Predicting the Types of J-Proteins Using Clustered Amino Acids

Abstract EN

J-proteins are molecular chaperones and present in a wide variety of organisms from prokaryote to eukaryote.

Based on their domain organizations, J-proteins can be classified into 4 types, that is, Type I, Type II, Type III, and Type IV.

Different types of J-proteins play distinct roles in influencing cancer properties and cell death.

Thus, reliably annotating the types of J-proteins is essential to better understand their molecular functions.

In the present work, a support vector machine based method was developed to identify the types of J-proteins using the tripeptide composition of reduced amino acid alphabet.

In the jackknife cross-validation, the maximum overall accuracy of 94% was achieved on a stringent benchmark dataset.

We also analyzed the amino acid compositions by using analysis of variance and found the distinct distributions of amino acids in each family of the J-proteins.

To enhance the value of the practical applications of the proposed model, an online web server was developed and can be freely accessed.