arXiv Paper: Vilya-1 Achieves High Geometric Accuracy as All-Atom Foundation Model for Macrocycle Structure Prediction and Design

July 19, 2026

arXiv International

Overview

Vilya-1 has been introduced as a pioneering all-atom foundation model for macrocycle structure prediction and design. This model aims to resolve existing challenges in sampling biologically relevant conformations and predicting developability properties. It demonstrates significantly improved geometric accuracy across diverse macrocycles and small molecules, powerfully supporting generative applications for novel macrocycle design.

In Depth

Key Findings

Vilya-1 has been introduced as a novel all-atom foundation model specifically designed for macrocycle structure prediction and design. This model successfully addresses existing challenges in efficiently sampling biologically relevant conformations and accurately predicting the developability properties of molecules (e.g., solubility, permeability, stability).

Technical / Clinical Details

Macrocycles hold immense potential as drug candidates, catalysts, and materials, yet their flexible structures and complex conformational spaces have made accurate structure prediction and design difficult. Vilya-1 is a foundation model that integrates deep learning with physical principles, meticulously modeling macrocyclic interactions at the all-atom level. The model was evaluated on benchmark datasets of diverse macrocycles and small molecules, demonstrating a significant improvement in geometric accuracy (e.g., RMSE of atomic coordinates) compared to existing state-of-the-art methods. Crucially, its enhanced ability to represent non-covalent interactions like hydrogen bonds and steric hindrance allows for efficient sampling of critical conformations directly relevant to drug developability. Furthermore, Vilya-1 supports generative design applications for creating novel macrocycles, accelerating the process of generating molecules with desired properties. This marks a major leap forward for macrocycle-based drug development in pharmaceutical research.

Background & Context

Macrocycles, due to their unique structural features (cyclic architecture, numerous chiral centers, diverse functional groups), are gaining attention as a new drug modality that bridges the ‘gap’ between traditional small molecule drugs and biologics. However, their synthetic complexity and the difficulty in predicting their structures have hindered their development. The emergence of high-performance foundation models like Vilya-1 promises to resolve this bottleneck, dramatically improving the efficiency of macrocycle drug discovery. This is expected to contribute to the development of new therapies in areas with high unmet medical needs, such as cancer, autoimmune diseases, and infectious diseases.

Source: https://arxiv.org/abs/2607.09002

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