Mapping Antibiotic Photocatalytic Transformation and Resistance Risks with a DFT-Informed Machine Learning Workflow.

Journal: Angewandte Chemie (International ed. in English)
Published Date: Jan 20, 2026

Abstract

The photocatalytic degradation of antibiotics is effective but may yield transformation products (TPs) that sustain or amplify ecological risks, including antibiotic resistance gene (ARG) induction. This study developed a predictive framework that couples photocatalytic experiments, high-resolution mass spectrometry, density functional theory (DFT) calculations and machine learning (ML) to assess risks of TPs. Using tetracycline as a model compound, we constructed a reaction network over 120 steps and 9 533 reactions, and trained an ML model to rapidly predict Gibbs free energy changes with DFT accuracy. Automatic transition-state searches were integrated to evaluate kinetic accessibility within the network. The generalizability of this approach was validated with pathways of five different antibiotics involving 545 reactions. Furthermore, a multi-dimensional scoring system was developed that integrates diversity, ecotoxicity, biodegradability, and feasibility (DEBF) to prioritize pathways by both reactivity and sustainability. Several hydroxylated, aminated, and amide-ketone TPs were identified as high-risk species with enhanced ARG-binding potential. By bridging molecular energetics with ecological outcomes, this work offers a generalizable, mechanism-anchored, and risk-aware approach for analyzing photocatalytic transformations and deriving design principles for pollutant degradation that balance efficiency with ecological safety.

Authors

  • Chen-Chen Zhao
    State Key Laboratory of Coordination Chemistry, School of Chemistry, Nanjing University, Nanjing, Jiangsu, 210023, P.R. China.
  • Sihan Xing
    State Key Laboratory of Coordination Chemistry, School of Chemistry, Nanjing University, Nanjing, Jiangsu, 210023, P.R. China.
  • Cheng Fu
    State Key Laboratory of Coordination Chemistry, School of Chemistry, Nanjing University, Nanjing, Jiangsu, 210023, P.R. China.
  • Lifeng Zheng
    State Key Laboratory of Coordination Chemistry, Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Engineering Research Center of Photoresist Materials of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
  • Huaizhu Wang
    School of Advanced Interdisciplinary Studies, Ningxia University, Zhongwei, 755000, China.
  • Zhong Jin
    State Key Laboratory of Coordination Chemistry, School of Chemistry, Nanjing University, Nanjing, Jiangsu, 210023, P.R. China.
  • Shuhua Li
    Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
  • Shujuan Zhang
    College of Agricultural Engineering, Shanxi Agriculture University, Jinzhong 030801, China.
  • Jing Ma
    Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.

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