Understanding types of Chemical data

1. CHEMICAL DATA
Abhik Seal
Indiana University Bloomington (dsdht.wikispaces.com)

2. Types of Chemical Data
Chemical
Data
Drugs
Agrochemic
als
Fragrances
Food
Additives
Natural
Products

3. Data on Drugs
• Chemical Properties
a) Solubility
b) ADME & Pharmacokinetics /Pharmacodynamics
c) LD50, IC50
d) Structural Properties
e) Chemical Reactions
f ) Chemogenomics interactions
Chemical-gene interactions
Chemical-disease interactions
Chemical-GO enriched interactions
Chemical-pathway enriched associations
• Adverse events / side effects of drugs
• Toxicological data

4. Data on Drugs (ADME)
Cell permeability and Absorption example
Real World Drug Discovery A Chemist’s Guide to Biotech and Pharmaceutical Research

5. Partition coefficients
1-Octanol is the most frequently used lipid phase in pharmaceutical research.
This is because:
§ It has a polar and non polar region (like a membrane phospholipid)
§ Po/w is fairly easy to measure
§ Po/w often correlates well with many biological properties
§ It can be predicted fairly accurately using computational models
Xaqueous
Xoctanol
P
Partition coefficient P (usually expressed as log10P or logP) is defined as:
P =
[X]octanol
[X]aqueous
P is a measure of the relative affinity of a molecule for the lipid and aqueous phases in
the absence of ionisation.

6. Modeling LogP an example
LogP for a molecule can be calculated from a sum of fragmental or atom-based terms plus
various corrections.
logP = Σ fragments + Σ corrections
C: 3.16 M: 3.16 PHENYLBUTAZONE
Class | Type | Log(P) Contribution Description Value
FRAGMENT | # 1 | 3,5-pyrazolidinedione -3.240
ISOLATING |CARBON| 5 Aliphatic isolating carbon(s) 0.975
ISOLATING |CARBON| 12 Aromatic isolating carbon(s) 1.560
EXFRAGMENT|BRANCH| 1 chain and 0 cluster branch(es) -0.130
EXFRAGMENT|HYDROG| 20 H(s) on isolating carbons 4.540
EXFRAGMENT|BONDS | 3 chain and 2 alicyclic (net) -0.540
RESULT | 2.11 |All fragments measured clogP 3.165
clogP for windows output
N
N
C
C
C
C
C
C
C
O
C
C
O
C
C
C
C
C
C
C
C
C
C
H
H
H
H
H H
H
H
H
H
H
H
H
H
H
H
H
H
H
HPhenylbutazone
Branch

7. logP
Binding to
enzyme /
receptor
Aqueous
solubility
Binding to
P450
metabolising
enzymes
Absorption
through
membrane
Binding to
blood / tissue
proteins –
less drug free
to act
Binding to
hERG heart
ion channel -
cardiotoxicity
risk
So log P needs to be optimised
What else does LogP affect?

8. How to predict properties ??
Molecular Descriptors
Molecular
descriptors
are
numerical
values
that
characterize
proper4es
of
molecules.
The
descriptors
fall
into
Four
classes
.
a)
Topological
b)
Geometrical
c)
Electronic
d)
Hybrid
or
3D
Descriptors

9. Classification of Descriptors
Topological descriptors are derived directly from the connection
table representation of the structure which include:
a) Atom and Bond Counts
b) substructure counts (MACCS Keys, ISIDA Fingerprints)
c) molecular connectivity Indices (Weiner Index , Randic Index, Chi
Index)
d) Kappa Indices
e) path descriptors ( ECFP, FCFP)
f) distance-sum Connectivity
g) Molecular Symmetry

10. Classification of Descriptors
Geometrical descriptors are derived from the three-dimensional
representations and include:
a) principal moments of inertia,
b) molecular volume,
c) solvent-accessible surface area,
d) Charged partial Surface area
e) Molecular Surface area

11. Classification of Descriptors
Electronic descriptors characterize the molecular structures with such as :
• Dipole moment,
• Quadrupole moment,
• Polarizibility,
• HOMO and LUMO energies,
• Dielectric energy
• Molar Refractivity

12. ToolsTo calculate Molecular Descriptors
Freely available some examples
• CDK tool
http://rguha.net/code/java/cdkdesc.html
• RDKit
http://www.rdkit.org/
• POWER MV
http://nisla05.niss.org/PowerMV/?q=PowerMV/
• MOLD2
http://www.fda.gov/ScienceResearch/BioinformaticsTools/
Mold2/default.htm
• PADEL Descriptor
http://www.downv.com/Windows/install-PaDEL-
Descriptor-10439915.htm