engleski

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

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.

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

Basic grant of MZO/RBI to Bono Lučić