PURE: a webserver for the prediction of domains in unassigned regions in proteins

Protein domains are the structural and functional units of proteins. The ability to parse proteins into different domains is important for effective classification, understanding of protein structure, function, and evolution and is hence biologically relevant. Several computational methods are available to identify domains in the sequence. Domain finding algorithms often employ stringent thresholds to recognize sequence domains. Identification of additional domains can be tedious involving intense computation and manual intervention but can lead to better understanding of overall biological function. In this context, the problem of identifying new domains in the unassigned regions of a protein sequence assumes a crucial importance.

Accumulation of domain information of sequence homologues can substantially aid prediction of new domains. In this paper, we propose a computationally intensive, multi-step bioinformatics protocol as a web server named as PURE (Prediction of Unassigned REgions in proteins) for the detailed examination of stretches of unassigned regions in proteins. Query sequence is processed using different automated filtering steps based on length, presence of coiled-coil regions, transmembrane regions, homologous sequences and percentage of secondary structure content. Later, the filtered sequence segments and their sequence homologues are fed to PSI-BLAST, cd-hit and Hmmpfam. Data from the various programs are integrated and information regarding the probable domains predicted from the sequence is reported.

PURE protocol as a web server for rapid and comprehensive analysis of unassigned regions in the proteins. This server integrates data from different programs and provides information about the domains encoded in the unassigned regions.

Do you want to know more?

A price tag of around US$1 billion to map human proteome

Ambitious plans to catalogue and characterize all proteins in the human body — a Human Proteome Project — are being drawn up by a small group of researchers. But with a price tag of around US$1 billion, some question whether the organizers can raise enough money or momentum for such an undertaking.

Project aims to characterize all human proteins. Talking about characterizing human proteins; there are several organizations working around the globe towards this initiative, spanning across both the public and commercial domains. Having missed out on HGMP, this time the industry in India is all geared up towards the mapping of human proteome.

Molecular Connections collaborates with Plasma Proteome Institute and with Max Planck Institute of Psychiatry, Proteomics & Biomarkers Research Group that would significantly aid them in the development of their new knowledgebase CliPro.

Phylogenetics Support Tyrannosaurus Rex's Evolutionary Relationship with Birds

Tyrannosaurus rex peptide sequences are more similar to modern-day birds than to reptiles, according to new research, providing added evidence for a relatively close evolutionary relationship between dinosaurs and birds.

About a year ago, researchers from Harvard University and elsewhere first reported that they could tease minuscule amounts of protein from mastodon and T. rex bone samples that were up to 600,000 and 68 million-years-old, respectively, and analyze them by mass spectrometry.

Now, members of the same team report using molecular phylogenetics to group mastodon and T. rex based on their collagen protein peptide sequences. These latest results, appearing in today’s issue of Science, suggest T. rex is more closely related to chickens and ostriches than to alligators and seem to confirm the long-held suspicion that dinosaurs and birds have a common ancestor. They also corroborate a relationship between mastodons and modern day elephants.

for more

MEGA: A biologist-centric software for evolutionary analysis of DNA and protein sequences

The Molecular Evolutionary Genetics Analysis (MEGA) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. In addition to the tools for statistical analysis of data, MEGA provides many convenient facilities for the assembly of sequence data sets from files or web-based repositories, and it includes tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolutionary distance matrices. Here we discuss the motivation, design principles and priorities that have shaped the development of MEGA. We also discuss how MEGA might evolve in the future to assist researchers in their growing need to analyze large data set using new computational methods.