Katarina Elez

/kah-tah-REE-nah EH-lez/

Room OG 104

Arnimallee 12

14195 Berlin, Germany

I am a researcher in drug discovery, with 5+ years of experience conducting and analyzing large-scale molecular simulations for medicinal chemistry and developing deep learning models for molecular structure representation.

Currently, I am pursuing a PhD in the AI4Science group at the Free University of Berlin and am a member of the IMPRS-BAC doctoral program at the Max Planck Institute for Molecular Genetics. I also hold an MSc in Bioinformatics and a BSc in Computer Science, both awarded with honors.

In my doctoral research, I have focused on computational drug discovery for inhibiting TMPRSS2, a protease involved in coronavirus cell entry, using docking, molecular dynamics and active learning. This work resulted in the discovery of a novel nanomolar TMPRSS2 inhibitor and a patent application for a pharmaceutical composition to treat COVID-19. I also worked on multi-scale message passing neural networks for protein representation learning and am currently developing structure-aware chemical language models. I gained valuable industry experience during my PhD through an internship at Microsoft Research.

Beyond my academic pursuits, I am passionate about teaching and science outreach, helping to inspire the next generation of scientists. Therefore, I have co-founded Bioinformatika, an NGO dedicated to providing free educational content in bioinformatics to young people from all socio-economic backgrounds.

I am naturally drawn to problem-solving and genuinely motivated to tackle real-world challenges, particularly those with a potential for meaningful impact. Whether in academia or industry, I look forward to contributing to drug discovery, one computational model at a time.

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selected publications

Synergistic Inhibition of SARS-CoV-2 Cell Entry by Otamixaban and Covalent Protease Inhibitors: Pre-Clinical Assessment of Pharmacological and Molecular Properties

Tim Hempel, Katarina Elez, Nadine Krüger, Lluís Raich, Jonathan H. Shrimp, and 8 more authors

Chemical Science, 2021

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SARS-CoV-2, the cause of the COVID-19 pandemic, exploits host cell proteins for viral entry into human lung cells. One of them, the protease TMPRSS2, is required to activate the viral spike protein (S). Even though two inhibitors, camostat and nafamostat, are known to inhibit TMPRSS2 and block cell entry of SARS-CoV-2, finding further potent therapeutic options is still an important task. In this study, we report that a late-stage drug candidate, otamixaban, inhibits SARS-CoV-2 cell entry. We show that otamixaban suppresses TMPRSS2 activity and SARS-CoV-2 infection of a human lung cell line, although with lower potency than camostat or nafamostat. In contrast, otamixaban inhibits SARS-CoV-2 infection of precision cut lung slices with the same potency as camostat. Furthermore, we report that otamixaban’s potency can be significantly enhanced by (sub-) nanomolar nafamostat or camostat supplementation. Dominant molecular TMPRSS2-otamixaban interactions are assessed by extensive 109 μs of atomistic molecular dynamics simulations. Our findings suggest that combinations of otamixaban with supplemental camostat or nafamostat are a promising option for the treatment of COVID-19.
@article{hempel_synergistic_2021, title = {Synergistic Inhibition of {{SARS-CoV-2}} Cell Entry by Otamixaban and Covalent Protease Inhibitors: Pre-Clinical Assessment of Pharmacological and Molecular Properties}, author = {Hempel, Tim and Elez, Katarina and Kr{\"u}ger, Nadine and Raich, Llu{\'i}s and H.~Shrimp, Jonathan and Danov, Olga and Jonigk, Danny and Braun, Armin and Shen, Min and D.~Hall, Matthew and P{\"o}hlmann, Stefan and Hoffmann, Markus and No{\'e}, Frank}, year = {2021}, journal = {Chemical Science}, volume = {12}, number = {38}, pages = {12600--12609}, publisher = {Royal Society of Chemistry}, doi = {10.1039/D1SC01494C}, altmetric = true, dimensions = true, bibtex_show = true, selected = true }
Distinguishing Crystallographic from Biological Interfaces in Protein Complexes: Role of Intermolecular Contacts and Energetics for Classification

Katarina Elez, Alexandre M. J. J. Bonvin, and Anna Vangone

BMC Bioinformatics, 2018

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Study of macromolecular assemblies is fundamental to understand functions in cells. X-ray crystallography is the most common technique to solve their 3D structure at atomic resolution. In a crystal, however, both biologically-relevant interfaces and non-specific interfaces resulting from crystallographic packing are observed. Due to the complexity of the biological assemblies currently tackled, classifying those interfaces, i.e. distinguishing biological from crystal lattice interfaces, is not trivial and often prone to errors. In this context, analyzing the physico-chemical characteristics of biological/crystal interfaces can help researchers identify possible features that distinguish them and gain a better understanding of the systems.
@article{elez_distinguishing_2018, title = {Distinguishing Crystallographic from Biological Interfaces in Protein Complexes: Role of Intermolecular Contacts and Energetics for Classification}, shorttitle = {Distinguishing Crystallographic from Biological Interfaces in Protein Complexes}, author = {Elez, Katarina and Bonvin, Alexandre M. J. J. and Vangone, Anna}, year = {2018}, journal = {BMC Bioinformatics}, volume = {19}, number = {15}, pages = {438}, doi = {10.1186/s12859-018-2414-9}, altmetric = true, dimensions = true, bibtex_show = true, selected = true }