Maximum Entropy in Drug Discovery

Entropy

Chih-Yuan Tseng¹ 

[1] Department of Oncology, University of Alberta, Edmonton, AB T6G 1Z2, Canada

关键词: maximum entropy;    inductive inference;    drug discovery;    target identification;    compound design;    pharmacokinetics;    pharmacodynamics;   

DOI  :  10.3390/e16073754

来源: mdpi

【 摘 要 】

Drug discovery applies multidisciplinary approaches either experimentally, computationally or both ways to identify lead compounds to treat various diseases. While conventional approaches have yielded many US Food and Drug Administration (FDA)-approved drugs, researchers continue investigating and designing better approaches to increase the success rate in the discovery process. In this article, we provide an overview of the current strategies and point out where and how the method of maximum entropy has been introduced in this area. The maximum entropy principle has its root in thermodynamics, yet since Jaynes’ pioneering work in the 1950s, the maximum entropy principle has not only been used as a physics law, but also as a reasoning tool that allows us to process information in hand with the least bias. Its applicability in various disciplines has been abundantly demonstrated. We give several examples of applications of maximum entropy in different stages of drug discovery. Finally, we discuss a promising new direction in drug discovery that is likely to hinge on the ways of utilizing maximum entropy.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland