Next Article in Journal
Next Article in Special Issue
Previous Article in Journal
Previous Article in Special Issue
Entropy 2014, 16(7), 3754-3768; doi:10.3390/e16073754
Review

Maximum Entropy in Drug Discovery

1,†,*  and 1,2
Received: 28 April 2014; in revised form: 28 May 2014 / Accepted: 27 June 2014 / Published: 7 July 2014
(This article belongs to the Special Issue Maximum Entropy and Its Application)
View Full-Text   |   Download PDF [744 KB, uploaded 7 July 2014]
Abstract: 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.
Keywords: maximum entropy; inductive inference; drug discovery; target identification; compound design; pharmacokinetics; pharmacodynamics maximum entropy; inductive inference; drug discovery; target identification; compound design; pharmacokinetics; pharmacodynamics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Tseng, C.-Y.; Tuszynski, J. Maximum Entropy in Drug Discovery. Entropy 2014, 16, 3754-3768.

AMA Style

Tseng C-Y, Tuszynski J. Maximum Entropy in Drug Discovery. Entropy. 2014; 16(7):3754-3768.

Chicago/Turabian Style

Tseng, Chih-Yuan; Tuszynski, Jack. 2014. "Maximum Entropy in Drug Discovery." Entropy 16, no. 7: 3754-3768.


Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert