10 citations · 16 across the 5 of their papers we have counts for
5 papers
Discontinuous Epitope Fragments as Sufficient Target Templates for Efficient Binder Design
Zhenfeng Deng, Ruijie Hou, Ningrui Xie +2
Recent advances in structure-based protein design have accelerated de novo binder generation, yet interfaces on large domains or spanning multiple domains remain challenging due to…
SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling
Andrei Rekesh, Miruna Cretu, Dmytro Shevchuk +6
Synthesizability remains a critical bottleneck in generative molecular design. While recent advances have addressed synthesizability in 2D graphs, extending these constraints to 3D…
Scalable and Cost-Efficient de Novo Template-Based Molecular Generation
Piotr Gaiński, Oussama Boussif, Andrei Rekesh +5
Template-based molecular generation offers a promising avenue for drug design by ensuring generated compounds are synthetically accessible through predefined reaction templates and…
RGFN: Synthesizable Molecular Generation Using GFlowNets
Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk +6
Generative models hold great promise for small molecule discovery, significantly increasing the size of search space compared to traditional in silico screening libraries. However,…
Generative Active Learning for the Search of Small-molecule Protein Binders
Maksym Korablyov, Cheng-Hao Liu, Moksh Jain +31
Despite substantial progress in machine learning for scientific discovery in recent years, truly de novo design of small molecules which exhibit a property of interest remains a si…