Timoleon Therapeutics
Computational Chemist
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About us
Timoleon Therapeutics is an early-stage, computational-first company building tumour-selective proximity therapeutics. We're looking for a computational chemist to help us design our first drug candidate, entirely in silico — and then help turn that into a repeatable platform. It's a ground-floor role: you'd shape the science and the company, not just execute someone else's plan. The tools are only as good as the chemist steering them, and that's where you come in.
Why this role exists
We need a computational chemist who genuinely understands proximity therapeutics to take ownership of ternary-complex design across our programmes. This is a founding-level seat: you will shape the methodology, not just execute it, and your fingerprints will be on the IP.
What you'll do
- Own the ternary-complex modelling workflow: recruiter–linker–effector geometry, cooperativity, and the structural basis of proximity-driven selectivity.
- Design and triage bifunctional / macrocyclic candidates in beyond-Rule-of-5 chemical space, balancing binary affinity against ternary cooperativity and drug-likeness.
- Drive de novo generation, docking, pose prediction, surrogate MD and free-energy workflows, and translate their outputs into defensible go/no-go decisions.
- Define and validate the geometric and energetic gates that qualify a candidate for synthesis — and know when a gate is physically impossible.
- Run ADMET and multi-objective (Pareto) optimisation to select synthesis-ready leads.
- Partner on IP strategy: recognising what is novel, patentable and defensible, and protecting it.
- Help build the pipeline itself — tooling, protocols, reproducibility.
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Must-haves
- Demonstrable proximity-therapeutics experience — PROTACs, molecular glues, or other ternary-complex / proximity-inducing modalities. This is the non-negotiable one. We want someone who thinks in terms of ternary cooperativity (α), effective molarity, and interface geometry, not just binary docking scores.
- Strong computational / medicinal chemistry foundation: structure-based design, conformational analysis, protein–protein interfaces, and the realities of beyond-Rule-of-5 and macrocyclic chemistry.
- Fluency with a modern comp-chem stack — e.g. AlphaFold-class structure prediction, pocket detection (P2Rank or similar), RDKit, docking / pose prediction (DiffDock, EquiBind or equivalent), MD (OpenMM / ANI-class potentials), and ML-based ADMET/affinity prediction.
- Comfortable in Python and working from raw structural coordinates (mmCIF/PDB) — reading ATOM records, checking geometry, not treating tools as black boxes.
- Sound scientific judgement: able to distinguish a real result from an artefact, and to say when a model can't support a claim.
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Nice-to-haves
- Free-energy methods (FEP / MM-GBSA / umbrella sampling) and multi-objective (Bayesian) optimisation.
- Peptidomimetic or covalent chemistry, and macrocyclisation strategies (e.g. click / CuAAC).
- A track record you can point to — publications, patents, or shipped programmes.
- Start-up instincts: comfort with ambiguity, breadth over narrow specialisation, and building from scratch.
Compensation
This is a founding-team, equity-based role. You'd be joining before we're funded, with an ownership stake and a genuine seat at the table on scientific and strategic direction — details discussed directly with candidates.
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