The sequence of amino acids as the basis for the model of biological activity of peptides

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F21%3A10425705" target="_blank" >RIV/00216208:11110/21:10425705 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DKF0.ikRLp" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DKF0.ikRLp</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00214-020-02707-8" target="_blank" >10.1007/s00214-020-02707-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The sequence of amino acids as the basis for the model of biological activity of peptides

Popis výsledku v původním jazyce

The algorithm of building up a model for the biological activity of peptides as a mathematical function of a sequence of amino acids is suggested. The general scheme is the following: The total set of available data is distributed into the active training set, passive training set, calibration set, and validation set. The training (both active and passive) and calibration sets are a system of generation of a model of biological activity where each amino acid obtains special correlation weight. The numerical data on the correlation weights calculated by the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). The target function aimed to give the best result for the calibration set (not for the training set). The final checkup of the model is carried out with data on the validation set (peptides, which are not visible during the creation of the model). Described computational experiments confirm the ability of the approach to be a tool for the design of predictive models for the biological activity of peptides (expressed by pIC50).

Název v anglickém jazyce

The sequence of amino acids as the basis for the model of biological activity of peptides

Popis výsledku anglicky

The algorithm of building up a model for the biological activity of peptides as a mathematical function of a sequence of amino acids is suggested. The general scheme is the following: The total set of available data is distributed into the active training set, passive training set, calibration set, and validation set. The training (both active and passive) and calibration sets are a system of generation of a model of biological activity where each amino acid obtains special correlation weight. The numerical data on the correlation weights calculated by the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). The target function aimed to give the best result for the calibration set (not for the training set). The final checkup of the model is carried out with data on the validation set (peptides, which are not visible during the creation of the model). Described computational experiments confirm the ability of the approach to be a tool for the design of predictive models for the biological activity of peptides (expressed by pIC50).

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10600 - Biological sciences

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Theoretical Chemistry Accounts

ISSN

1432-881X

e-ISSN

—

Svazek periodika

140

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

8

Strana od-do

15

Kód UT WoS článku

000612860700001

EID výsledku v databázi Scopus

2-s2.0-85099942352