PhoreGen is a pharmacophore-oriented 3D molecular generation framework designed to generate entire 3D molecules that are precisely aligned with a given pharmacophore model. It employs asynchronous perturbations and simultaneously updates on both atomic and bond information, coupled with a message-passing mechanism that incoporates prior knowledge of ligand-pharmacophore mapping during the diffusion-denoising process. By hierarchical learning on a large number of ligand-pharmacophore pairs derived from 3D ligands, complex structures, and docking-produced potential binding modes, PhoreGen can generate chemically and energetically reasonable 3D molecules well-aligned with the pharmacophore constraints, while maintaining structural diversity, drug-likeness, and potentially high binding affinity. Notably, it excels in generating feature-customized molecules, e.g. with covalent groups and metal-binding motifs, at high frequency, demonstrating its unparalleled ability and practicality even for challenging drug design scenarios.
Explore more about PhoreGen, including its source code, training datasets, and application details on [PhoreGen] (https://github.com/ppjian19/PhoreGen).
Here shows the process of PhoreGen generating an entire 3D molecule under the pharmacophore constraint.
Here shows an example of PhoreGen generating new molecules for metallo- and serine-β-lactamases.
We sincerely are open to receiving support and advice from academic and industrial communities to improve PhoreGen's usefulness, please email us: ddtmlab_gbl@sina.com.
We here provide a user-friendly web server for this purpose.
Please visit https://ancphore.ddtmlab.org/Modeling
Peng, J.; Yu, J.; Yang, Z.; Chen, Y.; Wei, S.; Meng, F.; Wang, Y.; Huang, X.; Li, G.-B*. Pharmacophore-Oriented 3D Molecular Generation towards Efficient Feature-Customized Drug Discovery (in submission)
*Correspondence: liguobo@scu.edu.cn