PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions

Sun et al. present PremPLI, a machine learning approach and web tool to predict how missense mutations in a drug’s target protein will affect the drug’s binding affinity. PremPLI can be applied to identify drug resistance mechanisms in cancer cells and microorganisms and develop drugs to combat drug...

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Autores principales:	Tingting Sun, Yuting Chen, Yuhao Wen, Zefeng Zhu, Minghui Li
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/111b029010554336953c7cbdd3a29d8b
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spelling	oai:doaj.org-article:111b029010554336953c7cbdd3a29d8b2021-11-21T12:08:42ZPremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions10.1038/s42003-021-02826-32399-3642https://doaj.org/article/111b029010554336953c7cbdd3a29d8b2021-11-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02826-3https://doaj.org/toc/2399-3642Sun et al. present PremPLI, a machine learning approach and web tool to predict how missense mutations in a drug’s target protein will affect the drug’s binding affinity. PremPLI can be applied to identify drug resistance mechanisms in cancer cells and microorganisms and develop drugs to combat drug resistance.Tingting SunYuting ChenYuhao WenZefeng ZhuMinghui LiNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Tingting Sun Yuting Chen Yuhao Wen Zefeng Zhu Minghui Li PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
description	Sun et al. present PremPLI, a machine learning approach and web tool to predict how missense mutations in a drug’s target protein will affect the drug’s binding affinity. PremPLI can be applied to identify drug resistance mechanisms in cancer cells and microorganisms and develop drugs to combat drug resistance.
format	article
author	Tingting Sun Yuting Chen Yuhao Wen Zefeng Zhu Minghui Li
author_facet	Tingting Sun Yuting Chen Yuhao Wen Zefeng Zhu Minghui Li
author_sort	Tingting Sun
title	PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
title_short	PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
title_full	PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
title_fullStr	PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
title_full_unstemmed	PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
title_sort	prempli: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/111b029010554336953c7cbdd3a29d8b
work_keys_str_mv	AT tingtingsun prempliamachinelearningmodelforpredictingtheeffectsofmissensemutationsonproteinligandinteractions AT yutingchen prempliamachinelearningmodelforpredictingtheeffectsofmissensemutationsonproteinligandinteractions AT yuhaowen prempliamachinelearningmodelforpredictingtheeffectsofmissensemutationsonproteinligandinteractions AT zefengzhu prempliamachinelearningmodelforpredictingtheeffectsofmissensemutationsonproteinligandinteractions AT minghuili prempliamachinelearningmodelforpredictingtheeffectsofmissensemutationsonproteinligandinteractions
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PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions

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