Learning objectives
The course is designed to provide the basic computational biophysics and chemistry knowledge for modelling biological systems and biological interactions. Particular emphasis will be given to molecular dynamics approaches and drug design methodologies for the identification of new lead compounds. During the practical sessions some of the theoretical concepts will be applied.
Prerequisites
Basic knowledge of physics, chemistry and biochemistry.
Course unit content
Structure of proteins and relationship between structure and function. The most important interactions in biological systems, the folding process and the hydrophobic effect. Experimental determination of the protein structure: x-ray crystallography and NMR. The Protein Data Bank and the Electron Density Server. Molecular mechanics and force fields. Calculation of the potential energy and the different energetic contributions. The most known force fields, MM2, Amber, CHARMm, OPLS. Atom type and atom name concepts. Examples of molecular graphic programs. Sequence alignment, BLAST and PSIBLAST. Methods for predicting proteins three-dimensional structure. Simple models, stepwise models and global models (MODELLER, SwissModel). Threading methods and ad initio calculations. Protein dynamics and flexibility. Classical Molecular Dynamics approaches. Parametrization, minimization and equilibration. Analysis of protein cavities and clefts. Essential dynamics, eigenvalues and eigenvectors. Accelerated MD variants. The energetics of biological interactions. The different types of water molecules in proteins and the energetic contribution of water. Modeling the protonation state of ionizable residues in protein binding pockets. Ligand-based drug design. Chemical similarity. Molecular descriptors and QSAR models, PCA and PLS. 3D-QSAR. 3D similarity. Comparative Molecular Field Analysis (CoMFA). Structure-based drug design. Combinatorial chemistry. Docking and scoring algorithms. Problems and limitations of common scoring functions. Libraries of compounds and the ZINC website. Ligand-based and virtual-based virtual screening. Consensus scoring.
Full programme
PROTEIN STRUCTURE: primary, secondary, tertiary and quaternary structures of proteins. Supersecondary structures and domains. Relationship between structure and function. Bonding and non-bonding interactions. The most important interactions in biological systems: salt bridges, hydrogen bonds and van der Waals interactions. Folding and hydrophobic effect, the structural and energetic roles of water. Experimental determination of the protein structure: x-ray crystallography and NMR. Parameters to assess the structure quality: resolution, R factor and B factor. The Protein Data Bank and the pdb file format. The Electron Density Server.
MOLECULAR MECHANICS & FORCE FIELDS: Differences between molecular mechanics and quantum mechanics approaches. Force fields, potential energy of biological molecules and energy minimization. Calculation of the potential energy: stretching, bending, torsional, van der Waals and electrostatic contributions. Examples of the most known force fields, MM2, Amber, CHARMm, OPLS. Atom types and atom names. Examples of molecular graphic programs: Sybyl, PyMOL, VMD.
PROTEIN STRUCTURE PREDICTION: Sequence similarity. Single and multiple sequence alignment. BLAST e PSIBLAST. Simple models, stepwise models and global models. Side chain prediction, loop prediction, comparative protein modeling. Examples of global modelling softwares (MODELLER, SwissModel). Threading methods and ab initio calculations.
PROTEIN DYNAMICS: Proteins as flexible systems. Time scale for protein motions. Classical MD approaches and force fields. Building a topology file, minimization, equilibration and MD runs. Analyses of MD trajectories. Analyses of the protein matrix cavities (PASS, FPOCKET, GRID-MD) and related examples. Essential dynamics, eigenvalues and eigenvectors. Accelerated MD variants: modified potential (umbrella sampling), modified sampling (LES, REMD), modified dynamics (SHAKE algorithm, coarse-grained models).
BIOLOGICAL INTERACTIONS: Protein-ligand, protein-DNA, protein-protein and protein-water recognition. The energetics of biological interactions.
PROTEINS, WATER and IONIZATION STATE: The different roles of water molecules, solvation waters, waters buried in cavities and in binding pockets. Catalytic waters and waters mediating the interaction between proteins and substrates or inhibitors. Tools for calculating the solvent contribution. The importace of modelling the ionization state of ligands and binding pocket residues. The HIV-1 protease case.
DRUG DESIGN: Ligand-based drug design. Molecular descriptors and molecular properties. Hydrophobicity, polarizability, electronic parameters, steric parameters. QSAR models. Prediction of the activity of new compounds using QSAR models: PCA and PLS. 3D-QSAR. 3D similarity. Comparative Molecular Field Analysis (CoMFA).
Structure-based drug design. Chemoinformatics, virtual and real libraries. Combinatorial chemistry. Docking algorithm classification. Point complementarity methods, systematic search, fragment-based methods, Monte Carlo, genetic algorithms, MD approaches, Tabú searches. Scoring algorithm: force field based methods, knowledge based methods and empirical functions. The HINT force field. Problems and limits of the scoring functions.
VIRTUAL SCREENING: Libraries of compounds. The ZINC website. Creation of a database. Ligand-based virtual screening and structure-based virtual screening. Creation of a pharmacophoric model. Screening, docking and consensus scoring. The FLAP algorithm.
LABORATORY:
Analysis of a protein-ligand structure with PyMOL. Different representations and pictures generation. Molecular modeling of a plant hemoglobin with MODELLER. Short MD simulations performed with the NAMD program. Generation of a topology file, minimization, equilibration and MD runs.
Bibliography
A.R. Leach. Molecular Modelling: Principles and Applications. Prentice Hall.
T. Lengauer. Bioinformatics – From Genomes to Drugs. WILEY-VCH.
Lessons notes.
Teaching methods
Oral lessons and practical experiments in the lab.
Assessment methods and criteria
Written report about some of the problems investigated during the theoretical and practical sessions. Discussion and questions about the report.
