As diseases caused by solar radiation have gained great prominence, several methods to prevent them have been developed. Among the most common, the use of sunscreens is customary and accessible. The application of theoretical methods has helped to design new compounds with therapeutic and protective functions. Natural compounds with described photoprotective potential properties (3-O-methylquercetin, gallic acid, aloin, catechin, quercetin, and resveratrol) were selected to perform theoretical studies. Computational methods were applied to predict their absorption spectra, using DFT and TD-DFT methods with functional B3LYP/6−311+g(d,p) basis sets and methanol (IEFPCM) as a solvent. The main electronic transitions of the compounds were evaluated by observing whether the differences in HOMO and LUMO energies that absorb in the UV range are UVA (320–400 nm), UVB (290–320 nm), or UVC (100–290 nm). Experimental validation was carried out for EMC, quercetin, and resveratrol, demonstrating the consistency of the computational method. Results obtained suggest that resveratrol is a candidate for use in sunscreens. The study provided relevant information about the in silico predictive power of natural molecules with the potential for use as photoprotective adjuvants, which may result in fewer time and resource expenditures in the search for photoprotective compounds.

This scientific article delves into the advantages, insights, and limitations of ChatGPT in various scientific domains. Alongside other large language models, this tool exhibits the potential to directly or indirectly assist in a range of scientific areas including Computer Science, Chemistry, Biology/Bioinformatics, and Medicine. Some of the functionalities of ChatGPT include text translation, code improvement, data visualization, and database cleaning. The model can aid in writing and translating scientific articles from mostly any language. In the field of chemoinformatics and computational chemistry, ChatGPT can provide code examples and assist in code development, by evaluating and enhancing code readability and project documentation. Furthermore, it can assist in the database cleaning process and create customized functions for performing specialized tasks. However, ChatGPT does possess some limitations, such as frequent occurrences of artificial hallucinations (a response generated by AI that comprises erroneous or misleading information presented as true), the inability to process multimodal information, and the potential for biases in its training datasets. Therefore, caution must be exercised when incorporating these technologies, considering their social impact and implications for the job market. Acknowledging limitations is crucial when using these tools. With careful and proper use, they can aid the scientific process with the potential to speed up drug discovery.

INTRODUÇÃO: Dor neuropática é classificada como dor causada por lesão ou doença no sistema somatossensorial e acomete de 6,9 a 10% da população mundial e o uso de agonistas do Receptor Canabinóide 2 (CB2R) tem-se mostrado eficaz no tratamento da patologia OBJETIVO: Realizar uma triagem virtual por docagem moléculas a busca de ligantes agonistas do CB2R. MATERIAIS E MÉTODOS: Foi realizada a triagem virtual por docagem molecular de 3968 moléculas nos programas GOLD 2020.3.0® e DockThor 2.0®. As 100 moléculas mais bem classificadas por cada programa foram selecionadas, e as estruturas em que houve consenso passaram por uma análise visual. RESULTADOS: Os programas apresentaram consenso em 22 moléculas, que após a análise visual, verificou-se que 11 compostos apresentaram acordo não só na classificação, mas também de pose, ou seja, na complementaridade com o alvo. CONCLUSÃO: As 11 moléculas selecionadas nesta triagem virtual, sugerem afinidade e, consequentemente, atividade com o receptor CB2, e devem ser estudadas no processo de busca de fármacos para dor neuropática