Computational Peptide Designer/Engineer

Job Description

Why Join Us?

FogPharma® is pioneering the discovery, development, and commercialization of HeliconTM peptides, an exciting new drug modality that uniquely combines the cell-permeability of traditional small molecule drugs with the specificity, broad target accessibility and discovery speed of monoclonal antibody drugs. Our patented Helicon peptide technology allows us to modulate the activity of well-known intracellular disease drivers that have thus far evaded small molecule and biologic therapies.

FogPharma's lead program targets β-Catenin, a cancer driver in the WNT pathway. Inhibition of β-Catenin has the potential to benefit more than one-fifth of all cancer patients and is just one of many opportunities for Fog's leaddiscovery platform to change future medicines, therapies and lives. We recently selected a lead development candidate and plan to initiate clinical development early next year.

What's the opportunity?

This position is a senior computational peptide design role reporting to the VP of Data Science, head of Computational Drug Discovery at Fog. We are seeking highly talented and motivated people to contribute to the development of the Computational Drug Discovery group, a strategic function in Data Science that is part of Fog's platform discovery engine for HeliconTM stapled-peptide drugs. The skill sets of the group includes state-of-the-art machine learning/generative AI, molecular modeling, cheminformatics, structural sciences and data science towards the discovery and development of HeliconTM stapled-peptide drugs.

You'll be part of a data science team that is a central pillar of FogPharma's innovative discovery platform and pipelines targeting "undruggable" genes of major therapeutic interest to patients. Our data science team is an integrated team ranging from computational biology, bioinformatics, computational drug discovery, research informatics and data engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science from building the discovery pipeline to supporting and developing our discovery platform.

Responsibilities

Provide leadership and computational expertise towards, but not limited to, targeted screening library designs, hit-to-lead progression using multi-objective optimization, initiating new projects, new drug-target assessments and advancing drug-pipeline projects towards the clinic.

Identify, implement, or apply 3D modeling techniques for sampling HeliconTM peptide conformations in presence of a target and in different physiological environments.

Analyze and derive 3D peptide-structure relationships.

Exemplify scientific leadership by partnering across functions and working within a team of talented and passionate scientists to discover drugs.

Interface with CROs or external partners.

What you'll need to be successful

PhD in Computational Biology, Computational Chemistry, Protein Engineering, Chemistry, Biophysics, Macromolecular sciences or related scientific field with 8+ years of experience in computational rational drug design (1-3 years industry).

Demonstrated experience with peptide design or protein engineering including affinity maturation 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, structure-based design (receptor and ligand-based), scaffold hopping, docking and conformational analysis.

Expertise with active learning methods/approaches or similar for virtual screening.

Expertise in one or more peptide modeling environments and methods (e.g. ICM, Rosetta, enhanced sampling MD, Monte Carlo) and general modeling environments.

Expertise with 3D biomolecular modeling that incorporates constraints from NMR, CryoEM or other structural, biochemical data.

Demonstrated understanding of critical assessment of molecule-property data and predictive model quality.

Demonstrated understanding of experiments behind the data that can be translated to computational analysis.

Experience with command line modeling applications. Familiarity with HPC workflow tools (e.g. Aiida) is a plus.

Experience with enterprise research informatics systems such as Dotmatics, SQL databases and chemical and biological data warehouses.

Experience with virtual screening and familiarity with cloud computing environments (e.g. Azure or AWS).

An understanding of modern drug discovery including, but not limited to, medicinal chemistry, multi-parametric optimization, molecular recognition principles, and the ability to adapt and translate these principles to stapled peptides.

Excellent communication, collaboration and scientific leadership skills within and across functions that contribute to and inspire a vibrant community of drug hunters.

Familiarity with cheminformatics techniques is a plus.

Demonstrated experience in leading teams (technical or drug-discovery focused) and the potential or experience in managing direct reports.

Strong scientific programming skills (Python) in a Linux environment.

As an equal opportunity employer, Fog values diversity and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.