Cervical cancer (CC) is a global threat to women and our knowledge is frighteningly little about its underlying genomic contributors. Our research aimed to understand the underlying molecular and genetic mechanisms of CC by integrating bioinformatics and network-based study. Transcriptomic analyses of three microarray datasets identified 218 common differentially expressed genes (DEGs) within control samples and CC specimens. KEGG pathway analysis revealed pathways in cell cycle, drug metabolism, DNA replication and the significant GO terms were cornification, proteolysis, cell division and DNA replication. Protein-protein interaction (PPI) network analysis identified 20 hub genes and survival analyses validated CDC45, MCM2, PCNA and TOP2A as CC biomarkers. Subsequently, 10 transcriptional factors (TFs) and 10 post-transcriptional regulators were detected through TFs-DEGs and miRNAs-DEGs regulatory network assessment. Finally, the CC biomarkers were subjected to a drug-gene relationship analysis to find the best target inhibitors. Standard cheminformatics method including in silico ADMET and molecular docking study substantiated PD0325901 and Selumetinib as the most potent candidate-drug for CC treatment. Overall, this meticulous study holds promises for further in vitro and in vivo research on CC diagnosis, prognosis and therapies.Communicated by Ramaswamy H. Sarma.

The Bromodomain (BRD4) and extra-terminal (BET) protein family are reversible; lysine-acetylated epigenetic readers identified as key important epigenetic regulators for protein recognition in posttranslational modifications for targeting cancer for its role in super-enhancers and transcription of oncogene expression in cancer and other forms of cancer and various diseases. Firstly, JQ-1a small potent BET inhibitors, targeting BET proteins were currently in clinical trials to ablate cancer. The identified compounds were taken from the library of preexisting therapeutically potent molecules. The objective of the present study is to identify the potential small molecule inhibitors against BRD4 through in-silico approach for the treatment of cancer. In present study, designed an in-silico screening of small molecules through ligand-based pharmacophore studies against bromodomain-containing protein 4 (BRD-4) protein and used for virtual screening through Database and their binding affinity and interaction of identified molecules were predicted through molecular docking, molecular dynamics simulations for 12 fixed time period, Molecular mechanics (MMGBSA) binding free energy calculations, ADME with drug-likeness properties including violations of lipinski's rule of 5, Jorgensens rule of 3 and other parameters were studied. The docking results indicate from the reported database screened molecules were validated with docking score -7.92 to -4.27Kcal/mol for BRD4-BD1 and the best model identified 21 hits. Among these two drugs were filtered and scrutinized for their ability based on binding modes and common interaction, MMGBSA of the highest affinity -54.53 Kcal/mol of BRD4-BD1 and ADME properties of selected molecules were predicted for its various parameters, dynamics studies evaluating its binding stability using Maestro software. In Conclusion, two BRD4 inhibitors were found to bind strongly in the similar binding sites as JQ-1, highlighting the role of BRD4-BD1. These compounds were identified as promising new options for regulating epigenetics and understanding the structural needs of BRD4 protein, further research in these areas could lead to the development of more effective and targeted cancer drugs.Communicated by Ramaswamy H. Sarma.

Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancers. In spite of great advances, treatment of the disease is a medical challenge. Epidermal-growth factor receptor (EGFR) has been taken as a promising cell surface target to develop anti-NSCLC therapies. The main bottleneck to attain clinical efficacy with current EGFR tyrosine kinase inhibitors (EGFR-TKIs) is the rapid spread of oncogenic mutations. Numerous efforts have been made for the synthesis of diverse EGFR-TKIs against resistance-conferring mutations. One of the best strategies to design potent agents would be to explore existing anti-NSCLC drugs at the nonclinical development stage and prioritize privileged structural patterns. Within current study, conformational stability of clinically frequent EGFR mutants (G719S, T790M, L858R and a double mutant form L858R/T790M) were validated via DynaMut and missense3D computational servers. Subsequently, structure activity relationship (SAR) and scaffold similarity inquiry were used to rationally propose a few erlotinib analogues. Intended molecules were subjected to molecular docking and top-scored binders were further analyzed through 50-ns all atom molecular dynamics (MD) simulations to infer the dynamic behavior. The aim was to offer potential binders to overwhelm clinically frequent EGFR-TK mutants. The linear interaction energy (LIE) method was applied to compute the binding free energies between EGFR and intended ligands. For this purpose, MD-based conformational sampling of ligand-enzyme complexes and ligand-water associations were used to acquire thermodynamic energy averages. Though mechanistic details are to be explored, results of the current study identify synthetically accessible quinazoline small molecules with potential affinity toward frequent EGFR-TK mutants.Communicated by Ramaswamy H. Sarma.