Improving sequence alignments for intrinsically disordered proteins.
Here we analyze sequence alignments for intrinsically disordered proteins. For 55 disordered protein families we measure the performance of different scoring matrices and propose one adjusted to disordered regions. An iterative algorithm of realigning sequences and recalculating matrices is designed and tested. For each matrix we also test a wide range of gap penalties. Results show an improvement in the ability to detect and discriminate related disordered proteins whose average sequence identity with the other family members is below 50%.
Radivojac
Predrag
P
Center for Information Science and Technology, Temple University, USA.
Obradovic
Zoran
Z
Brown
Celeste J
CJ
Dunker
A Keith
AK
D000595:Amino Acid Sequence; D005075:Biological Evolution; D003201:Computers; D016208:Databases, Factual; D008390:Markov Chains; D011336:Probability; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software
D011506:Proteins