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Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies.
Bassani, Davide; Moro, Stefano.
  • Bassani D; Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland.
  • Moro S; Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy.
Molecules ; 28(9)2023 May 05.
Article in English | MEDLINE | ID: covidwho-2312914
ABSTRACT
The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of "computer-aided drug design" (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. Because of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can also be obtained with other computer-based techniques. In this work, we revised the state-of-the-art computer-aided drug design methods, focusing on their application in different scenarios of pharmaceutical and biological interest, not only highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work can be considered a brief overview of computational methods for drug discovery.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Drug Design / Computer-Aided Design Language: English Journal subject: Biology Year: 2023 Document Type: Article Affiliation country: Molecules28093906

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Drug Design / Computer-Aided Design Language: English Journal subject: Biology Year: 2023 Document Type: Article Affiliation country: Molecules28093906