Literature DB >> 31965870

The impact of chemoinformatics on drug discovery in the pharmaceutical industry.

Karina Martinez-Mayorga1, Abraham Madariaga-Mazon1, José L Medina-Franco2, Gerald Maggiora3.   

Abstract

Introduction: Even though there have been substantial advances in our understanding of biological systems, research in drug discovery is only just now beginning to utilize this type of information. The single-target paradigm, which exemplifies the reductionist approach, remains a mainstay of drug research today. A deeper view of the complexity involved in drug discovery is necessary to advance on this field.Areas covered: This perspective provides a summary of research areas where cheminformatics has played a key role in drug discovery, including of the available resources as well as a personal perspective of the challenges still faced in the field.Expert opinion: Although great strides have been made in the handling and analysis of biological and pharmacological data, more must be done to link the data to biological pathways. This is crucial if one is to understand how drugs modify disease phenotypes, although this will involve a shift from the single drug/single target paradigm that remains a mainstay of drug research. Moreover, such a shift would require an increased awareness of the role of physiology in the mechanism of drug action, which will require the introduction of new mathematical, computer, and biological methods for chemoinformaticians to be trained in.

Keywords:  Chemoinformatics; artificial intelligence; big data; molecular modeling; polypharmacology; polyspecificity

Mesh:

Year:  2020        PMID: 31965870     DOI: 10.1080/17460441.2020.1696307

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


  17 in total

Review 1.  Recent progress on cheminformatics approaches to epigenetic drug discovery.

Authors:  Zoe Sessions; Norberto Sánchez-Cruz; Fernando D Prieto-Martínez; Vinicius M Alves; Hudson P Santos; Eugene Muratov; Alexander Tropsha; José L Medina-Franco
Journal:  Drug Discov Today       Date:  2020-09-30       Impact factor: 7.851

2.  Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics.

Authors:  Hanne S Antila; Tiago M Ferreira; O H Samuli Ollila; Markus S Miettinen
Journal:  J Chem Inf Model       Date:  2021-01-26       Impact factor: 4.956

Review 3.  Relevant Applications of Generative Adversarial Networks in Drug Design and Discovery: Molecular De Novo Design, Dimensionality Reduction, and De Novo Peptide and Protein Design.

Authors:  Eugene Lin; Chieh-Hsin Lin; Hsien-Yuan Lane
Journal:  Molecules       Date:  2020-07-16       Impact factor: 4.411

Review 4.  Therapeutic role of corticosteroids in COVID-19: a systematic review of registered clinical trials.

Authors:  Reshma Raju; Prajith V; Pratheeksha Sojan Biatris; Sam Johnson Udaya Chander J
Journal:  Futur J Pharm Sci       Date:  2021-03-17

Review 5.  Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: lessons from the pandemic and preparing for future health crises.

Authors:  Natesh Singh; Bruno O Villoutreix
Journal:  Comput Struct Biotechnol J       Date:  2021-04-26       Impact factor: 7.271

6.  Androgen Receptor Binding Category Prediction with Deep Neural Networks and Structure-, Ligand-, and Statistically Based Features.

Authors:  Alfonso T García-Sosa
Journal:  Molecules       Date:  2021-02-26       Impact factor: 4.411

Review 7.  Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence.

Authors:  José T Moreira-Filho; Arthur C Silva; Rafael F Dantas; Barbara F Gomes; Lauro R Souza Neto; Jose Brandao-Neto; Raymond J Owens; Nicholas Furnham; Bruno J Neves; Floriano P Silva-Junior; Carolina H Andrade
Journal:  Front Immunol       Date:  2021-05-31       Impact factor: 7.561

8.  A systematic review on use of aminoquinolines for the therapeutic management of COVID-19: Efficacy, safety and clinical trials.

Authors:  Vaishali M Patil; Shipra Singhal; Neeraj Masand
Journal:  Life Sci       Date:  2020-05-11       Impact factor: 5.037

Review 9.  Cheminformatics to Characterize Pharmacologically Active Natural Products.

Authors:  José L Medina-Franco; Fernanda I Saldívar-González
Journal:  Biomolecules       Date:  2020-11-17

10.  Computer-Aided Estimation of Biological Activity Profiles of Drug-Like Compounds Taking into Account Their Metabolism in Human Body.

Authors:  Dmitry A Filimonov; Anastassia V Rudik; Alexander V Dmitriev; Vladimir V Poroikov
Journal:  Int J Mol Sci       Date:  2020-10-11       Impact factor: 5.923

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