Optibrium demonstrates accelerated lead optimisation in complex agrochemical development
Optibrium’s QuanSA 3D-QSAR method uses an active learning approach to successfully and more efficiently identify a mimic of a macrocyclic natural product
Enamine screening collection
StarDrop users who have licensed the Surflex eSim3D module can freely download prepared virtual screening collections for use in StarDrop. Enamine’s commercially available screening…
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…
eMolecules screening collection
StarDrop users who have licensed the Surflex eSim3D module can freely download prepared virtual screening collections for use in StarDrop. During preparation, each…
Macrocyclic lead optimisation
Macrocycles are becoming increasingly popular in drug discovery, due to their vast potential against previously “undruggable” targets. But the size…
From UK-2A to florylpicoxamid: active learning to identify a mimic of a macrocyclic natural product
Scaffold replacement as part of an optimisation process that requires maintenance of potency, desirable biodistribution, metabolic stability, and considerations of synthesis at very large scale is a complex challenge.
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.
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…
Optibrium acquires BioPharmics LLC, expanding its 3D drug design and visualisation offering
BioPharmics’ Drs Ajay Jain (CEO) and Ann Cleves (Director of Applied Science) join the Optibrium team as Vice Presidents in the newly-created BioPharmics Division
Complex peptide macrocycle optimisation: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design
Systematic optimisation of large macrocyclic peptide ligands is a serious challenge. Here, we describe an approach for lead optimisation using the PD-1/PD-L1 system as a retrospective example of moving from initial lead compound to clinical candidate.
Unmasking the true identity of rapamycin’s minor conformer
The solution structure of the minor conformer of rapamycin was investigated using a combination of NMR techniques and computational methods
A distributional model of bound ligand conformational strain: from small molecules to large peptidic macrocycles
We show that the distribution of expected global strain energy values is dependent on molecular size in a superlinear manner. The distribution of strain energy follows a rectified normal distribution whose mean and variance are related to conformational complexity.
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…
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. ideo archive.
MPO explorer: sensitivity analysis
In this example, we will use the Sensitivity Analysis tool in StarDrop’s MPO Explorer module to check if the ranking of compounds in a data set is sensitive to any of the criteria or importance values in a scoring profile.
MPO explorer: automatically building a scoring profile with rule induction
In this example we will use the Profile Builder in StarDrop’s MPO Explorer module to derive a multi-parameter scoring profile, based on a CNS data set.
Guided multi-parameter optimisation of 2D and 3D SAR
This SeeSAR and ADME QSAR worked example uses a combination of 2D and 3D methods to understand and optimise a virtual library of Heat Shock Protein 90 (HSP90) inhibitors.
Synergy and complementarity between focused machine learning and physics-based simulation in affinity prediction
We present results on the extent to which physics-based simulation (exemplified by FEP+) and focused machine learning (exemplified by QuanSA) are complementary for ligand affinity prediction.
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.
