Applications to protonation state effects in kinase inhibition
Uncertainty estimation, model selection and experimental design using statistics.
Neeb et al. J. Med. Chem., 2014, 57 (13), pp 5554–5565
Where do they matter, and how can we exploit these?
"Writing code that no one can run is a waste of time."
Jun 2013 –MSc degree at VU Amsterdam
Sep 2013 – started the PBSB program
Jun 2014 – Joined the Chodera lab
May 2015 – Passed ACE exam
Summer 2015 – Internship at Genentech
Jun 2016 – First committee meeting
Feb 2017 – Second committee meeting?
Fall 2017 – Third committee meeting?
Fall 2018 – Graduate?
1. Constant-pH simulations of ligands in openmm, automated calibration routine for aminoacids and ligands using stochastic approximation technique
Showcase of our new code and its features
Goal : Submitted by Nov 2016
2. Bayesian hierarchical model of two-component and competitive-binding interaction in isothermal titration calorimetry experiments
Performing experiments, and showcase utility in experimental design.
Goal : Submitted by Feb 2017
3. Joint inference on pH dependent experiments, such as fluorescence at multiple pH’s and/or ITC with multiple buffers
(Co-)first author
Goal : Submitted by May 2017
4. Demonstrating Bayesian ITC in a comparative review of ITC experiments in literature
Reanalyzing public data using Bayesian ITC, developing new models when necessary to describe interesting side cases, such as multiple ligand binding etc.
Goal : Submitted by Aug 2017
5. Strategies for binding affinity inference from multiple types of data
Goal : Submitted by Mar 2018
6. Exploiting protonation state effects in kinase inhibitor binding
Free energy calculations, validated by Bayesian ITC, and Bayesian fluorescence experiments.
Goal : Submitted by Apr 2018
7. Statistical software paper about tool that combines binding models from several sources
Goal : Submitted by Jul 2018
On the short term,
On the long term
Alternative careers
2016:
Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge.
Rustenburg, Arien S.; Dancer, Justin; Lin, Baiwei; Feng, Jianwen; Ortwine, Daniel F.; Mobley, David L.; Chodera, John D.: Submitting to Journal of computer-aided molecular design this week.
2016:
Polarize or Not to Polarize? Charge-on-Spring versus KBFF Models for Water and Methanol Bulk and Vapor-Liquid Interfacial Mixtures.
Ploetz, Elizabeth A.; Rustenburg, Arien S.; Geerke, Daan P.; Smith, Paul E. (2016): To In Journal of chemical theory and computation 12 (5), pp. 2373–2387. DOI: 10.1021/acs.jctc.5b01115.
Toward Automated Benchmarking of Atomistic Force Fields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive.
Beauchamp, Kyle A.; Behr, Julie M.; Rustenburg, Arien S.; Bayly, Christopher I.; Kroenlein, Kenneth; Chodera, John D. (2015)
In The journal of physical chemistry. B 119 (40), pp. 12912–12920
Hypoxia Induces Production of L-2-Hydroxyglutarate.
Intlekofer, Andrew M.; Dematteo, Raymond G.; Venneti, Sriram; Finley, Lydia W. S.; Lu, Chao; Judkins, Alexander R. et al. (2015):In Cell metabolism 22 (2), pp. 304–311. DOI: 10.1016/j.cmet.2015.06.023.
QM/MM-Based Fitting of Atomic Polarizabilities for Use in Condensed-Phase Biomolecular Simulation
Vosmeer, C. Ruben; Rustenburg, Arien S.; Rice, Julia E.; Horn, Hans W.; Swope, William C.; Geerke, Daan P. (2012):
In Journal of chemical theory and computation 8 (10), pp. 3839–3853.