Computational biochemistry
Start with the big picture
The lesson begins with the Born–Oppenheimer approximation, which separates nuclear and electronic motion to make electronic-structure calculations practical. It compares ab initio methods, including Hartree–Fock and post-Hartree–Fock approaches, with density functional theory, and explains how basis-set choice affects accuracy and computational cost. Molecular mechanics force fields describe atoms through bonded and non-bonded interactions, with reliability shaped by parameterization and transferability. The topic then turns to molecular dynamics, Monte Carlo sampling, enhanced-sampling techniques, and free-energy methods, noting that convergence and entropy can remain challenging. Finally, it introduces QM/MM modeling, which treats a reactive region quantum mechanically and its surroundings with molecular mechanics.
What you'll learn
- Explain how the Born–Oppenheimer approximation simplifies electronic-structure calculations.
- Distinguish ab initio methods, density functional theory, and molecular mechanics.
- Describe how basis sets and force-field parameterization influence model accuracy and cost.
- Compare molecular dynamics, Monte Carlo, and enhanced-sampling approaches.
- Explain the purpose of free-energy methods and QM/MM modeling.
Continue your study
Work through the complete notes and reinforce the topic with the study tools available in the full lesson.
