Parabilis Medicines

Parabilis Medicines

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

Cambridge · Principal

Sponsorship not specified$200k-$250kDetected 40 days ago
PythonNode.jsAWSAzureLinuxMachine Learningscikit-learnPandasNumPyData AnalysisData EngineeringData ScienceData VisualizationLLMsBioinformaticsResearchLeadershipCommunicationCollaborationOrganizational Skills

About the role

  • The company has pioneered a new class of alpha-helical peptides - Helicons™ - capable of modulating intracellular proteins that have historically been beyond the reach of conventional medicines.
  • Zolucatetide is being evaluated in the clinic across multiple Wnt/β-catenin-driven diseases, including desmoid tumors, familial adenomatous polyposis (FAP) and a range of other solid tumor indications.
  • Beyond zolucatetide, Parabilis is advancing additional Helicon-based programs focused on other challenging targets where we believe our medicines could have life-altering impact.

Responsibilities

  • Provide computational expertise toward, but not limited to, ternary complex design for degraders and other proximity-based modalities, hit identification and prioritization, hit-to-lead progression using multi-objective optimization, initiating new projects, new drug-target assessments, and advancing drug-pipeline projects toward the clinic.
  • 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 peptide/chemical structure and property space to identify patterns and gaps that inform Helicon and monomer designs
  • Interface with internal and external partners.
  • 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 conformational analysis.
  • 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.

Requirements

  • 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 expertise with cheminformatics (e.g. RDKit, ICM, OEChem) and data science toolkits/libraries (e.g. Pandas, Scikit-Learn, NumPy), with a solid grasp of statistical principles and data analytics.
  • Expertise in one or more peptide modeling environments (e.g. ICM, Rosetta, Amber, GROMACS) and methods (enhanced sampling MD, Monte Carlo, MSM).
  • Strong scientific programming skills (Python) in a Linux environment, and experience with command-line modeling applications.
  • Experience with data visualization and exploration tools (e.g. Vortex, Spotfire, DataWarrior, Datagrok).
  • Excellent communication and collaboration skills, with the ability to work well in and inspire a vibrant, multidisciplinary community of drug hunters.

Nice to have

  • Demonstrated use of AI tools in your current role and responsibilities is required
  • advanced or innovative use of AI is a strong plus.
  • Familiarity with cloud computing environments (e.g. Google, AWS, Azure) is a plus.
  • Experience with enterprise research informatics systems such as Dotmatics and chemical and biological data warehouses is a plus.
  • Familiarity with use of LLMs and IDEs, such as Cursor, to enhance workflows, productivity and innovation is a plus.

Compensation

  • The base salary range for this position is $200,000-$250,000, depending on experience, qualifications, and internal practices.

Benefits

  • adapt and implement data analytics and machine learning techniques toward predictive models of Helicon™.
  • Excellent organizational skills and attention to detail, with a strong passion for learning new concepts and technologies.
  • Familiarity with machine learning and cheminformatics concepts applied to peptides is a plus.
  • The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.
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