Evidence map›Paper›PMID 33955480›Full record

ArticleProtein engineering, design & selection : PEDS2021

A fragment-based protein interface design algorithm for symmetric assemblies.

Joshua Laniado, Kyle Meador, Todd O Yeates

Open access · greenAbstract read
In one paragraph

Article in Protein engineering, design & selection : PEDS, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Joshua LaniadoUCLA Molecular Biology Institute, Los Angeles, CA 90095, USA.
Kyle MeadorUCLA Department of Chemistry and Biochemistry, Los Angeles, CA 90095, USA.
Todd O YeatesUCLA Molecular Biology Institute, Los Angeles, CA 90095, USA.
University of California, Los Angeles · US

Funding

CHEMISTRY BIOLOGY INTERFACE TRAINING PROGRAMT32GM008496 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MAYNARD, HEATHER D · 1993 to 2019
$6.3M
NIGMS NIH HHS T32 GM008496
6 · The paper itself

Abstract

Theoretical and experimental advances in protein engineering have led to the creation of precisely defined, novel protein assemblies of great size and complexity, with diverse applications. One powerful approach involves designing a new attachment or binding interface between two simpler symmetric oligomeric protein components. The required methods of design, which present both similarities and key differences compared to problems in protein docking, remain challenging and are not yet routine. With the aim of more fully enabling this emerging area of protein material engineering, we developed a computer program, nanohedra, to introduce two key advances. First, we encoded in the program the construction rules (i.e. the search space parameters) that underlie all possible symmetric material constructions. Second, we developed algorithms for rapidly identifying favorable docking/interface arrangements based on tabulations of empirical patterns of known protein fragment-pair associations. As a result, the candidate poses that nanohedra generates for subsequent amino acid interface design appear highly native-like (at the protein backbone level), while simultaneously conforming to the exacting requirements for symmetry-based assembly. A retrospective computational analysis of successful vs failed experimental studies supports the expectation that this should improve the success rate for this challenging area of protein engineering.

Indexed as

AlgorithmsProteinsProtein EngineeringRetrospective StudiesSoftwareProteinsalgorithmsdockingprotein designprotein interfacessecondary structureself-assemblysymmetry

Identifiers

PMID33955480
PMCPMC8101011
OpenAlexW3158342176

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.