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 …
Past, present, and future of CRISPR genome editing technologies
Genome editing has been a transformative force in the life sciences and human medicine,
offering unprecedented opportunities to dissect complex biological processes and treat the …
offering unprecedented opportunities to dissect complex biological processes and treat the …
Context-aware geometric deep learning for protein sequence design
Protein design and engineering are evolving at an unprecedented pace leveraging the
advances in deep learning. Current models nonetheless cannot natively consider non …
advances in deep learning. Current models nonetheless cannot natively consider non …
All‐Atom Protein Sequence Design Based on Geometric Deep Learning
J Liu, Z Guo, H You, C Zhang, L Lai - Angewandte Chemie, 2024 - Wiley Online Library
Designing sequences for specific protein backbones is a key step in creating new functional
proteins. Here, we introduce GeoSeqBuilder, a deep learning framework that integrates …
proteins. Here, we introduce GeoSeqBuilder, a deep learning framework that integrates …
Species-specific design of artificial promoters by transfer-learning based generative deep-learning model
Y Xia, X Du, B Liu, S Guo, YX Huo - Nucleic Acids Research, 2024 - academic.oup.com
Native prokaryotic promoters share common sequence patterns, but are species dependent.
For understudied species with limited data, it is challenging to predict the strength of existing …
For understudied species with limited data, it is challenging to predict the strength of existing …
Transferable deep generative modeling of intrinsically disordered protein conformations
Intrinsically disordered proteins have dynamic structures through which they play key
biological roles. The elucidation of their conformational ensembles is a challenging problem …
biological roles. The elucidation of their conformational ensembles is a challenging problem …
Int&in: A machine learning‐based web server for active split site identification in inteins
M Schmitz, JB Ballestin, J Liang, F Tomas… - Protein …, 2024 - Wiley Online Library
Inteins are proteins that excise themselves out of host proteins and ligate the flanking
polypeptides in an auto‐catalytic process called protein splicing. In nature, inteins are either …
polypeptides in an auto‐catalytic process called protein splicing. In nature, inteins are either …
Computational design of de novo bioenergetic membrane proteins
BJ Hardy, P Curnow - Biochemical Society Transactions, 2024 - portlandpress.com
The major energy-producing reactions of biochemistry occur at biological membranes.
Computational protein design now provides the opportunity to elucidate the underlying …
Computational protein design now provides the opportunity to elucidate the underlying …
Using Machine Learning to Enhance and Accelerate Synthetic Biology
Engineering synthetic regulatory circuits with precise input-output behavior—a central goal
in synthetic biology—remains encumbered by the inherent molecular complexity of cells …
in synthetic biology—remains encumbered by the inherent molecular complexity of cells …
Design of nanobody targeting SARS-CoV-2 spike glycoprotein using CDR-grafting assisted by molecular simulation and machine learning
MVF Ferraz, WCS Adan, TE Lima, AJC Santos… - bioRxiv, 2024 - biorxiv.org
The design of proteins capable to effectively bind to specific protein targets is crucial for
developing therapies, diagnostics, and vaccine candidates for viral infections. Here, we …
developing therapies, diagnostics, and vaccine candidates for viral infections. Here, we …