Abstract
Software has become an indispensable driving force in Computer-Aided
Drug Discovery (CADD), facilitating target identification, molecular modeling, and
virtual screening. Through bioinformatics and computational biology, software aids in
the efficient identification of drug targets. Molecular modeling software empowers
rational drug design by predicting molecular interactions and structures. Virtual
screening software accelerates hit-to-lead optimization, efficiently sifting through
chemical libraries. Machine learning algorithms and big data analytics enhance
predictive modeling and biomarker discovery, enabling personalized medicine.
Collaborative platforms and cloud-based solutions foster interdisciplinary
collaboration, streamlining the drug discovery process. Software in CADD reduces
costs, shortens development timelines, and fuels innovation, offering unprecedented
possibilities for novel therapeutics and improved healthcare outcomes.