In Silico Exploration of Novel EGFR Kinase Mutant-Selective Inhibitors Using a Hybrid Computational Approach.

Targeting epidermal growth factor receptor (EGFR) mutants is a promising strategy for treating non-small cell lung cancer (NSCLC). This study focused on the computational identification and characterization of potential EGFR mutant-selective inhibitors using pharmacophore design and validation by deep learning, virtual screening, ADMET (Absorption, distribution, metabolism, excretion and toxicity), and molecular docking-dynamics simulations. A pharmacophore model was generated using Pharmit based on the potent inhibitor JBJ-125, which targets the mutant EGFR (PDB 5D41) and is used for the virtual screening of the Zinc database.

Spectrum of Disease and Prescription Pattern for Outpatients with Neurological Disorders: An Empirical Pilot Study in Bangladesh.

Background: Neurological disorders represent one of the most prominent causes of morbidity and mortality that adversely affect the lifestyle of patients and a major percentage of these diseases exists in developing countries.

Purpose: The objective of this study was to examine the prevalence and prescription pattern for outpatients with neurological disorders in Bangladesh.

Methods: The study was conducted on 1,684 patients in 6 hospitals (National Institute of Neurosciences and Hospital, Dhaka Medical College and Hospital, Bangabandhu Sheikh Mujib Medical University, Shaheed Suhrawardy Medical College, Sir Salimullah Medical College, and Apollo Hospitals Dhaka) of the Dhaka City from March 2014 to June 2015.