Evidence map›Paper›PMID 35561171›Full record

ArticleBioinformatics (Oxford, England)2022

LPTD: a novel linear programming-based topology determination method for cryo-EM maps.

Bahareh Behkamal, Mahmoud Naghibzadeh, Andrea Pagnani, Mohammad Reza Saberi, Kamal Al Nasr

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2022. 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

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

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

5 authors.

Bahareh BehkamalDepartment of Computer Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran.ORCID 0000-0003-4630-1178
Mahmoud NaghibzadehDepartment of Computer Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran.ORCID 0000-0001-5550-5565
Andrea PagnaniDepartment of Applied Science and Technology (DISAT), Politecnico di Torino, Torino I-10129, Italy.ORCID 0000-0002-6509-0807
Mohammad Reza SaberiMedicinal Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad 9177899191, Iran.
Kamal Al NasrDepartment of Computer Science, Tennessee State University, Nashville, TN 37209, USA.ORCID 0000-0001-8459-9070

Funding

A Computational Tool for Modeling of Protein Macromolecules Guided by Cryo-Electron Microscopy DataR15GM126509 · NIGMS · TENNESSEE STATE UNIVERSITY · PI AL NASR, KAMAL, CHEN, WEI · 2017 to 2017
$399k
NIGMS NIH HHS R15 GM126509
6 · The paper itself

Abstract

summaryTopology determination is one of the most important intermediate steps toward building the atomic structure of proteins from their medium-resolution cryo-electron microscopy (cryo-EM) map. The main goal in the topology determination is to identify correct matches (i.e. assignment and direction) between secondary structure elements (SSEs) (α-helices and β-sheets) detected in a protein sequence and cryo-EM density map. Despite many recent advances in molecular biology technologies, the problem remains a challenging issue. To overcome the problem, this article proposes a linear programming-based topology determination (LPTD) method to solve the secondary structure topology problem in three-dimensional geometrical space. Through modeling of the protein's sequence with the aid of extracting highly reliable features and a distance-based scoring function, the secondary structure matching problem is transformed into a complete weighted bipartite graph matching problem. Subsequently, an algorithm based on linear programming is developed as a decision-making strategy to extract the true topology (native topology) between all possible topologies. The proposed automatic framework is verified using 12 experimental and 15 simulated α-β proteins. Results demonstrate that LPTD is highly efficient and extremely fast in such a way that for 77% of cases in the dataset, the native topology has been detected in the first rank topology in <2 s. Besides, this method is able to successfully handle large complex proteins with as many as 65 SSEs. Such a large number of SSEs have never been solved with current tools/methods. AVAILABILITY AND IMPLEMENTATION: The LPTD package (source code and data) is publicly available at https://github.com/B-Behkamal/LPTD. Moreover, two test samples as well as the instruction of utilizing the graphical user interface have been provided in the shared readme file. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Programming, LinearProteinsCryoelectron MicroscopyModels, MolecularProtein ConformationProtein Structure, SecondaryProteins

Identifiers

PMID35561171
PMCPMC9306757

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.