How do I get budget approval for drug discovery software?
Buying software for your company can be a challenge. Every organisation does things differently, and there is often no handbook…
What other software does StarDrop integrate with?
StarDrop — A Swiss Army knife for drug discovery It’s designed to fit right in with the other tools you…
Data integration in drug discovery software
At a very basic level, this means that StarDrop supports loading data from many different standard file formats (SDF, MOL2,…
How can I make the most of my predictive models for drug discovery?
What’s the purpose of a predictive model? What’s the value of predictive models for drug discovery? Most of the undergraduate…
How does generative chemistry work, and how can it help me?
The role of generative chemistry in drug discovery A key difficulty in finding new drugs is the sheer size of…
How to evaluate StarDrop: A step-by-step guide
Learn how to evaluate StarDrop with this step-by-step guide from Optibrium. Discover key features, trial objectives, and how to set up a successful evaluation of this powerful drug discovery platform
Which is the best metabolite prediction software?
Discover which metabolite prediction software is best for your needs in this comprehensive guide from Optibrium. Compare top tools like Meteor Nexus, MetaSite, and StarDrop to make informed decisions for drug metabolism prediction
What’s the difference between QSAR and imputation predictive models – which method should I use and when?
We’re often asked, “What’s the difference between QSAR and imputation models?”, so I’m going to explain how the methods differ, their advantages and disadvantages, and when each approach is applicable.
How much does drug discovery software cost?
How number of users affect drug discovery software costs The number of people who need access to the platform is…
What are the advantages of cloud-based drug discovery software?
We recently published a case study with Amazon Web Services, detailing how we were able to scale our StarDrop platform…
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
Matched series analysis
The objective in this worked example is to identify new derivatives that are likely to improve activity at their target, given the SAR already generated on a project.
Inspyra matched series analysis
Explore ways to use the Inspyra Panel, in combination with Matched Series Analysis (MSA).
Exploring optimisation strategies with Inspyra
This worked example uses Inspyra™ to interactively explore optimisation strategies to achieve a selective inhibitor of DPP-4 with appropriate physicochemical properties.
Reaction-based library enumeration
In this example, we are going to use the reaction-based library enumeration feature in StarDrop’s Nova module to generate a library of virtual compounds. This will be based on pre-defined sets of reagents that will be used to generate products using well-known reactions.
Ligand-based drug design using Surflex eSim 3D
This worked example uses StarDrop’s Surflex eSim3D module to assess a small library of compounds for their similarity to known Heat Shock Protein 90 (HSP90) ligands.
Automatic generation of new compound ideas
During this example we will consider three compounds from a lead series which we would like to try to evolve into a candidate. The compound has a good profile of ADME properties but insufficient inhibition of the target, the Serotonin transporter. In this example we will use StarDrop’s Nova module to generate new ideas for compounds to improve the potency while maintaining the balance of other properties.
