Evidence map›Paper›PMID 39546369›Full record

ArticleThe Journal of chemical physics2024

Designing proteins: Mimicking natural protein sequence heterogeneity.

Marcos Lequerica-Mateos, Jonathan Martin, José N Onuchic, Faruck Morcos, Ivan Coluzza

Abstract read
In one paragraph

Article in The Journal of chemical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Marcos Lequerica-MateosFundación BCMaterials, UPV/EHU, Leioa, Spain.ORCID 0009-0002-2067-2122
Jonathan MartinDepartment of Biological Sciences, University of Texas at Dallas, Richardson, Texas 75080, USA.ORCID 0000-0003-0946-3864
José N OnuchicCenter for Theoretical Biological Physics, Rice University, Houston, Texas 77005, USA.ORCID 0000-0002-9448-0388
Faruck MorcosDepartment of Biological Sciences, University of Texas at Dallas, Richardson, Texas 75080, USA.ORCID 0000-0001-6208-1561
Ivan ColuzzaCenter for Theoretical Biological Physics, Rice University, Houston, Texas 77005, USA.ORCID 0000-0001-7728-6033

Funding

Computational Tools to Characterize the Effects of Protein and RNA Variability in Function and InteractionsR35GM133631 · NIGMS · UNIVERSITY OF TEXAS DALLAS · PI Alonso Faruck Morcos · 2019 to 2026
$3.0M
NIGMS NIH HHS R35 GM133631
6 · The paper itself

Abstract

This study presents an enhanced protein design algorithm that aims to emulate natural heterogeneity of protein sequences. Initial analysis revealed that natural proteins exhibit a permutation composition lower than the theoretical maximum, suggesting a selective utilization of the 20-letter amino acid alphabet. By not constraining the amino acid composition of the protein sequence but instead allowing random reshuffling of the composition, the resulting design algorithm generates sequences that maintain lower permutation compositions in equilibrium, aligning closely with natural proteins. Folding free energy computations demonstrated that the designed sequences refold to their native structures with high precision, except for proteins with large disordered regions. In addition, direct coupling analysis showed a strong correlation between predicted and actual protein contacts, with accuracy exceeding 82% for a large number of top pairs (>4L). The algorithm also resolved biases in previous designs, ensuring a more accurate representation of protein interactions. Overall, it not only mimics the natural heterogeneity of proteins but also ensures correct folding, marking a significant advancement in protein design and engineering.

Indexed as

AlgorithmsProtein FoldingProteinsAmino Acid SequenceProtein EngineeringThermodynamicsProteins

Identifiers

PMID39546369
PMCPMC11568883

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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.