protein sturcture prediction and molecular modelling

PRESENTED BY:P. DILEEPB.Pharmacy

M.Pharmacy(2ND sem)SHIFT II, Roll no:30Department of PharmacologyVAAGDEVI COLLEGE OF PHARMACY

Contents of Seminar2

Introduction

Molecular modeling

Types of molecular modeling

Applications of molecular modeling

Proteins in brief

Purpose of protein structure prediction

Types of PSP

Conclusion

Molecular Modeling4

The science (or art) of representing molecular structures numerically and simulating their behavior with the equations of quantum and classical physics.

Combination of computational chemistry and computer graphics. Allows scientists to generate and present molecular data including

geometries (bond lengths, bond angles, torsion angles), energies (heat of formation, activation energy, etc.), electronic properties (moments, charges, ionization potential, electron affinity), spectroscopic properties (vibrational modes, chemical shifts) and bulk properties (volumes, surface areas, diffusion, viscosity, etc.).

Thomas L L, David A W, Victoria K(1999), Foye’s principles of Medicinal Chemistry, Lippincott Williams & Wilkins publications, 6th edition, 3, pp. 55-63.

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Potential energy variation


Molecular Modeling methods

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The two most common computational methods Molecular mechanics Quantum mechanics

Both these methods produce equations for the total energy(E) of the structure.

MOLECULAR MECHANICS: Calculation of energy of atoms, force on atoms and

their resulting motion. Used to model the geometry of the molecule, motion of

molecule and to get the global minimum energy structure.


Molecular mechanics7

Consider a molecule as system of rigid balls connected via springs.

Depends strongly on concepts of bonding Follows the Newtonian laws Neglect the electronic degrees of freedom

Leach A R(2001), Molecular Modelling: Principles and Applications, Oxford press, 4th edition, 1, pp. 1-3.

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Potential surface

Study of force field

Study of Electrostatics

Molecular dynamics

Conformational Analysis

Methods for Molecular mechanics study



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Force field is used to describe the total potential energy of a molecule or system as a function of geometry. and the set of parameters required is called “force field parameters”. The total energy is a sum of Taylor series expansions for stretches for every pair of bonded atoms, and adds additional potential energy terms coming from bending, torsional energy, Vander wall energy,

electrostatics and cross terms.

Study of Electrostatics involves the study of interaction between various dipoles.


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Molecular dynamics program allow the model to how the natural motion of atoms in the structure. This is achieved by including the kinetic energy term of atoms in the force field equation by using equations based on Newton's law of motion.

Conformational Analysis involves the determination or analysis of the spatial arrangement of the functional group of the respective molecule. Strategies used to study the conformational analysis are Rigid geometry approximation, Rigid body rotation, Conformational clustering.


QUANTUM MECHANICS12

Provides information about both nuclear position and distribution.

Based on study of arrangement and interaction of electrons and nuclei of a molecular system.

It does not require the use of parameters similar to those used in molecular mechanics.

It is based on the wave properties of electrons and all material particles.

Griffith S, David J(2004), Introduction to Quantum Mechanics, Prentice Hall press, 2nd edition, pp. 1-4.

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QUANTUM MECHANICS

Where,H = Hamiltonian for the system,Ψ(“p-sigh”) = wave function,E = energy.Simply put, the Hamiltonian is an “operator,” a mathematical construct that operates on the molecular orbital, Ψ, to determine the energy.U= Potential energy,K= Kinetic energy.

H Ψ = E Ψ = (U+K) Ψ


ADVANTAGES14

To calculate the value of potentials, electron affinities ,heat of formation, dipole moment and other physical properties

To find the electron density in a structure

To determine the points at which a structure will react with electrophiles and nucleophiles

To determine the shape and electron density of a molecule

Rajkumar B, Branson K, Giddy J, Abramson D(2003), The Virtual Laboratory : A toolset to enable distributed molecular modeling for drug design on the World-Wide Grid, Concurrency and computation, 15, pp. 1–25.

Proteins….16

http://courses.washington.edu/conj/protein/insulin2.gif

http://www.biochem.ucl.ac.uk/bsm/pdbsum/1gwf/main.html

If there is a job to be If there is a job to be done in the molecular done in the molecular world of our cells, world of our cells, usually that job is done usually that job is done by a protein.by a protein. CATALASE

An enzyme which removes Hydrogen peroxide from your body so it does not become toxic

A protein hormone which helps to regulate your blood sugar levels

Proteins for cell motility 17

Myosin and actin filaments work in coordination for the proper muscle contraction


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Eukaryotic exoskeleton

Tubulin frame work for the exoskeleton

Microtubules

Cellular coat

http://www.fz-juelich.de/ibi/ibi-1/Cellular_signaling/http://cpmcnet.columbia.edu/dept/gsas/anatomy/Faculty/Gundersen/main.html

Cell structures


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Energy

Progress of reaction

Substrate Product

+2 2


Enzymes

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Harmones and channels

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Immune response

Proteins can be fibrous or Proteins can be fibrous or globularglobular

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Fibrous proteins23

http://opbs.okstate.edu/~petracek/2002%20protein%20structure%20function/CH06.gif

http://my.webmd.com/hw/health_guide_atoz/zm2662.asp?printing=true

•Collagen is the most abundant protein in vertebrates. Collagen fibers are a major portion of tendons, bone and skin. Alpha helices of collagen make up a triple helix structure giving it tough and flexible properties.•Fibroin fibers make the silk spun by spiders and silk worms stronger weight for weight than steel! The soft and flexible properties come from the beta structure.•Keratin is a tough insoluble protein that makes up the quills of echidna, your hair and nails and the rattle of a rattle snake. The structure comes from alpha helices that are cross-linked by disulfide bonds.

Globular proteins24

Cell motility – proteins link together to form filaments which make movement possible.

Organic catalysts in biochemical reactions – enzymes

Regulatory proteins – hormones, transcription factors

Membrane proteins – protein channels

Defense against pathogens – poisons/toxins, antibodies, complement

Transport and storage – hemoglobin


Molecular Logic of Life is SameMolecular Logic of Life is Same

Biochemically, all things living – animals, plants, bacteria, viruses, etc. – are remarkably similar

English

26-Letter alphabet Only one grammar Extremely diverse literature

Genome

4-Letter alphabet Only one grammar Extremely diverse organisms

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G T A C T A

Chromosome

The order of bases in DNA is a code for making proteins. The code is read in groups of three

DNA

Gene

Cell machinery copies the code making an mRNA molecule. This moves into the cytoplasm.

Ribosomes read the code and accurately join Amino acids together to make a protein

AUGAGUAAAGGAGAAGAACUUUUCACUGGAUAM S E E LK G TF G

The protein folds to form its working shape

M

S EK G

E L TF G

M

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GE L TF G

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TF

G

M

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K

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EL

TF

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S

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T F

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CELL

NUCLEUS

Gene Expression

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M

S

E

K

G

EL

T F

G

T

GM

S

E

K

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F

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Hallmark of Proteins: SpecificityHallmark of Proteins: Specificity

Know exactly which small molecule (ligand) they should bind to or interact with.

Also know which part of a macromolecule they should bind to.

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Function is critically dependent on Function is critically dependent on structurestructure

One Aspect of Genome Sequence Analysis is to One Aspect of Genome Sequence Analysis is to Assign Functions to ProteinsAssign Functions to Proteins((Reverse GeneticsReverse Genetics))

Schween G, Egener T, Fritzkowsky D, Granado J, Guitton M C(2005), Large-scale analysis of Physcomitrella plants transformed with different gene disruption libraries: Production parameters and mutant phenotypes, Plant Biology, 7 (3), pp. 228–237.

Sequence

Structure Function

How Does Sequence Specify Structure?How Does Sequence Specify Structure?

Structure has to be determined experimentally

The Protein Folding ProblemThe Protein Folding Problem(second half of the genetic code)(second half of the genetic code)

??Functional Genomics

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Protein Structure30

• Levels of organization– Primary Sequence– Secondary Structure (Modular building

blocks)• α-helices• β-sheets

– Tertiary Structure– Quartenary Structure

• Hydrophobic/Hydrophilic Organization.Lubert S, Tymoczko J L, Jeremy M B(2003). Text book of biochemistry, W. H. Freeman and company

press, 5th edition, pp. 198-230.

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Lubert S, Tymoczko J L, Jeremy M B(2003). Text book of biochemistry, W. H. Freeman and company press, 5th edition, pp. 198-230.

Protein Structure

Secondary StructureSecondary Structure: -helix32


Secondary StructureSecondary Structure: -sheets33


Definition of -turn

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four consecutive residues i, i+1, i+2 and i+3 that do not form a helix and the turn lead to reversal in the protein chain.

The conformation of -turn is defined in terms of two central residues, i+1 and i+2 and can be classified into different types on the basis of this conformation.

i

i+1 i+2

i+3H-bond

D <7ÅLubert S, Tymoczko J L, Jeremy M B(2003). Text book of biochemistry, W. H. Freeman and company press, 5 th edition,

pp. 198-230.

Biology/Chemistry of Protein Structure

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Primary

Secondary

Tertiary

Quaternary

Assembly

Folding

Packing

Interaction

S T

R U

C T

U R

E P R

O C

E S

S

Lubert S, Tymoczko J L, Jeremy M B(2003). Text book of biochemistry, W. H. Freeman and company press, 5 th edition, pp. 198-230.

3 main questions…3 main questions…36

1. Why predict the structure?

2. Methods for structure prediction

3. What next?

Purpose of PSP

Explaining phenotype of existing mutations (experimental or patient-derived)

Designing mutants to disrupt or alter specific functions (leaving others unaffected)

Hints at function

Drug design (at high sequence identity)

Hypothesis generation

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Mateusz K, Michał J, Andrzej K(2011), Multiscale Approaches to Protein Modeling, Springer Science Business Media, 12th edition, pp. 21-32

• Anfinsen’s (1973) thermodynamic hypothesis:

Proteins are not assembled into their native structures by a biological process, but folding is a purely physical process that depends only on the specific amino acid sequence of the protein.

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Anfinsen C B(1973), Principles that govern the folding of protein chains, Biological Science, 181, pp. 223–230

The Prediction Problem39

Can we predict the final 3D protein structure knowing only its amino acid sequence?

• Studied for 4 Decades

• “Holy Grail” in Biological Sciences

• Primary Motivation for Bioinformatics

• Based on this 1-to-1 Mapping of Sequence to Structure

• Still very much an OPEN PROBLEMMateusz K, Michał J, Andrzej K(2011), Multiscale Approaches to Protein Modeling, Springer Science Business Media, 12th edition, pp. 21-32

PSP: Major Hurdles40

Energetics We don’t know all the forces involved in detail Too computationally expensive BY FAR!

Conformational search impossibly large 100 AA. protein, 2 moving dihedrals, 2 possible positions

for each diheral: 2200 conformations! Levinthal’s Paradox

Longer than time of universe to search Proteins fold in a couple of seconds??


PSP: Goals41

Accurate 3D structures. But not there yet. Good “guesses”

Working models for researchers Understand the FOLDING PROCESS

Get into the Black Box Only hope for some proteins

25% won’t crystallize, too big for NMR Best hope for novel protein engineering

Drug design, etc.


Comparative Modeling--Basic Protocol

1.Identification of homologue for target sequence2.Alignment of target sequence to template sequence and structure3.Side-chain modeling, copy the backbone of the template and model the new side chains onto this backbone4.Loop modeling, for insertions and deletions in the alignment5.Refinement of model -- moving template closer to target6.Assessment of (predicted) model quality7.Using the model to explain experiments and guide new ones

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David F B, Charlotte M D, Hampapathalu A N, Nuria C, An Iterative Structure-Assisted Approach to Sequence Alignment and Comparative Modeling, PROTEINS: Structure, Function, and Genetics Supplementations, 3, pp. 55-60.

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Experimental techniques for structure Experimental techniques for structure determinationdetermination

X-ray Crystallography Nuclear Magnetic Resonance

spectroscopy (NMR)

Electron Microscopy/Diffraction

Free electron lasers.

David F B, Charlotte M D, Hampapathalu A N, Nuria C, An Iterative Structure-Assisted Approach to Sequence Alignment and Comparative Modeling, PROTEINS: Structure, Function, and Genetics Supplementations, 3, pp. 55-60.

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From small molecules to viruses Information about the positions of

individual atoms Limited information about dynamics Requires crystals

X-ray CrystallographyX-ray Crystallography

Saville W B, Shearer G (1925), An X-ray Investigation of Saturated Aliphatic Ketones, Journal of the Chemical Society, 127, pp. 591.

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NMRNMR

Limited to molecules up to ~50kDa (good quality up to 30 kDa)

Distances between pairs of hydrogen atoms

Lots of information about dynamics Requires soluble, non-aggregating

material Assignment problem

Addess M, Kenneth J, Feigon J(1996). Introduction to 1H NMR Spectroscopy of DNA. Bioorganic Chemistry: Nucleic Acids, Oxford University Press, 8th edition, pp. 238.

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Electron Microscopy/ DiffractionElectron Microscopy/ Diffraction

Low to medium resolution Limited information about

dynamics Can use very small

crystals (nm range) Can be used for very large

molecules and complexes

Tertiary Structure Prediction47

Template Modeling Homology Modeling Threading

Template-Free Modeling ab initio Methods

Physics-Based Knowledge-Based

Thomas L, Ralf Z(2000), Protein structure prediction methods for drug design, Briefings in Bioinformatics, 3, pp. 275-288.

HOMOLOGY MODELING

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Constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental 3d structure of a related homologous protein (the "template").

Homology modeling relies on the identification of one or more known protein structures likely to resemble the structure of the query sequence, and on the production of an alignment that maps residues in the query sequence to residues in the template sequence

This approach can be complicated by the presence of alignment gaps (commonly called indels) that arise from poor resolution in the experimental procedure (usually X-ray crystallography).

Thomas L, Ralf Z(2000), Protein structure prediction methods for drug design, Briefings in Bioinformatics, 3, pp. 275-288

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Homology modeling can produce high-quality structural models when the target and template are closely related, which has inspired the formation of a structural genomics consortium.

The analysis and prediction of loop structures for small and medium sized loops and the positioning of side chains, given the conformation of the protein's backbone.

HOMOLOGY MODELING


Threading or Fold Recognition Method

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Computational protein structure prediction Distinction between two fold recognition scenarios. “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. After the best-fit template is selected, the structural model of the sequence is built based on the alignment with the chosen template.

Homologous folds share the Same structure through divergent evolution from a common ancestor.

Analogous folds, on the other hand, share the same structure, but give insufficient evidence for an evolutionary relationship.


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One popular model for protein folding assumes a sequence of events:

Hydrophobic collapse

Local interactions stabilize secondary structures

Secondary structures interact to form motifs

Motifs aggregate to form tertiary structure

Threading or Fold Recognition Method


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It calculates energetics involved in the process of folding

Finding the structure with lowest free energy It is based on the ‘thermodynamic hypothesis’, which states that the

native structure of a protein is the one for which the free energy achieves the global minimum.

2 components to ab initio prediction:1. devising a scoring (ie, energy) function that can

distinguish between correct (native or native-like) structures from incorrect ones.

2. a search method to explore the conformational space. The most difficult, but most useful approach.

Ab-initio method

Richard B, David B(2001), AB INITIO PROTEIN STRUCTURE PREDICTION: Progress and Prospects, Annual review of biophysical and biomolecular structures, 30, pp. 73-88.

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Ab-initio method

Sequence

Secondary structure

Prediction

Tertiary structure

Low energy structures

Predicted structureEnergy

Minimization

Validation

Mean field potentials

Richard B, David B(2001), AB INITIO PROTEIN STRUCTURE PREDICTION: Progress and Prospects, Annual review of biophysical and biomolecular structures, 30, pp. 73-88.

• Existing SSP Methods• Statistical Methods (Chou,GOR)• Physio-chemical Methods• A.I. (Neural Network Approach)• Consensus and Multiple Alignment

• Our Method APSSP of SSP• Neural Network• Example Based Learnning• Multiple Alignment

• Steps involved in APSSP• Blast search against protein sequence (NR)• Multiple Alignment (ClustalW)• Profile by HMMER, Result by Email

• Recogntion: CASP,CAFASP,LiveBench, MetaServer

Secondary Structure Prediction54


Web servers for structure prediction

JPRED:-http://www.compbio.dundee.ac.uk/~www-jpred/

PHD:-http://cubic.bioc.columbia.edu/predictprotein/

PSIPRED:-http://bioinf.cs.ucl.ac.uk/psipred/

Chou and Fassman:-http://fasta.bioch.virginia.edu/fasta_www/chofas.htm

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Future technologies

Modeling of biologically relevant states of proteins using all available templatesHomooligomers

Heterooligomers

Amino acid modifications

Bound ligands (small molecules, nucleic acids)

Modeling of specific classes of proteins

Antibodies

Repeat proteins (ARM/HEAT, WD repeats)

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Ram S, Yu Xia, Enoch H, Michael L(1999), Ab Initio Protein Structure Prediction Using a Combined Hierarchical Approach, PROTEINS: Structure, Function, and Genetics, 3, pp. 194–198.

Available databases, software, and services

Rotamer library

ProtBuD -- biological units database across families

PISCES -- non-redundant sequences in PDB

MolIDE 1.5

ArboDraw -- drawing phylogenetic trees

BioDownloader -- automatic updating of biological databases

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Assessment of accuracy of PSP

P = (N – total incorrect) N

total incorrect = total number of residues whose conformations are predicted incorrectlyN = the number of residues in the protein.

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Applications of PSP:

Drug targetting. Pharmacogenetics. Pharmacogenomics. MOA. Dosage regimen.

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Conclusion

Pharmacist

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Biotechnologist

Molecular modeling

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Conclusion

Pharmacist Biotechnologist

Protein structure prediction

References:References:

1. Lubert S, Tymoczko J L, Jeremy M B(2003). Text book of biochemistry, W. H. Freeman and company press, 5th edition, pp. 198-230.

2. Thomas L L, David A W, Victoria K(1999), Foye’s principles of Medicinal Chemistry, Lippincott Williams & Wilkins publications, 6th edition, 3, pp. 55-63.

3. Mateusz K, Michał J, Andrzej K(2011), Multiscale Approaches to Protein Modeling, Springer Science+Business Media, 12th edition, pp. 21-32.

4. Zhan Y Z, Tom L B(1996), The Use of Amino Acid Patterns of Classified Helices and Strands in Secondary Structure Prediction, Journal of Molecular biology, 260, pp. 61–76.

5. Schween G, Egener T, Fritzkowsky D, Granado J, Guitton M C(2005), Large-scale analysis of Physcomitrella plants transformed with different gene disruption libraries: Production parameters and mutant phenotypes, Plant Biology, 7 (3), pp. 228–237.

6. David F B, Charlotte M D, Hampapathalu A N, Nuria C, An Iterative Structure-Assisted Approach to Sequence Alignment and Comparative Modeling, PROTEINS: Structure, Function, and Genetics Supplementations, 3, pp. 55-60.

7. Thomas L, Ralf Z(2000), Protein structure prediction methods for drug design, Briefings in Bioinformatics, 3, pp. 275-288.

8. Anfinsen C B(1973), Principles that govern the folding of protein chains, Biological Science, 181, pp. 223–230.

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References:References:

9. Richard B, David B(2001), AB INITIO PROTEIN STRUCTURE PREDICTION: Progress and Prospects, Annual review of biophysical and biomolecular structures, 30, pp. 73-88.

10. Saville W B, Shearer G (1925), An X-ray Investigation of Saturated Aliphatic Ketones, Journal of the Chemical Society, 127, pp. 591.

11. Addess M, Kenneth J, Feigon J(1996). Introduction to 1H NMR Spectroscopy of DNA. Bioorganic Chemistry: Nucleic Acids, Oxford University Press, 8 th edition, pp. 238.

12. Ram S, Yu Xia, Enoch H, Michael L(1999), Ab Initio Protein Structure Prediction Using a Combined Hierarchical Approach, PROTEINS: Structure, Function, and Genetics, 3, pp. 194–198.

13. Rajkumar B, Branson K, Giddy J, Abramson D(2003), The Virtual Laboratory : A toolset to enable distributed molecular modeling for drug design on the World-Wide Grid, Concurrency and computation, 15, pp. 1–25.

14. Griffith S, David J(2004), Introduction to Quantum Mechanics, Prentice Hall press, 2nd edition, 1, pp. 1-4.

15. Leach A R(2001), Molecular Modelling: Principles and Applications, Oxford press, 4th edition, 1, pp. 1-3.

16. LEONOR C H, PAULO A S(2001), Protein folding : thermodynamic versus kinetic control, Journal of biological physics, 27, pp. 6-8.

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Useful links:Useful links:

Date: 28/10/2012.1. http://dunbrack.fccc.edu2. http://courses.washington.edu/conj/protein/insulin2.gif3. http://www.biochem.ucl.ac.uk/bsm/pdbsum/1gwf/main.html4. http://opbs.okstate.edu/~petracek/2002%20protein%20structure%20function/CH06.gif5. http://my.webmd.com/hw/health_guide_atoz/zm2662.asp?printing=true6. http://www.grin.com/object/

external_document.274822/5fbac5ddfea3cb2dd3dde8ad8ee981f9_LARGE.png

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Thank you…..Thank you…..

protein sturcture prediction and molecular modelling

Education

molecular mechanics

molecular modelling

molecular system

molecular modeling4

molecular dynamics program

molecular modeling methods6the

total potential energy

torsional energy