Elucidating the Sequence–Activity Relationship of Catalytic Peptides in Deep Eutectic Solvents in a Self-Driving Lab

Research topic/area

Enzymtechnik, Unkonventielle Medien, Reaktionstechnik, Analytik, Automatisierung

Type of thesis

Master

Start time

-

Application deadline

31.12.2026

Duration of the thesis

6 Monate

Description

This Master’s thesis is conducted jointly within the research groups of Electrobiotechnology (BLT) and Bioengineering and Biosystems (IFG) and addresses a fundamental question at the interface of enzymology and process engineering:

How does amino acid sequence determine catalytic function in non-conventional solvent environments?

Background and Research Objective

Deep eutectic solvents (DES) emerged as versatile alternatives to classical aqueous and organic solvents. Their tunable polarity, hydrogen-bonding networks, and adjustable physicochemical properties make them attractive reaction media for catalysis. At the same time, the molecular principles governing catalyst performance in these environments remain poorly understood. Many enzymes require substantial water fractions to remain active, even in DES-based systems, indicating that solvent–catalyst interactions are far from trivial. To systematically dissect these interactions, this project employs catalytic peptides as minimalist functional enzyme models. By reducing structural complexity compared to full enzymes, peptide catalysts allow direct investigation of sequence–activity relationships under defined solvent conditions. An established peptide library is available and may be rationally extended based on experimental findings. The central aim of the thesis is to identify how sequence features influence catalytic efficiency, stability, and kinetic behavior in DES and to translate these findings into generalizable design principles for catalysis in non-aqueous media.

Content of the Thesis

The experimental work is performed within an operational self-driving laboratory platform that automates liquid handling, reaction execution, and analytical measurements. High-throughput UV–Vis spectroscopy is used to monitor oxidation reactions of colorimetric substrates, while gas and liquid chromatography enable detailed analysis of reactions in tailored solvent systems. Catalytic performance will be quantified using established kinetic models such as Michaelis–Menten and Ping-Pong kinetics. Water content in the solvents will be analytically determined to ensure reproducibility, but the scientific focus lies on the interplay between solvent structure and peptide sequence rather than on water activity engineering. Depending on the candidate’s interest, machine learning approaches may be employed to assist in identifying sequence features that drive catalytic performance.
This thesis is designed for a motivated and independent Master’s student with a solid understanding of enzyme catalysis and reaction engineering. Applicants should have prior laboratory experience and a strong interest in quantitative experimentation, kinetic modeling, and automated research environments. The project particularly addresses students who are curious about how biological function can be systematically engineered in unconventional chemical settings and who are motivated to work at the intersection of biology and process engineering. Enthusiasm for automation, data-driven experimentation, and structured problem solving is essential, as the project requires persistence and analytical rigor.

Requirement

Requirements for students

• Applications should include a CV (less than 1 page) and a brief statement of motivation (less than 500 words) outlining prior work, the applicant’s interest in catalytic systems beyond classical aqueous environments, and their motivation to work within an automated laboratory framework. Selected candidates will be invited to an interview focusing on conceptual understanding of enzyme kinetics, motivation for interdisciplinary research, and readiness to engage in challenging experimental investigations at the interface of life sciences and engineering.

Faculty departments

• Engineering sciences
  Biological engineering
  Chemical & process engineering
• Natural sciences and Technology
  Biology
  Chemistry
  Chemical biology

Supervision

Title, first name, last name

Dr. Lukas Platz

Organizational unit

Institut für Bio- und Lebensmitteltechnik 2 - Elektrobiotechnologie

Email address

lukas.platz@kit.edu

Link to personal homepage/personal page

Website

Application via email

Application documents

• Cover letter
• Curriculum vitae

E-Mail Address for application
Senden Sie die oben genannten Bewerbungsunterlagen bitte per Mail an lukas.platz@kit.edu


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