Pishchalnikov Roman Y, Chesalin Denis D, Kurkov Vasiliy A, Shkirina Uliana A, Laptinskaya Polina K, Novikov Vasiliy S, Kuznetsov Sergey M, Razjivin Andrei P, Moskovskiy Maksim N, Dorokhov Alexey S, Izmailov Andrey Yu, Gudkov Sergey V
Prokhorov General Physics Institute of the Russian Academy of Sciences, 119991 Moscow, Russia.
Belozersky Research Institute of Physico-Chemical Biology, Moscow State University, 119992 Moscow, Russia.
Plants (Basel). 2023 Dec 15;12(24):4178. doi: 10.3390/plants12244178.
The possibility of pigment detection and recognition in different environments such as solvents or proteins is a challenging, and at the same time demanding, task. It may be needed in very different situations: from the nondestructive in situ identification of pigments in paintings to the early detection of fungal infection in major agro-industrial crops and products. So, we propose a prototype method, the key feature of which is a procedure analyzing the lineshape of a spectrum. The shape of the absorption spectrum corresponding to this transition strongly depends on the immediate environment of a pigment and can serve as a marker to detect the presence of a particular pigment molecule in a sample. Considering carotenoids as an object of study, we demonstrate that the combined operation of the differential evolution algorithm and semiclassical quantum modeling of the optical response based on a generalized spectral density (the number of vibronic modes is arbitrary) allows us to distinguish quantum models of the pigment for different solvents. Moreover, it is determined that to predict the optical properties of monomeric pigments in protein, it is necessary to create a database containing, for each pigment, in addition to the absorption spectra measured in a predefined set of solvents, the parameters of the quantum model found using differential evolution.
在不同环境（如溶剂或蛋白质）中进行色素检测和识别是一项具有挑战性且要求颇高的任务。在诸多不同情形下都可能需要进行此项工作：从对绘画中色素进行非破坏性原位鉴定到对主要农业工业作物及产品中的真菌感染进行早期检测。因此，我们提出了一种原型方法，其关键特性是一个分析光谱线形的程序。对应此跃迁的吸收光谱形状强烈依赖于色素的直接环境，并且可作为检测样品中特定色素分子存在的一个标记。以类胡萝卜素作为研究对象，我们证明了差分进化算法与基于广义光谱密度（振动电子模式数量任意）的光学响应半经典量子建模的联合操作，使我们能够区分色素在不同溶剂中的量子模型。此外，已确定要预测蛋白质中单体色素的光学性质，有必要创建一个数据库，对于每种色素，除了在预定义的一组溶剂中测量的吸收光谱外，还应包含使用差分进化找到的量子模型参数。
