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Prediction of activity cliffs on the basis of images using convolutional neural networks.

Published in Journal of computer-aided molecular design

An activity cliff (AC) is formed by a pair of structurally similar compounds with a large difference in potency. Accordingly, ACs reveal structure-activity relationship (SAR) discontinuity and provide SAR information for compound optimization. Herein, we have investigated the question if ACs could be predicted from image data. Therefore, pairs of s...

Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking

Published in Journal of Computer-Aided Molecular Design

Screening already approved drugs for activity against a novel pathogen can be an important part of global rapid-response strategies in pandemics. Such high-throughput repurposing screens have already identified several existing drugs with potential to combat SARS-CoV-2. However, moving these hits forward for possible development into drugs specific...

Best practices for repurposing studies

Published in Journal of Computer-Aided Molecular Design

On the NS-DSSB unidirectional estimates in the SAMPL6 SAMPLing challenge

Published in Journal of Computer-Aided Molecular Design

In the context of the recent SAMPL6 SAMPLing challenge (Rizzi et al. 2020 in J Comput Aided Mol Des 34:601–633) aimed at assessing convergence properties and reproducibility of molecular dynamics binding free energy methodologies, we propose a simple explanation of the severe errors observed in the nonequilibrium switch double-system-single-box (NS...

Ligand binding: evaluating the contribution of the water molecules network using the Fragment Molecular Orbital method.

Published in Journal of computer-aided molecular design

Water molecules play a crucial role in protein-ligand binding, and many tools exist that aim to predict the position and relative energies of these important, but challenging participants of biomolecular recognition. The available tools are, in general, capable of predicting the location of water molecules. However, predicting the effects of their ...

Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.

Published in Journal of computer-aided molecular design

Accurate prediction of lipophilicity-logP-based on molecular structures is a well-established field. Predictions of logP are often used to drive forward drug discovery projects. Driven by the SAMPL7 challenge, in this manuscript we describe the steps that were taken to construct a novel machine learning model that can predict and generalize well. T...

SAMPL7 physical property prediction from EC-RISM theory

Published in Journal of Computer-Aided Molecular Design

Inspired by the successful application of the embedded cluster reference interaction site model (EC-RISM), a combination of quantum–mechanical calculations with three-dimensional RISM theory to predict Gibbs energies of species in solution within the SAMPL6.1 (acidity constants, p K a) and SAMPL6.2 (octanol–water partition coefficients, log P ) the...

Energy–entropy method using multiscale cell correlation to calculate binding free energies in the SAMPL8 host–guest chal...

Published in Journal of Computer-Aided Molecular Design

Free energy drives a wide range of molecular processes such as solvation, binding, chemical reactions and conformational change. Given the central importance of binding, a wide range of methods exist to calculate it, whether based on scoring functions, machine-learning, classical or electronic structure methods, alchemy, or explicit evaluation of e...

Multiple linear regression models for predicting the n ‑octanol/water partition coefficients in the SAMPL7 blind challen...

Published in Journal of Computer-Aided Molecular Design

A multiple linear regression model called MLR-3 is used for predicting the experimental n -octanol/water partition coefficient (log P N) of 22 N -sulfonamides proposed by the organizers of the SAMPL7 blind challenge. The MLR-3 method was trained with 82 molecules including drug-like sulfonamides and small organic molecules, which resembled the main...