Walter Pirovano1, K Anton Feenstra, Jaap Heringa. 1. Centre for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, De Boelelaan 1081A, 1081 HV Amsterdam, The Netherlands.
Abstract
MOTIVATION: Membrane-bound proteins are a special class of proteins. The regions that insert into the cell-membrane have a profoundly different hydrophobicity pattern compared with soluble proteins. Multiple alignment techniques use scoring schemes tailored for sequences of soluble proteins and are therefore in principle not optimal to align membrane-bound proteins. RESULTS: Transmembrane (TM) regions in protein sequences can be reliably recognized using state-of-the-art sequence prediction techniques. Furthermore, membrane-specific scoring matrices are available. We have developed a new alignment method, called PRALINETM, which integrates these two features to enhance multiple sequence alignment. We tested our algorithm on the TM alignment benchmark set by Bahr et al. (2001), and showed that the quality of TM alignments can be significantly improved compared with the quality produced by a standard multiple alignment technique. The results clearly indicate that the incorporation of these new elements into current state-of-the-art alignment methods is crucial for optimizing the alignment of TM proteins. AVAILABILITY: A webserver is available at http://www.ibi.vu.nl/programs/pralinewww.
MOTIVATION: Membrane-bound proteins are a special class of proteins. The regions that insert into the cell-membrane have a profoundly different hydrophobicity pattern compared with soluble proteins. Multiple alignment techniques use scoring schemes tailored for sequences of soluble proteins and are therefore in principle not optimal to align membrane-bound proteins. RESULTS: Transmembrane (TM) regions in protein sequences can be reliably recognized using state-of-the-art sequence prediction techniques. Furthermore, membrane-specific scoring matrices are available. We have developed a new alignment method, called PRALINETM, which integrates these two features to enhance multiple sequence alignment. We tested our algorithm on the TM alignment benchmark set by Bahr et al. (2001), and showed that the quality of TM alignments can be significantly improved compared with the quality produced by a standard multiple alignment technique. The results clearly indicate that the incorporation of these new elements into current state-of-the-art alignment methods is crucial for optimizing the alignment of TM proteins. AVAILABILITY: A webserver is available at http://www.ibi.vu.nl/programs/pralinewww.
Authors: Leila Abbas; Saeed Hajihashemi; Lucy F Stead; Gordon J Cooper; Tracy L Ware; Tim S Munsey; Tanya T Whitfield; Stanley J White Journal: J Physiol Date: 2011-01-24 Impact factor: 5.182
Authors: Manpreet Kaur Rawal; Mohammad Firoz Khan; Khyati Kapoor; Neha Goyal; Sobhan Sen; Ajay Kumar Saxena; Andrew M Lynn; Joel D A Tyndall; Brian C Monk; Richard D Cannon; Sneha Sudha Komath; Rajendra Prasad Journal: J Biol Chem Date: 2013-07-03 Impact factor: 5.157