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Alzbeta Tuerkova

@alzbetatuerkova

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Experienced computational chemist specializing in drug discovery and leadership.

Czechia

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What I'm looking for

I seek a collaborative environment that fosters innovation and supports professional growth in drug discovery and computational chemistry.

I am a dedicated professional with over 8 years of experience in computational chemistry, focusing on drug discovery and development. Currently, I lead computational chemistry efforts at AI|ffinity, where I manage a talented team and oversee the creation of innovative virtual screening pipelines that leverage machine learning to enhance compound selection for prostate cancer treatments.

My academic journey includes a PhD in Pharmacy from the University of Vienna, where I conducted data-driven molecular modeling studies. I have a strong background in managing projects and teams, having led initiatives in various prestigious institutions across Europe. My commitment to scientific excellence is reflected in my numerous awards and recognitions, including the Wenner-Gren fellowship and contributions to impactful publications in the field.

Experience

Work history, roles, and key accomplishments

Current

Computational Chemistry Project Lead

Current

AI|ffinity

Jan 2024 - Present (1 year 9 months)

Led computational chemistry efforts on a drug discovery project targeting AR-V7 in prostate cancer. Line-managed and mentored two computational chemists, overseeing the development of a proprietary virtual screening pipeline.

Computational Chemistry Drug Discovery Machine Learning Medicinal Chemistry Project Management Team Leadership

Head of Computer-Aided Drug Design

Celeris Tx

Jan 2022 - Present (3 years 9 months)

Headed the Computer-Aided Drug Design department, focusing on the discovery of heterobifunctional degraders (PROTACs). Augmented the CADD portfolio with novel approaches and led a team of up to four professionals.

PROTACs Ensemble Docking Team Leadership Collaboration

PhD Candidate in Barbara Zdrazil lab

University of Vienna

Jan 2017 - Present (8 years 9 months)

Designed and implemented automated pipelines for ligand data mining and analysis using KNIME, Python, RDKit, and SciKit. Performed protein conformational sampling for ensemble docking with normal mode analysis.

Ligand Data Mining KNIME Python RDKit Protein Conformational Sampling QSAR Teaching

Education

Degrees, certifications, and relevant coursework

University of St. Francis

Master of Business Administration, Business Administration

Pursued a joint MBA program between the University of St. Francis in the USA and the Faculty of Business and Management (BUT) in Brno. Focused on business administration principles and practices.

Masaryk University

BSc in Chemoinformatics and Bioinformatics, Chemoinformatics and Bioinformatics

Obtained a Bachelor of Science degree with a thesis on the parametrization of the EEM approach for calculating charges in proteins. Supervised by RNDr. Stanislav Geidl, PhD.

University of Vienna

PhD in Pharmacy, Pharmacy

Conducted doctoral research with a thesis on data-driven molecular modeling studies, specifically focusing on hepatic uptake transporters. Supervised by Dr. Barbara Zdrazil.

Masaryk University

MSc in Biomolecular Chemistry, Biomolecular Chemistry

Completed a Master of Science degree with a thesis on the effect of peptide kink on the formation of membrane pores. Research was supervised by doc. RNDr. Robert Vácha, PhD.