Cédric Notredame (08/10/2015) Comparing Two Protein Sequences Cédric Notredame.

Cédric Notredame (19/04/23)

Comparing Two Protein Sequences

Cédric Notredame


Our Scope

Pairwise Alignment methods are POWERFUL

Pairwise Alignment methods are LIMITED

If You Understand the LIMITS they Become VERY POWERFUL

Look once Under the Hood


Outline

-WHY Does It Make Sense To Compare Sequences

-HOW Can we Align Two Sequences ?

-HOW can I Search a Database ?

-HOW Can we Compare Two Sequences ?


Why Does It Make Sense To Compare Sequences ?

Sequence Evolution


Why Do We Want To Compare Sequences

wheat --DPNKPKRAMTSFVFFMSEFRSEFKQKHSKLKSIVEMVKAAGER | | |||||||| || | ||| ||| | |||| ||||????? KKDSNAPKRAMTSFMFFSSDFRS----KHSDL-SIVEMSKAAGAA

EXTRAPOLATE

??????

Homology?

SwissProt


Why Do We Want To Compare Sequences


Why Does It Make Sense To Align Sequences ?

-Evolution is our Real Tool.

-Nature is LAZY and Keeps re-using Stuff.

-Evolution is mostly DIVERGEANT

Same Sequence Same Ancestor


Why Does It Make Sense To Align Sequences ?

SameSequence

Same Function

Same 3D Fold

Same Origin


Comparing Is Reconstructing Evolution


An Alignment is a STORY

ADKPKRPLSAYMLWLN

ADKPKRPKPRLSAYMLWLNADKPRRPLS-YMLWLN

ADKPKRPLSAYMLWLN ADKPKRPLSAYMLWLN

Mutations+

Selection


An Alignment is a STORY

ADKPRRP---LS-YMLWLNADKPKRPKPRLSAYMLWLN

Mutation

InsertionDeletion

ADKPKRPLSAYMLWLN

ADKPKRPKPRLSAYMLWLNADKPRRPLS-YMLWLN

ADKPKRPLSAYMLWLN ADKPKRPLSAYMLWLN

Mutations+

Selection


Evolution is NOT Always Divergent…

AFGP with (ThrAlaAla)nSimilar To Trypsynogen

N

AFGP with (ThrAlaAla)n

S

Chen et al, 97, PNAS, 94, 3811-16

NOT

Similar to Trypsinogen


Evolution is NOT Always Divergent

AFGP with (ThrAlaAla)nSimilar To Trypsynogen

AFGP with (ThrAlaAla)nNOT

Similar to Trypsinogen

N

S

SIMILAR Sequences BUT

DIFFERENT origin


Evolution is NOT always Divergent…

But in MOST cases, you may assume it is…

SameSequence

Same Function

Same 3D Fold

Same Origin

Similar Function DOES NOT REQUIRESimilar Sequence

Similar Sequence

Historical Legacy


How Do Sequences Evolve

Each Portion of a Genome has its own Agenda.


How Do Sequences Evolve ?

CONSTRAINED Genome Positions Evolve SLOWLY

EVERY Protein Family Has its Own Level Of Constraint

Family KS KA

Histone3 6.4 0Insulin 4.0 0.1Interleukin I 4.6 1.4Globin 5.1 0.6Apolipoprot. AI 4.5 1.6Interferon G 8.6 2.8

Rates in Substitutions/site/Billion Years as measured on Mouse Vs Human (80 Million years)Ks Synonymous Mutations, Ka Non-Neutral.


Different molecular clocks for different proteins--another prediction


GC

LIV A

F

Aliphatic

Aromatic

Hydrophobic

C

How Do Sequences Evolve ?The amino Acids Venn Diagram

To Make Things Worse, Every Residue has its Own Personality

ST

WY

QHK

R

ED N

Polar

PG

Small

C



In a structure, each Amino Acid plays a Special Role

OmpR, Cter Domain

In the core, SIZE MATTERS

On the surface, CHARGE MATTERS

--+



Accepted Mutations Depend on the Structure

Big -> BigSmall ->SmallNO DELETION

--+

Charged -> ChargedSmall <-> Big or SmallDELETIONS


How Can We Compare Sequences ?

Substitution Matrices



To Compare Two Sequences, We need:

Their Function

Their Structure

We Do Not Have Them !!!



We will Need To Replace Structural Information With Sequence Information.

SameSequence

Same Function

Same 3D Fold

Same Origin

It CANNOT Work ALL THE TIME !!!



To Compare Sequences, We need to Compare ResiduesWe Need to Know How Much it COSTS to SUBSTITUTE

an Alanine into an Isoleucinea Tryptophan into a Glycine…The table that contains the costs for all the

possible substitutions is called the SUBSTITUTION MATRIX

How to derive that matrix?



G

C

LIV A

F

Aliphatic

Aromatic

Hydrophobic

C

ST

W

YQH

K

R

ED N

Polar

PG

Small

C

Using Knowledge Could Work

But we do not know enough about Evolution and Structure.

Using Data works better.


How Can We Compare Sequences ?Making a Substitution Matrix

-Take 100 nice pairs of Protein Sequences, easy to align (80% identical).

-Align them…

-Count each mutations in the alignments

-25 Tryptophans into phenylalanine-30 Isoleucine into Leucine…

-For each mutation, set the substitution score to the log odd ratio:

Expected by chance

ObservedLog



The Diagonal Indicates How Conserved a residue tends to be.W is VERY Conserved

Some Residues are Easier To mutate into other similar

Cysteins that make disulfide bridges and those that do not get averaged





How Can We Compare Sequences ?Using Substitution Matrix

ADKPRRP---LS-YMLWLNADKPKRPKPRLSAYMLWLN

Mutation

InsertionDeletion

Given two Sequences and a substitution Matrix,We must Compute the CHEAPEST Alignment


Most popular Subsitution Matrices • PAM250• Blosum62 (Most widely used)

Raw Score

TPEA¦| |APGA

TPEA¦| |APGA

Score =1 = 9

• Question: Is it possible to get such a good alignment by chance only?

+ 6 + 0 + 2

Scoring an Alignment


Insertions and Deletions

Gap Penalties

• Opening a gap is more expensive than extending it

Seq AGARFIELDTHE----CAT||||||||||| |||

Seq BGARFIELDTHELASTCAT



gap

Gap Opening PenaltyGap Extension Penalty


How Can We Compare Sequences ?Limits of the substitution Matrices

They ignore non-local interactions and Assume that identical residues are equal

They assume evolution rate to be constant

ADKPKRPLSAYMLWLN

ADKPKRPKPRLSAYMLWLN

ADKPRRPLS-YMLWLN

ADKPKRPLSAYMLWLNADKPKRPLSAYMLWLN

Mutations+

Selection



Substitution Matrices Cannot Work !!!



I know… But at least, could I get some idea of when they are likely to do all right


How Can We Compare Sequences ?The Twilight Zone

Length

%Sequence Identity

100

Same 3D Fold

Twilight Zone

Similar SequenceSimilar Structure

30%

Different SequenceStructure ????

30


How Can We Compare Sequences ?The Twilight Zone

Substitution Matrices Work Reasonably Well on Sequences that have more than 30 % identity over more than 100 residues






How Can We Compare Sequences ?Which Matrix Shall I used

The Initial PAM matrix was computed on 80% similar Proteins

It been extrapolated to more distantly related sequences.

Pam 250Pam 350

Other Matrices Exist:BLOSUM 42BLOSUM 62

BLOSUM 62


How Can We Compare Sequences ?Which Matrix Shall I use

PAM: Distant Proteins High Index (PAM 350)BLOSUM: Distant Proteins Low Index (Blosum30)

•GONNET 250> BLOSUM62>PAM 250.

•But This will depend on:

•The Family.•The Program Used and Its Tuning.

Choosing The Right Matrix may be Tricky…

•Insertions, Deletions?


Dot MatricesGlobal AlignmentsLocal Alignment

HOW Can we Align Two Sequences ?



Dot Matrices

QUESTION

What are the elements shared by two sequences ?


Dot Matrices

>Seq1THEFATCAT>Seq2THELASTCAT

T H E F A T C A TTHEFASTCAT

Window

Stringency


Dot Matrices

Sequences Window size

Stringency


Dot MatricesStrigency

Window=1Stringency=1




Dot Matrices

xy

xy x


Dot Matrices


Dot Matrices


Dot Matrices


Dot Matrices


Dot MatricesLimits

-Visual aid

-Best Way to EXPLORE the Sequence Organisation

-Does NOT provide us with an ALIGNMENT

wheat --DPNKPKRAMTSFVFFMSEFRSEFKQKHSKLKSIVEMVKAAGER | | |||||||| || | ||| ||| | |||| ||||????? KKDSNAPKRAMTSFMFFSSDFRS----KHSDL-SIVEMSKAAGAA


Cost

L

Afine Gap Penalty

Global Alignments

-Take 2 Nice Protein Sequences

-A good Substitution Matrix (blosum)

-A Gap opening Penalty (GOP)

-A Gap extension Penalty (GEP)

GOP

GEP

GOP GOP

GOP

Parsimony: Evolution takes the simplest path

(So We Think…)


Insertions and Deletions

Gap Penalties

• Opening a gap is more expensive than extending it





gap

Gap Opening PenaltyGap Extension Penalty


Global Alignments

-Take 2 Nice Protein Sequences

-A good Substitution Matrix (blosum)

-A Gap opening Penalty (GOP)

-A Gap extension Penalty (GEP)

>Seq1THEFATCAT>Seq2THEFASTCAT

-DYNAMIC PROGRAMMING

DYNAMICPROGRAMMING

THEFA-TCATTHEFASTCAT


Global Alignments

F A S T

F A T

----FATFAST---

(L1+l2)!

(L1)!*(L2)!

---FAT-FAST---

--F-AT-FAST---

Brut Force Enumeration

2

( )

DYNAMIC PROGRAMMING


Global AlignmentsDYNAMIC PROGRAMMING

Match=1 MisMatch=-1Gap=-1

FAT

F A S T

1

-1

-1

-2

-3

0

-2 -3 -4

2

0

0

Dynamic Programming (Needlman and Wunsch)

FAT

F A S T

1

-1

-1

-2

-3

0

-2 -3 -4

2

0

0 -1 0

0

21-1-1

1

FAT

F A S T

1

-1 -2 -3 -4

2

0

2

1

F A S TF A - T



Global Alignments are very sensitive to gap Penalties

GOP

GEP



Global Alignments are very sensitive to gap Penalties

Global Alignments do not take into account the MODULAR nature of Proteins

C: K vitamin dep. Ca BindingK: Kringle DomainG: Growth Factor moduleF: Finger Module


Local Alignments

GLOBAL Alignment

LOCAL Alignment

Smith And Waterman (SW)=LOCAL Alignment


Local Alignments

We now have a PairWise Comparison Algorithm,

We are ready to search Databases


Database Search

1.10e-20

10

1.10e-100

1.10e-2

1.10e-1

10

3

1

3

6

1.10e-2

1

20

15

13

QUERRY

Comparison Engine

Database

E-valuesHow many time do we expect such anAlignment by chance?

SWQ



CONCLUSION


-There is a relation between Sequence and Structure.

The Easiest way to Compare Two Sequences is a dotplot.

Sequence Comparison

-Thanks to evolution, We CAN compare Sequences

-Substitution matrices only work well with similar Sequences (More than 30% id).


A few Addresses







Cédric Notredame (08/10/2015) Comparing Two Protein Sequences Cédric Notredame.

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