The document discusses different types of molecular descriptors that can be used to characterize chemical structures, including geometry-based descriptors, surface-based descriptors, structural fragments, and descriptors of lipophilicity. It provides examples of various quantum chemical descriptors, surface area descriptors, structural fragment descriptors, and ways to describe lipophilicity and log P values. The document also briefly mentions the varying computational requirements of different descriptor types.

1. Different types of descriptors that includes
geometry based, surface based, structural
fragments and lipophilicity
Presented by
Gaurav
19mslsbf03

2. Descriptors
 The manipulation and analysis of chemical structural information is made possible through the use of
molecular descriptors.
 These are numerical values that characterise properties of molecules.
 For example, they may represent the physicochemical properties of a molecule or they may be values that
are derived by applying algorithmic techniques to the molecular structures.
 Many different molecular descriptors have been described and used for a wide variety of purposes.
 They vary in the complexity of the information they encode and in the time required to calculate them.
• In general, the computational requirements increase with the level of discrimination that is achieved. For
For example, the molecular weight does not convey much about a molecule’s properties but it is very rapid
to compute.
• By contrast, descriptors that are based on quantum mechanics may provide accurate representations of
properties, but they are much more time consuming to compute.
• Some descriptors have an experimental counterpart (e.g.the octanol–water partition coefficient), whereas
others are purely algorithmic constructs (e.g. 2D fingerprints).

3. Geometry based descriptors

4. Quantum Chemical Descriptors
Quantitative values calculated in QUANTUM MECHANICS
(semi-empirical, HF Ab Initio or DFT ) calculations
• • LUMO - Lowest occupied molecular orbital energy
• • HOMO - Highest occupied molecular orbital energy
• • DIPOLE moment
• • Components of dipole moment along inertial axes (Dx, Dy, Dz)
• • Hf - Heat of formation
• • Mean Polarizability - α = 1/3(αxx+αyy+αzz)
• • EA – Electron Affinity
• • IP – Ionization Potential
• • ΔE – Energy of Protonation
• • Electrostatic Potential -

7. Surface-based descriptors
• Surface area
• Vander Waals, Solvent-Accessible, Molecular (Connolly)
surface area.

8. Surface Polarity descriptors
• Polar Surface Area: Total area of the part of the
molecular surface that corresponds to polar atoms:
O, N, halogens.

9. Structural fragments based descriptors
• Due to their enormous diversity, one could hardly review all
types of 2D fragment descriptors used for structural search in
chemical database or in SAR/QSAR/ QSPR studies. Here, we
focus on some of them which are the most efficiently used in
virtual screening and in silico design of organic compounds.
• Generally, molecular fragments can be classified with respect
to their topology (atom-based, chains, cycles, polycycles, etc),
information content of vertices in molecular graphs (atoms,
groups of atoms, pharmacophores, descriptor centers) and the
level of abstraction when some information concerning atom
and bond types is omitted.

12. Lipophilicity

13. Log P
quantitative representation of the lipophilicity of the molecules, it is obtained
by measuring the partitioning of the molecule between an aqueous phase
and a lipophilic phase which consists usually of water/n-octanol
• lipophilicity plays a fundamental role in biochemical processes such a
penetration, distribution, metabolism clearance and affect the activity of a
• molecule in the binding state environment.
• “Pioneering work by Hansch Leo had led to use of logP in QSAR methods as a
general descriptors of cell permeability”.
• The negative coefficient of LogP in the QSPR models indicate negative
contribution of lipophilicity towards the permeability of selected set of
compounds.
• The relative proportionality of the Log P values of whole molecule was
observed in both active and inactive compounds.

14. References:
• 1. “Tutorials in Chemoinformatics”, A. Varnek, Ed. ,
WILEY, 2017
• 2. A. Leach, V. Gillet “An Introduction to
Chemoinformatics”, Springer, 2007
• 3. R. Todeschini, V. Consonni “Handbook of Molecular
Descriptors”, WILEY, 1, 1992
• https://doi.org/10.1021/ed069p701
• 5. https://en.wikipedia.org/wiki/Molecular_descriptor

15. Thank you!