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Accelerated simulations and computer-aided drug design of nucleic acids and proteins
Akhter, Sana
Akhter, Sana
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Abstract
Over the last few decades, there has been a surge in developing small-molecule therapeutics for human pathologies. Although the dynamics and mechanisms of small molecule binding to various targets remain largely unknown, their low molecular weight and easy penetration in the cell have made them favorable for use by pharmaceuticals. This interaction varies enormously depending on the type of target, namely proteins or nucleic acids, their location inside the cell, and the host physiology. Over many decades, proteins have been repeatedly illustrated as a viable target for many FDA-approved drugs. Further, many available structural and functional data make proteins well-characterized therapeutic targets for drug discovery. For RNA, the negatively charged backbone, solvent-exposed binding pocket, and sizeable conformational flexibility of the backbone continue to pose a challenge for therapeutic design. Nonetheless, there is increasing interest in the area owing to its crucial role in controlling gene expression, cellular processes, various genetic pathologies, and cancer. Computer-aided drug Design has proven helpful in leveraging the existing information about the ligands and targets to identify and optimize the development of new drugs with significantly reduced cost. Molecular dynamics (MD) is a powerful computational technique for simulating biomolecular dynamics at an atomistic level. Due to its typical microsecond simulation timescale, conventional MD (cMD) cannot adequately sample a wide range of biological processes that are of interest. Enhanced sampling strategies like Gaussian accelerated MD (GaMD) have been developed to address this issue. This robust method provides simultaneous unconstrained sampling and free energy calculations of large biomolecules. A more recently developed Ligand GaMD (LiGaMD) algorithm enables efficient calculations of ligand binding free energies and kinetic rate constants. Here, we propose to utilize these techniques to uncover the dynamic mechanisms of small molecule interactions with nucleic acid and protein targets and identify novel leads for drug discovery.
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2024-01-01
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University of Kansas
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Akhter_ku_0099D_19626.pdf
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Keywords
Computational chemistry, Biophysics, Thermodynamics, Biophysics, Computer-aided drug design, GPCR, RNA, small molecules, Structure based drug design