Computational Approaches to Molecular Dynamics Simulation for Drug Design and Discovery

Since they offer profound insights into the atomic-level interactions between drug candidates and their biological targets, molecular dynamics (MD) simulations have become extremely effective computational tools for drug design and discovery. MD simulations allow for the estimation of binding affinities, conformational modifications, and the investigation of possible binding sites by simulating the dynamic behaviour of biomolecules over time. These simulations now run much faster and are more accurate thanks to recent improvements in computing power, improved algorithms, and machine learning incorporation. Methods like adaptive sampling and accelerated MD further maximise resource utilisation, making it easier to simulate intricate biological processes in realistic timescales. Furthermore, opportunities for accurate electronic structure analysis have been created by combining MD with quantum mechanical techniques. This presentation highlights how computational methods in MD simulations for drug design can revolutionise the process by supplying crucial information for structure-based drug discovery and promoting the creation of new therapeutic agents with improved efficacy and selectivity.