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Issue Trackers

Conscience Issue Tracker – August 2024

Conscience Issue Tracker – July 8 2024

Conscience Issue Tracker – June 21 2024

Conscience Issue Tracker – June 5 2024

Conscience Issue Tracker – May 20 2024

Conscience Issue Tracker- May 6 2024

Policy Briefs

WHO Includes Policy, Regulatory Reform as Priority for Combating Antimicrobial ResistanceAugust 2024

Climate Change, Dengue Fever, and Vaccine Shortages – July 2024

FTC Challenges Improper Patent Listings – June 2024

European Parliament Proposes Reforms to Legislation Around Pharmaceutical Data Exclusivity – May 2024

Posters and Slides from Our Events

Slides and Posters from our 2024 CACHE Symposium

Recordings from Events

Developing Medicines through Open Science – Information Session

CACHE Challenge 2 Participant Spotlight Webinar

Gravitate-Health Canadian Ecosystem Webinar (Conscience co-Organized)

Articles, Software and Data from our Network
Articles, preprints, and abstracts from CACHE Challenge Participants

In silico screening of LRRK2 WDR domain inhibitors using deep docking and free energy simulations

Subpocket Similarity-Based Hit Identification for Challenging Targets: Application to the WDR Domain of LRRK2

In silico fragment-based discovery of CIB1-directed anti-tumor agents by FRASE-bot

The First CACHE Challenge – Testing Diverse Virtual Screening Scoring Methods to Identify Potential LRRK2 Binders

High-throughput binding free energy simulations: Applications in drug discovery

Protein Structure-Based Organic Chemistry-Driven Ligand Design from Ultralarge Chemical Spaces

Integration of Deep Docking into Virtual Screening Workflow. The CACHE-1 Study Case

Computational Approaches in Drug Design (thesis)

CACHE Challenge #1: targeting the WDR domain of LRRK2, a Parkinson’s Disease associated protein (CACHE #1 Summary Paper)

Software developed by CACHE participants
CACHE Challenge 1 – LRRK2 WDR Domain

Koes Lab – University of Pittsburgh

  • GNINA – Deep learning for molecular docking
  • PharmIt – Interactive exploration of chemical space

Gorgulla Lab – Harvard University & St. Jude Children’s Research Hospital

  • VirtualFlow (github and webpage) – Discovering novel drug candidates by virtually screening chemical space on scales not possible before.

Isayev Lab – Carnegie Mellon University

  • OpenChem (github and paper) – PyTorch-based deep learning toolkit for computational chemistry and drug design

Kireev Lab – University of Missouri

  • FRASE-bot-RDKit (github and paper) – a collection of cheminformatics protocols designed for data processing on FRASE screening, developed in Python with RDKit.


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