Advanced Techniques and Coarse Graining Flashcards
What does “coarse-graining” (CG) mean?
- simulation method
- simplifies the system through the reduction of degrees of freedom.
- instead of simulating particles as single atoms/molecules, CG simulates by using clusters through qualifications in various criteria such as Martini Force Field, Solvent methods (explicit or implicit)
Describe the basic idea of the Martini force field
Martini Force Field is a popular CG model in the field of macromolecules (Lipids, Proteins, Carbohydrates)
BASIC IDEA: • Beads = Group of Molecule • 1 CG Bead = 4 Heavy Atom/ Molecule • CG Bead classified based on chemical nature - polarity - H-Bonding
• Based in simple non-bonded inter-action (LJ potential and Coulomb potential)
Which another microscopic coarse-graining (CG) models do you know?
• For proteins: PRIME which represents 4 beads per
amino acid residue
• For carbohydrates: REACH model represents monosaccharides in a single bead
What is the potential mean force (PMF)?
Potential mean force (PMF) is a measure of how a systems’ energy changes as a function of specific coordinates.
For example,
• for pair potentials = effective force to bring two particles from infinite to distance r.
• it is also related to RDF (equation here)
• incorporates the solvent-solute interaction which are neglected in using a “normal” pair potential.
How is the effect of the solvent in an explicit and implicit solvent model described?
① EXPLICIT model includes the solvent molecule
② IMPLICIT model excludes the solvent molecule.
- size of solvent molecule smaller than solute
- solvent molecule = background noise
(However, note that typically “exclusion” only means that the solvent the effect is already included in the simulation via (for example) adjustment of particle interaction.)
• Implicit is faster than explicit but explicit is more realistic.
Why is it so difficult to calculate free energies in simulation?
- Free energies are difficult to calculate in a simulation because it highly depends on the systems’ drN, where N is # of particle and r is the configuration.
- In reality there are numerous configuration that contributes to the Free energy value.
Explain the concept of the potential energy landscape (PES)
- mapping of all possible conformations of a molecular entity, or the spatial positions of interacting molecules in a system
- in a graph, it is ∆G versus configuration space
What is a method to find the global minimum and why are we interested in the global minimum?
- Global minimum is the “overall” minimum of a system over an entire range because it represents the system’s realistic ground state.
- one method to find a global minimum is through “simulated annealing”.
- inspired by slow annealing used in metallurgy.
(1) temperature is increased to induce particle mobility
(2) scan survey of PES is done.
(3) temperature is brought down by using a slow cooling rate such that the system comes to rest at the lowest minimum.
Advantage: very easy to implement
Disadvantage: slow and there is a possibility that narrow minima will be missed.
Describe an algorithm to find local minima without derivatives
A method to find the minima without derivatives is the simplex method.
① Performed by creating an initial “ simplex “ and reflect it to the PES the simplex is moved iteratively through the PES
② Simplex vertice with high PE is removed
Repeat process ① and ② until a local minimum is achieved
Describe an algorithm to find local minima with derivatives
An algorithm to find local minima with derivative is the gradient method
Algorithm:
Force equation is integrated at different positions (r + Δr) until a minimum is achieved
What is thermodynamic integration and what is it useful for?
Thermodynamic integration relates the immeasurable parameter to a measurable parameter. From this, we can calculate free energies.
Recall: Maxwell’s Square