Chemical Science

Edge Article Multi-objective active machine learning rapidly improves structure–activity models and reveals new protein–protein interaction inhibitors Open Access    Send PDF to Kindle Request Permissions This content is free, please choose one of the three options provided in the Log in section to gain access. Please choose one of the options provided in the log in section to gain access to this content: Active machine learning puts artificial intelligence in charge of a sequential, feedback-driven discovery process. We present the application of a multi-objective active learning scheme for identifying small molecules that inhibit the protein–protein interaction between the anti-cancer target CXC chemokine receptor 4 (CXCR4) and its endogenous ligand CXCL-12 (SDF-1). Experimental design by active learning was used to retrieve informative active compounds that continuously improved the adaptive structure–activity model.…

Link to Full Article: Chemical Science

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