Predicting pKa using a combination of quantum mechanical and machine learning methods
This study aimed to create a model for predicting pKa using a semi-empirical quantum mechanics (QM) approach combined with machine learning (ML).
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.
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…
AutoDock Models for the StarDrop Pose Generation Interface (PGI)
From the manuscript “DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design”, Miguel García-Ortegón, Sergio Bacallado, et al¹ have developed…
Augmenting Inspiration with generative chemistry
Out now in International Biopharmaceutical Industry, Optibrium’s CEO, Dr Matt Segall introduces the concept of augmented intelligence. He explains how to use dynamic…
Experimental validation of predictive models in a series of novel antimalarials
In this study, we identified a new antimalarial with an unusual structure – the only compound in the competition to be proven active, opening up new chemistry for exploration.
Addressing toxicity risk in multi-parameter optimisation
In this example we will illustrate how knowledge-based predictions of toxicity can be used within a MPO environment to guide the selection and design of compounds with a good balance of properties and reduced risk of toxicity.
3D virtual screening with Surflex eSim3D
When exploring chemistry space around a known hit or lead, you can use 3D virtual screening to identify new compounds…
Quantitative estimate of Drug-likeness in StarDrop
In the article, Bickerton et al. (2012) “The Chemical Beauty of Drugs” Nature Chemistry 4, 90–98, the authors proposed a measure of ‘drug-likeness’, the Quantitative…
Redesign to reduce drug toxicity risk
In this demo we look at how it’s possible to use the Derek Nexus module with StarDrop to guide the design of…
Advances in multi-parameter optimisation methods for de novo drug design
Summary This review article discusses recent developments in the methods and opinions around multi-parameter optimisation, focusing on applications to de novo drug…
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.
Guiding selection and design in hit-to-lead
The objective in this example is to identify one or more high quality chemistries for progression to detailed in vitro…
MolPort screening collection
StarDrop users who have licensed the Surflex eSim3D module can freely download prepared virtual screening collections for use in StarDrop. MolPort’s commercially available screening…
PAINS Filters
Baell and Holloway published a set of substructure filters for removal of what they termed “Pan Assay Interference Compounds (PAINS)” from…
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
Optibrium releases 3D ligand-based design module for StarDrop drug discovery software
Innovative predictive methods support virtual screening and compound design in the absence of 3D structure data.
Python custom model code for StarDrop
This example code shows how to write a custom model using Python. This example can be used to make in-house…
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…