Poster Presenter

Protein-Ligand Scoring Based On The Modified Semi-Empirical Quantum Chemical Pm6 Method
Jindrich Fanfrlik, Agnieszka K. Bronowska, Jan Rezac, and Pavel Hobza
Czech Republic

Ligand-protein docking is widely used to predict binding poses and affinities of tested drug-like molecules, and therefore plays increasingly important role in rational drug discovery. The success of such predictions depends on the docking scheme (scoring function among other factors) implemented.

Prediction of binding ligand/protein affinities based on the recent semiempirical quantum mechanical PM6 method is presented in the poster. In order to describe non-covalent interaction properly, the original PM6 method [1] was extended in two directions: i) inclusion of an empirical dispersion energy term, and ii) introduction of an additional electrostatic term, which improves the description of hydrogen bonding. [2,3].

Analyzing the binding process, we realize that the second critical step after binding is ligand relaxation and desolvation. The solvation energy was evaluated using the advanced techniques of a self-consistent reaction field (4), which is known to provide reliable energies for not only neutral but also charged systems. The estimated binding free energy of a protein-ligand complex in the present scoring function thus contains reliable description of all the important terms, i.e. interaction between ligand and protein, change of entropy, relaxation and also desolvation.

The scoring function was tested on HIV-1 protease (PR) and bovine carbonic anhydrase (BCA) II, and training sets of ligands (10 binders and 10 non-binders in each set) were applied. [5]

The results were compared to the structural crystallographic data and the experimental binding data (ITC, SPR). The PM6-DH2 scoring improved the docking results dramatically. Binders and non-binders in our training-ligand sets were correctly assigned, and also the proper order of the binders was achieved. The experimental results are thus reproduced correctly.

The PM6-DH2 scoring thus provides a novel, valuable and very promising tool for rational drug discovery and de novo design.

1. J. J. P. Stewart, J. Mol . Model, 2007, 13 (12), 1173-1213.

2. J. Rezac, J. Fanfrlik, D. Salahub and P. Hobza, JCTC, 2009, 5, 1749-1760.

3. M. Korth, M. Pitonak, J. Rezac and P.Hobza, JCTC, accepted.

4. Gaussian09.

5. Jindrich Fanfrlik, Agnieszka K. Bronowska, Jan Rezac, Jiong Ran and Pavel Hobza, submitted