported the outcomes of QSAR contour maps as ligand showed similar interactions with surrounded amino acids which were identified in contour map analysis. The results of the comprehensive study might be proved valuable for the development of potent telomerase inhibitors.

Linear Regression QSAR Models for Polo-Like Kinase-1 Inhibitors

A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the ChEMBL database and studied by means of a conformation-independent quantitative structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. The structural descriptors are derived with different freeware, such as PaDEL, Mold², and QuBiLs-MAS; such descriptor software complements each other and improves the QSAR results. The best multivariable linear regression models are found with the replacement method variable subset selection technique. The balanced subsets method partitions the dataset into training, validation, and test sets. It is found that the proposed linear QSAR model improves previously reported models by leading to a simpler alternative structure-activity relationship.