1. Sequence Based Analysis Tutorial
NIH Proteomics Workshop
Lai-Su L. Yeh, Ph.D.
Protein Science Team Lead
Protein Information Resource at
Georgetown University Medical Center

2. Retrieval, Sequence Search & Classification Methods
Retrieve protein info by text / UID
Sequence Similarity Search
BLAST, FASTA, Dynamic Programming
Family Classification
Patterns, Profiles, Hidden Markov Models, Sequence Alignments, Neural Networks
Integrated Search and Classification System

3. Sequence Similarity Search
Based on Pair-Wise Comparisons
Dynamic Programming Algorithms
Global Similarity: Needleman-Wunch
Local Similarity: Smith-Waterman
Heuristic Algorithms
FASTA: Based on K-Tuples (2-Amino Acid)
BLAST: Triples of Conserved Amino Acids
Gapped-BLAST: Allow Gaps in Segment Pairs
PHI-BLAST: Pattern-Hit Initiated Search
PSI-BLAST: Position-Specific Iterated Search

4. Sequence Similarity Search
Similarity Search Parameters
Scoring Matrices – Based on Conserved Amino Acid Substitution
Dayhoff Mutation Matrix, e.g., PAM250 (~20% Identity)
Henikoff Matrix from Ungapped Alignments, e.g., BLOSUM 62
Gap Penalty
Search Time Comparisons
Smith-Waterman: 10 Min
FASTA: 2 Min
BLAST: 20 Sec 10

5. Feature Representation
Features: Residue Physicochemical Properties, Context (Local & Global) Features, Evolutionary Features
Alternative Alphabets: Classification of Amino Acids To Capture Different Features of Amino Acid Residues

6. Substitution Matrix
Likelihood of One Amino Acid Mutated into Another Over Evolutionary Time
Negative Score: Unlikely to Happen (e.g., Gly/Trp, -7)
Positive Score: Conservative Substitution (e.g., Lys/Arg, +3)
High Score for Identical Matches: Rare Amino Acids (e.g., Trp, Cys) 10

7. BLAST BALST (Basic Local Alignment Search Tool) Extremely fast Robust
Most frequently used
It finds very short segment pairs (“seeds”) between the query and the database sequence
These seeds are then extended in both directions until the maximum possible score for extensions of this particular seed is reached

8. BLAST Search From BLAST Search Interface
Table-Format Result with BLAST Output and SSEARCH (Smith-Waterman) Pair-Wise Alignment

9. BLAST/SSEARCH Results
SSEARCH Alignment
BLAST Alignment

10. Family Classification Methods
Based on Family Information
ClustalW Multiple Sequence Alignment
ProSite Pattern Search
Profile Search
Hidden Markov Models (HMMs)
Neural Networks
Integrated Analysis

11. Multiple Sequence Alignment
ClustalW
Progressive Pairwise Approach
Base on Exhaustive Pairwise Alignments
Neighbor Joining
Joining Order Corresponding to a Tree
Alignment Varies
Dependent on Joining Order

12. How do you build a tree? Pick sequences to align Align them
Verify the alignment
Keep the parts that are aligned correctly
Build and evaluate a phylogenetic tree

13. Multiple Alignment and Tree
From Text/Sequence Search Result or ClustalW Alignment Interface

14. Here is an example of two different functions easily separated on a phylogenetic tree. Each functional group is used to build an HMM.

15. Motif Patterns (Regular Expressions)
Signature Patterns for Functional Motifs
ProClass Motif Alignments

16. PIR Pattern Search
From Text/Sequence Search Result or Pattern Search Interface
One Query Sequence Against PROSITE Pattern Database
One Query Pattern (PROSITE or User-Defined) Against Sequence DB

17. Pattern Search Result (I)
One Query Sequence Against PROSITE Pattern Database

18. Pattern Search Result (II)
One Query Pattern Against Sequence Database

19. Profile Method
Profile: A Table of Scores to Express Family Consensus Derived from Multiple Sequence Alignments
Num of Rows = Num of Aligned Positions
Each row contains a score for the alignment with each possible residue.
Profile Searching
Summation of Scores for Each Amino Acid Residue along Query Sequence
Higher Match Values at Conserved Positions

20. PIR HMM Domain/Motif Search
From Text/Sequence Search Result or HMM Search Interface
HMMER Model Building & Sequence Search
Search One Query Protein Against All HMMs
Search One HMM Against Sequence DB

21. HMM Search Result (I)
One Query Protein Against All Pfam HMMs

22. HMM Search Result (II)
Search User-Built HMM Against Protein Sequence DB
Input Sequences (Optional Residue Ranges) -> Multiple Sequence Alignment -> Model Building -> HMM Search

23. Secondary Structure Features
a Helix Patterns of Hydrophobic Residue Conservation Showing I, I+3, I+4, I+7 Pattern Are Highly Indicative of an a Helix (Amphipathic)
b Strands That Are Half Buried in the Protein Core Will Tend to Have Hydrophobic Residues at Positions I, I+2, I+4, I+6

24. Integrated Bioinformatics System for Function and Pathway Discovery
Data Integration
Associative Analysis

25. Analytical Pipeline Family Classification & Functional Analysis
Query Sequence
PIR-NREF
iProClass
Top-Matched Superfamilies/Domains
BLAST Search
HMM Domain Search
Predicated Superfamilies/Domains/Motifs/Sites/SignalPeptides/TMHs
SSEARCH
CLUSTALW
Superfamily/Domain/Motif Alignments
Family Relationships & Functional Features
Family Classification & Functional Analysis
HMM Motif Search
Pattern Search
SignalP/TMHMM
Analytical Pipeline

26. Integrated Bioinformatics System
Global Bioinformatics Analysis of 1000’s of Genes and Proteins
Pathway Discovery, Target Identification

27. Lab Section

28. Peptide Search & Results

29. Blast Similarity Search

30. Blast Search Results

31. Pair-Wise Alignment

32. Multiple Sequence Alignment

33. Pattern Search Results

34. HMM Domain Search Result

35. Building HMM Profile

36. Using HMM Profile for Searching

37. Rabbit Alpha Crystallin A Chain An iProClass View of the entry

38. alpha-Crystallin and Related Proteins