MOLECULAR MODELING N PRIMER DESIGN

MOLECULAR MODELIING AND PRIMER DESIGNING: A COMPUTATIONAL APPROACH : 

MOLECULAR MODELIING AND PRIMER DESIGNING: A COMPUTATIONAL APPROACH

Bioinformatics : 

Bioinformatics Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights and to create a global perspective from which unifying principles in biology can be discerned. Molecular Modeling is one of the important area of Bioinformatics

Molecular Modeling : 

Molecular Modeling Computational programs generate molecular data 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) bulk properties (volumes, surface areas, diffusion, viscosity, etc.).

Cont…. : 

Cont…. Molecular modeling encompasses theoretical methods and computational techniques used to model or mimic the behavior of different molecules. The most common feature of molecular modeling techniques is the atomistic level description of the molecular systems

Computer assisted molecular design (CAMD) : 

Computer assisted molecular design (CAMD) The starting point for many studies is generally a two dimensional drawing of a compound of interest. These diagrams can range from notebook or "back-of-the-envelope" sketches to electronically stored connection tables in which one defines the types of atoms in the molecule, their hybridization and how they are bonded to each other. Carbon dioxide, for example, would be defined as one SP2 oxygen atom (atom number 1) bonded to an SP carbon atom (atom number 2) with a double bond which in turn, is bonded to a second SP2 oxygen atom with a double bond.

Connection Table for Carbon Dioxide : 

Connection Table for Carbon Dioxide atom # Atom Name Atom Type Bound to atoms 1 O 5 2 2 C 2 1, 3 3 O 5 2Connection tables are easily stored and searched electronically. However, they must be transformed into three dimensional representations of chemical structure to study chemical properties.

Slide 7: 

The "mechanical" molecular model was developed out of a need to describe molecular structures and properties in as practical a manner as possible. Molecular mechanics is a mathematical formalism which attempts to reproduce molecular geometries, energies and other features by adjusting bond lengths, bond angles and torsion angles to equilibrium values that are dependent on the hybridization of an atom and its bonding scheme. Molecular Mechanics Background

Slide 8: 

Epot is the total steric energy which is defined as the difference in energy between a real molecule and an ideal molecule. Ebnd, the energy resulting from deforming a bond length from its natural value, is calculated using Hooke's equation for the deformation of a spring (E = 1/2 Kb(b - bo)2 where Kb is the force constant for the bond, bo is the equilibrium bond length and b is the current bond length). Eang, the energy resulting from deforming a bond angle from its natural value, is also calculated from Hooke's Law. Etor is the energy which results from deforming the torsion or dihedral angle. Eoop is the out-of-plane bending component of the steric energy. Enb is the energy arising from non-bonded interactions Eel is the energy arising from coulombic forces. Energy Calculation

Slide 9: 

An excellent approach to searching regions of conformational space, it is not an exhaustive search. The active conformation of a molecule can be missed as the dynamics simulation skips over the hills and valleys of the potential energy surface. Since the active conformation at a receptor may not always be the minimum energy structure (defined as the structure with the 3D geometry that places the molecule at the lowest point on the potential energy hypersurface), it is important to examine all potentially accessible conformations. For small molecules with a limited number of freely rotating bonds, this can be easily accomplished by driving each torsion angle stepwise over a 360 degree range. As an example, a graph of the conformationally dependent energy (shown along the Y-axis) of the molecule Butane. molecular dynamics

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The number of conformations for a molecule (defined as the "non-identical arrangements of the atoms in a molecule obtainable by rotation about one or more single bonds“ Number of conformers = (360/angle increment)(# rotatable bonds) Butane Conformers

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Optimize molecular geometry and calculate physical and electronic properties. An equally important aspect of CAMD/CADD is the ability to display these properties in a manner which increases the chemist's ability to interpret experimental findings and correlate these finding with structural features. Molecular surfaces play an important role in these studies.

Molecular Modeling Strategies : 

Molecular Modeling Strategies

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In the direct approach, the three-dimensional features of the known receptor site are determined from X-ray crystallography to design a lead molecule. In direct design, the receptor site geometry is known; the problem is to find a molecule that satisfies some geometric constraints and is also a good chemical match. After finding good candidates according to these criteria, a docking step with energy minimization can be used to predict binding strength. Direct drug design

Slide 15: 

The indirect drug design approach involves comparative analysis of structural features of known active and inactive molecules that are complementary with a hypothetical receptor site. If the site geometry is not known, as is often the case, the designer must base the design on other ligand molecules that bind well to the site. Indirect Drug Design

Structure-Based Drug-Design (SBDD) : 

Structure-Based Drug-Design (SBDD) SBDD is an iterative process, in which macromolecular crystallography has been the predominate technique used to elucidate the three-dimensional structure of drug targets Both nucleic acids and proteins are potential drug targets, but the majority of such targets are proteins. Proteins undergo considerable conformational change upon ligand binding, it is important to design drugs based on the crystallographic structures of protein-ligand complexes, not the un liganded structure.

Molecular modeling in drug discovery : 

Molecular modeling in drug discovery I. Two case studies for sequence to structure mapping: Small changes in protein sequence cause dramatic difference in drug binding: COX inhibitors Large changes in protein sequence still maintain similar structure: G protein coupled receptors Protein Structure Prediction III. Ligand Docking to Protein Structures

Mapping Sequence to Protein Structure and Dynamics : 

Mapping Sequence to Protein Structure and Dynamics Primary Sequence MNGTEGPNFY VPFSNKTGVV RSPFEAPQYY LAEPWQFSML AAYMFLLIML GFPINFLTLY VTVQHKKLRT PLNYILLNLA VADLFMVFGG FTTTLYTSLH GYFVFGPTGC NLEGFFATLG GEIALWSLVV LAIERYVVVC KPMSNFRFGE NHAIMGVAFT WVMALACAAP PLVGWSRYIP EGMQCSCGID YYTPHEETNN ESFVIYMFVV HFIIPLIVIF FCYGQLVFTV KEAAAQQQES 3D Structure Folding

Protein-ligand docking : 

Protein-ligand docking First (if structure is known) or second (after structure prediction) step in a drug design project: find a lead structure (=small molecule which binds to a given target) docking problem - predicting the energetically most favorable complex between a protein and a putative drug molecule For a given protein structure, one can apply docking algorithms to virtually search through the space 2 questions: 1. what does the protein-ligand complex look like 2. what is the affinity with respect to other candidates?

Steps in Molecular Docking : 

Steps in Molecular Docking Find a set of compounds to start with     - e.g. from inspecting known ligands for a protein (e.g. substrate in an enzyme) compounds from a screening experiment of a combinatorial library (in which there  is usually a molecular fragment that is common between all molecules of the library, the core, and the fragments attached to the core are R-groups) compounds from a filtering experiment using other software from varying other lead structures or known ligands virtual screening using a fast docking algorithm (typically from a million molecules) de novo design using fragments of compounds => get several hundred to thousands of ligands to start with

Docking Methods : 

Docking Methods Rigid-body docking algorithms Protein and ligand are held fixed in conformational space which reduces the problem to the search for the relative orientation fo the two molecules with lowest energy. All rigid-body docking methods have in common that superposition of point sets is a fundamental sub-problem that has to be solved efficiently: Superposition of point sets: minimize the RMSD Flexible ligand docking algorithms most ligands have large conformational spaces with several low energy states

Example Docking Programs : 

Example Docking Programs DOCK (I. D. Kuntz, UCSF) AutoDOCK (A. Olson, Scripps) RosettaDOCK (Baker, U Wash., Gray, JHU) More information in: http://www.bmm.icnet.uk/~smithgr/soft.html

DOCK : 

DOCK DOCK works in 5 steps: Step 1 Start with coordinates of target receptor Step 2 Generate molecular surface for receptor Step 3 Fill active site of receptor with spheres potential locations for ligand atoms Step 4 Match sphere centers to ligand atoms determines possible orientations for the ligand Step 5 Find the top scoring orientation

Other Docking programs : 

Other Docking programs AutoDock designed to dock flexible ligands into receptor binding sites Has a range of powerful optimization algorithms RosettaDOCK models physical forces Creates a large number of decoys degeneracy after clustering is final criterion in selection of decoys to output

Docking protocol: Step 1 : 

Docking protocol: Step 1 RANDOM START POSITION Creation of a decoy begins with a random orientation of each partner and a translation of one partner along the line of protein centers to create a glancing contact between the proteins

Docking protocol: Step 2 : 

Docking protocol: Step 2 LOW-RESOLUTION MONTE CARLO SEARCH Low-resolution representation: N, C, C, O for the backbone and a “centroid” for the side-chain One partner is translated and rotated around the surface of the other through 500 Monte Carlo move attempts The score terms: A reward for contacting residues, a penalty for overlapping residues, an alignment score, residue environment and residue-residue interactions

Docking protocol: Step 3 : 

Docking protocol: Step 3 HIGH-RESOLUTION REFINEMENT Explicit side-chains are added to the protein backbones using a rotamer packing algorithm, thus changing the energy surface An explicit minimization finds the nearest local minimum accessible via rigid body translation and rotation Start and Finish positions are compared by the Metropolis criterion

Docking protocol: Step 3 : 

Docking protocol: Step 3 Before each cycle, the position of one protein is perturbed by random translations and by random rotations To simultaneously optimize the side-chain conformations and the rigid body position, the side-chain packing and the minimization operations are repeated 50 times

Docking protocol: Step 3 : 

Docking protocol: Step 3 COMPUTATIONAL EFFICIENCY The packing algorithm usually varies the conformation of one residue at a time; rotamer optimization is performed once every eight cycles Periodically filter to detect and reject inferior decoys without further refinement

Docking protocol: Step 4 : 

Docking protocol: Step 4 CLUSTERING & PREDICTIONS Repeat search to create approximately 105 decoys per target Cluster best 200 decoys by a hierarchical clustering algorithm using RMSD The clusters with the most members become predictions, ranked by cluster size

Docking protocol: Results : 

Docking protocol: Results

Molecular docking hands on : 

Molecular docking hands on Download and install Arguslab in windows Load a PDB file, practice Arguslab tools Follow the tutorial at http://www.arguslab.com/tutorials/tutorial_docking_1.htm

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Molecular Docking using Argus lab: Ex : Benzamidine inhibitor docked into Beta Trypsin

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Create a binding site from bound ligand

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Setting docking parameters

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Analyzing docking results

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Polypeptide builder.

Conclusions : 

Conclusions The computational molecular docking problem is far from being solved. There are two major bottle-necks: The algorithms handle limited flexibility Need selective and efficient scoring functions

Slide 42: 

Molecular Modeling Applications

Slide 43: 

Molecular Modeling Applications I. Molecular structures may be generated by a variety of software. The 3D structures of molecules may be created by several common building functions like make-bond, break-bond, fuse rings, delete-atom, add-atom-hydrogens, invest chiral center, etc. Computer modeling allows chemists to build dynamic models of compounds which in turn allows them to visualize molecular geometry and demonstrate chemical principles

Slide 44: 

II. The most important area of the molecular modeling concept is visualization of molecular structures and interactions. The molecules are visualized in three dimensions by various representations like connected sticks, ball and stick models, space filling representations and surface displays.

Slide 45: 

III. The most active area of theoretical research using molecular orbital theory has been in the prediction of the preferred conformation of molecules. The preferred conformation of a molecule is a structural characteristic feature that arises as a response to the force of attraction and repulsion. The shape should be considered primarily in determining the interaction of the molecule with the receptor.

Slide 46: 

IV. The 3D structures of many ligands (drug molecules) that interact with the receptors may be known but the structures of most receptors are not known. The interaction of macromolecular receptors and of small drug molecules is an essential step in many biological processes.

PRIMER DESIGNING : 

PRIMER DESIGNING

General knowledge of DNA replication : 

General knowledge of DNA replication

PCR Background : 

PCR Background Invented in 1982 (Cetus Corp) Discovery of Taq polymerase in 1985 Kary Mullis: Nobel Prize 1993 Widely used method with wide application Many variations of commercial kits

Polymerase Chain Reaction : 

Polymerase Chain Reaction Method for exponential amplification of DNA or RNA sequences Basic requirements template DNA or RNA 2 oligonucleotide primers complementary to different regions of the template heat stable DNA polymerase 4 nucleotides and appropriate buffer

PCR : 

PCR

Slide 52: 

Cycling Program Step 1: 94o C for 30 sec Step 2: 94o C for 15 sec Step 3: 55o C for 30 sec Step 4: 72o C for 1.5 min Step 5: Go to step 2 for 35 times Step 6: 72o C for 10 min Step 7: 4o C forever Step 8: END

HISTORY : 

HISTORY

Considerations About Primers : 

Considerations About Primers Specificity Specific for the intended target sequence (avoid nonspecific hybridization) Stability Form stable duplex with template under PCR conditions Compatibility Primers used as a pair shall work under the same PCR condition Uniqueness Length Annealing Temperature Primer Pair Matching Internal Structure Base Composition Internal Stability Characteristics of primers: Thoughts on primer design: Melting Temperature

Good Primer’s Characteristic : 

Good Primer’s Characteristic A melting temperature (Tm) in the range of ~52°C to 65°C Absence of dimerization capability Absence of significant hairpin formation (>3 bp) Lack of secondary priming sites Low specific binding at the 3' end (ie. lower GC content to avoid mispriming)

Primer design elements : 

Primer design elements Primer length GC% Annealing 3’ complementary between primers G&C runs at the 3’ end Palindrome sequences

Uniqueness : 

Uniqueness There shall be one and only one target site in the template DNA where the primer binds, which means the primer sequence shall be unique in the template DNA. There shall be no annealing site in possible contaminant sources, such as human, rat, mouse, etc. (BLAST search against corresponding genome)

Length : 

Length Primer length has effects on uniqueness and melting/annealing temperature. Roughly speaking, the longer the primer, the more chance that it’s unique; the longer the primer, the higher melting/annealing temperature. Generally speaking, the length of primer has to be at least 15 bases to ensure uniqueness. Usually, we pick primers of 17-28 bases long. This range varies based on if you can find unique primers with appropriate annealing temperature within this range.

Melting Temperature : 

Melting Temperature Melting Temperature, Tm – the temperature at which half the DNA strands are single stranded and half are double-stranded.. Tm is characteristics of the DNA composition; Higher G+C content DNA has a higher Tm due to more H bonds. Calculation Shorter than 13: Tm= (wA+xT) * 2 + (yG+zC) * 4 Longer than 13: Tm= 64.9 +41*(yG+zC-16.4)/(wA+xT+yG+zC) (Formulae are from http://www.basic.northwestern.edu/biotools/oligocalc.html)

Internal Structure : 

Internal Structure If primers can anneal to themselves, or anneal to each other rather than anneal to the template, the PCR efficiency will be decreased dramatically. They shall be avoided. However, sometimes these 2 structures are harmless when the annealing temperature does not allow them to take form. For example, some dimers or hairpins form at 30 C while during PCR cycle, the lowest temperature only drops to 60 C.

Internal stability of the primers : 

Internal stability of the primers Primers with stable 5’ termini and unstable 3’ termini give the best performance: reduces false priming on unknown targets Low 3’ stability prevents formation of duplexes that may initiate DNA synthesis: 5’ end must also pair in order to form a stable duplex Optimal terminal DG ~ 8.5 kcal/mol; excessive low DG reduces priming efficiency

Summary - Primer Design Criteria : 

Summary - Primer Design Criteria Uniqueness: ensure correct priming site; Length: 17-28 bases.This range varies; Base composition: average (G+C) content around 50-60%; avoid long (A+T) and (G+C) rich region if possible; Optimize base pairing: it’s critical that the stability at 5’ end be high and the stability at 3’ end be relatively low to minimize false priming. Melting Tm between 55-80 C are preferred; Assure that primers at a set have annealing Tm within 2 – 3 C of each other. Minimize internal secondary structure: hairpins and dimmers shall be avoided.

Computer-Aided Primer Design : 

Computer-Aided Primer Design Primer design is an art when done by human beings, and a far better done by machines. Some primer design programs we use: Oligo: Life Science Software, standalone application - GCG: Accelrys, ICBR maintains the server. Primer3: MIT, standalone / web application http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi BioTools: BioTools, Inc. ICBR distributes the license. Others: GeneFisher, Primer!, Web Primer, NBI oligo program, etc. Melting temperature calculation software: - BioMath: http://www.promega.com/biomath/calc11.htm