BioV Suite – a collection of programs for the study of transport protein evolution

Abstract

The Bio-V Suite is a collection of python scripts designed specifically for bioinformatic research regarding transport protein evolution. The Bio-V Suite contains nine powerful programs for Unix-based environments, each of which can be run as a standalone tool or be accessed in a programmatic fashion. These programs and their functions are as follows: TMStats generates topological statistics for transport proteins. GSAT performs shuffle-based binary alignments and is fully scalable. It can cross compare two FASTA files or individual sequences. Protocol1 performs remote PSI-BLAST searches and filters redundant/similar sequences and annotates them. Protocol2 finds homologues between FASTA lists and generates graphical reports. TSSearch uses a rapid search algorithm to find distant homologues in FASTA files in a heuristic manner. SSearch is the exhuastive version of TSSearch. GBlast will identify potential transport proteins in any genome/proteome file, or find similar transport protein homologues between two different genomes/proteomes before generating a graphical report. AncientRep will find putative transmembrane repeat units using a list of homologues. DefineFamily will generate a FASTA list to represent an entire TC family. These nine programs are tabulated with descriptions of their capabilities in Table 1.

The Amino Acid-Polyamine-Organocation Superfamily

“…The program identified numerous pairs of proteins that suggested homology, seven of which are displayed in figure 1 . The Global Alignment Program (GAP) [Devereux et al, 1984] and the similar GSAT program [Reddy and Saier, 2012] were then used to analyze the sequences, supporting the relationships suggested by SSearch [Reddy and Saier, 2012;Yen et al, 2009]. Both programs randomly shuffle and compare amino acid sequences, correcting for unusual protein composition such as those within integral membrane proteins.…”

“…The results show that the previously recognized families are more similar to each other than they are to the newly added families. This can be explained since the methods used previously were not as refined and sensitive as the ones we have recently developed [Reddy and Saier, 2012].…”

“…2.A.3) and the six new families were shown to be related using the superfamily principle which states that if protein A is related to (shares a common origin with) protein B, and protein B is related to protein C, then protein A is related to protein C. The GAP or GSAT comparison scores reported are considered sufficient to establish homology if they give 11 SD or greater [Reddy and Saier, 2012]. This value corresponds to a probability that the degree of sequence similarity occurred by chance of 10 -29 [Dayhoff et al, 1983].…”

“…This database assigns proteins to superfamilies and their respective families or subfamilies while integrating novel bioinformatics software and relevant resources [Reddy and Saier, 2012]. The importance of identification and classification of protein families and superfamilies is emphasized by the fact that structural, functional, and mechanistic data for transporters can be extrapolated from one protein to another if and only if they have been shown to be related by a common descendent [Lam et al, 2011;Saier, 1996Saier, , 1999Saier, , 2000.…”

“…A major focus of our bioinformatics laboratory has been to update and develop novel computer programs to assist in the identification and expansion of protein superfamilies [Chang et al, 2004;Reddy and Saier, 2012]. These programs have been instrumental in establishing homology amongst proteins sharing common descent.…”