Protein Structure Prediction

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Protein Structure Prediction
Protein Sequence
Dr. G.P.S. Raghava
Structure
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Protein Structure Prediction

• Experimental Techniques
• X-ray Crystallography
• NMR
• Limitations of Current Experimental Techniques
• Protein DataBank (PDB) -gt 23000 protein
  structures
• SwissProt -gt 100,000 proteins
• Non-Redudant (NR) -gt 10,00,000 proteins
• Importance of Structure Prediction
• Fill gap between known sequence and structures
• Protein Engg. To alter function of a protein
• Rational Drug Design

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Different Levels of Protein Structure
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Protein Architecture

• Proteins consist of amino acids linked by peptide
  bonds
• Each amino acid consists of
• a central carbon atom
• an amino group
• a carboxyl group and
• a side chain
• Differences in side chains distinguish the
  various amino acids

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Amino Acid Side Chains

• Vary in
• Size
• Shape
• Polarity

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Peptide Bond
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Peptide Bonds
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Dihedral Angles
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Conformation Flexibility

• Backbone (main chain of atoms in peptide bonds,
  minus side chains)
• conformation
• Torsion or rotation angles around
• C-N bond (?)
• C-C bond (?)
• Sterical hinderance
• Most Pro
• Least - Gly

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Ramachandran Plot
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Protein Secondary Structure

• Secondary Structure

Regular Secondary Structure (?-helices, ?-sheets)
Irregular Secondary Structure (Tight turns,
Random coils, bulges)
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Secondary StructureHelices
ALPHA HELIX a result of H-bonding between every
fourth peptide bond (via amino and carbonyl
groups) along the length of the polypeptide chain
Individual Amino acid
H-bond
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Helix formation is local
THYROID hormone receptor (2nll)
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Secondary StructureBeta Sheets
BETA PLEATED SHEET a result of H-bonding between
polypeptide chains
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b-sheet formation is NOT local
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Definition of ??-turn

• A ?-turn is defined by four consecutive residues
  i, i1, i2 and i3 that do not form a helix and
  have a C?(i)-C?(i3) distance less than 7Å and
  the turn lead to reversal in the protein chain.
  (Richardson, 1981).
• The conformation of ?-turn is defined in terms
  of ? and ? of two central residues, i1 and i2
  and can be classified into different types on the
  basis of ? and ?.

i1
i2
i
i3
H-bond
D lt7Å
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Tight turns
Type No. of residues H-bonding
?-turn 2 NH(i)-CO(i1)
?-turn 3 CO(i)-NH(i2)
?-turn 4 CO(i)-NH(i3)
?-turn 5 CO(i)-NH(i4)
?-turn 6 CO(i)-NH(i5)
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Secondary Structureshortcuts
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Tertiary Structure Hexokinase (6000 atoms, 48
kD, 457 amino acids)
polypeptides with a tertiary level of structure
are usually referred to as globular
proteins, since their shape is irregular and
globular in form
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Quarternary StructureHaemoglobin
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What determines fold?

• Anfinsens 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 stucture.
• Some exceptions exist
• Chaperone proteins assist folding
• Abnormally folded Prion proteins can catalyze
  misfolding of normal prion proteins that then
  aggregate

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Levels of Description of Structural Complexity

• Primary Structure (AA sequence)
• Secondary Structure
• Spatial arrangement of a polypeptides backbone
  atoms without regard to side-chain conformations
• ?, ?, coil, turns (Venkatachalam, 1968)
• Super-Secondary Structure
• ?, ?, ?/?, ?? (Rao and Rassman, 1973)
• Tertiary Structure
• 3-D structure of an entire polypeptide
• Quarternary Structure
• Spatial arrangement of subunits (2 or more
  polypeptide chains)

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Techniques of Structure Prediction

• Computer simulation based on energy calculation
• Based on physio-chemical principles
• Thermodynamic equilibrium with a minimum free
  energy
• Global minimum free energy of protein surface
• Knowledge Based approaches
• Homology Based Approach
• Threading Protein Sequence
• Hierarchical Methods

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Energy Minimization Techniques

• Energy Minimization based methods in their pure
  form, make no priori assumptions and attempt to
  locate global minma.
• Static Minimization Methods
• Classical many potential-potential can be
  construted
• Assume that atoms in protein is in static form
• Problems(large number of variables minima and
  validity of potentials)
• Dynamical Minimization Methods
• Motions of atoms also considered
• Monte Carlo simulation (stochastics in nature,
  time is not cosider)
• Molecular Dynamics (time, quantum mechanical,
  classical equ.)
• Limitations
• large number of degree of freedom,CPU power not
  adequate
• Interaction potential is not good enough to model

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Molecular Dynamics

• Provides a way to observe the motion of large
  molecules such as proteins at the atomic level
  dynamic simulation
• Newtons second law applied to molecules
• Potential energy function
• Molecular coordinates
• Force on all atoms can be calculated, given this
  function
• Trajectory of motion of molecule can be determined

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Knowledge Based Approaches

• Homology Modelling
• Need homologues of known protein structure
• Backbone modelling
• Side chain modelling
• Fail in absence of homology
• Threading Based Methods
• 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

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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 (lt 25 pairwise
  identity)

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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 Ps structure as an approximation to Qs
  structure

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Threading

• Given
• sequence of protein P with unknown structure
• Database of known folds
• Find
• Most plausible fold for P
• Evaluate quality of such arrangement
• Places the residues of unknown P along the
  backbone of a known structure and determines
  stability of side chains in that arrangement

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Hierarcial Methods

• Intermidiate structures are predicted, instead of
  predicting tertiary structure of protein from
  amino acids sequence
• Prediction of backbone structure
• Secondary structure (helix, sheet,coil)
• Beta Turn Prediction
• Super-secondary structure
• Tertiary structure prediction
• Limitation
• Accuracy is only 75-80
• Only three state prediction

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Thanks