Coupled fragment-based generative modeling with stochastic interpolants

Digital Discovery 2026 Open access

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Authors: Tuan Le, Yanfei Guan, Djork-Arné Clevert, Kristof Sch utt
DOI: 10.1039/d5dd00535c
Cited by: 1
References: 35

Abstract

Fragment-based generative model using stochastic interpolants for structure-based drug design. Explicit conditional training outperforms inpainting (87% vs. 25%). PLK3 kinase validation confirms diverse fragment generation with key interactions.

Fields of Study & Subjects

Computational Drug Discovery Methods Protein Structure and Dynamics Microbial Natural Products and Biosynthesis

Publication details

Journal / source
Digital Discovery
Publisher
Royal Society of Chemistry (RSC)
Volume
5
Issue
4
Pages
1600–1612
Publication date
1 January 2026
Language
EN