Upcoming events

HGS Compact Course: Computational Methods and Strategies in Structure-based Drug Design

Dr. Joanna Panecka-Hofman, Dr. Daria Kokh, Dr. Neil Bruce (HITS)
4-5th December 2017, 9am - Mathematikon SR12 (5th Floor)

The course will present principles of simulation methods applicable in structure-based drug design and practical aspects of structure-based drug design strategies. We will focus on such techniques as ligand docking, molecular dynamics and binding free energy estimation methods. The course will cover the following TOPICS: 

  • Lead design strategies with examples
  • Force fields and interaction fields
  • Binding site identification, mapping and comparison
  • Ligand docking methods with examples
  • Thermodynamics vs. kinetics
  • Molecular dynamics and enhanced sampling in drug design

For more details, abstract and registration procedure please visit:   http://www.mathcomp.uni-heidelberg.de/curriculum/

Past events

Talk: Fixation Probabilities under Demographic Fluctuations

Dr. Peter Czuppon, Max Planck Institute for Evolutionary Biology, Plön
9th November 2017, 4pm - BioQuant SR043

We consider a population consisting of two species. Each type gives birth and dies independently of the other one. Population size is regulated by intra- and interspecific competition events letting the model follow generalized Lotka-Volterra dynamics. A quantity of interest in finite populations is the probability of fixation/extinction of one type. While it has been studied broadly in the context of fixed or deterministically varying population sizes we approximate the fixation probability in populations with stochastically fluctuating sizes. In order to do so we will take the limit of weak selection, i.e. the "fitness" benefit of one type over the other is very small.

Compact Course: "Virtual Screening of Drug Discovery"

Prof. Markus Lill, Purdue University
26-29th June 2017

Virtual screening has become an essential element of the drug discovery process. Virtual screening is used to search a large library of small molecules for binding to a target protein and select a small subset of compounds for subsequent experimental validation and optimization. In this block course we will discuss the methodological basis and practical applications of structure-based and ligand-based virtual screening methods such as docking, shape-based, pharmacophore and fingerprint concepts.

The course alternates lectures and practical sections in the computer lab.

Talk: "Modelling glioma growth with fully anisotropic diffusion"

Prof. Thomas Hillen, University of Alberta
6th June 2017

The human brain has a complex geometric structure consisting of white and gray matter, blood vessels, ventricles, skull etc. It forms a highly anisotropic medium. Glioma in the brain are known to invade along white matter tracks and along other brain structures. Using diffusion tensor imaging (DTI) it is now possible to obtain directional information of the brain geometry. In my talk I will show how this DTI information can be used to parametrize a fully anisotropic diffusion equation for glioma spread. We validate the model on clinical data of glioma patients and discuss the future use in treatment design. (joint work with A. Swan, K.J. Painter, C. Surulescu, C. Engwer, M. Knappitsch, A. Murtha).

Talk: "Analytical approximations for spatial stochastic gene expression in single cells and tissues"

Dr. Ramon Grima, Edinburgh University
8th March 2017

Gene expression occurs in an environment in which both stochastic and diffusive effects are significant. Spatial stochastic simulations are computationally expensive compared to their deterministic counterparts and hence little is currently known of the significance of intrinsic noise in a spatial setting. I will show how starting from the reaction-diffusion master equation (RDME) describing stochastic reaction-diffusion processes, we can derive closed-form expressions for the approximate steady-state mean concentrations which are explicit functions of the dimensionality of space, rate constants and diffusion coefficients. These are generally different from those given by the deterministic theory of reaction-diffusion processes, thus highlighting the importance of intrinsic noise. Our theory is confirmed by comparison with stochastic simulations, using the RDME and Brownian dynamics, of two models of stochastic and spatial gene expression in single cells and tissues. Lastly, time permitting, I will discuss how one can extend these results to stochastic spatial simulations of intracellular processes which take into account macromolecular crowding, namely the volume exclusion due to the finite size of molecules. 

Contact:

Diana-Patricia Danciu

Applied Analysis and Modelling in Biosciences
Institute of Applied Mathematics
Heidelberg University
Mathematikon, INF 205, Office 2.233
+49 (0)6221 5414138
  dpdanciu@math.uni-heidelberg.de

 

 

Ana Victoria Ponce Bobadilla

Numerical Methods for Multiscale Models
Institute of Applied Mathematics
Mathematikon, INF 205, Office 1.315
+49 (0)6221 5414113
  a.ponce@stud.uni-heidelberg.de

 

 

Verena Körber

Division of Theoretical Systems Biology
German Cancer Research Center (DKFZ)
Im Neuenheimer Feld 280
+49 (0)6221 5451384
  v.koerber@dkfz.de