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Other Related Techniques
With the advances in computational resources, there is an increasing urge among the computational researchers to make the in silico approaches fast, convenient, reproducible, acceptable, and sensible ones. Along with the typical two-dimensional (2D) and three-dimensional (3D) quantitative structure–...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149793/ http://dx.doi.org/10.1016/B978-0-12-801505-6.00010-7 |
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author | Roy, Kunal Kar, Supratik Das, Rudra Narayan |
author_facet | Roy, Kunal Kar, Supratik Das, Rudra Narayan |
author_sort | Roy, Kunal |
collection | PubMed |
description | With the advances in computational resources, there is an increasing urge among the computational researchers to make the in silico approaches fast, convenient, reproducible, acceptable, and sensible ones. Along with the typical two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationship (QSAR) methods, approaches like pharmacophore, structure-based docking studies, and combinations of ligand- and structure-based approaches like comparative residue interaction analysis (CoRIA) and comparative binding energy analysis (COMBINE) have gained a significant popularity in the computational drug design process. A pharmacophore can be developed either in a ligand-based method, by superposing a set of active molecules and extracting common chemical features which are vital for their bioactivity; or in a structure-based manner, by probing probable interaction points between the macromolecular target and ligands. The interaction of protein and ligand molecules with each other is one of the interesting studies in modern molecular biology and molecular recognition. This interaction can well be explained with the conceptof a docking study to show how a molecule can bind to another molecule to exert the bioactivity. Docking and pharmacophore are non-QSAR approaches in in silico drug design that can support the QSAR findings. Approaches like CoRIA and COMBINE can use information generated from the ligand–receptor complexes to extract the critical clue concerning the types of significant interaction at the level of both the receptor and the ligand. Employing the abovementioned ligand- and structure-based methodologies and chemical libraries, virtual screening (VS) emerged as an important tool in the quest to develop novel drug compounds. VS serves as an efficient computational tool that integrates structural data with lead optimization as a cost-effective approach to drug discovery. |
format | Online Article Text |
id | pubmed-7149793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
record_format | MEDLINE/PubMed |
spelling | pubmed-71497932020-04-13 Other Related Techniques Roy, Kunal Kar, Supratik Das, Rudra Narayan Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment Article With the advances in computational resources, there is an increasing urge among the computational researchers to make the in silico approaches fast, convenient, reproducible, acceptable, and sensible ones. Along with the typical two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationship (QSAR) methods, approaches like pharmacophore, structure-based docking studies, and combinations of ligand- and structure-based approaches like comparative residue interaction analysis (CoRIA) and comparative binding energy analysis (COMBINE) have gained a significant popularity in the computational drug design process. A pharmacophore can be developed either in a ligand-based method, by superposing a set of active molecules and extracting common chemical features which are vital for their bioactivity; or in a structure-based manner, by probing probable interaction points between the macromolecular target and ligands. The interaction of protein and ligand molecules with each other is one of the interesting studies in modern molecular biology and molecular recognition. This interaction can well be explained with the conceptof a docking study to show how a molecule can bind to another molecule to exert the bioactivity. Docking and pharmacophore are non-QSAR approaches in in silico drug design that can support the QSAR findings. Approaches like CoRIA and COMBINE can use information generated from the ligand–receptor complexes to extract the critical clue concerning the types of significant interaction at the level of both the receptor and the ligand. Employing the abovementioned ligand- and structure-based methodologies and chemical libraries, virtual screening (VS) emerged as an important tool in the quest to develop novel drug compounds. VS serves as an efficient computational tool that integrates structural data with lead optimization as a cost-effective approach to drug discovery. 2015 2015-04-03 /pmc/articles/PMC7149793/ http://dx.doi.org/10.1016/B978-0-12-801505-6.00010-7 Text en Copyright © 2015 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Roy, Kunal Kar, Supratik Das, Rudra Narayan Other Related Techniques |
title | Other Related Techniques |
title_full | Other Related Techniques |
title_fullStr | Other Related Techniques |
title_full_unstemmed | Other Related Techniques |
title_short | Other Related Techniques |
title_sort | other related techniques |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149793/ http://dx.doi.org/10.1016/B978-0-12-801505-6.00010-7 |
work_keys_str_mv | AT roykunal otherrelatedtechniques AT karsupratik otherrelatedtechniques AT dasrudranarayan otherrelatedtechniques |