Sosei Heptares (the corporate brand of Sosei Group Corporation) is a research-focused biotechnology group, publicly listed in Japan (TSE: 4565) and with sites in Tokyo, London and Cambridge (UK).

Our mission is to make a significant contribution to improving the quality of life and health of people around the world. To achieve this, we will discover, design and develop the most innovative and effective medicines for patients worldwide, through our world-leading patent-protected technology and platform.

Our primary focus is the discovery and early development of new medicines originating from its proprietary G Protein-Coupled Receptor (GPCR)-targeted StaR® technology and Structure-Based Drug Design (SBDD) platform capabilities. The company is advancing a broad and deep pipeline of novel medicines across multiple therapeutic areas, including CNS, immuno-oncology, gastroenterology, inflammation and other rare/specialty indications.

The company has established partnerships with some of the world’s leading pharmaceutical companies, including Allergan, AstraZeneca, Daiichi-Sankyo, Genentech (Roche), Novartis, Pfizer and Takeda and additionally with multiple emerging technology companies

Sosei Heptares has approximately 161 employees based at its new R&D research facility at Granta Park. The size of the company ensures a transparent linkage between all activities from early discovery through to clinical development.

We are growing our Computer-Aided Drug Design and Cheminformatics/AI capabilities by extending the Sosei Heptares Computational Chemistry team with three additional positions. These cover all experience levels from recent PhD to a well experienced senior computational chemist in drug discovery. The positions are flexible, so different combinations of skills and/or experience are acceptable for the right candidate, so please apply if you feel passionate about joining our team where scientific excellence and passion combine in a friendly fun environment to impact drug discovery projects and create new cutting-edge approaches.

This is an exciting and exceptional opportunity to participate in cutting-edge science using unique structural data whilst making significant contributions to the industry-leading drug discovery R&D. The Computational Chemistry team uses state-of-the-art CADD techniques to support and drive discovery projects from early exploratory stage to clinical candidate stage working closely with chemistry, pharmacology, biophysics and structural biology teams. The team is actively involved in Sosei Heptares internal and partnered drug discovery projects, and AI and SBDD collaborations, providing significant opportunities for scientific and leadership growth to contribute to advancing and leading drug discovery projects within multi-disciplinary teams.

As members of the Computational Chemistry team, you will:

• Contribute to multidisciplinary GPCR SBDD projects by applying a broad set of computational chemistry and cheminformatics approaches to support and creatively contribute to data-driven molecular design and medicinal chemistry efforts.
• Develop and apply customised computational chemistry and cheminformatics tools, workflows and models to extract, integrate, analyse and visualise complex chemical, structural, pharmacological and ADMET data within the context of structure-based drug discovery.
• Play an active role in new initiatives, such as:
  • GPCR SBDD optimized alchemical relative binding free energy approaches
  • Development of new computational chemistry CADD software via external collaborations
  • Generative models for GPCR structure-based artificially intelligent molecular design
  • Structural bioinformatics and StaR® data driven GPCR protein engineering
  • Structural GPCRome and chemogenomics guided virtual ligand screening
  • Structure-based optimization of GPCR StaR® enabled DNA-Encoded Library screening hits
  • GPCR structure-based design of Targeted Protein Degraders

The successful candidate(s) will be expected to work independently, and:

• Manage Sosei Heptares Drug Discovery databases and liaise with internal and external Discovery, Translational Sciences and Platform teams to coordinate data curation, annotation and integration.
• Develop and implement tools and workflows to extract, integrate, analyse and visualise chemical, pharmacological, biophysical and ADMET data to support Drug Discovery project decision making.
• Apply advanced Machine Learning and Real Intelligence (RI) to drive Artificial Intelligence (AI) approaches which exploit our broad datasets

Expected Skills/Requirements for all three positions:

• Ph.D. or equivalent experience in computational chemistry, cheminformatics, or a related discipline;
• Strong background in molecular recognition and the structural and physicochemical property determinants of small molecule binding to proteins;
• Computational chemistry experience within a collaborative multi-disciplinary medicinal chemistry research environment;
• Working knowledge and hands-on experience with molecular modelling, computer-aided drug design and cheminformatics software packages;
• Advanced analytical and critical problem-solving skills, combined with scientific creativity and a proactive, positive can-do attitude;
• Strong team player with an inclusive, pro-active and positive can-do mindset that is willing to listen and learn from others;
• Excellent interpersonal, oral and written communication skills: you will need to be able to communicate effectively with team members having diverse professional backgrounds.

Additional position specific qualifications include:

Computational Chemist 1:

• Experience in using CADD approaches to investigate structural protein-ligand interactions, including homology modeling, phamacophore modeling, molecular docking, MD simulations;
• Knowledge of cheminformatics, bioinformatics and computational chemogenomics approaches to guide protein-ligand interaction modeling and virtual ligand screening;
• Experience in the use of X-ray crystallographic or cryo-EM data of protein-ligand complexes;
• Familiarity with Python scientific programming language and/or scientific workflow systems;
• Experience in GPCR structural modelling and SBDD is considered very beneficial.

Computational Chemist 2:

• Experience using cheminformatics toolkits or computational chemistry tools to solve problems such as similarity searching, matched pair analysis, clustering, QSAR modelling, visualisation of structure-activity relationships and virtual library enumeration;
• Strong coding skills in Python and familiarity with common data science packages;
• Familiarity with querying of relational databases and use of scientific workflow systems;
• Experience in AI approaches such as Deep Generative Models is considered beneficial.

Computational Chemist 3:

• Extensive, relevant post-PhD experience, with a strong track record of scientific achievements in a collaborative, multi-disciplinary pharmaceutical or biotech environment;
• Established expertise and in-depth knowledge in computational chemistry/CADD approaches with the ability to fill CADD-related gaps;
• Proven experience in working collaboratively with medicinal chemists in SBDD projects, and other project teams, incorporating knowledge of small molecule properties based on a good understanding of medicinal chemistry, DMPK principles and multi-parameter optimization concepts;
• Knowledge of the fundamentals of GPCR modelling and their structural highlights;
• Experience in managing/mentoring junior staff and/or involvement in drug discovery project leadership roles are considered beneficial.

We offer a competitive salary and benefits package commensurate with qualifications and experience.

Heptares is an equal opportunities employer.

Applications should include a covering letter, providing a short description of the background to their interest in the role, with curriculum vitae including the names and contact details for two referees. Please apply through our on-line jobs portal with your application in pdf format, quoting reference number 2020_2CC. The closing date for applications is 15th March 2021.