THE USE OF COMPUTATION IN DRUG DISCOVERY AND DEVELOPMENT
Main Article Content
Keywords
Drug discovery, molecular modelling, chemoinformatics, and structure-activity connections are some of the topics that are covered in molecular docking
Abstract
Background: Drug development is a complex and expensive process involving multiple scientific disciplines. The integration of computational methods has become essential in this multifaceted endeavour.
Objective: To explore the contributions and challenges of computational methods in the drug development process and highlight the importance of teaching these methods in medicinal chemistry courses.
Methods: This study reviews the deployment of computational methodologies based on available system information and specific project objectives. It examines the contributions of these methods to data analysis, compound filtering for experimental screening, hypothesis generation for drug mechanisms, and the creation of new chemical structures. Additionally, the study discusses the impact of computational methods on currently used clinical medications.
Results: Computational methods have significantly improved efficient data analysis, facilitated the selection of molecules for experimental screening, generated hypotheses for understanding drug mechanisms, and aided in creating new chemical structures. These methods have also contributed substantially to the development of medications in clinical use. However, several challenges remain, including data quality, computational resource limitations, and methodological constraints.
Conclusion: Computational methods play a crucial role in drug development, enhancing efficiency and innovation. Addressing existing challenges will further refine these approaches and support the interdisciplinary efforts in medicinal chemistry education and drug production.
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