eMolecules screening collection
StarDrop users who have licensed the Surflex eSim3D module can freely download prepared virtual screening collections for use in StarDrop. eMolecules‘ commercially available screening…
An augmented approach to generative chemistry
Generative molecular design provides new exciting avenues of chemical space exploration. But how can we use these methods effectively to assess many optimisation strategies and find the compounds destined for success in our projects?
Join Dr Matt Segall and Dr Michael Parker as they explore state-of-the-art generative chemistry, and discuss the importance of an augmented intelligence approach for successful discovery.
Using StarDrop or Semeta in the AWS environment
This short video provides an orientation for StarDrop and Semeta users at organisations that are subscribing to Optibrium’s hosted services.…
How to be a great drug discovery chemist ebook
Discover the skills, knowledge and tools which are essential for success for today’s drug hunters.
How to run a successful drug discovery team
Watch industry leaders from Novartis, Apollo Therapeutics and Eikon Therapeutics as they discuss their highs and lows, experience and advice,…
Overcoming challenges in drug metabolism: in silico approaches
Interpreting metabolite-ID experiments; determining the right species for animal studies; providing optimisation suggestions for your medicinal chemistry colleagues to overcome…
Single-scaffold R-group analysis
In this quick example, we will look at a single-scaffold R-group analysis to identify any functionalities which are influencing potency. The data…
Optibrium enables collaborative design in its StarDrop platform
The new Idea Tracker capability further improves the efficiency of drug discovery by supporting project management, idea sharing and molecule design tracking
Introduction to Idea Tracker
Want to accelerate your drug discovery with collaborative design and informed decision making? Watch our introduction to Idea Tracker, an…
Transferable machine learning interatomic potential for bond dissociation energy prediction of drug-like molecules
Predicting metabolism at an early stage is important in maximising the chance of a drug’s success. However, accurate, useful models…
Optibrium’s quantum mechanics and machine learning methods predict routes of drug metabolism
Peer-reviewed study published in Xenobiotica describes an innovative new method that predicts the routes and products of Phase I and II metabolism with high sensitivity and greater precision than
other approaches
ScienceCloud access from StarDrop
This script provides the ability to connect directly to ScienceCloud, download data from libraries or saved queries of your choice and…
Mcule Access from StarDrop
This script enables you to search the Mcule database for purchasable compounds, fetch pricing information, and start the quote generation process from StarDrop.…
Predicting routes of Phase I and II metabolism based on quantum mechanics and machine learning
This peer-reviewed paper in Xenobiotica describes a new method to determine the most likely experimentally-observed routes of metabolism and metabolites based on our WhichP450™, regioselectivity and new WhichEnzyme™ model.
MolPort plug-in for StarDrop
Version This integration is available to use with the latest version of StarDrop. To find out which version you have installed, start…
Enamine plug-in for StarDrop
This script enables you to search EnamineStore, a database of commercially available compounds. This will return details about the availability of…
Lipophilicity efficiency script for StarDrop
This script provides a method for calculating Lipophilicity Efficiency; a simple metric for considering how much of the ligand’s ability…
Optibrium introduces cloud-based version of StarDrop drug discovery platform
Cloud-based version of StarDrop retains all the functionality and interactivity of desktop version with improved accessibility and lower total cost of ownership for customers.
