We are recruiting a computational postdoc for a structural biology project that investigates the role of water networks at dynamic protein ligand interfaces with a view towards ligand discovery. The position is available immediately.

We are looking for highly motivated candidates with curiosity and skills to reveal hidden factors that contribute to protein dynamics, hydration and protein-ligand binding and leverage this information for ligand discovery. As this project integrates experimental and computational data it will require both significant computational skills for custom data analysis and automation, and a solid background in structural biology. Despite the focus on computational structural biology, we will consider exceptional candidates with a suitable experimental background and a strong interest in computation, protein dynamics, ligands and water.

The project is housed in the Department of Chemical Biology and Therapeutics at St. Jude Children’s Research Hospital. It builds on strong investments into a world-class infrastructure in structural and chemical biology. You will be embedded into a dynamic lab that has strong expertise in modulating protein conformational ensembles with ligands and temperature (see references below). This is an exciting time to join us and build a career while living in an affordable city.

Essential requirements:

• PhD in computational (structural) biology or related field
• High proficiency in coding and data analysis (including Python)
• Interest in dynamic aspects of structural biology including protein flexibility and hydration

Optional requirements:

• Hands-on experience in molecular biology, crystallography, xFEL, biophysical assays
• Experience in molecular dynamics simulations, free-energy perturbation, Rosetta, ligand discovery, computational chemistry

Please direct your questions and application package including a cover letter, current CV, and 3 letters of reference to: Dr. Marcus Fischer (marcus.fischer@stjude.org).

Relevant papers include:

• Stachowski and Fischer (2024). FLEXR GUI: a graphical user interface for multi-conformer modeling of proteins. J Appl Cryst 57

• Stachowski and Fischer (2023). FLEXR: automated multi-conformer model building using electron-density map sampling. Acta D 354-367.

• Stachowski and Fischer (2022). Large-scale ligand perturbations of the protein conformational landscape reveal state-specific interaction hotspots. J Med Chem. 13692-13704

• Stachowski et al. (2022). Water networks repopulate protein-ligand interfaces with temperature. DOI: 10.1002/anie.202112919

• Bradford et al. (2021). Temperature artifacts in protein structures bias ligand-binding predictions. Chemical Science. DOI: 10.1039/D1SC02751D

• Fischer (2021). Macromolecular room temperature crystallography. Q Rev Biophys 54. E1

• Darby et al. (2019). Water networks can determine the affinity of ligand binding to proteins. JACS 141, 15818-26.

• Balius et al. (2017). Testing inhomogeneous solvation theory in structure-based ligand discovery. PNAS E6839-46.

• Fischer et al. (2014). Incorporation of protein flexibility & conformational energy penalties in docking screens to improve ligand discovery. Nature Chemistry 6, 575-83.

More info at:

https://www.stjude.org/fischer

https://scholar.google.com/citations?user=ijs3_vIAAAAJ&hl=en&oi=ao

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