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Authors: T. Worakul, M. Azzouzi, M. D. Wodrich, C. Corminboeuf
Description: A unified framework for 3D molecular generative models (de novo, property-directed, structure-guided, shape-, pocket-, fragment- and pharmacophore-conditioned design) covering data preparation, training, guided generation and evaluation behind one CLI.
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Authors: T. Worakul, O. Hernandez-Cuellar, C. Corminboeuf
Description: A locally deployed, no-code browser platform built on MolCraftDiffusion for running generation and training, curating datasets, and exploring structure–property relationships.
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Authors: LCMD
Description: A hub collecting LCMD tools and databases for digital catalyst optimization and discovery, including:
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Authors: R. Laplaza, S. Gallarati, C. Corminboeuf
Description: A flexible, pure-Python genetic algorithm for catalyst optimization over SMILES, SELFIES or 3D structures.
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Authors: R. Laplaza, S. Das, M. D. Wodrich, C. Corminboeuf
Description: Automatically builds molecular volcano plots and activity maps for homogeneous catalysis from reaction energy profiles.
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Authors: T. Worakul, R. Laplaza, S. Das, M. D. Wodrich, C. Corminboeuf
Description: Performs microkinetic modeling of homogeneous catalytic reactions from energy data and builds microkinetic volcano plots and activity/selectivity maps.
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Authors: A. A. Schoepfer, R. Laplaza, J. Waser, C. Corminboeuf
Description: Tools for the development, diagnosis and visualization of multivariate linear regression models for chemical applications.
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Authors: T. Worakul, C. Corminboeuf
Description: Describe a molecular-design goal in plain language; specialist LLM agents plan, configure, execute and analyse generative runs through MCP tools, keeping a traceable ledger from scientific intent to candidate molecules.
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Authors: O. Hernandez-Cuellar, Y. Cho, R. Laplaza, L. O. Marsh, S. Vela, C. Corminboeuf
Description: A tool to interpret crystallographic data and retrieve the connectivity, total charge, and spin of molecular complexes and their components including the oxidation state (OS) of metal atoms and the charge of ligands.
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Authors: K. R. Briling, O. Hernandez-Cuellar, J. W. Abbott, M. Ceriotti, C. Corminboeuf
Description: This tool predicts the electronic density of molecules using a symmetry-adapted Gaussian process regression model.
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