Evidence map›Paper›PMID 31752663›Full record

ArticleBMC bioinformatics2019

Identification of native protein structures captured by principal interactions.

Mehdi Mirzaie

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Intrinsically Disordered Proteins: An Overview.International journal of molecular sciences · 2022
    Review
4 · The record

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5 · Who and what money

Authors and funding

1 author.

Mehdi MirzaieDepartment of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, Jalal Ale Ahmad Highway, P.O.Box: 14115-134, Tehran, Iran. mirzaie@modares.ac.ir.

Funding

Iran National Science Foundation ( INSF ) 97003215
6 · The paper itself

Abstract

backgroundEvaluation of protein structure is based on trustworthy potential function. The total potential of a protein structure is approximated as the summation of all pair-wise interaction potentials. Knowledge-based potentials (KBP) are one type of potential functions derived by known experimentally determined protein structures. Although several KBP functions with different methods have been introduced, the key interactions that capture the total potential have not studied yet.

resultsIn this study, we seek the interaction types that preserve as much of the total potential as possible. We employ a procedure based on the principal component analysis (PCA) to extract the significant and key interactions in native protein structures. We call these interactions as principal interactions and show that the results of the model that considers only these interactions are very close to the full interaction model that considers all interactions in protein fold recognition. In fact, the principal interactions maintain the discriminative power of the full interaction model. This method was evaluated on 3 KBPs with different contact definitions and thresholds of distance and revealed that their corresponding principal interactions are very similar and have a lot in common. Additionally, the principal interactions consisted of 20 % of the full interactions on average, and they are between residues, which are considered important in protein folding.

conclusionsThis work shows that all interaction types are not equally important in discrimination of native structure. The results of the reduced model based on principal interactions that were very close to the full interaction model suggest that a new strategy is needed to capture the role of remaining interactions (non-principal interactions) to improve the power of knowledge-based potential functions.

Indexed as

Image Processing, Computer-AssistedKnowledge BasesPrincipal Component AnalysisProtein BindingProtein ConformationProtein FoldingProteinsReproducibility of ResultsProteinsDecoy setKnowledge-based potentialNative structurePrincipal interaction

Identifiers

PMID31752663
PMCPMC6873546

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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.