In silico structure prediction

1. In sillico
Stucture
Prediction

2. Primary structure
(Amino acid sequence)
↓
Secondary structure
(α-helix,β-sheet ）
↓
Tertiary structure
(Three-dimensional structure formed by assembly of
secondary structures ）
↓
Quaternary structure
(Structure formed by more than one polypeptide chains ）

4. STRUCTURE PREDICTION
• Experimental data
• X-ray crystallography
• NMR spectroscopy
• expensive & time consuming
• Computational methods
• Homology/comparative modeling
• Fold recognition (threading)
• Ab initio (de novo, new folds) methods

7. Homology/comparative modeling
• modeling a protein 3D structure using a known experimentally
determined structure of a homologous protein as a template
• usually provides the most reliable result.
• Used when the sequence is similar to a known structure with >30-
50% identity).
• two proteins belonging to the same family and sharing similar amino
acid sequences, will have similar three-dimensional structures

8. STEPS INVOLVED;
• template identification
• amino acid sequence alignment (multiple sequence alignment)
• alignment correction
• backbone generation
• generation of loops
• side chain generation & optimization
• ab initio loop building
• overall model optimisation
• model verification. Quality criteria, model quality

9. • MSA gives an overview of the general features of the protein family,
the degree of conservation, the consensus sequence motifs, etc.
• the positions of insertions and deletions should be correct, likewise the
conservation of important residues (active site residues)
• The modeling software will thread sequence on the template structure.
Creates a preliminary model of protein (backbone generation)
• Building of missing parts, generation of side chains for replaced
residues and optimization of side chain conformations.
• At the last step the overall model needs to be optimized followed by
verification of model quality.

10. Softwares used for modeling :
• Swiss Model
• Phyre
• I-tasser
• ROBETTA

11. (1)
(2)
(1)- sequence of the protein to be predicted
(2)- MSA
(3)- Homologus Template protein
(4)- backbone generation
(5)- overall model optimization
(3)
(4)
(5)

13. Protein threading(fold recognition)
• used to model those proteins which have the same fold as proteins of known
structures, but do not have homologous proteins with known structure.
• Fold recognition alignments are quite different from ordinary sequence alignments
since they are evaluated from a structural perspective.
• Threading works by using statistical knowledge of the relationship between the
structures deposited in the PDB and the sequence of the protein which one wishes to
model.
• The prediction is made by "threading" (i.e. placing, aligning) each amino acid in the
target sequence to a position in the template structure, and evaluating how well the
target fits the template.

14. Steps involved:
1. The construction of a structure template database:
• Select protein structures from the protein structure databases as structural
templates.
• Databases used are PDB, FSSP, SCOP, or CATH
2. The design of the scoring function:
• Design a good scoring function to measure the fitness b/w target
sequences and templates based on the knowledge of the known relationships between
the structures and the sequences.
• A good scoring function should contain mutation potential, environment
fitness potential, pairwise potential, secondary structure compatibilities, and gap
penalties.

15. • The quality of the energy function is closely related to the prediction
accuracy, especially the alignment accuracy.
3. Threading alignment:
• Align the target sequence with each of the structure templates by optimizing the
designed scoring function.
• This step is one of the major tasks of all threading-based structure prediction
programs that take into account the pairwise contact potential; otherwise, a
dynamic programming algorithm can fulfill it.
4. Threading prediction:
• Select the threading alignment that is statistically most probable as the threading
prediction.
• Then construct a structure model for the target by placing the backbone atoms of
the target sequence at their aligned backbone positions of the selected structural
template

16. Protein threading software:
• HHpredis
• RAPTOR
• Phyre
• MUSTER
• SPARKS X.
• BioShell

18. ab initio method
• means “from the beginning”
• predicts the native fold from amino acid sequence alone
• Methods for ab initio prediction includes;
• Molecular Dynamics (MD) simulations
• Monte Carlo (MC)
• Genetic Algorithms

19. Softwares used in ab initio methods
• I-TASSER
• ROBETTA
• Abalone

20. (1)
(2)
(1)- protein sequences
(2)- suitable folds

21. Prediction of protein structure from folds