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Chiral Graphs: Reduced Representations of Ligand Scaffolds for Stereoselective Biomolecular Recognition, Drug Design,
Simoun Mikhael1, Ravinder Abrol1
1Department of Chemistry and Biochemistry, College of Science and Mathematics, California State University, Northridge, CA, 91330, USA.
Abstract:
Rational structure-based drug design relies on a detailed, atomic-level understanding of protein-ligand interactions. The chiral nature of drug binding sites in proteins has led to the discovery of predominantly chiral drugs. A mechanistic understanding of stereoselectivity (which governs how one stereoisomer of a drug might bind stronger than the others to a protein) depends on the topology of stereocenters in the chiral molecule. Chiral graphs and reduced chiral graphs, introduced here, are new topological representations of chiral ligands using graph theory, to facilitate a detailed understanding of chiral recognition of ligands/drugs by proteins. These representations are demonstrated by application to all ≈14 000+ chiral ligands in the Protein Data Bank (PDB), which will facilitate an understanding of protein-ligand stereoselectivity mechanisms. Ligand modifications during drug development can be easily incorporated into these chiral graphs. In addition, these chiral graphs present an efficient tool for a deep dive into the enormous chemical structure space to enable sampling of unexplored structural scaffolds.
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