Applications of Quantum Mechanics and Computational Spectroscopy in Drug Design

The use of computational methods in drug discovery and development has become a well-established practice. Many students nowadays are familiar with terms like molecular docking, pharmacophore search, QSAR, molecular dynamics, and virtual screening. Because of the complexity of the underlying molecular phenomena, and the priority of speed over accuracy in high throughput screening, all of these techniques have mainly relied on simple empirical potentials (so-called force fields) to calculate the required molecular properties and interactions.

The use of force field-based methods will probably remain at the core of computational drug design in the foreseeable future (perhaps in combination with AI techniques). But in addition, the substantial advances in computational power over the last decades, coupled with steady improvements in software efficiency, are gradually enabling us to apply more sophisticated methods, based on quantum mechanics, in drug discovery. We are currently at a stage, such that when the question at hand can be reduced to modeling a few hundred to a few thousand atoms, and on time scales of a few hundred picoseconds, then the application of quantum mechanical methods might be the rule rather than the exception.

These advances have also strongly impacted academic research, the requirement to provide computational results to support the interpretation of the experimental findings is an extremely common request from reviewers. Because of this, substantial effort has been invested into making the required software accessible as a “black-box tool” to a non-expert user. The biggest challenge however, is not how to use a software to eventually get some numbers as an output, but rather how to ask the right questions, choose the suitable method, and correctly interpret the results. This requires at least some understanding the underlying assumptions, approximations, and physicochemical principles.

This course aims to introduce, without assuming previous training in theoretical chemistry, the most used quantum mechanical methods in drug discovery and development. The primary focus is on the applications of the methods using freely available software. Nevertheless, to accomplish this goal some cursory understanding of the underlying theory is necessary, albeit with more focus on an intuitive understanding of the concepts, rather than on strict mathematical rigor. A discussion of the applications of quantum mechanics in drug design cannot claim to be complete if it ignores spectroscopy, which plays a very prominent role, whether it is IR, Raman, UV/Vis, NMR, EPR, dielectric ... etc, spectroscopy, not to mention the numerous scattering-based techniques. In a sense, spectroscopy is the point where the organic/medicinal chemist, the structural biologist, and the theoretician converge. In computational spectroscopy, quantum mechanics is routinely used to simulate the spectra even of complex systems, and hence is in many cases indispensable for the interpretation of such complex spectra.

Every lecture will be followed by a tutorial. The tutorials will, as practically feasible as possible, present real case studies where the methods discussed in the lecture were used in published research. The aim is not only to enable the student to reproduce published research results, but most importantly to correctly understand its meaning and limitations, to critically assess the research.

Topics to be covered:

This is a tentative list of topics that will be covered. The plan is to remain flexible and partially adapt the exact course layout to the backgrounds and interests of the participants.

• Molecular potential energy surfaces with classical and quantum mechanics.
• Foundations of molecular orbital theory: semi-empirical methods.
• Ab initio molecular orbital theory: basis sets, Hartree-Fock method.
• Including electron correlation: MP2, multiconfiguration methods, Density functional theory.
• Quantum chemical methods to calculate charge distributions, electric, and magnetic properties.
• Quantum chemical methods to study intermolecular interactions. • Thermodynamic properties.
• Ab initio molecular dynamics simulations. • Hybrid quantal/classical methods.
• Vibrational spectroscopy in drug design: IR, Raman, and SFG spectroscopies.
• Magnetic resonance in drug design: NMR and EPR.
• UV/Visible spectroscopy in drug design.