Thermodynamic principles of molecular recognition. Binding free energy,
binding energy, binding entropy in the ligand-protein target
interaction. Statistical mechanics approach to the evaluation of the
drug-receptor equilibrium constant and thermodynamic background of
Molecular Docking scoring functions. Molecular mechanics (MM)
computational tools in modeling biomolecular systems: atomistic force
fields and MM Poisson-Boltzmann computation of single pose binding
energies in molecular Docking. Computer Lab applications of binding
affinities evaluation.
Knowledge acquired: the course is divided in a theoretical part and in
laboratory sessions. From the theoretical standpoint, the student
will be acquainted with the thermodynamic basis in molecular
recognition in biological systems and with a statistical mechanics
rationalization of Molecular Docking scoring functions in drug
design. Exercises in computer Lab will furnish the technical
skills for implementing on a Unix platform the calculation of
the equilibrium constant of drug-receptor systems.
Prerequisites
Courses recommended: General and Inorganic Chemistry, Organic Chemistry.
Type of Assessment
Oral
Course program
Atomistic Force fields in the modeling biological molecules. Bonded
or valence potential parameterization. Non bonded interaction, Coulomb
and dispersive-repulsive interactions in molecular systems.
Elementary approach to Statistical Mechanics. Phase space,
distribution functions, partition functions. Statistical Mechanics
formulation of the first and second thermodynamic principles. A+B=AB
chemical equilibrium in dilute solutions. Mean field treatment of the
solvent effects. Rigid Rotor Harmonic Oscillator approach in the
determination of the binding affinity in drug receptor systems.
Thermodynamic foundation of Molecular Docking scoring functions.
Energy and entropy balance in molecular recognition. Molecular
Mechanics, Poisson Boltzmann and Generalized Born methodologies for
the determination of the binding free energy starting for the
structural knowledge of the ligand and targets. Binding free energy:
the flexible molecule approach. Molecular dynamics simulation of
biological systems with explicit solvent. Outline of advanced
simulations techniques on parallel platforms in bioinformatic
applications.