Research Articles
Building a Modern High-Throughput Pharmacophore Screening Pipeline: From AI-Driven Foundations to Clinical Hit Validation
This article provides a comprehensive guide for researchers and drug development professionals on constructing and implementing a high-throughput pharmacophore virtual screening pipeline.
Ligand-Based Pharmacophore Modeling with LigandScout: A Comprehensive Workflow for Drug Discovery
This article provides a comprehensive guide to ligand-based pharmacophore modeling using LigandScout, tailored for researchers and drug development professionals.
Pharmacophore-Based Virtual Screening: A Comprehensive Workflow Guide for Modern Drug Discovery
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.
Pharmacophore Modeling in Modern Drug Discovery: A Comprehensive Guide to Methods, Applications, and AI-Driven Advances
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.
Pharmacophore Essentials: Mastering the IUPAC Definition and Applications in Drug Discovery
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.
Target-Specific Scoring Functions: A New Paradigm for Accelerating Cancer Drug Discovery
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.
Advancing Drug Resistance Prediction: Machine Learning and Genomic Approaches for Improved Accuracy
This article synthesizes current advancements in predicting antimicrobial and antitubercular drug resistance mutations, targeting researchers and drug development professionals.
Benchmarking Virtual Screening for Breast Cancer Subtypes: Methods, Challenges, and AI-Driven Advances
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).
Conquering Tumor Heterogeneity: AI and Multi-Omics Strategies in Computer-Aided Drug Design
Tumor heterogeneity presents a fundamental challenge in oncology drug discovery, often leading to drug resistance and therapeutic failure.
De Novo Drug Design for Oncology: AI-Driven Methods for Novel Cancer Therapeutics
This article provides a comprehensive overview of modern de novo drug design methods and their transformative application in oncology.