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Pregled bibliografske jedinice broj: 1216645

Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates


Batista, Jadranko; Kraljević, Antonija; Lučić, Bono
Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates // Book of abstracts, Math/Chem/Comp 2022 – 33rd MC2 Conference / Vančik, Hrvoje ; Cioslowski, Jerzy (ur.).
Zagreb: Hrvatsko kemijsko društvo, 2022. str. 30-30 (poster, recenziran, sažetak, znanstveni)


CROSBI ID: 1216645 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates

Autori
Batista, Jadranko ; Kraljević, Antonija ; Lučić, Bono

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of abstracts, Math/Chem/Comp 2022 – 33rd MC2 Conference / Vančik, Hrvoje ; Cioslowski, Jerzy - Zagreb : Hrvatsko kemijsko društvo, 2022, 30-30

Skup
33rd MC2 Conference (Math/Chem/Comp 2022)

Mjesto i datum
Dubrovnik, Hrvatska, 06.06.2022. - 10.06.2022

Vrsta sudjelovanja
Poster

Vrsta recenzije
Recenziran

Ključne riječi
protein folding rate, prediction, model, protein secondary structure, sequence-based attributes

Sažetak
Protein folding is a very important problem in life sciences that has been studied experimentally, but also through modelling (theoretical and simulation analyses).[1] It is assumed that all the information that determines the protein folding process and the protein folding rate is contained in the primary structure of the proteins (i.e. in the sequence of the amino acids). Modelling the protein folding constants kf (s-1), which are equal to 1 / (time required for protein folding), is a size-dependent problem, which means that ln (kf) depends on the length of the protein sequence. Here we have defined and calculated new descriptors (features) that take into account mutual arrangements of hydrophobic amino acids in the primary structure such as the average distance between amino acids. These attributes were found to have better agreement (correlation) with protein folding rates in three protein sets than protein length, relative contact order distance or other parameters calculated from the protein's primary sequence or its three-dimensional structure.

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Kemija

Napomena
Basic grant of MZO/RBI to Bono Lučić



POVEZANOST RADA


Projekti:
EK-KF-KK.01.1.1.01.0002 - Bioprospecting Jadranskog mora (Jerković, Igor; Dragović-Uzelac, Verica; Šantek, Božidar; Čož-Rakovac, Rozelinda; Kraljević Pavelić, Sandra; Jokić, Stela, EK ) ( CroRIS)

Profili:

Avatar Url Bono Lučić (autor)


Citiraj ovu publikaciju:

Batista, Jadranko; Kraljević, Antonija; Lučić, Bono
Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates // Book of abstracts, Math/Chem/Comp 2022 – 33rd MC2 Conference / Vančik, Hrvoje ; Cioslowski, Jerzy (ur.).
Zagreb: Hrvatsko kemijsko društvo, 2022. str. 30-30 (poster, recenziran, sažetak, znanstveni)
Batista, J., Kraljević, A. & Lučić, B. (2022) Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates. U: Vančik, H. & Cioslowski, J. (ur.)Book of abstracts, Math/Chem/Comp 2022 – 33rd MC2 Conference.
@article{article, author = {Batista, Jadranko and Kraljevi\'{c}, Antonija and Lu\v{c}i\'{c}, Bono}, year = {2022}, pages = {30-30}, keywords = {protein folding rate, prediction, model, protein secondary structure, sequence-based attributes}, title = {Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates}, keyword = {protein folding rate, prediction, model, protein secondary structure, sequence-based attributes}, publisher = {Hrvatsko kemijsko dru\v{s}tvo}, publisherplace = {Dubrovnik, Hrvatska} }
@article{article, author = {Batista, Jadranko and Kraljevi\'{c}, Antonija and Lu\v{c}i\'{c}, Bono}, year = {2022}, pages = {30-30}, keywords = {protein folding rate, prediction, model, protein secondary structure, sequence-based attributes}, title = {Novel structural attributes based on the average distances of hydrophobic amino acids improve models for predicting protein folding rates}, keyword = {protein folding rate, prediction, model, protein secondary structure, sequence-based attributes}, publisher = {Hrvatsko kemijsko dru\v{s}tvo}, publisherplace = {Dubrovnik, Hrvatska} }




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