This article provides a comprehensive introduction to pharmacophore-based virtual screening (PBVS), a powerful computational method that significantly accelerates drug discovery by identifying potential therapeutic candidates from large chemical databases.
This article provides a comprehensive examination of pharmacophore modeling's pivotal role in computer-aided drug design, addressing the needs of researchers and drug development professionals.
This article provides a comprehensive exploration of the pharmacophore concept, anchored by the official IUPAC definition as 'the ensemble of steric and electronic features' necessary for biological recognition and response.
This article explores the development and optimization of target-specific scoring functions (TSSFs) to overcome the limitations of generic scoring functions in structure-based virtual screening for cancer therapeutics.
This article synthesizes current advancements in predicting antimicrobial and antitubercular drug resistance mutations, targeting researchers and drug development professionals.
This article provides a comprehensive analysis of benchmarking virtual screening (VS) performance across the major molecular subtypes of breast cancer—Luminal, HER2-positive, and Triple-Negative Breast Cancer (TNBC).
Tumor heterogeneity presents a fundamental challenge in oncology drug discovery, often leading to drug resistance and therapeutic failure.
This article provides a comprehensive overview of modern de novo drug design methods and their transformative application in oncology.
This article provides a comprehensive overview of pharmacophore modeling applications in oncology drug discovery, tailored for researchers and drug development professionals.
This article provides a comprehensive overview of structure-based virtual screening (SBVS) applications in developing novel therapeutics for HER2-positive breast cancer.