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• W4313654640 startingPage "102526" @default.
• W4313654640 abstract "The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificial intelligence methods compile the three-dimensional structure of proteins has made protein targets more accessible to the drug design process. Here, we present our perspective of the significance of accurate protein structure prediction on various stages of the small molecule drug discovery life cycle focusing on current capabilities and assessing how further evolution of such predictive procedures can have a more decisive impact in the discovery of new medicines." @default.
• W4313654640 created "2023-01-07" @default.
• W4313654640 creator A5042279588 @default.
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• W4313654640 date "2023-02-01" @default.
• W4313654640 modified "2023-10-16" @default.
• W4313654640 title "AlphaFold2 protein structure prediction: Implications for drug discovery" @default.
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• W4313654640 doi "https://doi.org/10.1016/j.sbi.2022.102526" @default.
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• W4313654640 hasPublicationYear "2023" @default.
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