ReviewNature2022
The road to fully programmable protein catalysis.
Review in Nature, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 136 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
136 citing papers in PubMed.
- Yoda1-Functionalized Nanozymes Coordinate Piezo1 Activation and Mitochondrial Protection to Reprogram the Diabetic Osteoimmune Micromilieu and Promote Vascularized Bone Repair.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Axial ligand substitution in a microperoxidase-derived peptide enables P450-like electrocatalysis.RSC advances · 2026Article
- Do We Still Need Chemistry for Water-Soluble Prodrugs? What Biocatalysis Already Does, and What It Does Not.Pharmaceutics · 2026Review
- Next-Generation Manufacturing: The Evolving Role of Biocatalysis in AstraZeneca.Chembiochem : a European journal of chemical biology · 2026Review
- Article
- Directed evolution of an enantiocomplementary SNature communications · 2026Article
- New paradigm of q-CAR drug development targeting disease-specific protein conformations.npj drug discovery · 2026Review
- Molecular Access Engineering for Microbial Biocatalysis: from Enzyme Tunnels to Microbial Cell Factories.Journal of microbiology and biotechnology · 2026Review
- Reprogramming NAD(P)Angewandte Chemie (International ed. in English) · 2026Article
- A magic methyl effect in the active site of a methyltransferase ribozyme.Nature communications · 2026Article
- Intracellular assembly of artificial enzymes for cytoplasmic enantioselective Mannich reactions.Nature communications · 2026Article
- Challenges and opportunities in the enzymatic recycling of nylons.Nature chemical biology · 2026Review
- Zero-shot design of abioRxiv : the preprint server for biology · 2026Article
- High-throughput Optical Analysis to Inform Design of Electrochemical Biosensors.ACS measurement science au · 2026Review
- Merging Biocatalysis and Chemocatalysis in Flow: State-of-the-Art and Future Directions for Sustainable Synthesis.Angewandte Chemie (International ed. in English) · 2026Review
- Probing anion recognition in a cobalt(II) de novo designed metalloprotein.Journal of inorganic biochemistry · 2026Article
- Exploring PadR Proteins for Artificial Enzyme Design.Chembiochem : a European journal of chemical biology · 2026Article
- Engineering LmrR protein for L-proline-based asymmetric aldol biocatalysis.Nature communications · 2026Article
- From Enrichment to Fate: Transport, Transformation, and Fate of Micro- and Nanoplastics in Marine Environments.Toxics · 2026Review
- Unlocking enzymatic deracemization of structurally diverse allenes by designed photoenzymes.Nature communications · 2026Article
76 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.
Indexed as
Identifiers
35650353What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.