Senior Principal Scientist, Computational Drug Discovery - Molecular Modeling & Cheminformatics

Responsibilities

• Identify, implement, and apply 3D modeling techniques for sampling Helicon™ peptide conformations in the presence of a target, in ternary complex, and in different physiological environments; analyze and derive 3D peptide structure-property relationships.
• Analyze peptide/chemical structure and property space to identify patterns and gaps that inform Helicon and monomer designs; adapt and implement data analytics and machine learning techniques toward predictive models of Helicon™ properties.
• Contribute to the implementation and development of cheminformatics and research informatics systems and tools, working with IT and data engineering to enable and automate enterprise-level computational solutions.
• Exemplify scientific leadership by partnering across functions and working within a team of talented, passionate scientists to discover drugs and help teams make better decisions, faster.
• Interface with internal and external partners.
• What you'll need to be successful:
• PhD in Computational Chemistry, Cheminformatics, Data Science, Protein Engineering, Computational Biology/Biophysics, Chemistry, Physics, Macromolecular Sciences, or a closely related field.
• 10+ years of pharma/biotech industry experience in computational rational drug discovery, with a proven track record of impact in a drug discovery program using computational and/or informatics techniques.
• Demonstrated experience with ternary complex design and understanding, peptide design or protein engineering, and a good understanding of peptide structure-property relationships (e.g. helicity and amphiphilicity metrics, cell penetration).
• Demonstrated mastery of modern computational chemistry including, but not limited to, peptide folding and docking, use of co-folding foundation models such as Boltz, structure-based design (receptor- and ligand-based), scaffold hopping, and conformat

Benefits

Additional Information

Why Join Us? As a member of the Parabilis Medicines team, you will be a part of an organization dedicated to creating extraordinary medicines for diseases with urgent unmet needs, harnessing our proprietary peptide platform to transform treatment possibilities for patients. Parabilis is a clinical-stage biopharmaceutical company dedicated to unlocking high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides - Helicons™ - capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered "undruggable" despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and ARON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution. What's the opportunity? Parabilis Inc. is seeking a highly talented and self-motivated Senior Principal Scientist to be a versatile, hands-on pillar of the Computational Drug Discovery group, a strategic function that is part of Parabilis's platform discovery engine for Helicon™ stapled-peptide drugs. Reporting to the Senior Director of Computational Drug Discovery, this person will bridge two disciplines that are often siloed - 3D molecular modeling and molecular data science / cheminformatics - applying both to advance our peptide pipeline. We are looking for someone who can independently support project teams across the full computational spectrum, from sampling peptide conformations and designing ternary complexes to building predictive property models and running cheminformatics analyses, without needing to hand off between a dedicated 3D modeler and a dedicated cheminformatician. You'll be part of a data science team that is a central pillar of Parabilis's innovative discovery platform and pipelines targeting "undruggable" genes of major therapeutic interest to patients.

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