2nd Users' Conference of IT4Innovations

Efficient quantum-mechanical calculations for computer-aided drug design

Nov 7, 2018, 10:30 AM

15m

atrium (IT4Innovations)

User's talk Users' talks Users Talks I.: 6 contributions each 15 mins

Speaker

Dr Jan Řezáč (UOCHB AV ČR)

Description

We have improved the description of intermolecular interactions in semi-empirical quantum-mechanical (SQM) methods to the point where large molecular systems can be computed with accuracy allowing reliable predictions in the timescale of minutes.[1,2] This opened the way to applications of these methods to the calculations of biomolecules. In particular, we focus on the calculations of protein-ligand interactions that are applicable in computer-aided drug design (CADD). We've developed a general computational protocol based on SQM methods,[3] which could be simplified further to fit specific applications. The first task in a CADD workflow is finding the geometry of the protein-ligand complex. Docking algorithms can be used to generate suitable candidates (poses), but the accuracy of the scoring functions is not sufficient to identify the correct one. Only rescoring the poses with SQM-based protocol allows unambiguous identification of the native pose. In our study of four different and challenging proteins, the SQM-based scoring based on DFTB3 calculations complemented by a COSMO solvation model was the only approach that yielded no false positives.[4,5] Once the geometries of the protein-ligand complexes are determined, the next step is to predict the binding affinity. This is even more challenging as only small changes in the binding free enrgy translate into order of magnitude differences in dissociation constants. Achieving such accuracy for more challenging systems is clearly out of reach of empirical methods. We've used carbonic anhydrase II, a zinc metalloprotein, as a model for which there exist very detailed experimental data. Here, most of the common scoring functions fail, as does a molecular mechanics forcefields. Describing the active site is challenging even for most SQM methods, and only the DFTB approach is able to predict binding activities that correlate sufficiently well with the experiment.[6] The results obtained so far indicate that the SQM-based scoring is accurate enough to predict protein-ligand binding activities, and we are currently applying it to more diverse set of problems.

Summary

The activity of a potential drug is directly related to the energetics of the interaction of the molecule with its biological target which can be predicted by the means of computational chemistry. However, the size and complexity of the molecular system that has to be considered requires the use of very efficient computational methods (scoring functions) that involve severe approximations. The conventional scoring functions used in the field neglect the quantum-mechanical effects involved in the interaction what limits their accuracy. We have developed a scoring function based on semi-empirical quantum-mechanical calculations with corrections improving the description of intramolecular interactions (SQM/COSMO scoring). When combined with modern computational resources, it is fast enough even for large-scale virtual screening. We have shown in multiple projects that it significantly outperforms the standard methods used in the field.

References

(1) Řezáč, J.; Hobza, P. J Chem Theory Comput 2012, 8 (1), 141–151.

(2) Řezáč, J. J. Chem. Theory Comput. 2017, 13 (10), 4804–4817.

(3) Lepšík, M.; Řezáč, J.; Kolář, M.; Pecina, A.; Hobza, P.; Fanfrlík, J. ChemPlusChem 2013, 78 (9), 921–931.

(4) Pecina, A.; Meier, R.; Fanfrlík, J.; Lepšík, M.; Řezáč, J.; Hobza, P.; Baldauf, C. Chem. Commun. 2016, 52 (16), 3312–3315.

(5) Pecina, A.; Haldar, S.; Fanfrlik, J.; Meier, R.; Řezáč, J.; Lepsik, M.; Hobza, P. J. Chem. Inf. Model. 2017, 57 (2), 127–132.

(6) Pecina, A.; Brynda, J.; Vrzal, L.; Gnanasekaran, R.; Hořejší, M.; Eyrilmez, S. M.; Řezáč, J.; Lepšík, M.; Řezáčová, P.; Hobza, P.; et al. ChemPhysChem 2018, 19 (7), 873–879.

Presentation materials

Slides

Rezac Jan: Efficient quantum-mechanical calculations for computer-aided drug design