Prediction and classification of domain structural classes

Abstract

Can the coupling effect among different amino acid components be used to improve the prediction of protein structural classes? The answer is yes according to the study by Chou and Zhang (Crit. Rev. Biochem. Mol. Biol. 30:275-349, 1995), but a completely opposite conclusion was drawn by Eisenhaber et al. when using a different dataset constructed by themselves (Proteins 25:169-179, 1996). To resolve such a perplexing problem, predictions were performed by various approaches for the datasets from an objective database, the SCOP database (Murzin, Brenner, Hubbard, and Chothia. J. Mol. Biol. 247:536-540, 1995). According to SCOP, the classification of structural classes for protein domains is based on the evolutionary relationship and on the principles that govern the 3D structure of proteins, and hence is more natural and reliable. The results from both resubstitution tests and jackknife tests indicate that the overall rates of correct prediction by the algorithm incorporated with the coupling effect among different amino acid components are significantly higher than those by the algorithms without using such an effect. It is elucidated through an analysis that the main reasons for Eisenhaber et al. to have reached an opposite conclusion are the result of (1) misusing the component-coupled algorithm, and (2) using a conceptually incorrect rule to classify protein structural classes. The formulation and analysis presented in this article are conducive to clarify these problems, helping correctly to apply the prediction algorithm and interpret the results.

Prediction of structural classes for protein sequences and domains—Impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy

“…Although it is commonly recognized that resubstitution test leads to unrealistically high accuracies, traditionally this results is still being reported. In contrast, the jackknife test is perceived as very rigorous and reliable to evaluate classification accuracy and generalization abilities of the tested algorithms [3,25,[33][34][35]. Although we do not argue that the jackknife test is reliable, at the same time it is computationally very expensive.…”

iAMP-2L: A two-level multi-label classifier for identifying antimicrobial peptides and their functional types

“…To perform graphic analysis for the current case, let us consider the standard vectors [81,82] or norms [83] for AMPs and non-AMPs that were originally introduced for studying protein structural classification [81][82][83]. According to Eq.…”

Eukaryotic and prokaryotic promoter prediction using hybrid approach

“…Here, the MD was used to measure the similarity level between test sequence and training data. Commonly, the prediction rule can be formulated by (Chou et al 1998):…”