Zentalis Pharmaceuticals is a San Diego-based pharmaceutical company dedicated to the discovery and development of small molecule therapeutics targeting fundamental biological pathways of cancer. In the six years since our inception, we have successfully cleared four INDs with the FDA. We believe our deep pipeline of oncology therapeutics has the potential to significantly improve the lives of patients with various types of cancer.
We are seeking a highly motivated molecular modeler to join our Modeling and Informatics group to support drug discovery projects through target identification, hit discovery, lead optimization, and ultimately drug candidate selection. This individual will work at the interface of Medical Chemistry, Biology and Crystallography to identify novel chemistry starting points and design compounds with improved potency, selectivity, functional activity and ADME properties.
- Advanced expertise in (1) structure-based, (2) ligand-based and (3) fragment-based molecular design and modeling using state-of-the-art computational methods that integrate experimental structural and biological data with in-silico prediction models for drug properties, protein-drug interactions, and protein dynamics.
- Serve as a scientific research contributor to internal colleagues and external partners and provide recommendations regarding new target molecules and emerging external opportunities in drug design.
- Develop computational strategy to enhance modeling and cheminformatic approaches to analyze datasets for SAR trends.
- Collaborate with scientists across our organization to maximize the impact of computational chemistry on drug discovery projects.
- Ph.D. in Computational Chemistry, Structural Biology, or related fields with 5+ years of pharmaceutical, biotech or academic experience with a track record of key contributions to different stages of drug discovery from hit finding to candidate nomination.
- Expertise with a wide array of computational methods, including docking, scaffold hopping, conformational analysis, virtual screening, protein dynamics, homology model building and molecular design.
- Knowledge of commercial software, including Maestro (Schrodinger LLC), MOE (Chemical Computing Group), Spotfire (TIBCO), KNIME, Pipeline Pilot (Biovia), SeeSAR (BioSolveIT) and/or computational tools from OpenEye and Cresset.
- Familiarity with synthetic medicinal chemistry and software for predictive retrosynthesis.
- Strong records of scientific contributions including peer-reviewed first-author publications, patent applications and presentations at scientific conferences.
- Excellent oral and written communication skills.