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Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser

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Quantum mechanical polar surface area.

Gijs Schaftenaar¹, Jakob de Vlieg

¹CMBI, Computational Drug Discovery Group, Nijmegen Centre for Life Sciences, Nijmegen University, Geert-Grooteplein 28, 6525 Nijmegen, GA, The Netherlands. schaft@cmbi.ru.nl

Journal of Computer-Aided Molecular Design

|March 7, 2012

Summary

Oral drug absorption in humans correlates with Quantum Mechanical Polar Surface Area (QMPSA), especially when carboxyl groups are deprotonated. This highlights the importance of polar interactions in aqueous drug solutions for absorption.

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Area of Science:

Pharmacokinetics
Computational Chemistry
Drug Discovery

Background:

Oral drug administration is a common route, with absorption being a critical factor for efficacy.
Predicting drug absorption is crucial for efficient drug development.
Polar surface area is a known descriptor for drug permeability.

Purpose of the Study:

To establish a correlation between oral drug absorption and Quantum Mechanical Polar Surface Area (QMPSA).
To investigate the influence of molecular structure (deprotonated vs. neutral) on this correlation.
To provide guidelines for optimizing molecular properties for oral absorption.

Main Methods:

Calculation of QMPSA for training-set molecules using computational chemistry methods.
Analysis of correlation between QMPSA and experimentally determined absorbed fraction after oral administration.
Comparison of QMPSA calculated for deprotonated and neutral molecular structures.

Main Results:

A significant correlation was found between absorbed fraction and QMPSA when carboxyl groups were deprotonated.
The correlation was less pronounced for QMPSA calculated on neutral gas-phase structures.
This indicates that polar interactions in aqueous solution are key determinants of absorption.

Conclusions:

Deprotonated QMPSA is a reliable predictor of oral drug absorption in humans.
Drug absorption is primarily governed by polar interactions in solution.
Optimal polar/apolar ranges for electrostatic potential can be derived to guide drug design.