Predicting regioselectivity of cytosolic SULT metabolism for drugs
This paper describes a model to predict whether a particular site on a molecule will be metabolised by cytosolic sulfotransferase enzymes (SULTs).
Integrated prediction of Phase I and II metabolism
Watch Optibrium CEO Matt Segall and Principal Scientist Mario Öeren as they explore groundbreaking new quantum mechanics and machine learning models which go beyond P450s and provide insights on a broad range of enzymes involved in drug metabolism.
Predicting reactivity to drug metabolism: beyond CYPs
Introduction Predicting sites of metabolism (SoM) enable chemists to be more efficient in optimising the structure of new chemical entities…
Predicting regioselectivity of AO, CYP, FMO and UGT metabolism using quantum mechanical simulations and machine learning
This paper describes the prediction of the regioselectivity of metabolism by AOs, FMOs and UGTs for humans and CYPs for three preclinical species.
Perfecting the use of imperfect QSAR models
In this webinar, we examine the effective use of QSAR modelling in drug discovery and discuss a variety of pain points for medicinal chemists in knowing when a model can be trusted and how to avoid common pitfalls.
Predicting reactivity to drug metabolism: beyond P450s – modelling FMOs and UGTs
Methods for modelling two enzyme families, flavin-containing monoxygenases (FMOs) and uridine 5′-diphospho-glucuronosyltransferases (UGTs), to predict reactivity to drug metabolism.
N- and S-oxidation model of the flavin-containing monooxygenases
Introduction Existing computational models of drug metabolism are heavily focused on predicting oxidation by cytochrome P450 (CYP) enzymes, because of…
WhichP450: a multi-class categorical model
This paper describes the underlying methods and validation of the WhichP450 model, which predicts the most likely Cytochrome P450 isoforms…
Predicting regioselectivity and lability of P450 metabolism
This article describes the underlying methods, validation and example applications of the most recent models of Cytochrome P450 metabolism in…
ADMET property prediction: The state of the art and current challenges
Summary This article discusses Quantitative Structure – Activity relationships (QSAR) methods to predict absorption, distribution, metabolism, excretion and toxicity (ADMET)…
Beyond profiling: using ADMET models to guide decisions
Summary The main use of ADMET models, whether in silico or in vitro,tends to be molecule ‘profiling’; identifying compounds which are expected to…
Optibrium releases powerful metabolism prediction capability in next generation StarDrop software
Backed by six years’ research, the new StarDrop Metabolism module combines quantum mechanics and machine learning to better predict the metabolic fate of drug candidates.
Human volume of distribution models
The volume of distribution (VDss) is an in vivo pharmacokinetic parameter representing the hypothetical volume into which the dose of drug would…
Shen BBB models
Blood-brain barrier (BBB) penetration is a measure of the ratio between the compound concentration in brain and blood. Good BBB…
Models for success: improving drug metabolism prediction
Out now in Drug Target Review, Optibrium’s Director of Computational Chemistry, Dr Peter Hunt discusses why early in silico metabolism prediction is crucial…
Introduction to the Metabolism module
The Metabolism module enables you to accurately predict the major metabolic routes, sites, products and lability of Phase I and…
Optibrium launches a metabolism prediction software platform tailored to DMPK scientists
Semeta™ offers high sensitivity and superior precision for the prediction of Phase I and II metabolic routes, sites, products and liabilities in early drug discovery
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…