This article provides a comprehensive guide for computational chemists and drug development professionals on optimizing Comparative Molecular Similarity Indices Analysis (CoMSIA) field combinations to enhance model performance.
Activity cliffs (ACs), where minute structural modifications cause drastic potency shifts, represent a significant source of prediction error and a central challenge for 3D-QSAR modeling in drug discovery.
Overfitting presents a significant challenge in 3D-QSAR modeling, often leading to non-predictive models and failed optimizations in anticancer drug discovery.
This article provides a comprehensive guide for researchers and drug development professionals on optimizing Partial Least Squares (PLS) components to enhance the predictive power and reliability of 3D-QSAR models.
Activity cliffs (ACs), where minute structural modifications cause drastic potency shifts, represent a critical source of prediction error in quantitative structure-activity relationship (QSAR) modeling, often leading to failures in lead...
This article provides a comprehensive exploration of virtual screening utilizing 3D-QSAR models for the discovery of glioblastoma therapeutics.
This article provides a detailed computational protocol for applying Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) to design and optimize pteridinone-based Polo-like kinase 1 (PLK1)...
This article provides a comprehensive guide to the foundational principles and advanced applications of Three-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) modeling in the discovery and optimization of natural product-based anticancer compounds.
This article provides a comprehensive guide for researchers and drug development professionals on implementing field-based 3D-QSAR to accelerate the discovery of novel tumor inhibitors.
This comprehensive review elucidates the critical role of molecular descriptors in Quantitative Structure-Activity Relationship (QSAR) studies for anticancer drug development.