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Identifying structural templates using alignments of designed sequences. Stefan M. Larson Pande Group Biophysics Program December, 2002 smlarson@stanford.edu. Structure prediction & sequence space. ASDJFHLKASD ASDFLHUHOUI QWEONBLQWER ASDFPOIQWER QWEORSADFLK. ASDJFHLKASDLFH
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Identifying structural templates using alignments of designed sequences Stefan M. Larson Pande Group Biophysics Program December, 2002 smlarson@stanford.edu
Structure prediction & sequence space ASDJFHLKASD ASDFLHUHOUI QWEONBLQWER ASDFPOIQWER QWEORSADFLK ASDJFHLKASDLFH ASDFLHUHOUIQWE QWEONBLQWEROKJ ASDFPOIQWERUHO QWEORSADFLKJIJ ASDJFHLKASDLFHTJYH ASDFLHUHOUIQWEDFGH QWEONBLQWEROKJDGHJ ASDFPOIQWERUHODHGR QWEORSADFLKJIJGHFG QWOIEGTXKNBVALHERT ASDLFHIUWERHSDDFGH KBJDDURMWOFBMFERTJ FGJDKEGORTMVIRGHRT ASDJFHLKASDLFHTJYH ASDFLHUHOUIQWEDFGH QWEONBLQWEROKJDGHJ ASDFPOIQWERUHODHGR QWEORSADFLKJIJGHFG
Multiple sequence alignments aid comparative protein modeling • 1 in 3 sequences are recognizably related to at least one protein structure. • A significant fraction of the remaining 2/3 have solved structural homologues, but they are not recognized through sequence similarity searching techniques. • Marti-Renom et al. (2000) • Multiple sequence alignments greatly improve the efficacy and accuracy of almost all phase of comparative modeling. • Venclovas (2001)
Computational protein design New sequence Iterative refinement Native structure
“Reverse BLAST” study: Total structures 264 Total backbone variants 26,400 Total time of data collection 80 days Processors available 4,000 Total sequences generated 200,000 Large scale sequence generation
“Reverse BLAST”: finding templates for comparative modeling Larson SM, Garg A, Desjarlais JR, Pande VS. (2003) Proteins: Structure, Function, and Genetics
Experiment: Sequence quality ASDFASDFASDFAS FDSAFASDFASDFA FASDFASDFASDFA FHFDIDIFERIDKD ADHFYWTEFHHASD ASDFYEFHGASDFV ADHFYWTEFHHASD ASDFYEFHGASDFV DGSAHDYERCNDFK AKSLKALSDFPLAK Design BLAST E<0.01
GENOMICSEQUENCES GENOMICSEQUENCES Method: “Reverse BLAST” Designed Sequences Hypothetical Proteins Structural Templates THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF E<0.01 BLAST THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF
Do the designed sequences help? Correctly identified structural templates fold-increase in # of templates fold-increase in # of genes total hits
Optimizing structural diversity sequence entropy prediction accuracy prediction coverage mean pairwise %ID mean native %ID
Future work • Compare “reverse BLAST” to other remote homology detection approaches (3D-PSSM, HHMER, etc). • Retrodict CASP targets, especially those which were not successfully predicted by comparative modeling. • Increase the coverage and accuracy of the designed sequence sets.
Collaborators Stanford University • Amit Garg • Dr. Vijay Pande Harvard University • Jeremy England Xencor, Inc. • Dr. John Desjarlais