/tools/QSAR-activity-cliff-experiments

QSAR-activity-cliff-experiments

MarkusFerdinandDablander/QSAR-activity-cliff-experiments

22 stars7 forksJupyter NotebookWebsiteAdded February 4, 2026
summary

This repository explores QSAR models for predicting activity cliffs in small-molecule inhibitors, providing datasets and methodologies for molecular property prediction. It includes clean data for various targets and allows for the reproduction of experiments related to binding affinity and activity classification.

description

Exploring QSAR Models for Activity-Cliff Prediction

topics

deep-learningextended-connectivity-fingerprintsgraph-neural-networksmachine-learningmolecular-property-predictionmolecular-representationqsar-modelsactivity-cliff-predictionactivity-cliffsbinding-affinity-predictionphysicochemical-descriptorsgraph-isomorphism-networkscircular-fingerprintsmorgan-fingerprintsk-nearest-neighboursmultilayer-perceptronsrandom-forestssupervised-machine-learning

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