Computational Tools To Model Halogen Bonds in Medicinal Chemistry

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• 作者：Melissa Coates Ford ; P. Shing Ho
• 刊名：Journal of Medicinal Chemistry
• 出版年：2016
• 出版时间：March 10, 2016
• 年：2016
• 卷：59
• 期：5
• 页码：1655-1670
• 全文大小：804K
• 年卷期：Melissa C. Ford
  earned her undergraduate degree in Biology and Chemistry from the University of Virginia in 2010. She worked for two years in Dr. Patrice Guyenet’s lab studying the neurochemical phenotype of brainstem neurons involved in the regulation of breathing and autonomic function. In 2012, she began earning her Ph.D. in Biochemistry & Molecular Biology at Colorado State University. She joined Dr. P. Shing Ho’s group working on computational characterization and modeling of biological halogen bonds.
  P. Shing Ho
  earned his Ph.D. in 1984 with Professor Brian M. Hoffman at Northwestern University, studying long-range electron transfer in heme proteins. In 1984, he joined Dr. Alex Rich’s group at MIT as an American Cancer Society Postdoctoral Fellow, focused on the structure and function of noncanonical DNA structures, and wrote the first program to analyze genomic sequences for left-handed Z-DNA. Dr. Ho started his academic career in 1987 and became recognized for determining the crystal structure and sequence dependence of the DNA Holliday junction and mapping the transition from B-DNA to A-DNA at the atomic level. In 2004, he traveled to the Université de Strasbourg on a Fulbright grant, where he discovered the significance of halogen bonding in biomolecular structure and recognition.
• ISSN：1520-4804

文摘

The use of halogens in therapeutics dates back to the earliest days of medicine when seaweed was used as a source of iodine to treat goiters. The incorporation of halogens to improve the potency of drugs is now fairly standard in medicinal chemistry. In the past decade, halogens have been recognized as direct participants in defining the affinity of inhibitors through a noncovalent interaction called the halogen bond or X-bond. Incorporating X-bonding into structure-based drug design requires computational models for the anisotropic distribution of charge and the nonspherical shape of halogens, which lead to their highly directional geometries and stabilizing energies. We review here current successes and challenges in developing computational methods to introduce X-bonding into lead compound discovery and optimization during drug development. This fast-growing field will push further development of more accurate and efficient computational tools to accelerate the exploitation of halogens in medicinal chemistry.