In Silico Identification of Promising New Pyrazole Derivative-Based Small Molecules for Modulating CRMP2, C-RAF, CYP17, VEGFR, C-KIT, and HDAC-Application towards Cancer Therapeutics.

Despite continual efforts being made with multiple clinical studies and deploying cutting-edge diagnostic tools and technologies, the discovery of new cancer therapies remains of severe worldwide concern. Multiple drug resistance has also emerged in several cancer cell types, leaving them unresponsive to the many cancer treatments. Such a condition always prompts the development of next-generation cancer therapies that have a better chance of inhibiting selective target macromolecules with less toxicity. Therefore, in the present study, extensive computational approaches were implemented combining molecular docking and dynamic simulation studies for identifying potent pyrazole-based inhibitors or modulators for CRMP2, C-RAF, CYP17, c-KIT, VEGFR, and HDAC proteins. All of these proteins are in some way linked to the development of numerous forms of cancer, including breast, liver, prostate, kidney, and stomach cancers. In order to identify potential compounds, 63 in-house synthesized pyrazole-derivative compounds were docked with each selected protein. In addition, single or multiple standard drug compounds of each protein were also considered for docking analyses and their results used for comparison purposes. Afterward, based on the binding affinity and interaction profile of pyrazole compounds of each protein, potentially strong compounds were filtered out and further subjected to 1000 ns MD simulation analyses. Analyzing parameters such as RMSD, RMSF, RoG and protein-ligand contact maps were derived from trajectories of simulated protein-ligand complexes. All these parameters turned out to be satisfactory and within the acceptable range to support the structural integrity and interaction stability of the protein-ligand complexes in dynamic state. Comprehensive computational analyses suggested that a few identified pyrazole compounds, such as M33, M36, M72, and M76, could be potential inhibitors or modulators for HDAC, C-RAF, CYP72 and VEGFR proteins, respectively. Another pyrazole compound, M74, turned out to be a very promising dual inhibitor/modulator for CRMP2 and c-KIT proteins. However, more extensive study may be required for further optimization of the selected chemical framework of pyrazole derivatives to yield improved inhibitory activity against each studied protein receptor.

Overview of recent developments of pyrazole derivatives as an anticancer agent in different cell line.

Pyrazole is a five-membered aromatic heterocyclic ring with two adjacent nitrogen atoms C3H3N2H.The presence of this nucleus in pharmacological agents of various therapeutic categories gifts a broad spectrum of biological activities and pharmaceuticals that contain pyrazole like celecoxib (anti-inflammatory), CDPPB (antipsychotic), Rimonabant (anti-obesity), Difenamizole, (Analgesic), Betazole (H2 receptor agonist), Fezolamide (Antidepressant), etc… The pharmacological potential of the pyrazole fraction is proved in many publication where they synthesized and evaluated pyrazoles against several biological agents. The aim of this article review is to survey recent works linking pyrazole structures to anticancer activities corresponding to 9 different type of cancer.

Targeting EGFR, RSK1, RAF1, PARP2 and LIN28B for several cancer type therapies with newly synthesized pyrazole derivatives via a computational study.

Cancer remains the leading cause of death in the world despite the significant advancements made in anticancer drug discovery. This study is aimed to computationally evaluate the efficacy of 63 in-house synthesized pyrazole derivatives targeted to bind with prominent cancer targets namely EGFR, RSK1, RAF1, PARP2 and LIN28B known to be expressed, respectively, in lung, colon, skin, ovarian and pancreatic cancer cells. Initially, we perform the molecular docking investigations for all pyrazole compounds with a comparison to known standard drugs for each target. Docking studies have revealed that some pyrazole compounds possess better binding affinity scores than standard drug compounds. Thereafter, a long-range of 1 µs molecular dynamic (MD) simulation study for top ranked docked compounds with all respective proteins was carried out to assess the interaction stability in a dynamic environment. The results suggested that the top ranked complexes showed a stable interaction profile for a longer period of time. The outcome of this study suggests that pyrazole compounds, M33, M36, M76 and M77, are promising molecular candidates that can modulate the studied target proteins significantly in comparison to their known inhibitor based on their selective binding interactions profile. Furthermore, ADME-T profile has been explored to check for the drug-likeness and pharmacokinetics profiles and found that all proposed compounds exhibited acceptable values for being a potential drug-like candidate with non-toxic characteristics. Overall, extensive computational investigations indicate that the four proposed pyrazole inhibitors/modulators studied against each respective target protein will be helpful for future cancer therapeutic developments.Communicated by Ramaswamy H. Sarma.

Design and prediction of novel pyrazole derivatives as potential anti-cancer compounds based on 2D-2D-QSAR study against PC-3, B16F10, K562, MDA-MB-231, A2780, ACHN and NUGC cancer cell lines.

Despite the decades of scientific studies for developing promising new therapies, cancer remains a major cause of illness and mortality, worldwide. Several cancer types are the major topic of research in drug discovery programs due to their global incidence cases and growing frequency. In the present study, using two different statistical approaches PCA (principal component analysis) and PLS (partial least squares), six 2D-QSAR (quantitative structure activity relationship) models have been developed for the set of compounds retrieved against seven cancer cell lines vizPC-3, B16F10, K562, MDA-MB-231, A2780, and ACHN. For the creation and validation of 2D-QSAR models, OECD (Organization for Economic Co-operation and Development) requirements have been strictly followed. All of the generated 2D-QSAR models produce a significant and high correlation coefficient value with several other statistical parameters. Moreover, developed 2D-QSAR models have been used for activity predictions of in-house synthesized 63 pyrazole derivatives compounds. Precisely, most statistically significant and accepted2D-QSAR model generated for each cancer cell line has been used to predict the pIC50 value (anti-cancer activity) of all 63 synthesized pyrazole derivatives. Furthermore, designing of novel pyrazole derivatives has been carried out by substituting the essential functional groups based on the best derived 2D-QSAR models for each cancer cell line, more precisely, based on the most significant molecular descriptors with enhanced anti-cancer activity. Finally, the prediction of the new designed molecules reveals higher pIC50 than the standard compounds.

Identification of New Drug Target in Staphylococcus lugdunensis by Subtractive Genomics Analysis and Their Inhibitors through Molecular Docking and Molecular Dynamic Simulation Studies.

Staphylococcus lugdunensis is a coagulase-negative, Gram-positive, and human pathogenic bacteria. S. lugdunensis is the causative agent of diseases, such as native and prosthetic valve endocarditis, meningitis, septic arthritis, skin abscesses, brain abscess, breast abscesses, spondylodiscitis, post-surgical wound infections, bacteremia, and peritonitis. S. lugdunensis displays resistance to beta-lactam antibiotics due to the production of beta-lactamases. This study aimed to identify potential novel essential, human non-homologous, and non-gut flora drug targets in the S. lugdunensis strain N920143, and to evaluate the potential inhibitors of drug targets. The method was concerned with a homology search between the host and the pathogen proteome. Various tools, including the DEG (database of essential genes) for the essentiality of proteins, the KEGG for pathways analysis, CELLO V.2.5 for cellular localization prediction, and the drug bank database for predicting the druggability potential of proteins, were used. Furthermore, a similarity search with gut flora proteins was performed. A DNA-binding response-regulator protein was identified as a novel drug target against the N920143 strain of S. lugdunensis. The three-dimensional structure of the drug target was modelled and validated with the help of online tools. Furthermore, ten thousand drug-like compounds were retrieved from the ZINC15 database. The molecular docking approach for the DNA-binding response-regulator protein identified ZINC000020192004 and ZINC000020530348 as the most favorable compounds to interact with the active site residues of the drug target. These two compounds were subjected to an MD simulation study. Our analysis revealed that the identified compounds revealed more stable behavior when bound to the drug target DNA-binding response-regulator protein than the apostate.