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Comparative Protein Modeling: Enhancing Accuracy Through Structural Templates

This study explores the use of multiple sequence alignments in comparative protein modeling to improve accuracy. The research identifies structural templates by aligning designed sequences and discusses the efficacy of reverse BLAST method in finding templates for modeling. The experiment tests sequence quality and explores optimizing structural diversity and entropy prediction. Future work includes assessing different remote homology detection approaches and retrodicting CASP targets. Collaborators include researchers from Stanford University, Harvard University, and Xencor, Inc.

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Comparative Protein Modeling: Enhancing Accuracy Through Structural Templates

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  1. Identifying structural templates using alignments of designed sequences Stefan M. Larson Pande Group Biophysics Program December, 2002 smlarson@stanford.edu

  2. 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

  3. 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)

  4. Computational protein design New sequence Iterative refinement Native structure

  5. “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

  6. “Reverse BLAST”: finding templates for comparative modeling Larson SM, Garg A, Desjarlais JR, Pande VS. (2003) Proteins: Structure, Function, and Genetics

  7. Experiment: Sequence quality ASDFASDFASDFAS FDSAFASDFASDFA FASDFASDFASDFA FHFDIDIFERIDKD ADHFYWTEFHHASD ASDFYEFHGASDFV ADHFYWTEFHHASD ASDFYEFHGASDFV DGSAHDYERCNDFK AKSLKALSDFPLAK Design BLAST E<0.01

  8. Results: Sequence quality

  9. GENOMICSEQUENCES GENOMICSEQUENCES Method: “Reverse BLAST” Designed Sequences Hypothetical Proteins Structural Templates THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF E<0.01 BLAST THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF THEHYPOTHETICALPROTEINSEQUENCEASDFASDFASDFAASDFASDFASDFASDFASDFASDFASDFASDFHWERHWIENCVASDFNWEFUWEF

  10. Do the designed sequences help? Correctly identified structural templates fold-increase in # of templates fold-increase in # of genes total hits

  11. Remote homology detection

  12. Optimizing structural diversity sequence entropy prediction accuracy prediction coverage mean pairwise %ID mean native %ID

  13. 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.

  14. Collaborators Stanford University • Amit Garg • Dr. Vijay Pande Harvard University • Jeremy England Xencor, Inc. • Dr. John Desjarlais

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