Author

A. Volkamer

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· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:benchmark study· 1 Approach:deep learning· 1 Organism:human· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

J. D. Chodera· 2 shared C. D. Christ· 1 shared D. Schaller· 1 shared L. Wang· 1 shared R. Abel· 1 shared S. K. Albanese· 1 shared S. Keng· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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2 shared papersBiophysics

J. D. Chodera

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2 papers

Recent·Most cited

Benchmarking Cross-Docking Strategies for Structure-Informed Machine Learning in Kinase Drug Discovery

D. Schaller, C. D. Christ, J. D. Chodera, A. Volkamer

This study benchmarks docking strategies for generating kinase:inhibitor complex geometries to improve machine learning scoring in drug discovery, finding that combining shape and electrostatics-based methods achieves the highest success rate.

bioRxiv · Sep 11, 2023 · PreprintBiophysics

Is structure based drug design ready for selectivity optimization?

S. K. Albanese, J. D. Chodera, A. Volkamer, S. Keng, R. Abel, L. Wang

This study evaluates the accuracy of predicting compound selectivity using free energy calculations for kinase inhibitors, finding that systematic errors correlate between targets and longer simulations improve selectivity prediction.

bioRxiv · Jul 2, 2020Biophysics