AI Article Synopsis

  • Direct-coupling analysis (DCA) has been adapted into RADI/raDIMod to predict protein structures by grouping residues into two categories: polar and non-polar, based on their chemical properties.
  • This method simplifies the analysis and reduces the number of sequences needed for alignment while still capturing essential features of protein folding due to hydrophobic forces.
  • RADI and raDIMod deliver accurate protein conformations, especially when more than 30-50% of the sequence can be modeled using super-secondary structure motifs, demonstrating that different residue groupings can lead to similar structural predictions.

Article Abstract

Direct-coupling analysis (DCA) for studying the coevolution of residues in proteins has been widely used to predict the three-dimensional structure of a protein from its sequence. We present RADI/raDIMod, a variation of the original DCA algorithm that groups chemically equivalent residues combined with super-secondary structure motifs to model protein structures. Interestingly, the simplification produced by grouping amino acids into only two groups (polar and non-polar) is still representative of the physicochemical nature that characterizes the protein structure and it is in line with the role of hydrophobic forces in protein-folding funneling. As a result of a compressed alphabet, the number of sequences required for the multiple sequence alignment is reduced. The number of long-range contacts predicted is limited; therefore, our approach requires the use of neighboring sequence-positions. We use the prediction of secondary structure and motifs of super-secondary structures to predict local contacts. We use RADI and raDIMod, a fragment-based protein structure modelling, achieving near native conformations when the number of super-secondary motifs covers >30-50% of the sequence. Interestingly, although different contacts are predicted with different alphabets, they produce similar structures.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8061457PMC
http://dx.doi.org/10.1093/nargab/lqab027DOI Listing

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