Evidence map›Paper›PMID 37707646›Full record

ArticleAmino acids2023

Using the local symmetry in amino acids sequences of polypeptides to improve the predictive potential of models of their inhibitor activity.

Alla P Toropova, Andrey A Toropov

Abstract read
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In one paragraph

Article in Amino acids, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Alla P ToropovaLaboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy. alla.toropova@marionegri.it.
Andrey A ToropovLaboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The minimal inhibitory concentrations (pMIC) are a valuable measure of the biological activity of polypeptides. Numerical data on the pMIC are necessary to systematize knowledge on polypeptides' biochemical behaviour. The model of negative decimal logarithm of pMIC of polypeptides in the form of a mathematical function of a sequence of amino acids is suggested. The suggested model is based on the so-called correlation weights of amino acids together with the correlation weights of fragments of local symmetry (FLS). Three kinds of the FLS are considered: (i) three-symbol fragments '…xyx…', (ii) four-symbol fragments '…xyyx…', and (iii) five-symbol fragments '…xyzyx…'. The models built using the Monte Carlo technique improved by applying the index of ideality of correlation (IIC) and correlation intensity index (CII).

Indexed as

Amino AcidsQuantitative Structure-Activity RelationshipMonte Carlo MethodPeptidesSoftwareAmino AcidsPeptidesCORAL softwareFragment of local symmetryInhibitor activityMonte Carlo methodPolypeptide

Identifiers

PMID37707646

What OpenQuestion holds

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Registered trials

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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.