
For non-homologous proteins, and after cross-validation, the methods reviewed in this article exhibit a probability index (percentage of correctly predicted residues per predicted residues) of 59-65.5% according to the methods employed with a standard deviation of 7% for three conformational states: alpha-helix, beta-strand and coil. These present limitations in the accuracy of prediction are related both to the limited number of known structures and to the effect of long-range interactions. The methods based on sequence similarity can improve the accuracy of prediction by expressing the homology of the protein to be predicted explicitly with proteins in the database. Under these circumstances, the probability index can reach 87% with a standard deviation of 6.6%. This property was used for modelling homologous proteins by assisting in amino acid sequence alignments. Examples will be given for the alignment of serine proteinases.
Models, Molecular, Molecular Structure, Protein Conformation, [SDV]Life Sciences [q-bio], Molecular Sequence Data, Serine Endopeptidases, Proteins, Pattern Recognition, Automated, [SDV] Life Sciences [q-bio], Drug Design, Sequence Homology, Nucleic Acid, Animals, Humans, Amino Acid Sequence
Models, Molecular, Molecular Structure, Protein Conformation, [SDV]Life Sciences [q-bio], Molecular Sequence Data, Serine Endopeptidases, Proteins, Pattern Recognition, Automated, [SDV] Life Sciences [q-bio], Drug Design, Sequence Homology, Nucleic Acid, Animals, Humans, Amino Acid Sequence
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