How a researcher uses Codex and ChatGPT to search for new antimicrobial molecules
2026-09-10 · OpenAI
How a Researcher Uses Codex and ChatGPT to Search for New Antimicrobial Molecules
Introduction
In the ongoing battle against global health threats, artificial intelligence is playing an increasingly vital role. The laboratory led by César de la Fuente has demonstrated how advanced AI tools can be applied to biomedical research. Their work focuses on utilizing Codex and ChatGPT to search through extensive genomic data for new antimicrobial molecules, aiming to combat the growing problem of drug-resistant infections.
The Core Challenge: Drug-Resistant Infections
Drug-resistant infections represent one of the most significant challenges facing the medical community today. As pathogens continuously evolve, the efficacy of traditional antibiotics is declining. De la Fuente's lab directly addresses this challenge by seeking to discover entirely new antimicrobial candidates, providing fresh solutions for treating these stubborn infections.
Innovative Tools: The Application of Codex and ChatGPT
The laboratory employs a technology-driven approach, specifically utilizing two powerful artificial intelligence tools: Codex and ChatGPT.
- ChatGPT: As a large language model, ChatGPT can understand and process complex biological texts and concepts, assisting researchers in improving efficiency during literature review and hypothesis generation.
- Codex: As a code generation tool, Codex can help researchers write scripts and programs for bioinformatics analysis, thereby accelerating the processing and mining of massive genomic datasets.
By combining these two tools, the research team can screen potential drug candidates with unprecedented speed and scale. These AI models act as research assistants, capable of processing vast amounts of data that would typically take human teams a significant amount of time to complete.
Broad Search Scope: Living and Extinct Genomes
A notable feature of this research is the breadth of its search scope. The research team not only analyzes the genomes of living organisms but also delves into the genomes of extinct species.
- Living Genomes: These cover various organisms currently living on Earth, providing rich data on modern biodiversity.
- Extinct Genomes: Genetic information from extinct species, obtained through ancient DNA technologies, may contain unique antimicrobial mechanisms that have been lost in modern organisms. Exploring extinct genomes offers a unique opportunity to uncover evolutionary solutions that may no longer be present in the modern biosphere.
This cross-temporal genomic search strategy greatly expands the possibilities for discovering novel antimicrobial molecules.
Research Objective: Finding Antimicrobial Candidates
The ultimate goal of the laboratory is to identify candidate molecules with antimicrobial activity from the vast genomic data mentioned above. These molecules are expected to be developed into new drugs to combat pathogens that have developed resistance to existing antibiotics.
Conclusion
The work of César de la Fuente's lab demonstrates the immense potential of artificial intelligence in the field of drug discovery. By combining the computational power of Codex and ChatGPT with extensive genomic searches (including both living and extinct species), the team is forging an innovative path to solve the global challenge of drug-resistant infections. This research not only accelerates the discovery process of antimicrobial candidates but also provides a valuable paradigm for using AI to solve complex biomedical problems in the future. This innovative approach highlights how large language models and code generators can go beyond traditional software applications to find practical utility in fundamental scientific research.