Generative protein design

Biotechnology & Synthetic BiologyUpdated Aug 20, 2026Version v1

Evidence

Public papers linked to this topic and used as evidence for gaps, timelines, and knowledge views.

32 papers

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Showing 1-12 of total 32 evidence records.

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2026CrossrefSupporting evidence2 citations

De novo protein–ligand design including protein flexibility and conformational adaptation

Jakob Agamia; Martin Zacharias

Feb 3, 2026Bioinformatics

2026PubMedSupporting evidence

ScrambleBench: a workflow for comparative assessment of structure-based de novo generative models.

Yap V; Xu P; Mak FS; Foo K; Kang C; Anbazhagan P; Xu W

Jan 1, 2026Journal of cheminformatics

2026PubMedSupporting evidence

ScrambleBench: a workflow for comparative assessment of structure-based de novo generative models.

Yap V; Xu P; Mak FS; Foo K; Kang C; Anbazhagan P; Xu W

Jan 1, 2026Journal of cheminformatics

2024OpenAlexSupporting evidence93 citations

A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation

Xiangru Tang; Howard Dai; Elizabeth Knight; Fang Wu; Yunyang Li; Tianxiao Li; Mark Gerstein

May 23, 2024Briefings in Bioinformatics

2024OpenAlexSupporting evidence93 citations

A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation

Xiangru Tang; Howard Dai; Elizabeth Knight; Fang Wu; Yunyang Li; Tianxiao Li; Mark Gerstein

May 23, 2024Briefings in Bioinformatics

2023OpenAlexSupporting evidence2,018 citations

De novo design of protein structure and function with RFdiffusion

Joseph L. Watson; David Juergens; Nathaniel R. Bennett; Brian L. Trippe; Jason Yim; Helen E. Eisenach; Woody Ahern; Andrew J. Borst; Robert J. Ragotte; Lukas F. Milles; Basile I. M. Wicky; Nikita Hanikel; Samuel J. Pellock; Alexis Courbet; William Sheffler; Jue Wang; Preetham Venkatesh; Isaac Sappington; Susana Vázquez Torres; Anna Lauko; Valentin De Bortoli; Émile Mathieu; Sergey Ovchinnikov; Regina Barzilay; Tommi Jaakkola; Frank DiMaio; Minkyung Baek; David Baker

Jul 11, 2023Nature

2023OpenAlexSupporting evidence2,018 citations

De novo design of protein structure and function with RFdiffusion

Jul 11, 2023Nature

2023OpenAlexSupporting evidence91 citations

De novo protein design by inversion of the <scp>AlphaFold</scp> structure prediction network

Casper A. Goverde; Benedict Wolf; Hamed Khakzad; Stéphane Rosset; Bruno E. Correia

May 11, 2023Protein Science

2023OpenAlexSupporting evidence91 citations

De novo protein design by inversion of the <scp>AlphaFold</scp> structure prediction network

Casper A. Goverde; Benedict Wolf; Hamed Khakzad; Stéphane Rosset; Bruno E. Correia

May 11, 2023Protein Science

2023OpenAlexSupporting evidence368 citations

Improving de novo protein binder design with deep learning

Nathaniel R. Bennett; Brian Coventry; Inna Goreshnik; Buwei Huang; Aza Allen; Dionne Vafeados; Ying Po Peng; Justas Dauparas; Minkyung Baek; Lance Stewart; Frank DiMaio; Steven De Munck; Savvas N. Savvides; David Baker

May 6, 2023Nature Communications

2023OpenAlexSupporting evidence368 citations

Improving de novo protein binder design with deep learning

May 6, 2023Nature Communications

Generative protein design

Evidence

<i>De novo</i> protein–ligand design including protein flexibility and conformational adaptation

<i>De novo</i> protein–ligand design including protein flexibility and conformational adaptation

ScrambleBench: a workflow for comparative assessment of structure-based de novo generative models.

ScrambleBench: a workflow for comparative assessment of structure-based de novo generative models.

A survey of generative AI for <i>de novo</i> drug design: new frontiers in molecule and protein generation

A survey of generative AI for <i>de novo</i> drug design: new frontiers in molecule and protein generation

De novo design of protein structure and function with RFdiffusion

De novo design of protein structure and function with RFdiffusion

De novo protein design by inversion of the <scp>AlphaFold</scp> structure prediction network

De novo protein design by inversion of the <scp>AlphaFold</scp> structure prediction network

Improving de novo protein binder design with deep learning

Improving de novo protein binder design with deep learning