ReviewBiophysical journal2016
Using Evolution to Guide Protein Engineering: The Devil IS in the Details.
Review in Biophysical journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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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.
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Who cites it
24 citing papers in PubMed, 47 citations in OpenAlex.
- Engineering of Nocardioides acrostichi lipase: utilizing natural variation and mutational free energy to alter expression and functional properties.Journal of biological engineering · 2025Article
- Dynamic Allostery: Evolution's Double-Edged Sword in Protein Function and Disease.Journal of molecular biology · 2025Review
- Dissecting the effects of single amino acid substitutions in SARS-CoV-2 Mpro.Protein science : a publication of the Protein Society · 2025Article
- Identification of positions in human aldolase a that are neutral for apparent KArchives of biochemistry and biophysics · 2024Article
- Dynamics-based protein network features accurately discriminate neutral and rheostat positions.Biophysical journal · 2024Article
- Rheostatic contributions to protein stability can obscure a position's functional role.Protein science : a publication of the Protein Society · 2024Article
- Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function.The Journal of biological chemistry · 2024Review
- Article
- Engineering the kinetic stability of a β-trefoil protein by tuning its topological complexity.Frontiers in molecular biosciences · 2023Article
- Article
- Evolution of tunnels in α/β-hydrolase fold proteins-What can we learn from studying epoxide hydrolases?PLoS computational biology · 2022Article
- Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants.PLoS computational biology · 2022Article
- Evolution-Based Protein Engineering for Antifungal Peptide Improvement.Molecular biology and evolution · 2021Article
- MHCEpitopeEnergy, a Flexible Rosetta-Based Biotherapeutic Deimmunization Platform.Journal of chemical information and modeling · 2021Article
- Recent advances in user-friendly computational tools to engineer protein function.Briefings in bioinformatics · 2021Review
- Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions.Molecular biology and evolution · 2021Article
- Article
- Rheostat positions: A new classification of protein positions relevant to pharmacogenomics.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2020Article
- Allostery and Epistasis: Emergent Properties of Anisotropic Networks.Entropy (Basel, Switzerland) · 2020Article
- funtrp: identifying protein positions for variation driven functional tuning.Nucleic acids research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
For decades, protein engineers have endeavored to reengineer existing proteins for novel applications. Overall, protein folds and gross functions can be readily transferred from one protein to another by transplanting large blocks of sequence (i.e., domain recombination). However, predictably fine-tuning function (e.g., by adjusting ligand affinity, specificity, catalysis, and/or allosteric regulation) remains a challenge. One approach has been to use the sequences of protein families to identify amino acid positions that change during the evolution of functional variation. The rationale is that these nonconserved positions could be mutated to predictably fine-tune function. Evolutionary approaches to protein design have had some success, but the engineered proteins seldom replicate the functional performances of natural proteins. This Biophysical Perspective reviews several complexities that have been revealed by evolutionary and experimental studies of protein function. These include 1) challenges in defining computational and biological thresholds that define important amino acids; 2) the co-occurrence of many different patterns of amino acid changes in evolutionary data; 3) difficulties in mapping the patterns of amino acid changes to discrete functional parameters; 4) the nonconventional mutational outcomes that occur for a particular group of functionally important, nonconserved positions; 5) epistasis (nonadditivity) among multiple mutations; and 6) the fact that a large fraction of a protein's amino acids contribute to its overall function. To overcome these challenges, new goals are identified for future studies.
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What 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.