Database of articles cited by EMDB/PDB/SASBDB data

Keywords
Structure methods	All X-ray diffraction NMR electron microscopy small angle scattering neutron diffraction fiber diffraction powder diffraction infrared spectroscopy EPR fluorescence transfer theoretical model Hybrid
Author
Journal
IF	>30 >20 >10 >5 all

Title	Scalable protein design using optimization in a relaxed sequence space.
Journal, issue, pages	Science, Vol. 386, Issue 6720, Page 439-445, Year 2024
Publish date	Oct 25, 2024
Authors	Christopher Frank / Ali Khoshouei / Lara Fuβ / Dominik Schiwietz / Dominik Putz / Lara Weber / Zhixuan Zhao / Motoyuki Hattori / Shihao Feng / Yosta de Stigter / Sergey Ovchinnikov / Hendrik Dietz /
PubMed Abstract	Machine learning (ML)-based design approaches have advanced the field of de novo protein design, with diffusion-based generative methods increasingly dominating protein design pipelines. Here, we ...Machine learning (ML)-based design approaches have advanced the field of de novo protein design, with diffusion-based generative methods increasingly dominating protein design pipelines. Here, we report a "hallucination"-based protein design approach that functions in relaxed sequence space, enabling the efficient design of high-quality protein backbones over multiple scales and with broad scope of application without the need for any form of retraining. We experimentally produced and characterized more than 100 proteins. Three high-resolution crystal structures and two cryo-electron microscopy density maps of designed single-chain proteins comprising up to 1000 amino acids validate the accuracy of the method. Our pipeline can also be used to design synthetic protein-protein interactions, as validated experimentally by a set of protein heterodimers. Relaxed sequence optimization offers attractive performance with respect to designability, scope of applicability for different design problems, and scalability across protein sizes.
External links	Science / PubMed:39446959 / PubMed Central
Methods	EM (single particle) / X-ray diffraction
Resolution	2.1 - 3.36 Å
Structure data	50040 9exk EMDB-50040, PDB-9exk: Scalable protein design using hallucination in a relaxed sequence space Method: EM (single particle) / Resolution: 3.36 Å 50113 9f0l EMDB-50113, PDB-9f0l: Scalable protein design using hallucination in a relaxed sequence space Method: EM (single particle) / Resolution: 2.76 Å PDB-8s89: Efficient and scalable protein design using a relaxed sequence space Method: X-RAY DIFFRACTION / Resolution: 2.1 Å PDB-8yl4: Crystal structure of the de novo designed protein 200 AA in the crystal form 1 Method: X-RAY DIFFRACTION / Resolution: 2.88 Å PDB-8yl8: Crystal structure of the de novo designed protein 200 AA in the crystal form 2 Method: X-RAY DIFFRACTION / Resolution: 2.21 Å PDB-9exz: Efficient and scalable protein design using a relaxed sequence space Method: X-RAY DIFFRACTION / Resolution: 2.8 Å
Chemicals	ChemComp-SO4: SULFATE ION ChemComp-HOH: WATER ChemComp-GOL: GLYCEROL
Source	synthetic construct (others) escherichia coli (E. coli)
Keywords	DE NOVO PROTEIN / P400 / De novo protein design / De novo designed protein K12 / P600