LigandDiff: de Novo Ligand Design for 3D Transition Metal Complexes with Diffusion Models

Abstract

Transition metal complexes are a class of compounds with varied and versatile properties, making them of great technological importance. Their applications cover a wide range of fields, either as metallodrugs in medicine or as materials, catalysts, batteries, solar cells, etc. The demand for the novel design of transition metal complexes with new properties remains of great interest. However, the traditional high-throughput screening approach is inherently expensive and laborious since it depends on human expertise. Here, we present LigandDiff, a generative model for the de novo design of novel transition metal complexes. Unlike the existing methods that simply extract and combine ligands with the metal to get new complexes, LigandDiff aims at designing configurationally novel ligands from scratch, which opens new pathways for the discovery of organometallic complexes. Moreover, it overcomes the limitations of current methods, where the diversity of new complexes highly relies on the diversity of available ligands, while LigandDiff can design numerous novel ligands without human intervention. Our results indicate that LigandDiff designs unique and novel ligands under different contexts, and these generated ligands are synthetically accessible. Moreover, LigandDiff shows good transferability by generating successful ligands for any transition metal complex.

Simulating Metal-Imidazole Complexes

“…However, reproducing metal ions’ structural features and thermodynamic properties in water or protein systems is still challenging for these methods under the prerequisite of maintaining a low computational cost and being physically meaningful. Apart from the accurate machine learning models, − some commonly used physically meaningful force field models include but are not limited to bonded models, nonbonded models, Drude oscillators models, , cationic dummy atom (CDA) and CDA pol models, , and the ReaxFF model …”