Protein Fold recognition

Morten Nielsen,CBS, BioCentrum,

DTU

Objectives

• Understand the basic concepts of fold recognition

• Learn why even sequences with very low sequence similarity can be modeled– Understand why is %id such a terrible

measure for reliability

• See the beauty of sequence profiles– Position specific scoring matrices (PSSMs)

Protein Homology modeling?

• Identify template(s) – initial alignment• Can give you protein function

• Improve alignment• Can give you active site

• Backbone generation• Loop modeling

• Most difficult part• Side chains• Refinement• Validation

How to do it?

Identify fold (template) for modeling– Find the structure in

the PDB database that resembles your new protein the most

– Can be used to predict function

– And maybe active sites

Align protein sequence to template– Simple alignment

methods– Sequence profiles– Threading methods– Pseudo force fields

Model side chains and loops

Homology modeling and the human genome

Identification of fold

If sequence similarity is high proteins share structure (Safe zone)

If sequence similarity is low proteins may share structure (Twilight zone)

Most proteins do not have a high sequence homologous partner

Rajesh Nair & Burkhard Rost Protein Science, 2002, 11, 2836-47

Example.

>1K7C.A TTVYLAGDSTMAKNGGGSGTNGWGEYLASYLSATVVNDAVAGRSARSYTREGRFENIADVVTAGDYVIVEFGHNDGGSLSTDNGRTDCSGTGAEVCYSVYDGVNETILTFPAYLENAAKLFTAKGAKVILSSQTPNNPWETGTFVNSPTRFVEYAELAAEVAGVEYVDHWSYVDSIYETLGNATVNSYFPIDHTHTSPAGAEVVAEAFLKAVVCTGTSLKSVLTTTSFEGTCL

• What is the function• Where is the active site?

A post doc in our group did her PhD obtaining the structure of the sequence below

What would you do?

• Function• Run Blast against PDB

• No significant hits

• Run Blast against NR (Sequence database)• Function is Acetylesterase?

• Where is the active site?

Example. Where is the active site?

1WAB Acetylhydrolase

1G66 Acetylxylan esterase

1USW Hydrolase

Example. Where is the active site?

• Align sequence against structures of known acetylesterase, like• 1WAB, 1FXW, …

• Cannot be aligned. Too low sequence similarity

1K7C.A 1WAB._ RMSD 11.2397QAL 1K7C.A 71 GHNDGGSLSTDNGRTDCSGTGAEVCYSVYDGVNETILTFDAL 1WAB._ 160 GHPRAHFLDADPGFVHSDGTISH--HDMYDYLHLSRLGY

Is it really impossible?

Protein homology modeling is only possibleif %id greater than 30-50%

WRONG!!!

!!!!

Why %id is so bad!!

1200 models sharing 25-95% sequence identity with the submitted sequences (www.expasy.ch/swissmod)

Identification of correct fold

• % ID is a poor measure– Many evolutionary related proteins

share low sequence homology– A short alignment of 5 amino acids can

share 100% id, what does this mean?• Alignment score even worse

– Many sequences will score high against every thing (hydrophobic stretches)

• P-value or E-value more reliable

What are P and E values?

• E-value– Number of expected hits

in database with score higher than match

– Depends on database size

• P-value – Probability that a

random hit will have score higher than match

– Database size independent Score

P(S

core

)

Score 15010 hits with higher score (E=10)10000 hits in database => P=10/10000 = 0.001

What goes wrong when Blast fails?

• Conventional sequence alignment uses a (Blosum) scoring matrix to identify amino acids matches in the two protein sequences

Blosum scoring matrix

A R N D C Q E G H I L K M F P S T W Y VA 4 -1 -2 -2 0 -1 -1 0 -2 -1 -1 -1 -1 -2 -1 1 0 -3 -2 0R -1 5 0 -2 -3 1 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1 -3 -2 -3N -2 0 6 1 -3 0 0 0 1 -3 -3 0 -2 -3 -2 1 0 -4 -2 -3D -2 -2 1 6 -3 0 2 -1 -1 -3 -4 -1 -3 -3 -1 0 -1 -4 -3 -3C 0 -3 -3 -3 9 -3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1 -2 -2 -1Q -1 1 0 0 -3 5 2 -2 0 -3 -2 1 0 -3 -1 0 -1 -2 -1 -2E -1 0 0 2 -4 2 5 -2 0 -3 -3 1 -2 -3 -1 0 -1 -3 -2 -2G 0 -2 0 -1 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2 -2 -3 -3H -2 0 1 -1 -3 0 0 -2 8 -3 -3 -1 -2 -1 -2 -1 -2 -2 2 -3I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1 -3 -1 3L -1 -2 -3 -4 -1 -2 -3 -4 -3 2 4 -2 2 0 -3 -2 -1 -2 -1 1K -1 2 0 -1 -3 1 1 -2 -1 -3 -2 5 -1 -3 -1 0 -1 -3 -2 -2M -1 -1 -2 -3 -1 0 -2 -3 -2 1 2 -1 5 0 -2 -1 -1 -1 -1 1F -2 -3 -3 -3 -2 -3 -3 -3 -1 0 0 -3 0 6 -4 -2 -2 1 3 -1P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4 7 -1 -1 -4 -3 -2S 1 -1 1 0 -1 0 0 0 -1 -2 -2 0 -1 -2 -1 4 1 -3 -2 -2T 0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5 -2 -2 0W -3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1 1 -4 -3 -2 11 2 -3Y -2 -2 -2 -3 -2 -1 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2 2 7 -1V 0 -3 -3 -3 -1 -2 -2 -3 -3 3 1 -2 1 -1 -2 -2 0 -3 -1 4

What goes wrong when Blast fails?

• Conventional sequence alignment uses a (Blosum) scoring matrix to identify amino acids matches in the two protein sequences• This scoring matrix is identical at all positions in the protein sequence!

EVVFIGDSLVQLMHQC

X X X

X X X

AGDS.GGGDS

Alignment accuracy. Scoring functions

• Blosum62 score matrix. Fg=1. Ng=0?

• Score =2+6+6+4-1=17• Alignment

L A G D S D

F 0 -2 -3 -3 -2 -3

I 2 1 -4 -3 -2 -3

G -4 0 6 -1 0 -1

D -4 -2 -1 6 0 6

S -2 1 0 0 4 0

L 4 -1 -4 -4 -2 -4

LAGDSI-GDS

When Blast works!

1PLC

._

1PLB._

When Blast fails!

1PLC

._

1PMY._

When Blast fails, use sequence profiles!

When Blast fails, use sequence profiles!

1PLC

._

1PMY._

Sequence profiles

• In reality not all positions in a protein are equally likely to mutate

• Some amino acids (active cites) are highly conserved, and the score for mismatch must be very high

• Other amino acids can mutate almost for free, and the score for mismatch should be lower than the BLOSUM score

• Sequence profiles can capture these differences

Protein world

Protein fold

Protein structure classification

Protein superfamily

Protein familyNew Fold

All : Hemoglobin (1bab)

All : Immunoglobulin (8fab)

Triose phosphate isomerase (1hti)

: Lysozyme (1jsf)

ADDGSLAFVPSEF--SISPGEKIVFKNNAGFPHNIVFDEDSIPSGVDASKISMSEEDLLN TVNGAI--PGPLIAERLKEGQNVRVTNTLDEDTSIHWHGLLVPFGMDGVPGVSFPG---I-TSMAPAFGVQEFYRTVKQGDEVTVTIT-----NIDQIED-VSHGFVVVNHGVSME---IIE--KMKYLTPEVFYTIKAGETVYWVNGEVMPHNVAFKKGIV--GEDAFRGEMMTKD----TSVAPSFSQPSF-LTVKEGDEVTVIVTNLDE------IDDLTHGFTMGNHGVAME---VASAETMVFEPDFLVLEIGPGDRVRFVPTHK-SHNAATIDGMVPEGVEGFKSRINDE----TVNGQ--FPGPRLAGVAREGDQVLVKVVNHVAENITIHWHGVQLGTGWADGPAYVTQCPI

Sequence profiles

Conserved

Non-conserved

Matching any thing but G => large negative score

Any thing can match

TKAVVLTFNTSVEICLVMQGTSIV----AAESHPLHLHGFNFPSNFNLVDPMERNTAGVP

TVNGQ--FPGPRLAGVAREGDQVLVKVVNHVAENITIHWHGVQLGTGWADGPAYVTQCPI

How to make sequence profiles

• Align (BLAST) sequence against large sequence database (Swiss-Prot)

• Select significant alignments and make profile (weight matrix) using techniques for sequence weighting and pseudo counts

• Use weight matrix to align against sequence database to find new significant hits

• Repeat 2 and 3 (normally 3 times!)

Example. (SGNH active site)

Example. Where is the active site?

• Sequence profiles might show you where to look!• The active site could be around

• S9, G42, N74, and H195

Profile-profile scoring matrix

1K

7C

.A

1WAB._

Example. Where is the active site?

Align using sequence profiles

ALN 1K7C.A 1WAB._ RMSD = 5.29522. 14% ID1K7C.A TVYLAGDSTMAKNGGGSGTNGWGEYLASYLSATVVNDAVAGRSARSYTREGRFENIADVVTAGDYVIVEFGHNDGGSLSTDN S G N1WAB._ EVVFIGDSLVQLMHQCE---IWRELFS---PLHALNFGIGGDSTQHVLW--RLENGELEHIRPKIVVVWVGTNNHG------

1K7C.A GRTDCSGTGAEVCYSVYDGVNETILTFPAYLENAAKLFTAK--GAKVILSSQTPNNPWETGTFVNSPTRFVEYAEL-AAEVA1WAB._ ---------------------HTAEQVTGGIKAIVQLVNERQPQARVVVLGLLPRGQ-HPNPLREKNRRVNELVRAALAGHP

1K7C.A GVEYVDHWSYVDSIYETLGNATVNSYFPIDHTHTSPAGAEVVAEAFLKAVVCTGTSL H1WAB._ RAHFLDADPG---FVHSDG--TISHHDMYDYLHLSRLGYTPVCRALHSLLLRL---L

Where was the active site?

Rhamnogalacturonan acetylesterase (1k7c)

How good are we?

Alignment accuracy

Alignment performance

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

0.450

Fractional n4

Train 0.259 0.393 0.417

Test 0.212 0.348 0.386

Blast Profile Profile+SS

AUC performance measure

Query Templ Score Hit/nonhit1CJ0.A 1B78.A 0.170963 0 1CJ0.A 1B8A.A -0.040029 0 1CJ0.A 1B8B.A -0.012789 0 1CJ0.A 1B8G.A 12.342823 1 1CJ0.A 1B9H.A 13.394361 1 1CJ0.A 1BAR.A -1.281068 0 1CJ0.A 1BAV.C -1.091305 0

Query Templ Score Hit/nonhit1CJ0.A 1B8G.A 12.342823 1 1CJ0.A 1DTY.A 11.867786 1 1CJ0.A 1DGD._ 11.271914 1 1CJ0.A 1GTX.A 11.010288 1 1CJ0.A 2GSA.A 10.958170 1 1CJ0.A 1BW9.A 2.651775 0 1CJ0.A 1AUP._ 2.507336 1 1CJ0.A 1GTM.A 2.444512 0

AUC (area under the ROC curve)

Fold recognition performance

Fold recognition

0.700

0.750

0.800

0.850

0.900

0.950

1.000

AUC

Per Protein 0.971 0.888 0.809

Prof-Prof PDB-blast Blast

Outlook

• Include position dependent gap penalties• The conventional alignment methods use

equal gap penalties through out the scoring matrix

• In real proteins placement of insertions and deletions is highly structure dependent

• No gaps in secondary structure elements• Gaps most frequent in loops• Distance dependency

Take home message

• Identifying the correct fold is only a small step towards successful homology modeling

• Do not trust % ID or alignment score to identify the fold. Use P-values

• You can do reliable fold recognition AND homology modeling when for low sequence homology

• Use sequence profiles and local protein structure to align sequences

What are (some of) the different available methods?

• Simple sequence based methods– Align (BLAST) sequence against sequence of proteins with

known structure (PDB database)

• Sequence profile based methods– Align sequence profile (Psi-BLAST) against sequence of

proteins with known structure (PDB, FUGUE)– Align sequence profile against profile of proteins with

known structure (FFAS)

• Sequence and structure based methods– Align profile and predicted secondary structure against

proteins with known structure (3D-PSSM, Phyre)

• Sequence profiles and structure based methods– HHpred