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Vilya-1: An All-Atom Foundation Model for Macrocycle Structure Prediction and Design

Jul 14, 2026

Researchers have developed Vilya-1, a deep learning model that predicts the structures and properties of macrocycles using an all-atom representation. Vilya-1 demonstrates improved geometric accuracy over existing computational methods and supports the generative design of novel macrocycles across diverse chemical classes.

Why it matters: Vilya-1 could significantly accelerate the development of macrocycle-based therapeutics by enabling more accurate and generalizable structure prediction and design.

Full story at: arXiv Machine Learning ↗

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