Accelerating Structural Biology: IntelliFold Now Available on Vecura

What is IntelliFold?

IntelliFold is a controllable foundation model designed for the accurate prediction of 3D atomic structures for proteins, DNA, RNA, and small-molecule ligands. By accepting a unified YAML input, it jointly predicts the coordinates of complex biomolecular systems—including heterogeneous complexes—without requiring task-specific pipelines. It leverages advanced diffusion processes to provide high-quality structural models accompanied by rigorous confidence metrics, such as pLDDT scores, to assess local and global geometric reliability.

It helps users streamline structural biology workflows by integrating diverse biological entities into a single, cohesive prediction pipeline. It is especially useful for researchers studying protein-ligand interactions, multi-chain complexes, or complex assemblies involving nucleic acids who require fast, high-accuracy structural insights.

What can users do with IntelliFold on Vecura?

With IntelliFold on Vecura, users can:

• Predict the 3D structures of complex biomolecular systems from simple YAML configurations.
• Generate structural insights for protein-ligand, protein-nucleic acid, and heteromeric complexes within a unified environment.
• Access confidence metrics like pLDDT, pTM, and ipTM to evaluate the reliability of each predicted structure.
• Utilize multiple model variants, such as the high-speed v2-flash or the high-accuracy v2, to balance computational costs with project requirements.

What the output means

The output provides a comprehensive structural package, including the predicted 3D structure in standard mmCIF or PDB formats and a JSON summary of confidence metrics. The structure_cif file contains atomic-level details, while the summary_confidence data helps identify the most accurate samples among multiple diffusion generations.

This output should be used to support scientific decision making. It does not replace experimental validation.

Why this matters

The ability to accurately predict the structural landscape of heterogeneous biomolecular complexes is a cornerstone of modern drug discovery and systems biology. By eliminating the need for fragmented, task-specific pipelines, IntelliFold enables researchers to transition from sequence information to structural hypothesis generation with unprecedented speed and consistency.

The model's ability to handle protein, nucleic acid, and ligand interactions simultaneously allows for a more holistic understanding of biological pathways, facilitating the identification of potential therapeutic targets and the design of novel molecular interventions.

• Developed by: IntelliGen AI
• Source: IntelliFold GitHub Repository
• Reference: IntelliFold 2 Release Note (bioRxiv)