Research Projects

Understanding the carcinogenic effects of ultraviolet radiation on DNA necessitates a comprehensive investigation into the photophysics and photochemistry of nucleic acid bases. In natural DNA, the Watson-Crick hydrogen bonding between adenine-thymine (A–T) and guanine-cytosine (G–C) pairs stabilizes the double helix. However, people have been expanding the genetic alphabet by introducing unnatural base pairs (UBPs), offering huge potential in biotechnology and genetic engineering. While the photophysical properties of natural bases have been extensively studied, UBPs remain comparatively underexplored. Recent efforts have focused on designing UBPs that can integrate into the DNA duplex with high fidelity. Examples include isoG–isoC and d5SICS–dNaM, developed by the Benner and Romesberg groups, respectively. Unlike natural bases that rely primarily on hydrogen bonding, many UBPs exploit π–π stacking and hydrophobic interactions for pairing. The Ds–Pa pair, comprising 7-(2-thienyl)imidazo[4,5-b]pyridine (Ds) and pyrrole-2-carbaldehyde (Pa), is stabilized via shape complementarity and hydrophobic effects, reducing mispairing and improving fidelity. A crucial factor for the integration of UBPs into biological systems is their photostability under UV exposure. Natural bases have evolved ultrafast non-radiative decay mechanisms, often mediated by conical intersections, to dissipate UV energy and prevent damage. These decay pathways differ between purine and pyrimidine bases—purines (A, G) typically undergo rapid, barrierless relaxation, while pyrimidines (T, C, U) follow slower, multi-step decay due to more complex potential energy surfaces. Sloped CIs promote efficient internal conversion, enhancing photostability, whereas peaked CIs are often associated with photoproduct formation and potential damage. While computational and spectroscopic studies—using TD-DFT, MS-CASPT2, and QM/MM approaches have shed light on UBPs such as d5SICS, dTPT3, many others remain uncharacterized. The presence of triplet states in UBPs adds further complexity and risk of photodamage. Given the importance of excited-state topologies, especially CIs, a systematic classification of UBPs based on their deactivation behavior is essential. This project aims to: (i) classify UBPs into purine-like and pyrimidine-like categories based on their non-radiative decay pathways, (ii) map their excited-state potential energy surfaces, with a focus on identifying and characterizing conical intersections and triplet-state involvement, (iii) develop a machine learning model, trained on quantum chemical descriptors (e.g., excitation energies, CI topologies) and dynamical features (e.g., deactivation time), to predict photostability and deactivation efficiency. The outcome will be a predictive framework for designing photostable UBPs, offering mechanistic insight into excited-state dynamics and enhancing our capacity to engineer synthetic DNA for next-generation biotechnological applications.