Speak to a Protein: An Interactive Multimodal Co-Scientist for Protein Analysis

TL;DR

This paper presents 'Speak to a Protein,' an interactive AI system that enables real-time, multimodal protein analysis through dialogue, visualization, and code generation, significantly simplifying complex structural biology tasks.

Contribution

It introduces a novel interactive AI platform that integrates literature, structural data, visualization, and coding to facilitate protein analysis and hypothesis testing.

Findings

Reduces analysis time from question to evidence.

Enables hypothesis generation through integrated multimodal tools.

Accessible via a free online platform.

Abstract

Building a working mental model of a protein typically requires weeks of reading, cross-referencing crystal and predicted structures, and inspecting ligand complexes, an effort that is slow, unevenly accessible, and often requires specialized computational skills. We introduce \emph{Speak to a Protein}, a new capability that turns protein analysis into an interactive, multimodal dialogue with an expert co-scientist. The AI system retrieves and synthesizes relevant literature, structures, and ligand data; grounds answers in a live 3D scene; and can highlight, annotate, manipulate and see the visualization. It also generates and runs code when needed, explaining results in both text and graphics. We demonstrate these capabilities on relevant proteins, posing questions about binding pockets, conformational changes, or structure-activity relationships to test ideas in real-time. \emph{Speak to a Protein} reduces the time from question to evidence, lowers the barrier to advanced structural analysis, and enables hypothesis generation by tightly coupling language, code, and 3D structures. \emph{Speak to a Protein} is freely accessible at https://open.playmolecule.org.