An Outline of What Computational Chemistry is All About

Summary of Chapter 1

Computational chemistry allows one to calculate molecular geometries, reactivities, spectra, and other properties. It employs:

• Molecular mechanics — based on a ball-and-springs model of molecules;

• Ab initio methods — based on approximate solutions of the Schrödinger equation without appeal to fitting to experiment;

• Semiempirical methods — based on approximate solutions of the Schrödinger equation with appeal to fitting to experiment (i.e. using parameterization);

• DFT methods — based on approximate solutions of the Schrödinger equation, bypassing the wavefunction that is a central feature of ab initio and semiempirical methods;

• Molecular dynamics methods study molecules in motion.

Ab initio and the faster DFT enable novel molecules of theoretical interest to be studied, provided they are not too big. Semiempirical methods, which are much faster than ab initio or even DFT, can be applied to fairly large molecules (e.g. cholesterol, C₂₇H₄₆O, while MM will calculate geometries and energies of very large molecules such as proteins and nucleic acids; however, MM does not give information on electronic properties. Computational chemistry is widely used in the pharmaceutical industry to explore the interactions of potential drugs with biomolecules, for example by docking a candidate drug into the active site of an enzyme. It is also used to investigate the properties of solids (e.g. plastics) in materials science.

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