2024 Nobel Prize in Chemistry

Nobel Prize 2018

On October 4th, the Nobel Prize in Chemistry 2024 was awarded to David Baker “for computational protein design” and to Demis Hassabis and John M. Jumper “for protein structure prediction”. *

This year’s Nobel Laureates didn’t achieve their breakthroughs overnight. Below you can read, share, and download a selection of their research that’s published across Springer Nature’s journals and books. Read the story of this year’s Laureates in Chemistry.

*The Nobel Prize in Chemistry 2024 - NobelPrize.org.

Publications by David Baker

Articles

Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers. Published in: Analytical and Bioanalytical Chemistry

Fully automated high-quality NMR structure determination of small 2H-enriched proteinsPublished in: Journal of Structural and Functional Genomics

De novo protein structure determination using sparse NMR data. Published in: Journal of Biomolecular NMR

De novo protein structure generation from incomplete chemical shift assignments. Published in: Journal of Biomolecular NMR

Improving 3D structure prediction from chemical shift dataPublished in: Journal of Biomolecular NMR

Improved chemical shift based fragment selection for CS-Rosetta using Rosetta3 fragment picker. Published in: Journal of Biomolecular NMR

Catalytic efficiencies of directly evolved phosphotriesterase variants with structurally different organophosphorus compounds in vitro. Published in: Archives of Toxicology

Fully automated high-quality NMR structure determination of small 2H-enriched proteinsPublished in: Journal of Structural and Functional Genomics

phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and RosettaPublished in: Journal of Structural and Functional Genomics

more

Predicting protein structures with a multiplayer online game. Published in: NatureAccurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA. Published in: Nature MethodsThe trRosetta server for fast and accurate protein structure prediction. Published in: Nature Protocols
Deep learning and protein structure modeling. Published in: Nature MethodsThe coming of age of de novo protein design. Published in: NatureKemp elimination catalysts by computational enzyme design. Published in: Nature
Computational design of ligand-binding proteins with high affinity and selectivity. Published in: NatureEvolution of a designed protein assembly encapsulating its own RNA genomePublished in: NatureDe novo design of bioactive protein switches. Published in: Nature

Functional rapidly folding proteins from simplified amino acid sequences. Published in: Nature

Exploitation of binding energy for catalysis and design. Published in: Nature Structural Biology

Exploitation of binding energy for catalysis and design. Published in: Nature

Accurate design of co-assembling multi-component protein nanomaterials. Published in: Nature

Accurate de novo design of hyperstable constrained peptides. Published in: Nature

Design of a hyperstable 60-subunit protein icosahedron. Published in: Nature

De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy. Published in: Nature Chemical Biology

Computational design of self-assembling cyclic protein homo-oligomers. Published in: Nature Chemistry

De novo design of a non-local β-sheet protein with high stability and accuracy. Published in: Nature Structural & Molecular Biology

De novo design of potent and selective mimics of IL-2 and IL-15. Published in: Nature

Receptor subtype discrimination using extensive shape complementary designed interfaces. Published in: Nature Structural & Molecular Biology

Computational design of transmembrane pores. Published in: Nature

De novo protein design by deep network hallucination. Published in: Nature

Role of backbone strain in de novo design of complex α/β protein structures. Published in: Nature Communications

Design of protein-binding proteins from the target structure alone. Published in: Nature

Accurate computational design of three-dimensional protein crystals. Published in: Nature Materials

Improving de novo protein binder design with deep learning. Published in: Nature Communications

Multistate and functional protein design using RoseTTAFold sequence space diffusion. Published in: Nature Biotechnology

Protein interactions in human pathogens revealed through deep learning. Published in: Nature Microbiology

De novo design of pH-responsive self-assembling helical protein filaments. Published in: Nature Nanotechnology

Book chapters

Structural Genomics of Pathogenic Protozoa: an Overview. In: Methods in Molecular Biology

Redesigning the Specificity of Protein–DNA Interactions with Rosetta. In: Methods in Molecular Biology

Template Scoring Methods for Protein Torsion Angle Prediction. In: Biomedical Engineering Systems and Technologies

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