Receptor.AI Inc. (“Receptor.AI”), a TechBio company developing AI-driven discovery platforms for molecular design and preclinical drug discovery, and Onepot AI, Inc. (“onepot”), an AI-native automated chemistry company, today announced a strategic collaboration to accelerate the transition from computationally prioritized small molecules to experimentally testable, assay-ready compounds.
The collaboration brings together Receptor.AI’s AI-driven drug discovery capabilities and its REAXENSE™ chemistry enablement platform with onepot’s CORE chemical compound space and automated synthesis infrastructure. Together, the companies aim to address one of the most persistent bottlenecks in small-molecule discovery: converting promising virtual hits into high-quality physical compounds that can be synthesized, tested, and optimized within practical project timelines.
Receptor.AI will access onepot’s CORE chemical compound space, an enumerated collection of 2.7 billion synthesis-ready compounds derived from medicinal-chemistry reaction classes and commercially available building blocks. This will expand Receptor.AI’s ability to identify and prioritize molecules that are not only computationally promising but also readily accessible for rapid experimental validation.
onepot contributes its CORE compounds and automated synthesis platform, providing access to a differentiated, unique library with over 70% Rule-of-Five-compliant molecules and delivery in as little as five business days. By combining these capabilities with Receptor.AI’s AI-guided molecular design and prioritization workflows, the collaboration aims to make selected computational hits more directly actionable for synthesis, testing, and iterative optimization.
As prioritized compounds advance toward experimental validation, Receptor.AI will leverage the REAXENSE™ platform to bridge computational prioritization and synthesis-aware chemistry workflows, enabling a more efficient transition from virtual discovery to assay-ready materials.
Together, Receptor.AI and onepot aim to create a tighter connection between molecular design, compound prioritization, synthesis execution, and experimental feedback. This integrated approach is designed to help pharmaceutical and biotech teams shorten DMTA cycles, reduce friction between in silico discovery and laboratory validation, and move promising small-molecule programs forward with greater speed and confidence.
“The real bottleneck in AI-driven drug discovery is not only finding promising molecules, but deciding which ones are worth making, testing, and optimizing,” said Dr. Alan Nafiiev, Founder and CEO of Receptor.AI. “By connecting Receptor.AI’s AI-driven discovery capabilities and REAXENSE™ chemistry enablement platform with onepot’s CORE chemical space and rapid synthesis infrastructure, we can help partners move faster from virtual hits to assay-ready compounds and make experimental validation more actionable.”
“At onepot, we believe the Make step should move at the speed of modern computational discovery,” said Dr. Daniil Boiko, Co-Founder and CEO of onepot. “The collaboration with Receptor.AI connects AI-guided compound prioritization with the AI-charted part of synthesis-ready chemical space. Together, we can help teams move from molecular ideas to real compounds, assay data, and optimization decisions fast.”
The initial phase will focus on connecting onepot’s CORE chemical compound space with Receptor.AI’s small-molecule discovery workflows, while using REAXENSE™ to support synthesis-aware chemistry coordination and execution planning. Over time, Receptor.AI and onepot expect the partnership to support joint discovery opportunities and broader applications across AI-driven small-molecule drug discovery.
The collaboration addresses a growing need in AI-enabled drug discovery: computational models can generate and prioritize molecules at unprecedented scale, but experimental progress still depends on practical access to compounds that can be synthesized, delivered, tested, and improved.
About Receptor.AI
Receptor.AI is a U.S.-based TechBio company developing adaptive discovery platforms for AI-guided molecular design and preclinical drug discovery. Its technology combines generative AI, structure- and physics-based modeling, multi-objective optimization, and decision engines to help pharmaceutical and biotech partners design, prioritize, and optimize drug candidates across small molecules, peptides, and induced proximity modalities. More information: https://www.receptor.ai/
About onepot
onepot is an AI-native automated chemistry company building infrastructure to accelerate the “Make” step in modern drug discovery. Its platform combines synthesis-ready chemical space, synthesis prediction, route selection, automated execution, purification, and QC to enable rapid access to assay-ready compounds, all guided and executed by AI models and agents. By reducing timelines and increasing confidence in synthetic feasibility, onepot helps discovery teams translate molecular ideas into real compounds faster.
