Identifying structural templates using Identifying structural templates using alignments of designed sequencesalignments of designed sequences

Stefan M. LarsonPande GroupBiophysics ProgramDecember, 2002 smlarson@stanford.edu

Structure prediction & sequence spaceStructure prediction & sequence space

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Multiple sequence alignments aid Multiple sequence alignments aid comparative protein modelingcomparative 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 designComputational protein design

Native structure

Iterative refinementNew sequence

Large scale sequence Large scale sequence generationgeneration

200,000Total sequences generated

4,000Processors available

80 daysTotal time of data collection

26,400Total backbone variants

264Total structures

“Reverse BLAST” study:

““Reverse BLAST”: Reverse BLAST”: finding templates for finding templates for

comparative modelingcomparative modeling

Larson SM, Garg A, Desjarlais JR, Pande VS. (2003) Proteins: Structure, Function, and Genetics

Experiment: Sequence qualityExperiment: Sequence quality

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Design BLAST E<0.01

Results: Sequence qualityResults: Sequence quality

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Designed sequence profile (ranked by E-value)

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Method: “Reverse BLAST”Method: “Reverse BLAST”

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BLAST E<0.01

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Designed Sequences Hypothetical Proteins Structural Templates

Do the designed sequences help?Do the designed sequences help?

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Remote homology detectionRemote homology detection

Optimizing structural diversityOptimizing structural diversity

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RMSD of structural ensemble (Angstroms)

(%)

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Seq

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sequence entropy

prediction accuracy

prediction coverage

mean pairwise %ID

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Future workFuture 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.

CollaboratorsCollaborators

Stanford University• Amit Garg• Dr. Vijay Pande

Harvard University• Jeremy England

Xencor, Inc.• Dr. John Desjarlais