Photoactive Molecular Systems and Antimicrobial Resistance

Research Overview

The growing challenge of antimicrobial resistance (AMR) motivates the development of therapeutic strategies that operate through mechanisms distinct from conventional antibiotics.

Photoactive molecular systems are particularly attractive in this context because light provides spatial and temporal control over molecular activation and can trigger multiple cytotoxic pathways through the generation of reactive excited states, reactive oxygen species, or therapeutic small molecules.

My previous research on Re(I)-based photochemically CO-releasing molecules (PhotoCORMs) provides the foundation for developing this direction towards computationally designed, multimodal photoactive molecular therapeutics.

Mechanism of Light-Induced CO Release

My work on Re(I) tricarbonyl PhotoCORMs has focused first on understanding the fundamental mechanism of light-induced CO release .

Using electronic-structure calculations and reaction-pathway analysis, I investigated the evolution of the photoexcited complex from metal-to-ligand charge-transfer states towards metal-centred states responsible for ligand dissociation.

These studies showed that CO photorelease cannot be described by a simple transition from an emissive state to a single dissociative state. Instead, the reaction proceeds across a complex excited-state potential-energy landscape involving multiple metal-centred states and selective dissociation of the axial CO ligand (ChemRxiv 2024, DOI: 10.26434/chemrxiv-2024-p132r) .

This mechanistic picture provides a basis for understanding how molecular structure controls photochemical reactivity and why not every metal-centred excited state is necessarily dissociative.

Molecular Structure and Competing Phototherapeutic Pathways

I subsequently extended this work to connect molecular structure with competing phototherapeutic pathways .

In visible-light-absorbing Re(I) PhotoCORMs, we investigated how ligand isomerism changes absorption, emission, CO photorelease, and singlet-oxygen generation.

The results demonstrated that relatively subtle structural modifications can strongly alter both spectroscopy and photochemistry (Spectrochim. Acta A 2026, 344, 126647) .

Importantly, molecular features favouring efficient CO release do not necessarily maximise singlet-oxygen production. This reveals a multi-objective design problem in which absorption wavelength, excited-state lifetime, photoproduct formation, and reactive oxygen-species generation must be optimised together.

Multimodal Photoactive Molecules

Building on these results, my future research will investigate multimodal photoactive molecules for antimicrobial applications .

A central objective will be to understand and control the competition between CO release, singlet-oxygen generation, electron transfer, and non-radiative relaxation following photoexcitation.

Rather than considering these processes independently, I will map the complete excited-state landscape connecting photon absorption to the formation of chemically active species.

Particular emphasis will be placed on shifting activation towards the visible and longer-wavelength regions while maintaining favourable photochemical efficiency and molecular stability.

Non-Adiabatic Excited-State Dynamics

Static electronic-structure calculations will be complemented by non-adiabatic excited-state dynamics to determine how population moves between charge-transfer, metal-centred, and ligand-centred states.

These simulations will investigate how excited-state dynamics determine the branching between fluorescence, intersystem crossing, CO dissociation, electron transfer, and reactive oxygen-species formation.

This dynamical perspective is important because experimentally observed photochemical outcomes are controlled not only by the energies of individual excited states but also by how rapidly molecular population moves between them.

Molecular Environment and Biological Conditions

Environmental effects—including solvent, hydrogen bonding, electrostatic interactions, and interactions with model biological environments—will be incorporated to understand how photochemical behaviour changes under conditions relevant to application.

These effects may modify absorption energies, excited-state ordering, charge-transfer character, reaction barriers, and the relative probabilities of CO release and reactive oxygen-species generation.

Connecting molecular-level calculations with realistic environments will therefore be essential for translating fundamental photochemistry into useful molecular design principles.

Data-Driven Discovery of Photoactive Therapeutic Molecules

A further objective will be to move from understanding individual complexes to the data-driven discovery of photoactive therapeutic molecules .

Automated high-throughput quantum-chemical calculations will generate datasets containing absorption energies, excited-state characters, redox properties, CO-release energetics, and descriptors related to singlet-oxygen formation.

Machine-learning and active-learning approaches will then be used to identify structural modifications controlling these competing properties and to explore larger chemical spaces more efficiently.

Multi-objective optimisation will be particularly important for identifying molecules that combine long-wavelength activation, efficient formation of therapeutic species, selectivity, and photochemical stability.

Computational Framework

• Ground- and excited-state density-functional theory
• Multireference electronic-structure calculations
• Excited-state potential-energy surfaces
• Reaction-pathway and transition-state analysis
• Spin–orbit coupling and intersystem crossing
• Non-adiabatic molecular dynamics
• Solvent and environmental modelling
• Automated high-throughput calculations
• Active learning and machine learning
• Multi-objective molecular optimisation

Principal Research Objectives

Experimental Collaboration

In the longer term, computationally identified candidates will be investigated in collaboration with synthetic, spectroscopic, and biological research groups.

This collaborative framework will connect molecular-level predictions with experimentally measured absorption, photoreactivity, reactive-species generation, molecular stability, and antimicrobial activity.

Iterative comparison between computation and experiment will also improve the accuracy of predictive models and identify limitations in the underlying theoretical descriptions.

Long-Term Research Vision

The long-term goal is to establish a predictive framework in which excited-state chemistry, molecular dynamics, and machine learning enable the rational design of light-activated molecules with controllable and potentially complementary modes of action.