ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs
We introduce the ForceGen method for 3D structure generation and conformer elaboration of drug-like small molecules.
We introduce the ForceGen method for 3D structure generation and conformer elaboration of drug-like small molecules.
Surflex-QMOD integrates chemical structure and activity data to produce physically-realistic models for binding affinity prediction.
We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands.
Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk.
We present a hybrid structure-guided strategy that combines molecular similarity, docking, and multiple-instance learning such that information from protein structures can be used to inform models of structure–activity relationships.
This paper demonstrates how the Surflex-PSIM method can help investigate hypotheses around protein function in cases where function cannot be determined by sequence similarity.
Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.”
This article discusses logic fallacies in the context of off-target predictive modelling.
To compare chemical structures, we can look at a number of 2D and 3D characteristics. In this paper, a group of 358 drugs with overlapping pharmacology were assessed for chemical similarity, using a new framework.
Optibrium’s QuanSA 3D-QSAR method uses an active learning approach to successfully and more efficiently identify a mimic of a macrocyclic natural product
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
From the manuscript “DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design”, Miguel García-Ortegón, Sergio Bacallado, et al¹ have developed…
When exploring chemistry space around a known hit or lead, you can use 3D virtual screening to identify new compounds…
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…
Innovative predictive methods support virtual screening and compound design in the absence of 3D structure data.
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…
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StarDrop users who have licensed the Surflex eSim3D module can freely download prepared virtual screening collections for use in StarDrop. eMolecules‘ commercially available screening…