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A Guide to In Silico Drug Design

The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility o...

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Autores principales: Chang, Yiqun, Hawkins, Bryson A., Du, Jonathan J., Groundwater, Paul W., Hibbs, David E., Lai, Felcia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867171/
https://www.ncbi.nlm.nih.gov/pubmed/36678678
http://dx.doi.org/10.3390/pharmaceutics15010049
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author Chang, Yiqun
Hawkins, Bryson A.
Du, Jonathan J.
Groundwater, Paul W.
Hibbs, David E.
Lai, Felcia
author_facet Chang, Yiqun
Hawkins, Bryson A.
Du, Jonathan J.
Groundwater, Paul W.
Hibbs, David E.
Lai, Felcia
author_sort Chang, Yiqun
collection PubMed
description The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area.
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spelling pubmed-98671712023-01-22 A Guide to In Silico Drug Design Chang, Yiqun Hawkins, Bryson A. Du, Jonathan J. Groundwater, Paul W. Hibbs, David E. Lai, Felcia Pharmaceutics Review The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area. MDPI 2022-12-23 /pmc/articles/PMC9867171/ /pubmed/36678678 http://dx.doi.org/10.3390/pharmaceutics15010049 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Chang, Yiqun
Hawkins, Bryson A.
Du, Jonathan J.
Groundwater, Paul W.
Hibbs, David E.
Lai, Felcia
A Guide to In Silico Drug Design
title A Guide to In Silico Drug Design
title_full A Guide to In Silico Drug Design
title_fullStr A Guide to In Silico Drug Design
title_full_unstemmed A Guide to In Silico Drug Design
title_short A Guide to In Silico Drug Design
title_sort guide to in silico drug design
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867171/
https://www.ncbi.nlm.nih.gov/pubmed/36678678
http://dx.doi.org/10.3390/pharmaceutics15010049
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