Controllable protein design with language models
The twenty-first century is presenting humankind with unprecedented environmental and
medical challenges. The ability to design novel proteins tailored for specific purposes would …
medical challenges. The ability to design novel proteins tailored for specific purposes would …
Opportunities and challenges in design and optimization of protein function
The field of protein design has made remarkable progress over the past decade. Historically,
the low reliability of purely structure-based design methods limited their application, but …
the low reliability of purely structure-based design methods limited their application, but …
Large language models generate functional protein sequences across diverse families
Deep-learning language models have shown promise in various biotechnological
applications, including protein design and engineering. Here we describe ProGen, a …
applications, including protein design and engineering. Here we describe ProGen, a …
OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
AlphaFold2 revolutionized structural biology with the ability to predict protein structures with
exceptionally high accuracy. Its implementation, however, lacks the code and data required …
exceptionally high accuracy. Its implementation, however, lacks the code and data required …
Diffusion probabilistic modeling of protein backbones in 3d for the motif-scaffolding problem
Construction of a scaffold structure that supports a desired motif, conferring protein function,
shows promise for the design of vaccines and enzymes. But a general solution to this motif …
shows promise for the design of vaccines and enzymes. But a general solution to this motif …
Deep transfer learning for inter-chain contact predictions of transmembrane protein complexes
Membrane proteins are encoded by approximately a quarter of human genes. Inter-chain
residue-residue contact information is important for structure prediction of membrane protein …
residue-residue contact information is important for structure prediction of membrane protein …
Big data mining, rational modification, and ancestral sequence reconstruction inferred multiple xylose isomerases for biorefinery
S Chen, Z Xu, B Ding, Y Zhang, S Liu, C Cai, M Li… - Science …, 2023 - science.org
The isomerization of xylose to xylulose is considered the most promising approach to initiate
xylose bioconversion. Here, phylogeny-guided big data mining, rational modification, and …
xylose bioconversion. Here, phylogeny-guided big data mining, rational modification, and …
Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP
The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus
valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user …
valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user …
Sparks of function by de novo protein design
Abstract Information in proteins flows from sequence to structure to function, with each step
causally driven by the preceding one. Protein design is founded on inverting this process …
causally driven by the preceding one. Protein design is founded on inverting this process …
An all-atom protein generative model
Proteins mediate their functions through chemical interactions; modeling these interactions,
which are typically through sidechains, is an important need in protein design. However …
which are typically through sidechains, is an important need in protein design. However …