SGC Careers

Equity, Diversity and Inclusion

The Structural Genomics Consortium (SGC) is strongly committed to equity, diversity, and inclusion. We strive to create an environment that welcomes individuals from all groups, countries, organizations and institutions in our research community. With the mission of creating global access to drug discovery through open science, SGC also endeavours to further the diversity of ideas and approaches in the workplace.

Donated chemical probes

In this unique project, pharmaceutical companies and leading academic laboratories make their innovative high-quality chemical probes available to the research community through the SGC. These donated probes complement the probes generated by the SGC and its collaborators. All compounds accepted into the donated probes program meet the chemical probe quality criteria and have been evaluated by an internal as well as an external expert committee. Moreover, several probes are suitable for in vivo use. Control compounds are also provided and profiled. 

Chemical Probes

SGC chemical probes are open-access reagents that are meant to be used by the biomedical research community with no restrictions on use. SGC-developed probes are complemented by a growing set of donated high-quality chemical probes developed in industry and non-SGC laboratories. These are also available for unencumbered use.

Privacy Policy

This policy (the “Privacy Policy”) applies to information that personally identifies you (“You”) (other than publicly available information) (“personal information”), that is collected by SGC, a company limited by guarantee (Company No. 4714553) and registered as a charity in England and Wales (Charity No. 1097737) (“SGC”), including on www.thesgc.org or any other SGC web properties (together, the “Website”), or that is otherwise provided by You to SGC.

Legal Information

Website Terms of Use and Disclaimer

IMPORTANT! YOUR ACCESS TO, USE OF, OR REGISTRATION ON WWW.THESGC.ORG OR ANY OTHER SGC WEB PROPERTIES (TOGETHER, THE “WEBSITE”), OR YOUR PROVISION TO SGC OF ANY CONTENT OR PERSONAL INFORMATION VIA THE WEBSITE, CONSTITUTES YOUR ACCEPTANCE OF, AND IS CONDITIONAL UPON YOUR ACCEPTANCE OF AND COMPLIANCE WITH, THESE TERMS AND CONDITIONS, INCLUDING THE SGC PRIVACY POLICY (THE “PRIVACY POLICY”), ALL AS AMENDED FROM TIME TO TIME. CAREFULLY READ ALL OF THE FOLLOWING TERMS AND CONDITIONS AND THE PRIVACY POLICY BEFORE PROCEEDING.

Accessibility

Accessibility statement for the SGC website

The Structural Genomics Consortium is committed to providing an accessible web presence. We want as many people as possible to be able to use this website. For example, that means you should be able to:

18.01.2024

SGC Utilizes AI-driven hit-finding technologies to discover novel small molecule ligands for the WDR protein family

by: SGC

A recent study led by researchers at the SGC-Toronto identified a first-in-class small molecule ligand for WDR91 to better understand the role of this protein in physiology and viral infection.

Among the approximately 20,000 human proteins encoded by genes, not all are amenable to modulation by drug-like small molecules. Only a small fraction of them can bind to a small molecule and serve as potential drug targets. This subset of proteins is known as the druggable proteome.

Expression Vectors

The table below contains the entire collection of SGC’s expression vectors. To browse the collection, find associated data, or acquire samples, select the desired expression vector in the table below and read the PDF information sheet for the vector. You can sort the table by clicking the column headers. To purchase a vector, follow the links to AddGene and Source BioScience in the Description column.

10.01.2024

Structural Genomics Consortium (SGC) Appoints Benjamin Haibe-Kains as Head of Data Science

by: SGC

[Toronto, January 10, 2024] - Professor Benjamin Haibe-Kains has joined the Structural Genomics Consortium as the Head of Data Science to further support SGC’s ambition to generate high-quality and reproducible data. In his new role, Dr. Haibe-Kains will establish a robust mechanism to ensure transparency, interoperability, and accessibility of SGC’s data for machine learning and pattern recognition.