Author

Felipe Engelberger

Leipzig UniversityORCID 0000-0002-1529-932XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Assay:protein sequence· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Organism:E. coli· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

César A. Ramírez‐SarmientoiD· 2 shared A. Kazimir· 1 shared Amparo Núñez Verdejo· 1 shared Aransa GriñéniD· 1 shared Beatriz Dı́eziD· 1 shared Christina LamersiD· 1 shared Clara T. SchoederiD· 1 shared Georg KünzeiD· 1 shared

Activity by Year

2023-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

César A. Ramírez‐SarmientoORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

A Quantum Lens on Molecular Design: A Machine-Learned Energy Function from Interacting Quantum Atoms.

M. Hoffmann, A. Kazimir, T. Oestereich, Luisa Kaermer, Felipe Engelberger, J. Meiler, Christina Lamers

The paper introduces a machine learning framework to predict accurate energy functions derived from the Interacting Quantum Atoms (IQA) scheme, enabling rapid and interpretable analysis of molecular interactions.

bioRxiv · Mar 5, 2026 · PreprintBioinformatics

Polar Marine Microbial Communities as Reservoirs of Polyester Degrading Enzymes

Aransa Griñén, Jerónimo Cifuentes-Anticevic, Marianne Buscaglia, Pablo Vergara-Barros, Amparo Núñez Verdejo, Felipe Engelberger, César A. Ramírez‐Sarmiento, Beatriz Dı́ez

This study identifies diverse polyester-degrading enzymes in polar marine microbes, revealing their potential for cold-adapted plastic bioremediation.

bioRxiv · Jan 23, 2026 · PreprintBioinformatics

FrustraMPNN: An ultra-fast deep learning tool for proteome-scale analysis of deep mutational single-residue local energetic frustration in proteins

Max Beining, Felipe Engelberger, R. Gonzalo Parra, Clara T. Schoeder, César A. Ramírez‐Sarmiento, Jens Meiler

FrustraMPNN rapidly predicts single-residue frustration in proteins at proteome scale with high accuracy, enabling new insights into protein function and dynamics.

bioRxiv · Jan 23, 2026 · PreprintBioinformatics

Directing Protein Design Choices by Per-Residue Energy Breakdown Analysis with an Interactive Web Application

Felipe Engelberger, Jonathan D. Zakary, Georg Künze

The paper introduces ENDURE, a web tool for analyzing energetic contributions of protein mutations to guide design, showing it improves thermodynamic stability in PET-degrading enzymes.

bioRxiv · Feb 27, 2023 · PreprintBioinformatics