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L-12 Modeling protein Structure


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How accurate is Predicting Secondary Structure From Primary Structure?
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accuracy 64- 75% higher accuracy for -helices than for -sheets predictions of engineered (artificial) proteins are less accurate accuracy is dependent on protein famIly

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How accurate is Predicting Secondary Structure From Primary Structure?
Accuracy 64- 75% higher accuracy for -helices than for -sheets predictions of engineered (artificial) proteins are less accurate accuracy is dependent on protein famIly
Why is molecular dynamics important?
• Provides a way to observe the motion of large molecules such as proteins at the atomic level – dynamic simulation • Newton’s second law applied to molecules
Importance of Potential energy function?
• Molecular coordinates • Force on all atoms can be calculated, given this function • Trajectory of motion of molecule can be determined
What does Knowledge Based Approaches include?
-Homology Modelling -Threading Based Methods
How does homology Modelling work?
Need homologues of known protein structure • Backbone modelling • Side chain modelling • Fail in absence of homology
How does threading based methods work?
• New way of fold recognition • Sequence is tried to fit in known structures • Motif recognition • Loop & Side chain modelling • Fail in absence of known example
What are the properties of homology modeling?
Simplest, reliable approach Basis: proteins with similar sequences tend to fold into similar structures Has been observed that even proteins with 25% sequence identity fold into similar structures Does not work for remote homologs (< 25% pairwise identity)
What is the approach of homology modeling?
• Given: • A query sequence Q • A database of known protein structures • Find protein P such that P has high sequence similarity to Q • Return P’s structure as an approximation to Q’s structure
What does secondary structure prediction assume?
• The entire information for forming secondary structure is contained in the primary sequence • Side groups of residues will determine structure • Examining windows of 13-17 residues is sufficient to predict secondary structure • -helices 5–40 residues long • -strands 5–10 residues long
What are the Measures of prediction accuracy?
Qindex and Q3 Correlation coefficient
Methods of secondary structure prediction?
First generation methods: single residue statistics Second generation methods: segment statistics The GOR method Third generation methods
Explain the first generation method single residue statistics?
Chou & Fasman (1974 & 1978) : Some residues have particular secondary-structure preferences. Based on empirical frequencies of residues in -helices, -sheets, and coils. Examples: Glu α-helix Val β-strand Accuracy: Q3 = 50-60%
Explain Second generation methods segment statistics?
Similar to single-residue methods, but incorporating additional information (adjacent residues, segmental statistics). • Problems: • Low accuracy - Q3 below 66% (results). • Q3 of -strands (E): 28% - 48%. • Predicted structures were too Short.
What is the GOR method?
• developed by Garnier, Osguthorpe & Robson • build on Chou-Fasman Pij values • evaluate each residue PLUS adjacent 8 N-terminal and 8 carboxyl-terminal residues • sliding window of 17 residues • underpredicts -strand regions • GOR method accuracy Q3 = ~64%
What ideas Third generation methods are based on?
• Third generation methods reached 77% accuracy. • They are based on two new ideas: 1. A biological idea – Using evolutionary information based on conservation analysis of multiple sequence alignments. 2. A technological idea – Using neural networks
What is Artificial Neural Networks?
An attempt to imitate the human brain (assuming that this is the way it works
What does proteins consist of?
Proteins consist of amino acids linked by peptide bonds
What is the significance of secondary structure prediction?
• Historically first structure prediction methods predicted secondary structure • Can be used to improve alignment accuracy • Can be used to detect domain boundaries within proteins with remote sequence homology • Often the first step towards 3D structure prediction • Informative for mutagenesis studies
What are the limitations of Energy Minimization Techniques?
• large number of degree of freedom, CPU power not adequate • Interaction potential is not good enough to model
How does Dynamical Minimization Methods work?
• Motions of atoms also considered • Monte Carlo simulation (stochastics in nature, time is not considered) • Molecular Dynamics (time, quantum mechanical, classical equ.)
How does Static Minimization Methods work?
• Classical many potential-potential can be constructed • Assume that atoms in protein is in static form • Problems (large number of variables & minima and validity of potentials)
What are the Energy Minimization Techniques?
Energy Minimization based methods in their pure form, make no priori assumptions and attempt to locate global minima.
How does the Knowledge Based approaches in protein structure prediction work?
• Homology Based Approach • Threading Protein Sequence • Hierarchical Methods
How does Computer simulation based on energy calculation work?
• Based on physio-chemical principles • Thermodynamic equilibrium with a minimum free energy • Global minimum free energy of protein surface
What are the techniques of structure prediction?
-Computer simulation based on energy calculation -Knowledge Based approaches
What are the levels of protein structural complexity?
• Primary structure (AA sequence) • Secondary structure • Spatial arrangement of a polypeptide’s backbone atoms without regard to side-chain conformations • alpha, beta, coil, turns (Venkatachalam, 1968) • Super-secondary structure • alpha, beta, alpha/beta, alpha+Beta (Rao and Rassman, 1973) • Tertiary structure • 3-D structure of an entire polypeptide • Quaternary structure • Spatial arrangement of subunits (2 or more polypeptide chains)
What are the exceptions in protein folding?
Chaperone proteins assist folding • Abnormally folded Prion proteins can catalyze misfolding of normal prion proteins that then aggregate
What did the Anfinsen’s experiments in 1957 demonstrate?
Anfinsen’s experiments in 1957 demonstrated that proteins can fold spontaneously into their native conformations under physiological conditions. This implies that primary structure does indeed determine folding or 3-D structure.
What are the limitations of predicting proteins structure?
• Not all proteins or parts of proteins assume a well- defined 3D structure in solution. • Protein structure is not static, there are various degrees of thermal motion for different parts of the structure. • There may be a number of slightly different conformations in solution. • Some proteins undergo conformational changes when interacting with STUFF.
Why is predicting protein structures important?
Structural knowledge = some understanding of function and mechanism of action • Predicted structures can be used in structure-based drug design • It can help us understand the effects of mutations on structure and function • It is a very interesting scientific problem (still unsolved in its most general form after more than 50 years of effort)
How can you distinguish amino acids ?
Differences in side chains distinguish the various amino acids
What does amino acids consists of?
• a central carbon atom • an amino group • a carboxyl group and • a side chain