Methods of experimental structure elucidation

  • X-ray crystallography and interpretation of structure quality
  • NMR
  • Various other methods (SAXS, CD, cryo-EM)

Principles of protein structures

  • Properties of amino acids, Peptide bond, main degrees of freedom/ main chain dihedral angles
  • Hierarchies of protein structure, secondary structure assignments (DSSP),
  • Packing constraints, cavities

Fold classification and structure comparison

  • Folding topologies, term “topology”, fold databases
  • Structure comparison (RMSD, contact map overlap)

Protein folding

  • Thermodynamic hypothesis
  • Detailed discussion of enthalpic/entropic contributions to delta-G (bonds, angles, electrostatics, van-der Waals, solvation etc.),
  • Levinthal paradox, folding funnel, folding pathways, concepts of folding (two-state, framework model)
  • “lattice”-proteins

Molecular dynamics

  • Force fields (AMBER, ECEPP-2, CHARMM)
  • Newtonian equations of motion, Taylor expansion, Verlet algorithm, boundary conditions, time step, neighbor lists

Energy minimization

  • Search problem (global vs. local minima)
  • Steepest descent, conjugate gradient, ensemble properties, Monte Carlo simulation, simulated annealing.

Database-derived potentials

  • Inverse Boltzmann statistic, pairwise potentials of mean force, solvent exposure interactions, fold quality assessment


  • Protein-protein interaction and docking
  • Small-molecule docking, binding pocket identification, geometric  hashing
  • Intro to cheminformatics (descriptors of small molecules, comparison)

Secondary structure prediction

  • Chou-Fasman, GOR, neural networks, ab-initio methods
  • Advanced Machine Learning Methods (deep learning)

Homology modeling

  • Profile methods, true homology modeling (incl. loop modelling with dead-end elimination)
  • Public resources for Homol. Modelling


  • Optimal threading (branch-and-bound)
  • Structure quality assessment
  • CASP competition

Principles of DNA/RNA structure

  • Principles governing nucleic acid structures
  • Descriptors of RNA structures
  • Concept of isostericity

RNA structure prediction

  • RNA secondary structure prediction (Nussinov algorithm, energy minimization)
Elective module Master Bioinformatics.
Elective module in Master Biochemistry and Molecular Biology.
Mandatory course for Master Biochemistry and Molecular Biology.