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A World of New Discovery. STRUCTFAST : Novel Dynamic Programming and Profile Scoring CASP6 & CAFASP4 Servers EXPM, BNMX &SFST Aleksandar Poleksic, Joseph F. Danzer, & Derek A. Debe. Derek A. Debe, Aleksandar Poleksic, Joseph F. Danzer, respectively.

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A World of New Discovery

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A world of new discovery

A World of New Discovery

STRUCTFAST: Novel Dynamic Programming and Profile Scoring

CASP6 & CAFASP4 Servers EXPM, BNMX &SFST

Aleksandar Poleksic, Joseph F. Danzer, & Derek A. Debe


A world of new discovery

Derek A. Debe, Aleksandar Poleksic, Joseph F. Danzer, respectively.


Outline what s different about our methods

OutlineWhat's Different About Our Methods?

1. Bridge-Bulge Dynamic Programming

2. Analytical Profile-Profile Scoring

3. Convergent Island Statistics p-Values


Structfast

STRUCTFAST

StructureRealization Utilizing Cogent Tips From Aligned Structural Templates

Basic Principle: Gaps known to exist should not be strongly penalized.

Known Gap

Known Gap

Structure Alignment of Homologous Crystal Structures

Structure-Structure alignments give us clues...


Bridge bulge dynamic programming

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Bridge-BulgeDynamic Programming

Dynamic Programming

STRUCTFAST

BIG-TOWNSOWN---

BIGBROWNTOWNOWN

BIG-----TOWNSOWN

BIGBROWNTOWN-OWN


A world of new discovery

CASP Target T0247

Template: 1pj5A. “Bridge” taken from 1wooA

Query: 2 AQ---QTPLYEQHTLCGARMVDFHGWMMPLHYGS-------------------------- 32

P H GA GW P

Sbjct: 427 PrnlrVSPFHARHKELGAFFLEAGGWERPYWFEAnaallkempaewlppardawsgmfss 486

Query: 33 --QIDEHHAVRTDAGMFDVSHMTIVDLRGSRTREFLRYLLANDVAKLtkSGKALYSGMLN...

E RT M D G L L D AK G Y L

Sbjct: 487 piAAAEAWKTRTAVAMYDMTPLKRLEVSGPGALKLLQELTTADLAKK—PGAVTYTLLLD...

Query: 91 ASGGVIDDLIVYYFTEDFFRLVVNSATREKDLSWITQHAEPF-----GIEI-TVRDDLSM 144

GGV D V ED F L N H

Sbjct: 545 HAGGVRSDITVARLSEDTFQLGANGNIDTAYFERAARHQTQSgsatdWVQVrDTTGGTCC 604

Query: 145 IAVQGPNAQAKAATLFN-DAQRQAV-EGMKPFFGVQAGDLFIATTGYTGEAGYEIALPNE 202

I GP A D Y GE G E

Sbjct: 605 IGLWGPLARDLVSKVSDdDFTNDGLkYFRAKNVVIGGIPVTAMRLSYVGELGWELYTSAD 664

Query: 203 KAADFWRALVEAG----VKPCGLGARDTLRLEAGMNLYGQEMDETISPLAANMGWTIAWE 258

W AL AG V G A LRLE G G M P A G

Sbjct: 665 NGQRLWDALWQAGqpfgVIAAGRAAFSSLRLEKGYRSWGTDMTTEHDPFEAGLGFAVKMA 724

Query: 259 paDRDFIGREALEVQREHG-TEKLVGLVMTE-KGVLRNELPVRFtdaqGNQHEGIITSGT 316

FIG ALE E L L PV Q G TS

Sbjct: 725 --KESFIGKGALEGRTEEAsARRLRCLTIDDgRSIVLGKEPVFY----KEQAVGYVTSAA 778

Query: 317 FSPTLGYSIALARVPEGI--GETAIVQIRNREMPVKVTKPVFV-RNGKAV 363

T IA P G R VT

Sbjct: 779 YGYTVAKPIAYSYLPGTVsvGDSVDIEYFGRRITATVTEDPLYdPKMTRL 828

1wooA

1pj5A

1pj5A “Bulge”


A world of new discovery

CASP Target T0263

Template: 1iujB. “Bridge” taken from 1a7gA

Query: 1 MaTLLQLHFAFN-GpFGDAMAEQLKPLAESINQEPGFLWKVWTESEknhEAGGIYL---- 55

M E A PGF G Y

Sbjct: 1 M-FVTMNRIPVRpE-YAEQFEEAFRQRARLVDRMPGFIRNLVLRPK---NPGDPYVvmtl 55

Query: 56 FTDEKSALAYLE--KHTARLKNLG-------VEEVVAKVFDV 88

E A E G F V

Sbjct: 56 WESEEAFRAWTEspAFKEGHARSGtlpkeafLGPNRLEAFEV 97

1a7gA

1iujB

1iujB “Bulge”


Outline what s different about our methods1

OutlineWhat's Different About Our Methods?

1. Bridge-Bulge Dynamic Programming

2. Analytical Profile-Profile Scoring

3. Convergent Island Statistics p-Values


A world of new discovery

STRUCTFASTScoring

Score = ?

Seq1: VLKRAKAKGDRLILEADGEKNKLNVIF

Seq2: FRGVTLSAKEFKKIVDTFSQLSDSVNFQVDKEGIKL

L DB

Profile-Profile Case


A world of new discovery

STRUCTFASTScoring

Like Throwing Dice

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Which die is

more likely to

generate D?

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Score = log(PL(D) / PB(D))

We solve this analytically.

Details to be published...


A world of new discovery

How do we evaluate the statistical significance of our STRUCTFAST alignments?


The challenge

4

12

e

The Challenge

Secondary Structure

Profiles

Parameters

(Gaps, et al.)

Bridges & Bulges

Rigorous

Statistical Significance

of the Alignment

(p-Value)


A world of new discovery

Island Statistics

Altschul, et al.

Not fast enough for full database search


A world of new discovery

.

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Convergence Trick

K

Lower p-values

Higher p-values

Higher p-values

Lower p-values

True

True K

We shuffle until there is evidence that the

sequences are not related.


A world of new discovery

Benefits of CIS

(Convergent Island Statistics)

Analytical e-values

No need for distribution fitting

Analytical (yet tunable) trade-off between

speed and sensitivity

Allows one to change any algorithm parameters

on the fly


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