Screening of natural product libraries in MCF7 cell line reveals the pro-apoptotic properties of β tetralone.

Despite the exponential increase in research toward better treatment options for breast cancer patients, developing an effective drug with fewer side effects continues to remain a challenge. Natural compounds have emerged as a viable option and several drugs have been derived or inspired from them. In this study, we screened a library of natural compounds with diverse chemical structures against selected kinase proteins using methods such as molecular docking and dynamics simulation.

Targeted Screening for Gaucher Disease in High Suspicion Patients and Clinical Profile of Screen Positives in a Large Pediatric Multispecialty Hospital.

Objectives:  The proposed screening study was aimed at determining the prevalence of Gaucher disease in a selected high-risk population of patients and describing the clinical profile of diagnosed patients.

Methodology: It was a prospective observational study from January 2020 to September 2022 (two years and eight months) in the genetic clinic of the pediatric department. A total of 22 patients were suspected to be having Gaucher disease based on clinical findings of hepatosplenomegaly with bicytopenia or isolated thrombocytopenia.

Comprehensive molecular docking and dynamic simulations for drug repurposing of clinical drugs against multiple cancer kinase targets.

Drug repurposing is a method to identify novel therapeutic agents from the existing drugs and clinical compounds. In the present comprehensive work, molecular docking, virtual screening and dynamics simulations were carried out for ten cancer types viz breast, colon, central nervous system, leukaemia, melanoma, ovarian, prostate, renal and lung (non-small and small cell) against validated eighteen kinase targets. The study aims to understand the action of chemotherapy drugs mechanism through binding interactions against selected targets via comparative docking simulations with the state-art molecular modelling suits such as MOE, Cresset-Flare, AutoDock Vina, GOLD and GLIDE.

A Review on Computational Analysis of Big Data in Breast Cancer for Predicting Potential Biomarkers.

Breast cancer is the most predominantly occurring cancer in the world. Several genes and proteins have been recently studied to predict biomarkers that enable early disease identification and monitor its recurrence. In the era of high-throughput technology, studies show several applications of big data for identifying potential biomarkers.