Evidence map›Paper›PMID 35060221›Full record

ArticleProtein science : a publication of the Protein Society2022

Structure-conditioned amino-acid couplings: How contact geometry affects pairwise sequence preferences.

Jack Holland, Gevorg Grigoryan

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Jack HollandDepartment of Computer Science, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0001-6682-0659
Gevorg GrigoryanDepartment of Computer Science, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0003-4645-7666

Funding

Computational design of novel protein binders based on structure mining and learning from dataR01GM132117 · NIGMS · DARTMOUTH COLLEGE · PI GRIGORYAN, GEVORG, KEATING, AMY E · 2020 to 2023
$1.5M
NIGMS NIH HHS R01 GM132117
6 · The paper itself

Abstract

Relating a protein's sequence to its conformation is a central challenge for both structure prediction and sequence design. Statistical contact potentials, as well as their more descriptive versions that account for side-chain orientation and other geometric descriptors, have served as simplistic but useful means of representing second-order contributions in sequence-structure relationships. Here we ask what happens when a pairwise potential is conditioned on the fully defined geometry of interacting backbones fragments. We show that the resulting structure-conditioned coupling energies more accurately reflect pair preferences as a function of structural contexts. These structure-conditioned energies more reliably encode native sequence information and more highly correlate with experimentally determined coupling energies. Clustering a database of interaction motifs by structure results in ensembles of similar energies and clustering them by energy results in ensembles of similar structures. By comparing many pairs of interaction motifs and showing that structural similarity and energetic similarity go hand-in-hand, we provide a tangible link between modular sequence and structure elements. This link is applicable to structural modeling, and we show that scoring CASP models with structured-conditioned energies results in substantially higher correlation with structural quality than scoring the same models with a contact potential. We conclude that structure-conditioned coupling energies are a good way to model the impact of interaction geometry on second-order sequence preferences.

Indexed as

Amino AcidsModels, MolecularProtein ConformationAmino Acidscontact potentialcoupling energysequence-structure relationshipsstatistical energystructural modelingtertiary motifs

Identifiers

PMID35060221
PMCPMC8927866

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Registered trials

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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.