Evidence map›Paper›PMID 41042117›Full record

ArticleJournal of computational chemistry2025

Navigating Homogeneous Graph Paths Through Amyloidogenic and Non-Amyloidogenic Hexapeptides.

László Keresztes, Evelin Szögi, Bálint Varga, Viktor Farkas, András Perczel, Vince Grolmusz

Abstract read
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Article in Journal of computational chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

László KeresztesPIT Bioinformatics Group, Eötvös University, Budapest, Hungary.
Evelin SzögiPIT Bioinformatics Group, Eötvös University, Budapest, Hungary.
Bálint VargaPIT Bioinformatics Group, Eötvös University, Budapest, Hungary.
Viktor FarkasHUN-REN-ELTE Protein Modeling Research Group, Eötvös University, Budapest, Hungary.
András PerczelHUN-REN-ELTE Protein Modeling Research Group, Eötvös University, Budapest, Hungary.
Vince GrolmuszPIT Bioinformatics Group, Eötvös University, Budapest, Hungary.ORCID https://orcid.org/0000-0001-9456-8876

Funding

Nemzeti Kutatási és Technológiai Hivatal 2021-NKTA-62
6 · The paper itself

Abstract

Hexapeptides are increasingly applied as model systems for studying the amyloidogenic properties of oligo- and polypeptides. It is possible to construct 64 million different hexapeptides from the twenty proteinogenic amino acid residues. Today's experimental amyloid databases contain only a fraction of these annotated hexapeptides. For labeling all the possible hexapeptides as "amyloidogenic" or "non-amyloidogenic" there exist several computational predictors with good accuracy. It may be of interest to define and study a simple graph structure on the 64 million hexapeptides as nodes, when two hexapeptides are connected by an edge if they differ by only a single residue. For example, in this graph, HIKKLM is connected to AIKKLM, or HIKKNM, or HIKKLC, but it is not connected with an edge to VVKKLM or HIKNPM. In the present contribution, we consider our previously published artificial intelligence-based tool, the Budapest Amyloid Predictor (BAP for short), and demonstrate a spectacular property of this predictor in the graph defined above. We show that for any two hexapeptides predicted to be "amyloidogenic" by the BAP predictor, there exists an easily constructible path of length at most six that passes through neighboring hexapeptides all predicted to be "amyloidogenic" by BAP. For example, the predicted amyloidogenic ILVWIW and FWLCYL hexapeptides can be connected through the length-6 path ILVWIW-IWVWIW-IWVCIW-IWVCIL-FWVCIL-FWLCIL-FWLCYL in such a way that the neighbors differ in exactly one residue, and all hexapeptides on the path are predicted to be amyloidogenic by BAP. The symmetric statement also holds true for non-amyloidogenic predicted hexapeptides: For any such pair, there exists a path of length at most six, traversing only predicted non-amyloidogenic hexapeptides. It is noted that the mentioned property of the Budapest Amyloid Predictor https://pitgroup.org/bap is not proprietary; it is also true for any linear Support Vector Machine (SVM)-based predictors; therefore, for any future improvements of BAP using the linear SVM prediction technique.

Indexed as

AmyloidOligopeptidesAmyloidOligopeptidesamyloidshexapeptidesmutational graphpeptides

Identifiers

PMID41042117
PMCPMC12493017

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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.