pregHosh/MolCraftDiffusion
A generative AI framework for 3D molecular generation and data-driven molecular design in computational chemistry.
This tool helps computational chemists, drug designers, and materials scientists create new 3D molecular structures for applications like drug discovery and catalyst design. You provide a dataset of existing molecules, and it generates novel molecules, allowing you to guide the generation toward desired properties (e.g., excitation energy or dipole moment) or explore variations around a starting molecule. The output consists of 3D molecular structures with specified properties.
Available on PyPI.
Use this if you need to generate novel 3D molecular structures with specific chemical properties or explore variations of existing molecules in your computational chemistry research.
Not ideal if you are looking for a simple tool to visualize existing molecules or perform basic molecular dynamics simulations without an interest in generative design.
Stars
13
Forks
2
Language
Python
License
MIT
Category
Last pushed
Mar 07, 2026
Commits (30d)
0
Dependencies
27
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