Results 11 to 20 of about 9,762,259 (268)
Biophysics-based protein language models for protein engineering. [PDF]
Nat MethodsProtein language models trained on evolutionary data have emerged as powerful tools for predictive problems involving protein sequence, structure and function.
Gelman S +7 more
europepmc +2 more sources
Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models [PDF]
Briefings Bioinform., 2023 Protein engineering is an emerging field in biotechnology that has the potential to revolutionize various areas, such as antibody design, drug discovery, food security, ecology, and more.
Yuchi Qiu, Guo-Wei Wei
semanticscholar +1 more source
Phage-assisted evolution and protein engineering yield compact, efficient prime editors
Cell, 2023 Summary Prime editing enables a wide variety of precise genome edits in living cells. Here we use protein evolution and engineering to generate prime editors with reduced size and improved efficiency.
Jordan L. Doman +16 more
semanticscholar +1 more source
Adaptive machine learning for protein engineering [PDF]
Current Opinion in Structural Biology, 2021 Machine-learning models that learn from data to predict how protein sequence encodes function are emerging as a useful protein engineering tool. However, when using these models to suggest new protein designs, one must deal with the vast combinatorial ...
B. Hie, Kevin Kaichuang Yang
semanticscholar +1 more source
A human bispecific antibody neutralizes botulinum neurotoxin serotype A
Scientific Reports, 2023 Botulinum neurotoxin (BoNT) shows high lethality and toxicity, marking it as an important biological threat. The only effective post-exposure therapy is botulinum antitoxin; however, such products have great potential for improvement. To prevent or treat
Jiansheng Lu +10 more
doaj +1 more source
Machine Learning-Guided Protein Engineering
ACS Catalysis, 2023 Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in ...
Petr Kouba +9 more
semanticscholar +1 more source
Cell Communication and Signaling, 2023 Fibroblast growth factors (FGFs) and their receptors (FGFRs) constitute complex signaling hubs that are crucial for the development and homeostasis of the human body.
Aleksandra Gedaj +9 more
doaj +1 more source
Combining chemistry and protein engineering for new-to-nature biocatalysis
Nature Synthesis, 2022 Biocatalysis, the application of enzymes to solve synthetic problems of human import, has blossomed into a powerful technology for chemical innovation. In the past decade, a threefold partnership, where nature provides blueprints for enzymatic catalysis,
David C. Miller, S. Athavale, F. Arnold
semanticscholar +1 more source
Data‐Driven Protein Engineering for Improving Catalytic Activity and Selectivity
ChemBioChem, 2023 Protein engineering is essential for altering the substrate scope, catalytic activity and selectivity of enzymes for applications in biocatalysis. However, traditional approaches, such as directed evolution and rational design, encounter the challenge in
Yu-Fei Ao +5 more
semanticscholar +1 more source
Protein Engineering with Lightweight Graph Denoising Neural Networks
bioRxiv, 2023 Protein engineering faces challenges in finding optimal mutants from the massive pool of candidate mutants. In this study, we introduce a deep learning-based data-efficient fitness prediction tool to steer protein engineering. Our methodology establishes
Bingxin Zhou +7 more
semanticscholar +1 more source