“Docking” and “Molecular Dynamics Simulations”

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An introduction into “Docking” and “Molecular Dynamics simulations” Univ. Ass. Dipl.-Ing. (FH) Dr. scient. med. Bernhard Knapp Center for Medical Statistics, Informatics and Intelligent Systems Department for Biosimulation and Bioinformatics Medical University of Vienna / AKH (General Hospital) [email protected] 23.02.2012 Bernhard Knapp 1 TOC 1. Basic biology knowledge 2. Docking • Docking in general • Example AutoDock 3. Molecular Dynamics • Introduction • Limitations • Example Gromacs 3. Tutorial on PDB / jmol 23.02.2012 Bernhard Knapp 2 Basic biology knowledge 23.02.2012 Bernhard Knapp 3 Amino acids Build up proteins (german “Eiweiß”) all have the same basic structure (“backbone” consisting of an amine group, a carboxylic acid group and a C-alpha atom) but differ in their side-chain => residue (the side chain defines which AA it is) 20 different canonical amino acids (AAs) are existing (that means 20 different side-chains) 23.02.2012 4 Wikimedia Wikimedia 23.02.2012 5 Several amino acids are connected via „peptide bonds“ Wikimedia 23.02.2012 Bernhard Knapp 6 Then they are called: peptide: > 1 AA oligopeptide: < 10 (other sources state 30) polypeptide: > 10 AAs protein: > 50 AAs macropeptide: > 100 AAs monopeptide: 1 AA dipeptide: 2 AA tripeptide: 3 AA tetrapeptide: 4 AA pentapeptide: 5 AA hexapeptide: 6 AA heptapentide: 7 AA octapeptide: 8 AA nonapeptide: 9 AA decapeptide: 10 AA undecapeptide: 11 AAs ... icosapeptide: 20 AAs tricontapeptide: 30 AAs tetracontapeptide: 40 AAs … however the exact definitions differ (and you do not need to learn them for the examination of this lecture!) 23.02.2012 Bernhard Knapp 7 Structure levels Primary structure: the pure sequence of the AAs Secondary structure: e.g. beta-sheet, alpha-helix, or turns Tertiary structure: 3D arrangement of secondary structure elements Quaternary structure: several proteins together Wikimedia 23.02.2012 Bernhard Knapp 8 How we can illustrate them (also see the tutorial at the end) 23.02.2012 9 And what about the size of proteins and AAs? [Janeway] ~20x20x20 nm ~13x6x5 nm 1 Nanometer == 10-9m == 0.0000000001m 2 more definitions: Ligand: also known as (small) peptide, epitope, guest, antigenic determinant Receptor: also known as (big) protein, host, macro molecule 23.02.2012 Bernhard Knapp 12 Docking in general 23.02.2012 Bernhard Knapp 13 What does docking mean? trying to find the „best matching“ between 2 molecules 23.02.2012 Bernhard Knapp 14 Who could fit to me? / / / / . Let us try with this one … - („induced fit“) 23.02.2012 15 23.02.2012 Bernhard Knapp 16 [Kitchen et al., 2004] 23.02.2012 Bernhard Knapp 17 Why is docking useful? Docking (~Virtual Screening) is of paramount interest for drug discovery For one target millions of different possible drugs can be tested The best n matches will be tried in experiments Will save time, resources and money 23.02.2012 Bernhard Knapp 18 Usually 3 steps 1) Decide how to search through the spatial space 2) Decide how flexible ligand and receptor can be 3) Decide how to score various parameter sets 23.02.2012 Bernhard Knapp 19 Where is the difficulty? 1) 6 degrees of freedom in 3d space (3 translational, 3 rotational) 2) 100+ degrees of freedom if we consider full flexibility of all bounds 3) nearly each atom interacts witch every other one 23.02.2012 BernhardB h d KnappK 20 Ad 1) Search Algorithms used (for spatial space) Systematic docking - Brute Force - Fragmentation - Database Heuristic docking - Monte Carlo - Genetic algorithms - Tabu search Simulations Docking - Molecular Dynamics - Gradient (Energy) Methods 23.02.2012 Bernhard Knapp 21 Ad 2) Deciding about the flexibility “rigid body” docking - receptor and ligand are considered as 100% rigid - very fast (6dfs only), but inaccurate “induced fit” docking - moveable [backbone| side] chains “flexible ligand” - only the ligand is considered als flexible, the receptor remains rigid “full flexibility” - computational very expensive 23.02.2012 Bernhard Knapp 22 Ad 3) Scoring functions (1/2) Force Field based scoring function - energy of the interaction and internal energy of the ligand - combination of : Van der Waales, Lennard Jones, electrostatic energy, … - e.g. D-Score, GoldScore, AutoDock, CHARMM, … empirical scoring functions - Trying to reproduce experimental observed docking behaviors by means of formulas - usually the sum of uncorrelated terms - e.g. LUDI, F-Score, SCORE, X-SCORE, … 23.02.2012 Bernhard Knapp 23 Scoring Funktionen (2/2) Knowledge based scoring function - trying the deduce rules form experiments - e.g. DrugScore, PMF, … Geometrical scoring function - based on shape complementarity - e.g. Connely Surface, Soft Belt Scoring Consensus scoring function - hybrid versions - e.g. various Review Papers: [Trost, 2005] 23.02.2012 Bernhard Knapp 24 Difference between position score and rank score „The pose score is often a rough measure of the fit of a ligand into the active site. The rank score is generally more complex and might attempt to estimate binding energies.“ "relatively small chemical modifications can lead to significant changes in binding." [Kitchen et al., 2004] 23.02.2012 25 23.02.2012 Bernhard Knapp [Sousa, 2006] 26 23.02.2012 Bernhard Knapp [Sousa, 2006] 27 Correct result vs incorrect result 23.02.2012232 .02.2012 Bernhard Knapp 28 … and what about the correctness and reliability? Currently correct results are more or less restricted to the area where the tools have been calibrated e.g. for pMHC the area under the ROC is between 0.5 and 0.75 using different substitution and scoring tools [Knapp, 2008] But "We have long known that there is nothing in biology which is fundamentally inconsistent or incommensurable with mathematics, chemistry, and physics. Biology long ago rejected vitalism. The only information needed for life is provided by an organism's chemical constituents. It is unlikely in the extreme that living systems cannot be understood in terms of chemistry and physics.“ [Wan, 2008] 23.02.2012 Bernhard Knapp 29 Example Autodock 23.02.2012 Bernhard Knapp 30 What is Autodock “AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. AutoDock actually consists of two main programs: AutoDock performs the docking of the ligand to a set of grids describing the target protein; AutoGrid pre-calculates these grids. In addition to using them for docking, the atomic affinity grids can be visualised. This can help, for example, to guide organic synthetic chemists design better binders.” url: http://autodock.scripps.edu/ 23.02.2012 Bernhard Knapp 31 search algorithms used for spatial space Systematic docking - Brute Force - Fragmentation - Database Heuristic docking - Monte Carlo - Genetic algorithms - Tabu search Simulations Docking - Molecular Dynamics - Gradient (Energy) Methods 23.02.2012 Bernhard Knapp 32 Deciding about the flexibility “rigid body” docking - receptor and ligand are considered as 100% rigid - very fast (6dfs only), but inaccurate “induced fit” docking - moveable [backbone| side] chains “flexible ligand” - only the ligand is considered als flexible, the receptor remains rigid “full flexibility” - computational very expensive 23.02.2012 Bernhard Knapp 33 Scoring functions (1/2) Force Field based scoring function - energy of the interaction and internal energy of the ligand - combination of : Van der Waales, Lennard Jones, electrostatic energy, … - e.g. D-Score, GoldScore, AutoDock, CHARMM, … empirical scoring functions - Trying to reproduce experimental observed docking behaviors by means of formulas - ususlly the sum of uncorrelated terms - e.g. LUDI, F-Score, SCORE, X-SCORE, … 23.02.2012 Bernhard Knapp 34 Scoring Funktionen (2/2) Knowledge based scoring function - trying the deduce rules form experiments - e.g. DrugScore, PMF, … Geometrical scoring function - based on shape complementarity - e.g. Connely Surface, Soft Belt Scoring Consensus scoring function - hybrid versions - e.g. various Review Papers: [Trost, 2005] 23.02.2012 Bernhard Knapp 35 Autodock: sampling of spatial space (1/4) Simulated Annealing Random start up position, e.g. here Quality of solution ofQuality Stack in local min Global min Different solutions 23.02.2012 Bernhard Knapp 36 Autodock: sampling of spatial space (2/4) simulated annealing (german “abkühlen”) procedure: Idea: local neighborhood search but „sometimes“ accepting worse solutions (certain probability) Similar to annealing of crystals in physics E j Ei kBT 1. Melt a solid body in a heating pot p e 2. Atoms are almost randomly distributed 3. Slowly anneal 4. At each temperature a thermical balance is found 5. Atoms will arrange in an energetically advantageous position 23.02.2012 Bernhard Knapp 37 Autodock: sampling of spatial space (3/4) Genetic Algorithms - A set a values is used to define the ligand, receptor and their current states - Doing it as nature: 1. Creating random population of solutions P1 P2 C1 2. Evaluation of fitness 24 23 24 3. Selection of the fittest n solutions 46 66 46 78 84 78 4. cross over, mutation, … 90 × 90 90 5. goto 2 again 4 92 92 33 12 12 99 78 5 65 44 44 23.02.2012 Bernhard Knapp 38 Autodock: Flexibility (1/1) receptor hold rigid ligands bounds have full flexibility according to a rotamer library state of ligands bounds are represented as genes in the GA 23.02.2012 Bernhard Knapp 39 Autodock: Scoring in 1998 (1/1) 12, 6 Lennard Jones potential Hydrogen bounds, weighted by
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