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CZ3253: Computer Aided Drug design Lecture 4: Structural modeling of chemical molecules Prof. Chen Yu Zong Tel: 6874-6877 Email: csccyz@nus.edu.sg.

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Presentation on theme: "CZ3253: Computer Aided Drug design Lecture 4: Structural modeling of chemical molecules Prof. Chen Yu Zong Tel: 6874-6877 Email: csccyz@nus.edu.sg."— Presentation transcript:

1 CZ3253: Computer Aided Drug design Lecture 4: Structural modeling of chemical molecules Prof. Chen Yu Zong Tel: Room 07-24, level 7, SOC1, National University of Singapore

2 Formula for chemical compounds:
Molecular formula: Element(No. of atom) .Element (No. of atom) .... Elements are placed in the order of C, N, H, O, and others. There can be exceptions to this rule.          Examples:   Carbon dioxide  CO2 Ammonia   NH3 Octane   C8H18

3 Formula for chemical compounds:
Condensed formula   Formula reflects organization. Members of the same functional group are placed together. Example:

4 Formula for chemical compounds:
Structural formula 2D drawing of whole organization of chemical compound. Example:

5 Formula for chemical compounds:

6 Chemical bonds: There are 3 types of bonds:
There are 3 types of bonds: single bond (1 bond between 2 atoms) double bond (2 bonds between 2 atoms) triple bond (3 bonds between 2 atoms) Two atoms may be connected by one of these types of bonds according to their chemical properties. The length of each types of bonds are in certain ranges

7 Chemical bonds:

8 Chemical bonds: Problem solving example:
Problem solving example: In each pair of bonds, predict which will be shorter? (a) C=C or C-C (b) C=C or C=O Solution: (a) C=C For the same pair of atoms, double bond is always shorter than single bond. (b) C=O According to the Table, the length of C=O is 122pm which is shorter than that (134pm) of the C=C.

9 Chemical Compounds: Stereochemistry Three features:
Stereochemistry Three features: Configuration (atom organization). Conformation (atom spatial arrangement). Shape (Surface landscape, steric packing)

10 Chemical Compounds: Configuration:
Configuration:   The organization of atoms and chemical bonds.   Change of configuration requires breaking of bonds.

11 Chemical Compounds: An important aspect of configuration is chirality.
An important aspect of configuration is chirality. Chirality defines the property of mirror image.   If mirror image is not the same as the original, the compound is called chiral.

12 Chemical Compounds: Example

13 Chemical Compounds: Conformation:
Conformation:   Determined by the spatial positions of its constituent atom. Interconvertible without breaking and making of bonds.   Conformation change is the key in many chemical reactions in living system.

14 Chemical Compounds: III. Shape
Steric packing (what part of space is covered by the compound).     Surface features (cavities, grooves where other molecules can bind to).     Molecular shape determines the binding of two molecules.

15 Atomic Motions in Chemical Compounds:
Atoms are not rigidly positioned.   External and internal forces can induce atomic motions. Some motions have chemical effect.   Example: Binding of a drug to a protein can induce an atomic motion in protein that leads to the change of the 3D shape of that protein. This shape change makes a chemically important cavity inaccessible to other molecules.

16 Atomic Motions in Chemical Compounds:
The effect of motions are described by energy:     Energy measures the ability to do work.   Motion is associated with energy.   There are two types of energy: Kinetic energy -- motional energy. Kinetic energy is related to the speed and mass of a moving object. The higher the speed and the heavier the object is, the bigger work it can do.

17 Atomic Motions in Chemical Compounds:
Potential Energy -- "positional" energy Potential energy description: Water falls from higher ground to lower ground. In physics such a phenomenon is modeled by potential energy description: Objects move from higher potential energy place to lower potential energy place.

18 Atomic Motions in Chemical Compounds:
Potential Energy -- "positional" energy Potential energy description: Water falls from higher ground to lower ground. In physics such a phenomenon is modeled by potential energy description: Objects move from higher potential energy place to lower potential energy place.

19 Atomic Motions in Chemical Compounds:
Potential Energy -- "positional" energy Different types of bond motions are modeled by different energy functions.   Energy terms are additive.   The total energy determines overall effect.

20 Structural Modeling of Compounds: Basic Interactions and Their Models
The stretching energy equation is based on Hooke's law. The "kb" parameter controls the stiffness of the bond spring, while "ro" defines its equilibrium length.

21 Structural Modeling of Compounds: Basic Interactions and Their Models
The stretching energy equation is based on Hooke's law. The "kb" parameter controls the stiffness of the bond spring, while "ro" defines its equilibrium length.

22 Structural Modeling of Compounds: Basic Interactions and Their Models
The bending energy equation is also based on Hooke's law

23 Structural Modeling of Compounds: Basic Interactions and Their Models
The bending energy equation is also based on Hooke's law

24 Structural Modeling of Compounds: Basic Interactions and Their Models
The torsion energy is modeled by a simple periodic function Why?

25 Structural Modeling of Compounds: Basic Interactions and Their Models
Torsion energy as a function of bond rotation angle.

26 Structural Modeling of Compounds: Basic Interactions and Their Models
The non-bonded energy accounts for repulsion, van der Waals attraction, and electrostatic interactions.

27 Structural Modeling of Compounds: Basic Interactions and Their Models
van der Waals attraction occurs at short range, and rapidly dies off as the interacting atoms move apart. Repulsion occurs when the distance between interacting atoms becomes even slightly less than the sum of their contact distance. Electrostatic energy dies out slowly and it can affect atoms quite far apart.

28 Structural Modeling of Compounds: Basic Interactions and Their Models
Hydrogen Bond: N-H … O N-H … N O-H … N O-H … O Modeled by VdW+electrostatic Modeled by More potential

29 Structural Modeling of Compounds: Basic Interactions and Their Models
Concept of energy scale is Important for molecular Modeling

30 Structural Modeling of Compounds: Basic Interactions and Their Models
Concept of energy scale is Important for molecular modeling

31 Structural Modeling of Compounds: Basic Interactions and Their Models
Sources of force parameters: Bonds, VdW, Electrostatic (for amino acids, nucleotides only): AMBER: J. Am. Chem. Soc. 117, CHARMM: J. Comp. Chem. 4, H-bonds (Morse potential): Nucleic Acids Res. 20, Biophys. J. 66, Electrostatic parameters of organic molecules need to be computed individually by using special software (such as Gaussian)

32 Representation of Chemical Compounds
How to represent a compound? Each structure represented by digital form of structural, physico-chemical properties: Simple molecular properties (molecular weight, no. of rotatable bonds etc.) Molecular Connectivity and shape Electro-topological state polarity Quantum chemical properties (electric charge, polaritability etc. 13 in total) Geometrical properties (molecular size vectors, van der Waals volume, molecular surface etc. 16 in total) J. Chem. Inf. Comput. Sci. 44,1630 (2004) J. Chem. Inf. Comput. Sci. 44, 1497 (2004) Toxicol. Sci. 79,170 (2004).

33 Molecular Descriptors
Constitutional MW, N atoms, Topological Connectivity,Weiner index Electrostatic Polarity, polarizability, partial charges Geometrical Descriptors Length, width, Molecular volume Quantum Chemical HOMO and LUMO energies Vibrational frequencies Bond orders Total energy

34 Molecular Descriptors
van der Waals volume The sum of the non-overlaping volume of van der Waals sphere of each atom of the molecule Molecular surface The area of the surface contours generated by rolling a probing sphere against the surface atoms of the molecule

35 Molecular Descriptors
Molecular size vectors Define ranges for distances and angles

36 Molecular Descriptors
Octanol-Water Partition Coefficients P = C(octanol) / C(water) log P like rG = - RT ln Keq Hydrophobic - hydrophilic character P increases then more hydrophobic

37 Molecular Descriptors BCI Chemical Descriptors
Descriptors are binary and represent: - augmented atoms - atom pairs - atom sequences - ring compositions

38 Molecular Descriptors
Molecular Structures MW: D LogP: 6.71 Connectivity Matrix e.g. , BCUT’s

39 Molecular descriptors
Slide 7 Molecular descriptors chemical fingerprint Hashed binary fingerprint Encodes topological properties of the chemical graph: connectivity, edge label (bond type), node label (atom type) Allows the comparison of two molecules with respect to their chemical structure Construction Find all 0, 1, …, n step walks in the chemical graph Generate a bit array for each walks with given number of bits set Merge the bit arrays with logical OR operation This example illustrates how a 10 bits long topological chemical fingerprint is created for a simple chain structure. In this example all walks up to 3 steps are considered, and 2 bits are set for each pattern.

40 Molecular descriptors
Slide 7 Molecular descriptors chemical fingerprint Example CH3 – CH2 – OH walks from the first carbon atom length walk bit array C 1 C – H C – C 2 C – C – H C – C – O 3 C – C – O – H This example illustrates how a 10 bits long topological chemical fingerprint is created for a simple chain structure. In this example all walks up to 3 steps are considered, and 2 bits are set for each pattern. merge bit arrays for the first carbon atom:

41 Molecular descriptors
Slide 8 Molecular descriptors chemical fingerprint Two β2 adrenoceptor agonist molecules, and their 64 bit hashed chemical fingerprints. These fingerprints clearly reflect the high structural similarity between the two compounds: there are only two bits that differ.

42 Molecular descriptors
Slide 10 Molecular descriptors Pharmacophore fingerprint Pharmacophore point type based coloring of atoms: acceptor, donor, hydrophobic, none. The pharmacophores of these two structures are the same (these are both ACE inhibitors). A topological cross-correlation pharmacophore fingerprint is constructed from the structures and the mapped pharmacophoric point types. (In this example only three different pharmacophore point types were considered: acceptor, donor and hydrophobic.) Each point type pair is counted in a corresponding histogram bin depending on their topological distance. (Topological distances from 1 to 6 bonds apart were considered.) The two histograms visibly represent the pharmacophoric similarity of the two compounds, especially specific (or hard) pharmacophore points (hydrogen bond acceptor and donor) related histograms (AA, DA) show significant similarity. Bars in the histograms of the second structure are higher due to the larger size of the corresponding molecular graph.

43 Topological pharmacophore fingreprint
Encodes pharmacophore properties of molecules as frequency counts of pharmacophore point pairs at given topological distance Allows the comparison of two molecules with respect to their pharmacophore Construction Perceive pharmacophoric features Map pharmacophore point type to atoms Calculate length of shortest path between each pair of atoms Assign a histogram to every pharmacophore point pairs and count the frequency of the pair with respect to its distance

44 Pharmacophore perception
Rule based approach donor acceptor donor Rule 1: The pharmacophore type of an atom is an acceptor, if it is a nitrogen, oxygen or sulfur, and it is not an amide nitrogen or sulfur, and it is not an aniline nitrogen, and it is not a sulfonyl sulfur, and it is not a nitro group nitrogen.

45 Exceptions to simple rules
donor n-cyano-methil piperidine sp2 atom exception  extra rules  large number of rules  maintenance, performance

46 Effect of pH acceptor pH = 7 donor pH = 1
pH  pH specific rules  large number of rules  maintenance, performance

47 Pharmacophore Construction
Calculation based approach Step 1: estimation of pKa allows the determination of the protonation state for ionizable groups at the given pH Step 2: partial charge calculation

48 Pharmacophore Construction
Calculation based approach Step 3: hydrogen bond donor/acceptor recognition Step 4: aromatic perception Step 5: pharmacophore property assignment acceptor negatively charged acceptor acceptor and donor hydrophobic none

49 Pharmacophore fingerprint
Pharmacophore type coloring: acceptor, donor, hydrophobic, none.


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