High-resolution protein design with backbone freedom.

By Pehr Harbury, Joseph J. Plecs, B. Tidor, T. Alber, P. S. Kim. 1998

Subfields: Computational Biology & Bioinformatics, Computational Chemistry & Drug Discovery

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Citations in the corpus

Generating functional protein variants with variational autoencoders (2020, background): “Recent progress has also been made in the rational design of proteins 43 with artificial folds from scratch [7, 8, 9].”
Learning inverse folding from millions of predicted structures (2022, background): “, 1991), or with flexibility in the backbone conformation (Harbury et al., 1998).”
Essentials of de novo protein design: Methods and applications (2018, background): “The first computational designs of novel protein sequences, 18 structures, 19 and folds 20 unlike those observed in nature were major breakthroughs ultimately demonstrating the possibility of creating a new, human-made, protein universe.”
Achievements and Challenges in Computational Protein Design. (2017, methodology): “In 1998 the Kim lab designed right-handed coiled coils applying backbone flexibility, hydrophobic-polar residue patterning for the superhelical axis and the hydrophobic core along with modeling of packing [21].”
Hallucinating protein assemblies (2022, background): “Because of the many applications of cyclic protein oligomers, ranging from small molecule binding and catalysis to building blocks for nanocage assemblies( 5 ), de novo design of such structures has been of considerable interest from the beginning of the protein design field ( 6 , 7 ).”
The coming of age of de novo protein design (2016, background): “Many helical bundles have been designed in this way 30,31,33,34,48–52 (Fig.”
De novo protein design, a retrospective (2020, methodology): “1998 Harbury, Kim and Alber (Harbury et al., 1998) Design of coiled coil using flexible-backbone methods and parametric equations.”
RamaNet: Computational de novo helical protein backbone design using a long short-term memory generative neural network (2019, methodology): “Others have used parametric equations to study and specify the desired protein geometry [16] [7] [6] [10] [11] [17].”
Recent advances in de novo protein design: Principles, methods, and applications (2021, background): “Helical bundles were the ﬁ rst type of protein fold designed de novo at atomic accuracy (22, 57).”
A de novo redesign of the WW domain (2003, background): “Freezing the coordinates of the backbone is thus overly restrictive, and the relaxation of this unrealistic constraint is expected to provide a broader range of solutions to the sequence-structure problem (Harbury et al. 1995, 1998; Wollacott and Desjarlais 2001; Larson et al. 2003).”