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Pregled bibliografske jedinice broj: 1216649

Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids


Batista, Jadranko; Kraljević, Antonija; Lučić, Bono
Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids // Math/Chem/Comp 2021 – 32rd MC2 Conference : Book of abstracts / Vančik, Hrvoje ; Cioslowski, Jerzy (ur.).
Zagreb: Hrvatsko kemijsko društvo, 2021. str. 40-40 (poster, recenziran, sažetak, znanstveni)


CROSBI ID: 1216649 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids

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

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

Izvornik
Math/Chem/Comp 2021 – 32rd MC2 Conference : Book of abstracts / Vančik, Hrvoje ; Cioslowski, Jerzy - Zagreb : Hrvatsko kemijsko društvo, 2021, 40-40

Skup
32nd International Course and Conference on the Interfaces among Mathematics, Chemistry and Computer Sciences: Mathematics, Chemistry, Computing (Math/Chem/Comp, MC2-32)

Mjesto i datum
Dubrovnik, Hrvatska, 07.06.2021. - 12.06.2021

Vrsta sudjelovanja
Poster

Vrsta recenzije
Recenziran

Ključne riječi
protein folding rate ; prediction ; model ; amino acid content ; sequence-based attributes

Sažetak
Protein folding is a very important problem in the biosciences that is studied experimentally but also by modelling (theoretical and simulation analyses) [1]. Undoubtedly, all information related to folding is contained in the primary structure of proteins - in the sequence of amino acids. For the past 20 years, attempts have been made to model the dependences of the protein folding constants kf (s-1), which are equal to 1 / (time needed for protein folding). It was observed in the very beginning that this is a size-dependent problem, which means that ln(kf) significantly depends on the length of the protein sequence, i.e. on the number of amino acid residues in the protein chain. Then, the dependence on the number of amino acids that take on the correct secondary structure of alpha or beta, on the topology of the 3D structure, was also observed [2]. As better predictors of protein folding constants, new structural parameters based on the total number of amino acids in regular secondary structures in the protein chain were obtained [3]. Furthermore, the parameters that calculate the permutation entropy of the secondary structure of the protein also show good agreement with the protein folding constants.

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)

Ustanove:
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Bono Lučić (autor)


Citiraj ovu publikaciju:

Batista, Jadranko; Kraljević, Antonija; Lučić, Bono
Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids // Math/Chem/Comp 2021 – 32rd MC2 Conference : Book of abstracts / Vančik, Hrvoje ; Cioslowski, Jerzy (ur.).
Zagreb: Hrvatsko kemijsko društvo, 2021. str. 40-40 (poster, recenziran, sažetak, znanstveni)
Batista, J., Kraljević, A. & Lučić, B. (2021) Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids. U: Vančik, H. & Cioslowski, J. (ur.)Math/Chem/Comp 2021 – 32rd MC2 Conference : Book of abstracts.
@article{article, author = {Batista, Jadranko and Kraljevi\'{c}, Antonija and Lu\v{c}i\'{c}, Bono}, year = {2021}, pages = {40-40}, keywords = {protein folding rate, prediction, model, amino acid content, sequence-based attributes}, title = {Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids}, keyword = {protein folding rate, prediction, model, amino acid content, 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 = {2021}, pages = {40-40}, keywords = {protein folding rate, prediction, model, amino acid content, sequence-based attributes}, title = {Modelling protein folding rates by novel descriptors based on the amount of regular secondary structure and hydrophobic amino acids}, keyword = {protein folding rate, prediction, model, amino acid content, sequence-based attributes}, publisher = {Hrvatsko kemijsko dru\v{s}tvo}, publisherplace = {Dubrovnik, Hrvatska} }




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