Advanced Techniques and Coarse Graining Flashcards

1
Q

What does “coarse-graining” (CG) mean?

A
  • 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)
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2
Q

Describe the basic idea of the Martini force field

A

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)

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3
Q

Which another microscopic coarse-graining (CG) models do you know?

A

• For proteins: PRIME which represents 4 beads per
amino acid residue

• For carbohydrates: REACH model represents monosaccharides in a single bead

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4
Q

What is the potential mean force (PMF)?

A

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.

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5
Q

How is the effect of the solvent in an explicit and implicit solvent model described?

A

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.

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6
Q

Why is it so difficult to calculate free energies in simulation?

A
  • 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.
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7
Q

Explain the concept of the potential energy landscape (PES)

A
  • 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
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8
Q

What is a method to find the global minimum and why are we interested in the global minimum?

A
  • 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.

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9
Q

Describe an algorithm to find local minima without derivatives

A

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

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10
Q

Describe an algorithm to find local minima with derivatives

A

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

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11
Q

What is thermodynamic integration and what is it useful for?

A

Thermodynamic integration relates the immeasurable parameter to a measurable parameter. From this, we can calculate free energies.

Recall: Maxwell’s Square

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