Computer-based prediction of molecular biological (drug, odorant, toxic) activity. The electron-conformational method"
Monday, October 7, 2019
2PM – 3:30PM
Based on ab initio calculations, the main features of a molecule with N atoms in its interaction with a bio receptor (electronic structure, topology, and reactivity) are presented by an NxN matrix (for each populated conformation) – the electron-conformational (EC) matrix of congruity (ECMC), with matrix elements as donor-acceptor properties, bond orders, and interatomic distances. Then by comparison of the ECMCs of a series of compounds with a given biological activity (the training set), a smaller number of matrix elements, common for all the active compounds (with tolerances), is revealed, - the submatrix of activity (ECSA), or the numerical Pharmacophore.
The presence of the ECSA in the ECMC of at least one of its populated conformations is an absolutely reliable necessary condition of the biological activity under consideration (within the completeness of the training set and the chosen limits of activity). Its determination is straightforward, fully computerized, and very fast. The application of this EC method shows that it works well in revealing the possible biological (drug, odorant, toxic) activity of any molecular system, and it even allowed us to discover that in some cases the activity takes place in dimers. In comparison with existing statistical methods of pharmacophore identification, the EC method has no limitations and no a priori chosen arbitrary descriptors, which lead to chance correlations and artifacts.
However, the presence of the ECSA, being a necessary condition of activity, is not a sufficient condition of activity. To reveal the latter, we worked a parametrized procedure, which takes into account the presence of anti-pharmacophore shielding and other groups that compete with the pharmacophore in the interaction with the bio receptor. Together with handling the conformations and the dependence of the activity on tolerances and substrate-enzyme bonding energies, we got a general formula for prediction numerical activities in reasonable agreement with experimental data [for some details, see, e.g., I. B. Bersuker, Comput. Aided Mol. Des. (2008) 22:423–430; DOI 10.1007/s10822-008-9191-x].
Hosted by Ron Elber