Author

Dietrich Klakow

Saarland UniversityORCID 0000-0002-4147-9690Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:machine learning (classical)· 2 Assay:protein sequence· 2 Approach:statistical model· 2 Organism:bacteria (other)· 1 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1

Frequent Co-Authors

Kenan A. J. BozhüyükiD· 2 shared Olga V. KalininaiD· 2 shared Alejandro Martínez LeóniD· 1 shared Andrea VolkameriD· 1 shared Andreas M. KanyiD· 1 shared Anna K. H. HirschiD· 1 shared Dirk W. HeinziD· 1 shared Emre Fatih BülbüliD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBioinformatics

Kenan A. J. BozhüyükORCID

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Author profile →

3 papers

Recent·Most cited

A data-driven rediscovery of the specificity-conferring code of adenylation domains in nonribosomal peptide synthetases

Zhengjian Li, Kenan A. J. Bozhüyük, Olga V. Kalinina, Dietrich Klakow

The paper identifies compact, data-driven codes for adenylation domain substrate specificity in NRPSs, outperforming traditional codes and revealing new positions critical for specificity.

bioRxiv · Jun 18, 2026 · PreprintBioinformatics

Generative AI designs functional thiolation domains for reprogramming non-ribosomal peptide synthetases

Emre Fatih Bülbül, Seounggun Bang, Kevin George, Gabriele Bianchi, Prateek Raj, Seonyong Chung, Vincent Pauline, Ramon Hochstrasser, Hannah A. Minas, Walid A. M. Elgaher, Andreas M. Kany, Anna K. H. Hirsch, Steven Schmitt, Dirk W. Heinz, Olga V. Kalinina, , Kenan A. J. Bozhüyük

This paper uses generative AI to design functional thiolation domains for reprogramming NRPSs, improving product formation and stability.

bioRxiv · Mar 4, 2026 · PreprintSynthetic Biology

Accelerating ligand discovery by combining Bayesian optimization with MMGBSA-based binding affinity calculations

Lucas Andersen, Max Rausch-Dupont, Alejandro Martínez León, Andrea Volkamer, Jochen S. Hub, Dietrich Klakow

The paper combines Bayesian optimization with MMGBSA-based binding affinity calculations to improve ligand discovery by enhancing compound ranking and recovery rates.

Digital Discovery · Jan 1, 2026Peer-reviewedBioinformatics