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Virtual screening, especially the structure-based virtual screening, has emerged as a reliable, cost-effective and time-saving technique for the discovery of lead compounds. Here, the basic ideas and computational tools for virtual screening have been briefly introduced, and emphasis is placed on aspects of recent development of docking-based virtual screening, scoring functions in molecular docking and ADME/Tox-based virtual screening. This paper gives an overview of drug discovery process and emphasizes in the area of virtual screening. Virtual screening (VS) has emerged as an important tool in identifying bioactive compounds through computational means, by employing knowledge about the protein target or known bioactive ligands. In silico approaches has given a tremendous opportunity to pharmaceutical companies to identify new potential drug targets which in turn affect the success and time of performing clinical trials for discovering new drug targets. The main goal of this work is to review in silico methods for drug discovery process with emphasis on identifying drug targets, where there are genes or proteins associated with specific diseases. This review provides a succinct overview of several recent approaches that employ bioinformatics for the systematic characterization of the targets of bioactive compounds.
Keywords:
Drug Discovery, In-Silico Method, Virtual Screening, Structural based virtual screening, Ligand based virtual screening Pharmacophore based virtual screening, Machine learning virtual screening, Structure Based Virtual Screening, ADME/Tox-Based Virtual Screening, Ubiquitination Regulator, Ubiquitination Regulator in Cancer.
Cite Article:
"Brief Introduction to In-Silico Drug Discovery Process and Virtual Screening Method; Ubiquitination Regulator in Cancer: A Review", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 3, page no.31 - 40, March-2022, Available :http://www.ijrti.org/papers/IJRTI2203009.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator