Literature DB >> 25682781

The importance of employing computational resources for the automation of drug discovery.

Martha Cecilia Rosales-Hernández1, José Correa-Basurto.   

Abstract

INTRODUCTION: The application of computational tools to drug discovery helps researchers to design and evaluate new drugs swiftly with a reduce economic resources. To discover new potential drugs, computational chemistry incorporates automatization for obtaining biological data such as adsorption, distribution, metabolism, excretion and toxicity (ADMET), as well as drug mechanisms of action. AREAS COVERED: This editorial looks at examples of these computational tools, including docking, molecular dynamics simulation, virtual screening, quantum chemistry, quantitative structural activity relationship, principal component analysis and drug screening workflow systems. The authors then provide their perspectives on the importance of these techniques for drug discovery. EXPERT OPINION: Computational tools help researchers to design and discover new drugs for the treatment of several human diseases without side effects, thus allowing for the evaluation of millions of compounds with a reduced cost in both time and economic resources. The problem is that operating each program is difficult; one is required to use several programs and understand each of the properties being tested. In the future, it is possible that a single computer and software program will be capable of evaluating the complete properties (mechanisms of action and ADMET properties) of ligands. It is also possible that after submitting one target, this computer-software will be capable of suggesting potential compounds along with ways to synthesize them, and presenting biological models for testing.

Entities:  

Keywords:  ADMET properties; docking; molecular dynamics simulations; virtual screening

Mesh:

Year:  2015        PMID: 25682781     DOI: 10.1517/17460441.2015.1005071

Source DB:  PubMed          Journal:  Expert Opin Drug Discov        ISSN: 1746-0441            Impact factor:   6.098


  4 in total

1.  Molecular modeling and LC-MS-based metabolomics of a glutamine-valproic acid (Gln-VPA) derivative on HeLa cells.

Authors:  M J Fragoso-Vázquez; D Méndez-Luna; M C Rosales-Hernández; G R Luna-Palencia; A Estrada-Pérez; Benedicte Fromager; I Vásquez-Moctezuma; J Correa-Basurto
Journal:  Mol Divers       Date:  2020-04-24       Impact factor: 2.943

2.  Design and synthesis of a new steroid-macrocyclic derivative with biological activity.

Authors:  Maria López-Ramos; Lauro Figueroa-Valverde; Socorro Herrera-Meza; Marcela Rosas-Nexticapa; Francisco Díaz-Cedillo; Elodia García-Cervera; Eduardo Pool-Gómez; Regina Cahuich-Carrillo
Journal:  J Chem Biol       Date:  2017-02-23

3.  Design and synthesis of an indol derivative as antibacterial agent against Staphylococcus aureus.

Authors:  Hau-Heredia Lenin; Figueroa-Valverde Lauro; Rosas-Nexticapa Marcela; Herrera-Meza Socorro; López-Ramos Maria; Díaz-Cedillo Francisco; García-Cervera Elodia; Pool-Gómez Eduardo; Paat-Estrella Josefa; Cauich-Carrillo Regina; Euan-Hau Saidy
Journal:  J Chem Biol       Date:  2017-06-08

4.  ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database.

Authors:  Jie Dong; Ning-Ning Wang; Zhi-Jiang Yao; Lin Zhang; Yan Cheng; Defang Ouyang; Ai-Ping Lu; Dong-Sheng Cao
Journal:  J Cheminform       Date:  2018-06-26       Impact factor: 5.514

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.