Dr. Lars Eicholt


Postdoctoral Research Associate




Email: l.eicholt[at]uni-muenster.de

Tel.: +492518321634

Room: 100.20

ORCID iD iconORCID: 0000-0002-3985-3698

@lacholt

Google Scholar

Curriculum

  • Visiting Researcher in the group of Prof. Dr. Richard A. Goldstein, University College London, United Kingdom, 06/2024-07/2024
  • Postdoctoral Research Associate in the group of Prof. Dr. Erich Bornberg-Bauer, University of Muenster, 05/2024-present
  • PhD student in the group of Prof. Dr. Erich Bornberg-Bauer, University of Muenster, 01/2022-05/2024
  • Research Helper in the group of Prof. Dr. Erich Bornberg-Bauer, University of Muenster, 07/2021-12/2021
  • Research Assistant in the group of Prof. Dr. Roland Riek, ETH Zurich, Switzerland; Topic: Amyloids in the Origin of Life, 11/2020-05/2021
  • Master Thesis in the group of Prof. Dr. Dan S. Tawfik, Weizmann Institute of Science, Israel; Title: Enzyme Engineering of a D-Ribulose-1-Phosphate 5-Kinase, 01/2020-06/2020
  • Visiting Student in the group of Prof. Dr. Klara Hlouchova, Charles University in Prague, Czech Republic; Topic: Reversed Evolution of HIV-Protease, 07/2019-09/2019
  • Master of Science in Biotechnology, Lund University, Sweden, 08/2018-09/2020
  • Erasmus+ student at University of Gothenburg, Sweden, 08/2016-11/2016
  • Bachelor of Science in Biological Science, University of Muenster, Germany; Bachelor Thesis in the group of Prof. Dr. Erich Bornberg-Bauer; Title: Expression and purification of possible de novo genes of Mus musculus for further investigation via CD and NMR, 10/2014-08/2018

Scholarships

  • Full Scholarship of the Friedrich-Ebert Foundation
  • EMBO Short-term fellowship
  • 2x Santander Mobility Grant
  • 3x Erasmus+ scholarship

Research Interests

  • Structure Predictions & Molecular Dynamics of de novo proteins
  • Structural Biology
  • Expression and Purification of de novo proteins

Publications

  • Middendorf, L, Iyengar, BR, Eicholt, LA: Sequence, Structure and Functional space of Drosophila de novo proteins. biorxiv https://www.biorxiv.org/content/10.1101/2024.01.30.577933v1.full.pdf
  • Middendorf, L, Eicholt, LA. Random, de novo and conserved proteins: How structure and disorder predictors perform differently. Proteins: Structure, Function, and Bioinformatics. 2024 Jan 16. https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.26652
  • Aubel, M, Eicholt, L, Bornberg-Bauer, E. Assessing structure and disorder prediction tools for de novo emerged proteins in the age of machine learning. F1000Research 2023, 12:347. https://doi.org/10.12688/f1000research.130443.1
  • Eicholt, LA, Aubel, M, Berk, K, Bornberg-Bauer, E, Lange, A. Heterologous expression of naturally evolved putative de novo proteins with chaperones. Protein Science. 2022; 31( 8):e4371. https://doi.org/10.1002/pro.4371