NIH, NIDDK, LBG**Travis Hoppe**, Allen Minton, Di Wu

(deck source)

against

Human serum albumin, Ovalbumin, Lysozyme, Bovine Serum Albumin respectively.

How do we model the interaction between proteins on a larger scale? Can we **predict** aggregates?

Phase separations lead to sudden fundamental changes in liquid structure and local density.

This is usually really important.

**Match** experimental data with results

of computational models.

**Classify** common protein solution behavior

from coarse-grained models.

**Predict** behavior of mutations and unknown solutions.

is the pairwise interaction of

...

From the equation of state you can calculate many thermodynamic properties.

Necessary first step for a verifiable model.

For rotationally invariant molecules

(where is the pairwise interaction energy)but in general...

How do you model a

Need an expression for the interaction energy

This is not the free energy, but the **enthalpy**

Important terms:

- Volume exclusion
- Electrostatics
- Non-specific interactions (London/dispersion forces)

How do you model a

Second-order effects?

- Non spherical geometries
- Polarization
- Internal conformational energies
- Solvent effects

Must decide if this approximation is valid for the system.

modeling the

modeling the

Coulomb's Law (point charge)

Correction for dielectrics?

First order approximation to **screening** effects.

Charge strength **decays exponentially** due to ions.

Describes the electrostatic interaction between a charge distribution and an **ionic** solution.

Can be **linearized** and solved on a computer efficiently.

Splits space into regions of discrete .

Start with the crystallized PDB Structure (HSA)

Typically (in the absence of ions)

,

Electrostatic field

Determine a region of excluded volume.

Spherical Harmonic decomposition for large distances.

Best fit macrocharges to replicate the field.

Good approximation of the near field, poor up close.

Captures the anisotropic field*especially* near the **isoelectric point**.

Macrocharge approximations make for reasonable

models of large protein solutions.

Excluded volume for modeled as a hard sphere.

Representation of the protein *electrostatics*

in an ionic solution for a given pH.

Our charge distributions are *not isotropic* anymore,

we *must* to compute this:

There are many pairwise orientations.

Blind sampling may miss specific interactions.

Need to know at different if we want to scale the model.

counts the number of ways

we can get a particular energy,

efficiently calculate with Wang-Landau.

Calculate the **non-ideality** of a protein molecule after including both the excluded volume *and* electrostatics.

Predict the second-virial coefficient as a function of pH values, protein concentrations, binary mixtures, and salt concentrations.

If experimental results agree, use the model in higher-order simulations to predict phase behavior via Gibb's ensembles.

*results for square-well potentials shown*

A **text-based** human-readable markup.

SVG equations , and links!

The code for *this particular slide* looks like this:

```
## How does it work?
A *text-based* human-readable markup.
Equation rendering is simple $e^{i \pi} = -1$.
and [links](http://thoppe.github.io/)!
The code for this _particular slide_ looks like this:
```