The theoretical simulation of biological systems plays an essential role in the efforts pursued to solve important challenges in our society, like the increasing need to develop new antibiotics. The size and complexity of biosystems has led to a variety of theoretical methodologies aimed at studying such systems at different levels of resolution, ranging from quantum chemistry to multiscale atomistic and coarse-grain molecular simulations and bioinformatics.
The school on Computational Biochemistry combines theory and practice with the aim of providing attendees with the necessary background to understand and appropriately apply the main tools of computational biochemistry in their research. This field is of interest for students, as well of researchers, from different backgrounds, both from physical and life sciences. The school on “Computational Biochemistry” is thus open to master and PhD students and postdocs with interest in the simulation of biosystems from different backgrounds, although the level of the school is most appropriate for students in the areas of physics and chemistry. We specially encourage students of the European Master in Theoretical Chemistry and Computational Modelling to attend the school, thus reinforcing the contacts among different European initiatives.
The school covers different topics, which can be divided in three categories. First, we will give an introduction to biomolecules, their structural properties and corresponding databases, and the key relation among energy and structure that determines their function. Second, we will discuss the nature of intermolecular forces and introduce the physical and mathematical foundations of the main methodologies used to estimate the energy of biosystems, including ab initio and semiempirical quantum chemical methods, classical force fields, mixed QM/MM and coarse-grain strategies and solvation models. Finally, we will introduce strategies to explore the potential energy surfaces of biosystems, including energy minimization, Monte Carlo and Molecular Dynamics, as well as the basic tools used to simulate enzimatic reactivity, develop quantitative structure-activity relationships, or develop new drugs, like molecular docking and the prediction of binding free energies.
The school is organized in 10 theory lectures, complemented with 5 practical lessons in the computer lab. Theory lectures will be of 2 hours, whereas practical lessons will be of 3 hours. The practical lessons will take place in the afternoons, after the appropriate theoretical concepts are progressively introduced in the 2 theory lectures of the morning.
Session 1. Introduction. Biomolecules and their properties. Structural databases of biomolecules. Structure-energy relationship: Biomolecules modeling (Carles Curutchet)
Session 2. Potential energy surfaces in biomolecules. Intermolecular forces. (Carles Curutchet)
Session 3. Potential energy surfaces in biomolecules. Quantum mechanics (QM). Molecular mechanics (MM): Force fields. (Carles Curutchet)
Session 4. Potential energy surfaces in biomolecules. Mixed QM/MM models. Coarse grain models. Solvation models. (Carles Curutchet)
Session 5. Radiation-matter interactions. (Carles Curutchet)
Session 6-7. Conformational exploration. Minimization: Reaction coordinate.
Molecular Dynamics and Monte Carlo methods. Structure prediction methods. (Victor Guallar)
Session 8. Enzymatic catalysis. Basic concepts in enzymatic catalysis. Modeling enzymatic reactivity. (Victor Guallar)
Session 9. Structure-activity relationships. Molecular descriptors. Quantitative structure-activity relationships (QSAR). (Jaime Rubio)
Session 10. Protein-ligand interaction. Docking techniques. Calculation of binding free energies. (Jaime Rubio)
We will use a computer room of the ZCAM node where each student will be able to work individually. In the lab practice, the students will use the Gaussian and Maestro softwares.
Practice 1: Mixed Quantum Mechanical/Molecular Mechanical (QM/MM) calculations with the ONIOM strategy, application to the study of proton transfer potential energy surfaces in a biomolecule. (Carles Curutchet & Jaime Rubio)
Practice 2: Development of quantitative structure-activity relationships (QSAR). Application of quantum chemical continuum solvation models to predict octanol-water partition coefficients and study the impact of hydrophobicity in drug activity. (Carles Curutchet & Jaime Rubio)
Practice 3: Preparation of a biomolecule for a simulation. Selection of the initial coordinates from a structural database, multimeric forms, protonation patterns, modelling of missing atoms. (Víctor Guallar & Jaime Rubio)
Practice 4: Molecular dynamics simulation of a protein. (Victor Guallar & Jaime Rubio)
Practice 5: Ligand-protein docking with application in drug design. (Victor Guallar & Jaime Rubio)