Psylo (https://psylo.bio) is a pre-clinical biotech company using computer aided design to develop psychedelic-inspired NCEs. The company’s goal is to produce highly optimised and proprietary psychedelic therapeutics for current and emerging clinical needs. Psylo is based at the University of
New South Wales in Sydney, Australia.
We are seeking a highly motivated and intellectually curious scientist to lead our Computational Drug Design team. In addition to providing scientific and technical leadership, they will contribute to a "predict-first" culture where predictive models generate testable hypotheses in chemistry, biology, and pharmacology.
The successful candidate will own the business’ efforts in two primary areas of computational chemistry: designing and implementing large scale virtual docking campaigns to discover novel psychedelic chemotypes in vast areas of uncharted chemical space, and advancing our “In-psylico” platform, a virtual assay for assessing the desirable pharmacological properties of the
molecules we design before experimental validation.
● Drive a culture of innovation in molecular design, act as Psylo’s subject matter expert in computational chemistry
● Apply a variety of computational chemistry methods to improve potency, selectivity, and ADME properties of lead compounds.
● Develop hypotheses to understand ligand-protein interactions and SAR by assimilating and interpreting data using modelling and data-mining technologies.
● Leverage physics-based and machine learning approaches to NCE design to develop new IP.
● Perform computational experiments and data analyses that accelerate the discovery of high-quality drug candidates.
● Stay up to date with the latest developments in computational chemistry,especially SBDD and machine learning/AI by continuous exposure to the latest scientific publications and conferences.
● Work collaboratively with the CSO and other team members to advance multiple NCE programs to IND filing.
● Contribute to the writing of project proposals, research grants, patents, and scientific papers.
THE IDEAL CANDIDATE
● Ph.D. degree in computational chemistry, biophysics, or related disciplines.
● Competitive track record of publications/patents/grants in drug discovery.
● Advanced knowledge of medicinal and computational chemistry principles and demonstrated application of these techniques to drug discovery projects.
● Extensive experience in structure-based drug design, including docking, homology modelling, molecular dynamics simulation, and free energy calculation; ligand-based drug design, including pharmacophore modelling, QSAR, 3D-QSAR, pharmacophore- or shape-based database searching, combinatorial library design, fragment-based drug discovery, and target focused library construction.
● Experience with commercial and/or open-source molecular modelling and data mining software and cheminformatics tools, such as Maestro, MOE, Stardrop, Data Warrior, Spotfire, Knime, etc.
● Excellent communication, organisation, and time management skills.
● Demonstrated ability to troubleshoot and problem solve.
● Capable of working independently and as part of a multidisciplinary team.
● Experience with the structural biology of GPCRs or 5-HT receptors, or the pharmacology of psychedelics is highly desirable.