Recent trends in remote homology detection: an Indian Medley

The development of remote homology detection methods is a challenging area in Bioinformatics. Sequence analysis-based approaches that address this problem have employed the use of profiles, templates and Hidden Markov Models (HMMs). These methods often face limitations due to poor sequence similarities and non-uniform sequence dispersion in protein sequence space. Search procedures are often asymmetrical due to over or under-representation of some protein families and outliers often remain undetected. Intermediate sequences that share high similarities with more than one protein can help overcome such problems. Methods such as MulPSSM and Cascade PSI-BLAST that employ intermediate sequences achieve better coverage of members in searches. Others employ peptide modules or conserved patterns of motifs or residues and are effective in overcoming dependencies on high sequence similarity to establish homology by using conserved patterns in searches. We review some of these recent methods developed in India in the recent past.