Rapid assessment of correlated amino acids from pair-to-pair (P2P) substitution matrices.
Identification of correlated amino acids in proteins has been a topic of broad interest in view of its functional implications and importance in protein design. A new set of pair-to-pair (P2P) substitution matrices for amino acids was recently introduced as a useful tool for inferring information on such correlated sites. We present a website developed for automated application of these matrices for analysis of query sequences. The site offers options for graphical analysis of correlations, as well as visualization of correlated amino acids on representative, structurally characterized, members of the examined family of sequences.


BACKGROUND
http://www.ccbb.pitt.edu/p2p.
Eyal
Eran
E
Department of Computational Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA. eyal@ccbb.pitt.edu
Pietrokovski
Shmuel
S
Bahar
Ivet
I
D000596:Amino Acids / Q000737:chemistry*; D001331:Automation; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D015233:Models, Statistical; D009154:Mutation; D011336:Probability; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D014584:User-Computer Interface
D000596:Amino Acids; D011506:Proteins