Author

D. Schaller

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· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Approach:benchmark study· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Assay:protein structure· 1

Frequent Co-Authors

A. Volkamer· 1 shared C. D. Christ· 1 shared C. Omieczynski· 1 shared D. Sribar· 1 shared D. Stepanov· 1 shared G. Wolber· 1 shared J. D. Chodera· 1 shared L. Deng· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBiophysics

A. Volkamer

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Author profile →

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

BiasDB: A Comprehensive Database for Biased GPCR Ligands

C. Omieczynski, T. N. Nguyen, D. Sribar, L. Deng, D. Stepanov, D. Schaller, G. Wolber, M. Bermudez

BiasDB compiles and analyzes known biased GPCR ligands, offering a resource for medicinal chemistry and pharmacology.

bioRxiv · Aug 24, 2019 · PreprintPharmacology & Toxicology