Quinoline-based hydrazones for biocide detection: Machine learning-aided design of new TBT chemosensors

Abstract

Antifouling compounds are used as paint components to mitigate biofouling on ships and submerged structures. One of the most known and used antifouling compounds is tributyltin (TBT). However, TBT is toxic to aquatic living beings, causing problems such as reduction of growth and imposex. The development of a TBT chemosensor could be of utter relevance in the building of an in-situ TBT monitoring device. Therefore, this work reports the synthesis of five new quinoline-based hydrazones (HZ) and two new quinoline-based thiosemicarbazones (TSC), with synthesis yields from 17 to 83 %. The compounds were tested in the presence of TBT, and some compounds of the group showed colorimetric or fluorimetric changes. The interaction between these compounds and TBT was tested by spectrophotometric or spectrofluorimetric titrations, which allowed to calculate the limit of detection (LOD) for each interaction. The fluorimetric interaction between HZ 4a and TBT was shown to be the most sensitive chemosensory method, with a LOD value of 1.7 µM. A Ridge classifier model was developed to correlate the ability for TBT detection and the modification of the structure of each molecule. The validity of the proposed model was tested by assessing the TBT-sensing ability of the two novel TSC 5a and 5b, which were synthesized after the development of the model. These two compounds also showed colorimetric changes in the presence of TBT, with LODs of 13.8 and 3.1 µM, respectively, in good accordance with the model’s predictions. Further analysis of the model’s decision process provided some insights on the desirable properties of the novel quinoline-derived TBT optical chemosensors.