Open Access<p>Attractor – a new turning point in drug discovery</p>
Author(s) -
Xucan Hou,
Meng Li,
Congmin Jia,
Xian-Bao Zhang,
Yun Wang
Publication year - 2019
Publication title -
drug design, development and therapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.964
H-Index - 64
ISSN - 1177-8881
DOI - 10.2147/dddt.s216397
Subject(s) - drug discovery , attractor , identification (biology) , computer science , scope (computer science) , drug development , process (computing) , drug , computational biology , artificial intelligence , bioinformatics , mathematics , medicine , pharmacology , biology , mathematical analysis , botany , programming language , operating system
Drug discovery for complex diseases can be viewed as a challenging problem in which the influence of compounds on dynamic features of disease system should be considered, especially the strategies escaping from the disease attractors. Moreover, escaping from the disease-related attractors has been proved to be a cue for the treatment of the complex diseases. The drug discovery methodology based on the attractor theory indicates new solutions for target identification, drug discovery and drug combination design. The methodology is based on the holism level of the organism and the features of system dynamics, so it has advantages for the classification of complex diseases and drug discovery. Currently, research results of this method have increased, which expand the insight scope for drug discovery. This article introduces the major drug discovery methods in the history of pharmacy development and their characteristics, so as to illustrate the reasons and inevitability of the appearance of attractor method, its position in the history of pharmacy development, and its advantages for drug discovery and design, thereby to prove that the attractor method can indeed become the next major drug development method. In addition, it provides a comprehensive description about the concept of attractor, the pipeline of attractor analysis, the common methods of each process and its research progress, so as to provide a macroscopic framework and optional methods and tools for the follow-up researchers.