Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–11 of 11 results
Advanced filters: Author: Birte Höcker Clear advanced filters
  • Some of the principles underlying how amino-acid sequences determine the three-dimensional structures of proteins have been defined. This has enabled a successful approach to designing protein folds from scratch. See Article p.222

    • Birte Höcker
    News & Views
    Nature
    Volume: 491, P: 204-205
  • Metal ions are frequently used in enzyme catalysis. The extension of computational methods to metalloenzyme redesign opens up new ways to construct enzymes with new functions.

    • Birte Höcker
    News & Views
    Nature Chemical Biology
    Volume: 8, P: 224-225
  • The de novo design of a pair of complementary peptides, one basic for cell penetration and target binding and one acidic that can be fused to proteins of interest, provides an approach for delivery into mammalian cells and subcellular targeting.

    • Guto G. Rhys
    • Jessica A. Cross
    • Derek N. Woolfson
    Research
    Nature Chemical Biology
    Volume: 18, P: 999-1004
  • A genetically encoded sensor for the quantitative visualization of auxin distribution in plants enables real-time monitoring of its uptake and clearance by individual cells and within cellular compartments.

    • Ole Herud-Sikimić
    • Andre C. Stiel
    • Gerd Jürgens
    ResearchOpen Access
    Nature
    Volume: 592, P: 768-772
  • Protein design aims to build novel proteins customized for specific purposes, thereby holding the potential to tackle many environmental and biomedical problems. Here the authors apply some of the latest advances in natural language processing, generative Transformers, to train ProtGPT2, a language model that explores unseen regions of the protein space while designing proteins with nature-like properties.

    • Noelia Ferruz
    • Steffen Schmidt
    • Birte Höcker
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-10
  • A deep learning algorithm for protein structure prediction is used in reverse for de novo protein design.

    • Noelia Ferruz
    • Birte Höcker
    News & Views
    Nature Biotechnology
    Volume: 40, P: 171-172
  • Despite substantial effort, the de novo design of a stable TIM-barrel protein fold has remained elusive. A Rosetta-based computational strategy identifies a unique 184-residue sequence that adopts a TIM-barrel structure, as revealed by X-ray crystallography.

    • Po-Ssu Huang
    • Kaspar Feldmeier
    • David Baker
    Research
    Nature Chemical Biology
    Volume: 12, P: 29-34
  • Finding evolutionary links between protein superfamilies has proven challenging. Advanced bioinformatics tools now identify relationships across two superfolds as well as a hybrid family whose structure displays characteristics of both.

    • José Arcadio Farías-Rico
    • Steffen Schmidt
    • Birte Höcker
    Research
    Nature Chemical Biology
    Volume: 10, P: 710-715
  • Both proteins and natural language are essentially based on a sequential code, but feature complex interactions at multiple scales, which can be useful when transferring machine learning models from one domain to another. In this Review, Ferruz and Höcker summarize recent advances in language models, such as transformers, and their application to protein design.

    • Noelia Ferruz
    • Birte Höcker
    Reviews
    Nature Machine Intelligence
    Volume: 4, P: 521-532