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Berlin
Nagmeh Naderi

Nagmeh Naderi

Bioinformatician

Pharmazeutik / Biotechnologie

Berlin, Berlin

Soziales


Über Nagmeh Naderi:

I am a bioinformatician with hands-on experience in computational drug discovery, molecular dynamics simulations, and data analysis using Python. I enjoy tackling challenging problems by combining scientific knowledge with computational tools, often working with multidisciplinary teams to achieve meaningful results. My passion lies in applying biotechnology and computational biology to develop innovative solutions that make a realworld impact.

Erfahrung

Targenomix GmbH | Potsdam, Germany 
Junior Bioinformatician (Sep 2024 – Feb 2025 )

• Conducted molecular dynamics simulations (GROMACS & OpenMM) to explore the dynamics of Phytoene Desaturase (PDS) and its cofactor. 
• Led ensemble docking efforts (Glide & AutoDock Vina), analyzing PDS inhibitors and a 500,000-compound screening library to uncover scoring patterns and potential new inhibitors. 
• Built and implemented the first MD simulation and ensemble docking pipeline (Snakemake). 
• Supported the virtual ligand screening team by integrating molecular dynamics and docking data to guide inhibitor selection and optimization. 
• Applied PCA and KMeans clustering to extract MD trajectory snapshots for docking and presented insights through visualizations (Python tools like Seaborn, Matplotlib & Pandas). 

Max Plank Institute | Magdeburg, Germany (Hybrid) 
HiWi Research Assistant (Aug 2023 – July 2024 )

• Conducted research on computer-aided drug discovery (Python, OpenMM, & ProDy) for molecular dynamics and normal mode analysis on CYLD protein. 
• Performed allostery pathway analysis and docked deubiquitinating enzyme inhibitors to identify potential allosteric drug candidates. 
• Identified top 10 ligands from 15,300 small molecules (Glide), focusing on allosteric site targeting. Side Project 
• Conducted in silico pharmacokinetics analysis (RDKit & Zinc20 database), predicting blood-brain barrier permeability (logBB) for 5000+ molecules. 
• Developed a machine learning model (scikit-learn) with an MSE of 0.40

Bildung

Master of Sciences in Molecular Biotechnology

(2021 – 2024) Anhalt University – Köthen, Germany

Thesis Topic: Modelling and simulation of small molecule drug binding to the deubiquitinate enzyme CYLD

Final grade: 1,4 (excellent)

Master of Arts in Applied English Linguistics

(2017 – 2019) Sobhe Sadegh Institute of Higher Education - Isfahan, Iran

Bachelor of Sciences in Molecular and Cell Biology (Genetics)

(2013 – 2017) Azad University - Isfahan, Iran

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