Systemic computational investigation to identify potential inhibitors against cancer by targeting P21-activated kinase 4 and D(CGATCG)

Cancer accounts for more than 10 million deaths in the year 2020. Development of drugs that specifically target cancer signaling pathways and proteins attain significant importance in the recent past. The p21-activated kinase 4 enzyme, which plays diverse functions in cancer and is reported in elevated expression makes this enzyme an attractive anti-cancer drug target. Similarly, cancer cells' DNA could also serve as a good platform for anti-cancer drug development. Herein, a robust in silico framework is designed to virtually screen multiple drug libraries from diverse sources to identify potential binders of the mentioned cancer targets. The virtual screening process identified three compounds (BAS_01059603, ASN_10027856, and ASN_06916672) as best docked molecules with a binding energy score of ≤ -10 kcal/mol for p21-activated kinase 4 and ≤ -6 kcal/mol for D(CGATCG). In the docking analysis, the filtered compounds revealed stable binding to the same site to which controls bind in X-ray structures. The binding interactions of the compounds with receptors are dominated by van der Waals interactions. The average root mean square deviation (rmsd) value for p21-activated kinase 4 systems is noticed at ∼2 Å, while for D(CGATCG), the average rmsd is 2.7 Å. The MMGB/PBSA interpreted ASN_12674021 to show strong intermolecular binding energy compared to the other two systems and control in both receptors. Moreover, the entropy energy contribution is less than the mean binding energy. In short, the compounds are showing promising binding to the biomolecules and therefore must be evaluated for anti-cancer activity in experimental studies.Communicated by Ramaswamy H. Sarma.

Expression and genetic polymorphism of Foxp3 gene and its association to breast cancer susceptibility

Introduction and Aim: Breast cancer is responsible for more deaths in women than all other types of cancer combined, and it is also responsible for thirty percent of all new cancer diagnoses. FOXP3 is the key transcription factor necessary for the development of regulatory T cells (Treg), and it functions as a selection marker for regulatory T cells. The purpose of this study was to establish a correlation between genetic polymorphism and the degree to which breast cancer genes are expressed in the patients who participated in the study.   Materials and Methods: This study included 40 breast cancer patients who had been histologically and clinically verified to have the disease, as well as 40 healthy subjects. Blood drawn from each participant was subjected to RNA extraction. The extracted RNA was converted to its cDNA and SNP rs3761547 genotyped. RT-PCR was used to estimate the Foxp3gene expression levels in all samples.   Results: The discrepancy between the TT genotype in the control group and the patients (40% vs 12.5%, respectively) was accompanied by a low odd ratio that was statistically significant (Odds=0.21, under p-value = 0.01). Additionally, the TC genotype was more prevalent in the control group (37.5% vs 10%, respectively) than in the patient group, with a significant Odds ratio (Odds=0.19, p-value=0.008). On the other hand, the CC genotype was significantly more common in patients (77.5% vs 22.5%, respectively) than in controls (Odds=11.86). Foxp3 gene expression was significantly greater in patients (7.098) compared to the control (1.375) under level (P-value=0.001).   Conclusion: There is a possibility that breast cancer is associated with variants in the SNP rs3761547, which would result in an elevated level of Foxp3 gene expression.

Molecular Insights into Binding Mode and Interactions of Structure-Based Virtually Screened Inhibitors for Pseudomonas aeruginosa Multiple Virulence Factor Regulator (MvfR)

Multi-drug resistance (MDR) bacterial pathogens pose a threat to global health and warrant the discovery of new therapeutic molecules, particularly those that can neutralize their virulence and stop the evolution of new resistant mechanisms. The superbug nosocomial pathogen, Pseudomonas aeruginosa, uses a multiple virulence factor regulator (MvfR) to regulate the expression of multiple virulence proteins during acute and persistent infections. The present study targeted MvfR with the intention of designing novel anti-virulent compounds, which will function in two ways: first, they will block the virulence and pathogenesis P. aeruginosa by disrupting the quorum-sensing network of the bacteria, and second, they will stop the evolution of new resistant mechanisms. A structure-based virtual screening (SBVS) method was used to screen druglike compounds from the Asinex antibacterial library (~5968 molecules) and the comprehensive marine natural products database (CMNPD) (~32 thousand compounds), against the ligand-binding domain (LBD) of MvfR, to identify molecules that show high binding potential for the relevant pocket. In this way, two compounds were identified: Top-1 (4-((carbamoyloxy)methyl)-10,10-dihydroxy-2,6-diiminiodecahydropyrrolo[1,2-c]purin-9-yl sulfate) and Top-2 (10,10-dihydroxy-2,6-diiminio-4-(((sulfonatocarbamoyl)oxy)methyl)decahydropyrrolo[1,2-c]purin-9-yl sulfate), in contrast to the co-crystallized M64 control. Both of the screened leads were found to show deep pocket binding and interactions with several key residues through a network of hydrophobic and hydrophilic interactions. The docking results were validated by a long run of 200 ns of molecular dynamics simulation and MM-PB/GBSA binding free energies. All of these analyses confirmed the presence of strong complex formation and rigorous intermolecular interactions. An additional analysis of normal mode entropy and a WaterSwap assay were also performed to complement the aforementioned studies. Lastly, the compounds were found to show an acceptable range of pharmacokinetic properties, making both compounds potential candidates for further experimental studies to decipher their real biological potency.