Drug development is a critical endeavor within the pharmaceutical sector.
Integrating computational approaches has significantly reduced both the time and costs
associated with discovering new drugs. This chapter starts by highlighting the pivotal
role of multiscale molecular simulations in determining drug-binding sites on target
macromolecules and elucidating the mechanisms underlying drug actions. It then
delves into molecular dynamics (MD) simulation methods, focusing on drug design
strategies based on structure and ligand considerations. Additionally, the chapter
explores the development of advanced analysis tools and the integration of machine
learning techniques, which collectively enhance the efficiency of the drug discovery
process. Traditional MD analysis methods, such as root mean square deviation
(RMSD) of backbone atoms, root mean square fluctuation (RMSF), radius of gyration,
and interaction analyses, are extensively used to monitor structural changes and
convergence during simulations. Beyond these, newer trajectory mapping methods
offer intuitive and conclusive ways to visualize protein simulations by plotting the
protein's backbone movements as heat maps. Molecular dynamics simulations utilize
physical algorithms to model chemical systems and compute atomic and molecular
properties. In drug design and discovery, computational chemistry methods are
employed to predict mechanisms such as drug binding to targets and the chemical
properties of potential drug candidates. The combined use of traditional and novel
analysis methods is anticipated to have wide applications in deriving meaningful
insights from protein MD simulations across fields like structural biology,
biochemistry, and pharmaceutical research. The chapter concludes with several case
studies and success stories demonstrating the application of MD simulations as a
powerful computer-aided drug discovery tool in diabetes and Alzheimer's treatments.Highlighted examples include achievements in anticancer, antibacterial, antileishmaniasis, and antiviral drug design, showcasing the impact of in silico drug design
in developing innovative therapies.
Keywords: Alzheimer's disease , Anticancer, Antimicrobial, Drug discovery, In silico drug design, MD simulations.
