Evidence map›Paper›PMID 33270805›Full record

ArticlePloS one2020

PolyFold: An interactive visual simulator for distance-based protein folding.

Andrew J McGehee, Sutanu Bhattacharya, Rahmatullah Roche, Debswapna Bhattacharya

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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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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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Andrew J McGeheeDepartment of Computer Science and Software Engineering, Auburn University, Auburn, AL, United States of America.
Sutanu BhattacharyaDepartment of Computer Science and Software Engineering, Auburn University, Auburn, AL, United States of America.
Rahmatullah RocheDepartment of Computer Science and Software Engineering, Auburn University, Auburn, AL, United States of America.
Debswapna BhattacharyaDepartment of Computer Science and Software Engineering, Auburn University, Auburn, AL, United States of America.ORCID 0000-0002-9630-0141

Funding

GPU-accelerated high-performance computing to supercharge foundational deep learning method development for scalable and accurate prediction of protein structuresR35GM138146 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI Debswapna Bhattacharya · 2020 to 2026
$2.5M
NIGMS NIH HHS R35 GM138146
6 · The paper itself

Abstract

Recent advances in distance-based protein folding have led to a paradigm shift in protein structure prediction. Through sufficiently precise estimation of the inter-residue distance matrix for a protein sequence, it is now feasible to predict the correct folds for new proteins much more accurately than ever before. Despite the exciting progress, a dedicated visualization system that can dynamically capture the distance-based folding process is still lacking. Most molecular visualizers typically provide only a static view of a folded protein conformation, but do not capture the folding process. Even among the selected few graphical interfaces that do adopt a dynamic perspective, none of them are distance-based. Here we present PolyFold, an interactive visual simulator for dynamically capturing the distance-based protein folding process through real-time rendering of a distance matrix and its compatible spatial conformation as it folds in an intuitive and easy-to-use interface. PolyFold integrates highly convergent stochastic optimization algorithms with on-demand customizations and interactive manipulations to maximally satisfy the geometric constraints imposed by a distance matrix. PolyFold is capable of simulating the complex process of protein folding even on modest personal computers, thus making it accessible to the general public for fostering citizen science. Open source code of PolyFold is freely available for download at https://github.com/Bhattacharya-Lab/PolyFold. It is implemented in cross-platform Java and binary executables are available for macOS, Linux, and Windows.

Indexed as

AlgorithmsProtein FoldingSoftwareProtein ConformationProteinsProteins

Identifiers

PMID33270805
PMCPMC7714222

What OpenQuestion holds

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LicenceCC BY
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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.