AI-Enabled Synthesis Planning
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THRUST 1

Thrust 1 is developing an AI-enabled synthesis planning tool for molecule discovery and manufacturing that will be a component of AlphaSynthesis, a platform of new AI to solve chemistry problems. This new synthesis planning tool uses AI to identify the most effective and automatable synthetic routes to explore both chemical and biological catalysts for the manufacture and discovery of new molecules. The unique features include the following firsts:

  • synthesis framework, preferentially utilizing highly versatile building blocks and coupling reactions to maximize the efficiency, practicality and ease of small molecule making;
  • AI-driven synthesis design operable in both forward and reverse modes, to enable discovery and manufacturing goals, respectively;
  • integrating both chemical and biological catalysts;
  • driven by a dynamic database of chemical and biological catalytic reactions, the content of which will be continuously optimized via AI-guided automated experimentation;
  • building a chemical information knowledge base and database with efficient querying and search inferences for chemical and biological catalytic reactions.
The databases and knowledge bases curated from multi-modal datasets and literature will be utilized by tools in the AlphaSynthesis platform for application problems in the other three Thrusts.

CURRENT PROJECTS

Multimodal Molecular Structure, Natural Language, Reaction Knowledge Representation, and Knowledge Base Construction
Create a dynamic, searchable database and knowledge base(s) for chemical information
Leveraging NCSA Supercomputing Resources to Develop a MMLI Database
Transition cyberinfrastructure to production, providing an expanding user base with real-time, self-serve access to datasets and compute resources
Developing an Integrated Synthesis Planning Tool for Retrosynthesis and Retrobiosynthesis
Combine chemical and enzymatic reactions in predicted synthesis routes
AI-Driven Biosynthesis Planning
Develop an integrated pathway design tool that captures novel enzymes, thermodynamic considerations, and enzyme redesign
Molecular Lego Kit Maker
Create a highly optimized algorithm that can be applied to a wide range of different molecular functions

LEAD RESEARCHERS

Peng_0
Jian Peng
Associate Professor
Burke_0
Martin D. Burke
Thrust 3 Leader
Denmark_1
Scott E. Denmark
Thrust 2 Leader
Han_0
Jiawei Han
Professor; Executive Committee
Ji
Heng Ji
Thrust 1 Leader
Maranas
Costas D. Maranas
Professor; Executive Committee
McHenry
Kenton McHenry
Associate Director for Software, NCSA
Sinha_0
Saurabh Sinha
Professor
Zanibbi
Richard Zanibbi
Professor
Zhao
Huimin Zhao
Director; Executive Committee
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