Author

A. S. Rustenburg

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 4

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Approach:deep learning· 1 Approach:experimental assay· 1

Frequent Co-Authors

J. D. Chodera· 4 shared D. L. Mobley· 2 shared M. Isık· 2 shared A. A. Makarov· 1 shared A. Rizzi· 1 shared D. D. L. Minh· 1 shared D. Levorse· 1 shared G. A. Ross· 1 shared

Activity by Year

2018-2020 · peak 3/yr

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10 top collaborators · 26 mutual co-author links

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4 shared papersBiophysics

J. D. Chodera

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4 papers

Recent·Most cited

Overview of the SAMPL6 pKa Challenge: Evaluating small molecule microscopic and macroscopic pKa predictions

M. Isık, A. S. Rustenburg, A. Rizzi, M. R. Gunner, D. L. Mobley, J. D. Chodera

The paper evaluates pKa prediction methods for drug-like molecules, finding that top submissions achieved RMSE of 0.7-1.0 pKa units, but significant inaccuracies remain, especially for sulfur-containing heterocycles and multiprotic molecules.

bioRxiv · Oct 15, 2020Biophysics

pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments

M. Isık, D. Levorse, A. S. Rustenburg, I. E. Ndukwe, H. Wang, X. Wang, M. Reibarkh, G. E. Martin, A. A. Makarov, D. L. Mobley, T. Rhodes, J. D. Chodera

The paper evaluates pKa prediction methods using a dataset of kinase inhibitor-like fragments measured by UV absorbance and NMR.

bioRxiv · Sep 25, 2018Biophysics

Bayesian analysis of isothermal titration calorimetry for binding thermodynamics

T. H. Nguyen, A. S. Rustenburg, S. G. Krimmer, H. Zhang, J. D. Clark, P. A. Novick, K. Branson, V. S. Pande, J. D. Chodera, D. D. L. Minh

This paper introduces a Bayesian framework for analyzing ITC data to better estimate thermodynamic parameters and their uncertainties.

bioRxiv · May 21, 2018Biophysics

Biomolecular simulations under realistic macroscopic salt conditions

G. A. Ross, A. S. Rustenburg, P. B. Grinaway, J. Fass, J. D. Chodera

This paper introduces a Monte Carlo osmostat to simulate biomolecules under dynamic salt conditions, showing significant differences in salt concentration distributions compared to fixed-salt simulations.

bioRxiv · Mar 18, 2018Biophysics