Exploring Potential Non-steroidal Aromatase Inhibitors for Therapeutic Application against Estrogen-dependent Breast Cancer.

BACKGROUND: Breast cancer is one of the most commonly diagnosed cancer types among women worldwide. Cytochrome P450 aromatase (CYP19A1) is an enzyme in vertebrates that selectively catalyzes the biosynthesis of estrogens from androgenic precursors. Researchers have increasingly focused on developing non-steroidal aromatase inhibitors (NSAIs) for their potential clinical use, avoiding steroidal side effects. OBJECTIVES: The objective of the present work is to search for potential lead compounds from the ZINC database through various in silico approaches. METHODS: In the present study, compounds from the ZINC database were initially screened through receptor independent-based pharmacophore virtual screening. These screened molecules were subjected to several assessments, such as Lipinski rule of 5, SMART filtration, ADME prediction using SwissADME and lead optimization. Molecular docking was further applied to study the interaction of the filtered compounds with the active site of aromatase. Finally, the obtained hit compounds, consequently represented to be ideal lead candidates, were escalated to the MD simulations. RESULTS: The results indicated that the lead compounds might be potential anti-aromatase drug candidate. CONCLUSION: The findings provided a valuable approach in developing novel anti-aromatase inhibitors for the treatment of ER+ breast cancer.

An in silico scientific basis for LL-37 as a therapeutic for Covid-19.

A multi-pronged approach with help in all forms possible is essential to completely overcome the Covid-19 pandemic. There is a requirement to research as many new and different types of approaches as possible to cater to the entire world population, complementing the vaccines with promising results. The need is also because SARS-CoV-2 has several unknown or variable facets which get revealed from time to time. In this work, in silico scientific findings are presented, which are indicative of the potential for the use of the LL-37 human anti-microbial peptide as a therapeutic against SARS-CoV-2. This indication is based on the high structural similarity of LL-37 to the N-terminal helix, with which the virus interacts, of the receptor for SARS-CoV-2, Angiotensin Converting Enzyme 2. Moreover, there is positive prediction of binding of LL-37 to the receptor-binding domain of SARS-CoV-2; this is the first study to have described this interaction. In silico data on the safety of LL-37 are also reported. As Vitamin D is known to upregulate the expression of LL-37, the vitamin is a candidate preventive molecule. This work provides the possible basis for an inverse correlation between Vitamin D levels in the body and the severity of or susceptibility to Covid-19, as widely reported in literature. With the scientific link put forth herein, Vitamin D could be used at an effective, medically prescribed, safe dose as a preventive. The information in this report would be valuable in bolstering the worldwide efforts to eliminate the pandemic as early as possible.

Mutational analysis in international isolates and drug repurposing against SARS-CoV-2 spike protein: molecular docking and simulation approach.

The novel SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) is spreading, as the causative pathogen of coronavirus disease-19 (COVID-19). It has infected more than 1.65 billion people all over the world since it was discovered and reported 3.43 million deaths by mid of May 2021. SARS-CoV-2 enters the host cell by binding to viral surface glycoprotein (S protein) with human ACE2 (angiotensin-converting enzyme2). Spike protein (contains S1 and S2 sub-domains) molecular interaction with the host cells is considered as a major step in the viral entry and disease initiation and progression and this identifies spike protein as a promising therapeutic target against antiviral drugs. Currently, there are no efficient antiviral drugs for the prevention of COVID-19 infection. In this study, we have analyzed global 8719 spike protein sequences from patients infected with SAR-CoV-2. These SAR-CoV-2 genome sequences were downloaded from the GISAID database. By using an open reading frame (ORF) tool we have identified the spike protein sequence. With these, all spike protein amino acid sequences are subjected to multiple sequence alignment (MSA) with Wuhan strain spike protein sequence as a query sequence, and it shows all SAR-CoV strain spike proteins are 99.8% identical. In the mutational analysis, we found 639 mutations in the spike protein sequence of SARS-CoV-2 and identified/highlighted 20 common mutations L5F, T22I, T29I, H49Y, L54F, V90F, S98F, S221L, S254F, V367F, A520S, T572I, D614G, H655Y, P809S, A879S, D936Y, A1020S, A1078S, and H1101Y. Further, we have analyzed the crystal structure of the 2019-nCoV chimeric receptor-binding complex with ACE2 (PDB ID: 6VW1) as a major target protein. The spike receptor binding protein (RBD) used as target region for our studies with FDA-approved drugs for repurposing, and identified few anti-SARS-CoV2 potential drugs (Silmitasertib, AC-55541, Merimepodib, XL413, AZ3451) based on their docking score and binding mode calculations expected to strongly bind to motifs of ACE2 receptor and may show impart relief in COVID-19 patients.

Molecular profiling of multidrug-resistant river water isolates: insights into resistance mechanism and potential inhibitors.

Polluted waters are an important reservoir for antibiotic resistance genes and multidrug-resistant bacteria. This report describes the microbial community, antibiotic resistance genes, and the genetic profile of extended spectrum ß-lactamase strains isolated from rivers at, Pune, India. ESBL-producing bacteria isolated from diverse river water catchments running through Pune City were characterized for their antibiotic resistance. The microbial community and types of genes which confer antibiotic resistance were identified followed by the isolation of antibiotic-resistant bacteria on selective media and their genome analysis. Four representative isolates were sequenced using next generation sequencing for genomic analysis. They were identified as Pseudomonas aeruginosa, Escherichia coli, and two isolates were Enterobacter cloacae. The genes associated with the multidrug efflux pumps, such as tolC, macA, macB, adeL, and rosB, were detected in the isolates. As MacAB-TolC is an ABC type efflux pump responsible for conferring resistance in bacteria to several antibiotics, potential efflux pump inhibitors were identified by molecular docking. The homology model of their MacB protein with that from Escherichia coli K12 demonstrated structural changes in different motifs of MacB. Molecular docking of reported efflux pump inhibitors revealed the highest binding affinity of compound MC207-110 against MacB. It also details the potential efflux pump inhibitors that can serve as possible drug targets in drug development and discovery.