MSCA Doctoral Network PhD position: Bioinformatic- and machine-learning-based search for new β-catenin peptide binders

Project Title: Bioinformatic- and machine-learning-based search for new β-catenin peptide binders Objectives:

1. Quantify common and overrepresented elements in IDR sequences known to bind to β-catenin.
2. i) Use the elements as features to query the proteome; ii) Develop a protocol to model IDR/β-catenin complexes.
3. Improve and update the models i) and ii) based on experimental data. Project Overview: This project builds on our established expertise in discovering functionally relevant features of human IDRs and using those features for IDR classification proteome-wide. Bioinformatics strategies will be used to determine and quantify common and overrepresented elements of IDR sequences known to bind to β-catenin. Given the limited initial training set, in the first instance an expectation-maximization algorithm coupled with regularized logistic regression (FAIDR) will be used to isolate sequence features that distinguish known β-catenin IDR binders from the rest of the proteome. Once trained, the FAIDR model will be used to predict putative β-catenin IDR binders proteome-wide for screening in WP2 (Maric, JMU). Due to the expected scarcity of the initial training data, precision of the initial model is expected to be low. The initial model will be subsequently retrained using experimentally validated binders as positive examples to refine the model weights and improve its predictive performance. Structural modeling of known and putative binders will be undertaken using AlphaFold Multimer and related models., as well as foundation models Boltz-1 and Chai-1, and if needed further refined by e.g. Rosetta FlexPepDock. A subset of known beta-catenin peptide interface structures will be used to template AF2-Multimer to produce initial models. High-scoring structural models (evaluated using actifPTM developed by the Schueler-Furman group (HJU)) are expected to capture key interface features, enhancing definition of features and improving FAIDR model optimization and improved proteome-wide predictions. Contribution to the overall research program: Couples in-silico screening for putative novel β-catenin IDR binders with experimental validation (WP2) and informs design of novel binders (WP5)., * Education - you do not hold a doctoral degree and hold (or will shortly complete) a science Master’s degree (see individual project requirements), with excellent results, qualifying you for admission to the doctoral program of the respective host institution. The successful candidate must fulfil the admission requirements of the respective doctoral programme and will be enrolled in a doctoral programme during the project.

Enrolment in Doctoral degree(s): Helmholtz Munich Grad. School HELENA & TUM (Pritisanac), Research Field Chemistry Education Level Master Degree or equivalent, * Mobility - you must not have resided or carried out your main activity (work, studies, etc.) in recruiting beneficiary’s country for more than 12 months during the 36 months before your recruitment. Compulsory national service, holidays/short stays and time spent obtaining refugee status under the Geneva Convention4 are not considered for this purpose.

• Language & communication - excellent command of spoken and written English (min. B2 level). Ability to communicate results clearly to diverse audiences, both in writing and verbally.
• Motivation - motivation for multidisciplinary, international doctoral research, hands-on experimental work, mandatory academic/industy secondment(s), to publish research findings in international journals, present results at conferences and contribute to project deliverables. Willingness to contribute to project network-wide activities, communication, training events, and dissemination efforts.
• Technical skills - specific to the individual DC project (see individual project descriptions).

Specific Requirements Contribution to the overall research program: Couples in-silico screening for putative novel β-catenin IDR binders with experimental validation (WP2) and informs design of novel binders (WP5). Languages ENGLISH Level Excellent Research Field Chemistry Years of Research Experience 1 - 4