morFeus network of orthology for fission yeast Apc13, a subunit of the Anaphase Promoting Complex.
Due to the size of the databases, morFeus has become VERY slow. We have taken it off-line and are trying to improve its speed.
We are interested in discovering remote orthologs. Identifying orthologous proteins is one of the key tasks in computational biology: we need to know a protein’s orthologs to understand its evolution. Orthologs also tell us, whether the process a protein is involved in, is conserved beyond model species and across kingdoms.
Orthologs are equally important for wet-lab research: we transfer functional information across orthologous proteins and can therefore provide testable hypothesis for a protein’s function for uncharacterized proteins.
The level of sequence conservation even between orthologs is however sometimes below the detection limit of standard software and settings.
We have addressed this problem and developed a web-based method, morFeus (Wagner, et al., BMC Bioinformatics 15 (1), 263, 2014, doi: 10.1186/1471-2105-15-263) for the detection of orthologs in the twilight and midnight zone of sequence similarity.
We compare weighted, binary representations of sequence alignments from a relaxed BLAST search and cluster hits based on their similarity to the query. Iterative reciprocal BLAST searches are carried out to verify orthology. Not only the query, but also other verified orthologs can establish orthology and include further hits for back-BLASTs. In a final step, a network of orthology (see figure) is created and a score independent of the BLAST E-value is calculated for putative orthologs using centrality scoring. We have tested morFeus against the state-of-the-art resources HomoloGene and Inparanoid and achieve significantly higher sensitivity with equal specificity.
This work was supported by the Max Planck Society and Scionics Computer Innovation.