Literature DB >> 25727255

Combining label-free cell phenotypic profiling with computational approaches for novel drug discovery.

Ye Fang1.   

Abstract

INTRODUCTION: Drug discovery is a long and costly process. Innovations and paradigm shifts are essential for continuous improvement in the productivity of pharmaceutical R&D. AREAS COVERED: The author reviews the progress of label-free cell phenotypic and computational approaches in early drug discovery since 2004 and proposes a novel paradigm, which combines both approaches. EXPERT OPINION: Label-free cell phenotypic profiling techniques offer an unprecedented and integrated approach to comprehend drug-target interactions in their native environments. However, these approaches have disadvantages associated with the lack of molecular details. Computational approaches, including ligand-, structure- and phenotype-based virtual screens, have become versatile tools in the early drug discovery process. However, these approaches mostly predict the binding of drug molecules to targets of interest and are limited to targets that are either well annotated for ligands or that are structurally resolved. Thus, combining label-free cell phenotypic profiling with computational approaches can provide a potential paradigm to accelerate novel drug discovery by taking advantages of the best of both approaches.

Entities:  

Keywords:  chemical similarity; drug discovery; label-free cell phenotypic approach; ligand-based virtual screen; polypharmacology; structure-based virtual screen; text mining

Mesh:

Substances:

Year:  2015        PMID: 25727255     DOI: 10.1517/17460441.2015.1020788

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


  4 in total

Review 1.  Emerging machine learning approaches to phenotyping cellular motility and morphodynamics.

Authors:  Hee June Choi; Chuangqi Wang; Xiang Pan; Junbong Jang; Mengzhi Cao; Joseph A Brazzo; Yongho Bae; Kwonmoo Lee
Journal:  Phys Biol       Date:  2021-06-17       Impact factor: 2.959

Review 2.  Systems Pharmacology in Small Molecular Drug Discovery.

Authors:  Wei Zhou; Yonghua Wang; Aiping Lu; Ge Zhang
Journal:  Int J Mol Sci       Date:  2016-02-18       Impact factor: 5.923

Review 3.  Computer Aided Drug Design and its Application to the Development of Potential Drugs for Neurodegenerative Disorders.

Authors:  Mohammad Hassan Baig; Khurshid Ahmad; Gulam Rabbani; Mohd Danishuddin; Inho Choi
Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

4.  An integrated strategy for identifying new targets and inferring the mechanism of action: taking rhein as an example.

Authors:  Hao Sun; Yiting Shen; Guangwen Luo; Yuepiao Cai; Zheng Xiang
Journal:  BMC Bioinformatics       Date:  2018-09-06       Impact factor: 3.169

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.