Computational Drug Discovery: Modeling Drug- Target and Drug-Disease Interactions (en Inglés)
Reseña del libro "Computational Drug Discovery: Modeling Drug- Target and Drug-Disease Interactions (en Inglés)"
Computational Drug Discovery: Modeling Drug-Target and Drug-Disease Interactions presents a focused technical perspective on computational methods used to investigate relationships among therapeutic compounds, biological targets, and disease processes. The subject integrates concepts from drug discovery, computational chemistry, bioinformatics, molecular modeling, pharmacology, systems biology, and data-driven analysis. The book explores how computational models can represent and analyze drug-target interactions, examine drug-disease relationships, organize biological information, and support systematic investigation of molecular associations. Topics naturally associated with the subject include molecular interaction modeling, drug-target prediction, drug-disease association analysis, virtual screening, molecular descriptors, biological networks, computational pharmacology, and bioinformatics-based drug discovery. By connecting chemical, biological, and computational perspectives, the book provides a foundation for understanding the role of computational analysis within the broader drug discovery process. It is relevant to readers working in pharmaceutical sciences, medicinal chemistry, computational biology, bioinformatics, pharmacology, biotechnology, and biomedical research. The material can support postgraduate learners, researchers, scientists, and technical professionals seeking a clear introduction to computational approaches for analyzing drug-related interactions. The book also emphasizes the interdisciplinary character of computational drug discovery, where molecular data, biological relationships, mathematical representations, and analytical techniques can be examined together. This perspective is useful for understanding how computational approaches help structure complex information and investigate relationships between compounds, targets, and diseases.