Abstract We explore a “best-of-both” approach to modelling molecular properties by combining learned molecular descriptors from a graph neural network…
Summary This article discusses Quantitative Structure – Activity relationships (QSAR) methods to predict absorption, distribution, metabolism, excretion and toxicity (ADMET)…
In this multi-parameter optimisation review, we survey the range of methods used for MPO in drug discovery, compare their strengths…
Summary The main use of ADMET models, whether in silico or in vitro,tends to be molecule ‘profiling’; identifying compounds which are expected to…
In this article, Olga describes how we extend the application of Gaussian Processes technique to classification problems. These computational techniques…
Summary In this study, our researchers combined an automatic model generation process for building QSAR models with the Gaussian Processes…
Summary In this study, the researchers look to solve classification quantitative structure−activity relationship (QSAR) modelling problems using Gaussian processes. They…
Summary This article explores the psychological barriers and risks of cognitive biases to R&D decision-making. It contrasts current practice with…
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.
Summary This article on applying med chem transformations and multi-parameter optimisation describes the concepts and algorithms underlying StarDrop’s Nova module. We’ve developed…
This article discusses logic fallacies in the context of off-target predictive modelling.
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.”
Summary There are many different definitions of ‘drug-like’, with rules proposed based on property trends seen in successful drugs. In…
We introduce a new method for rapid computation of 3D molecular similarity that combines electrostatic field comparison with comparison of molecular surface-shape and directional hydrogen-bonding preferences (called “eSim”).
ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks.
This article describes a novel deep learning neural network method and its application for the imputation of bioactivity data, such…
This paper describes the underlying methods and validation of the WhichP450 model, which predicts the most likely Cytochrome P450 isoforms…
We introduce the ForceGen method for 3D structure generation and conformer elaboration of drug-like small molecules.
This paper, co-authored with our colleagues at NextMove Software, explores applications of Matched Series Analysis within StarDrop’s Nova module to…
