[Colloquium] TALK TOMORROW: Jay Bardhan

[Katie Casey]

Tomorrow, Wednesday 13 October, we will have a mini-workshop on
computational methods for dielectric models. This will be centered
around two talks as follows.

2:30pm, Ryerson 251
Jay Bardhan, Rush Medical Center
Title: "Teaching an Old Dog New Tricks: Re-visiting a Boundary
Integral Equation for the Mixed-Dielectric Poisson Problem"

Abstract:
I will describe recent work on a boundary-integral equation (BIE)
approach to studying biomolecular electrostatics using continuum
theory.  Although this BIE has been used widely for almost 50 years,
numerous important aspects have gone unrecognized, including both
analytical approximations and numerical ones.  First, I will show that
solving the BIE numerically using boundary-element methods (BEM)
requires special care in discretization, especially when simulating
problems such as ion channel proteins.  Second, I will describe how
analytical approximations to the BIE not only eliminate the need for
Generalized Born (GB) heuristic electrostatics, but more importantly
give rapidly computed and furthermore provable upper and lower bounds
to the electrostatic energy.

 4pm in Eckhart 202
Andreas Hildebrandt, Center for Bioinformatics, Saarland University.
Title: "Biomolecules in a structured solvent - a nonlocal electrostatics treatment"
The successful development of new drugs is one of science's most difficult tasks today. Even under optimal circumstances, it takes years to finish, has a very low probability of success, and is immensely expensive. In this talk, I want to show how molecular modeling techniques can help to make drug design cheaper, faster, and more reliable. In particular, I will focus on the accurate computation of electrostatic effects which play an important role in the energetics of biomolecules. Many of those effects are dominated by the shielding effect of the water that is always present in biochemical reactions. Therefore, a highly accurate computation of electrostatic potentials of biomolecules in water is an important precursor for many applications in bioinformatics, like the mentioned computer aided development of inhibitors for disease related enzymes.

In the literature, nonlocal extensions of classical macroscopic electrostatics have been proposed to capture the effects of the water on the electric potential. We propose a reformulation of the resulting equations, which we can be addressed numerically.

The method has been shown to yield very accurate results on small systems like mono- or polyatomic ions and initial results on selected proteins are highly promising.
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