Why does conformational flexibility matter in drug design?
What are conformational ensembles? A conformational ensemble is a collection of the different 3D shapes a molecule can adopt in…
Leveraging structure-based and ligand-based techniques in drug discovery
In our recent article in Innovations in Pharmaceutical Technology, we explore the principles, techniques, and applications of structure-based and ligand-based…
How much does 3D molecular modelling software cost?
Introduction 3D molecular modelling plays a vital role in modern drug discovery, offering powerful applications to streamline research, reduce costs,…
Optibrium Widens Access to Industry-Leading Docking Method
New PyMOL interface extends access to Optibrium’s structure-based design method Surflex-Dock CAMBRIDGE, UK, 04 February 2025 – Optibrium, a leading…
How can I model large molecules like macrocycles?
What comprises large molecules? When we talk about “large molecules,” we often think of biologics like monoclonal antibodies, proteins, and…
Optibrium demonstrates superior molecular docking method for small molecules and macrocycles
CAMBRIDGE, UK, 22 October 2024 – Optibrium, a leading developer of software and AI solutions for molecular design today announced…
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…
R-group clipping of reagents for library enumeration
In this example, using StarDrop’s R-group clipping tool, we will quickly transform chemical building blocks into their corresponding substituents, ready to enumerate a virtual library in StarDrop’s Nova module.
SeeSAR pose – 3D analysis of virtual libraries
This worked example explores ways to assess and design compounds in 3D using the SeeSAR Pose module.
SeeSAR affinity – binding affinity and torsion angle analysis of virtual libraries
This worked example explores ways to assess the binding affinity of docked compounds.
Physical Parameter Estimation vs. Pure Machine-Learning for Drug Design
Nearly all computational methods in the CADD field depend on parameters whose values are derived from various types of experimental…
Physical model induction with QuanSA™: Affinity prediction that is synergistic with simulation-based methods
The QuanSA method To define a ‘pocket field’, an initial alignment of all training molecules is constructed and function parameters…
Macrocyclic peptide optimisation: Integrating computational approaches with biophysical data
Introduction Using the integrated set of computational methods within the BioPharmics™ Platform, macrocycles can be effectively modelled for lead optimisation.…
Molecular docking: Extrapolating to new scaffolds with Surflex-Dock
Interested in improving your binding mode predictions? Surflex-Dock is a unique method for molecular docking, offering automatic pipelines for ensemble docking, applicable to both small molecules and large peptidic macrocycles alike.
Macrocyclic lead optimisation
Macrocycles are becoming increasingly popular in drug discovery, due to their vast potential against previously “undruggable” targets. But the size…
Challenges and approaches in 3D ligand-based drug design
Ann and Ajay discuss the science behind and applications of the eSim molecular similarity method, a ligand-based drug design approach which considers surface-shape, electrostatics, and directionally sensitive hydrogen-bonding when comparing two molecules.
How to be a great drug discovery chemist
Watch our panel of experts as they discuss tactics to achieve success in your medicinal chemistry projects, experiences they’ve had and advice they would give. Learn about the key challenges today’s drug hunter needs to overcome, the skills it takes to gain success across pharma and biotech, and what the future may hold for this industry.
Imputation of sensory properties using deep learning: webinar
In this webinar, we demonstrate how Augmented Chemistry®, a unique deep learning method, can learn from higher throughput data together with limited panel data to provide high-quality imputations for sensory properties.
