Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs

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, Biol...

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Main Authors: Michell O. Almeida, Artur C. G. Soares, Gustavo H. M. Sousa, Witor R. Ferraz, Gustavo Trossini
Format: Article
Language:English
Published: Universidade Federal de Mato Grosso do Sul 2024-12-01
Series:Orbital: The Electronic Journal of Chemistry
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Online Access:https://periodicos.ufms.br/index.php/orbital/article/view/21129
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author Michell O. Almeida
Artur C. G. Soares
Gustavo H. M. Sousa
Witor R. Ferraz
Gustavo Trossini
author_facet Michell O. Almeida
Artur C. G. Soares
Gustavo H. M. Sousa
Witor R. Ferraz
Gustavo Trossini
author_sort Michell O. Almeida
collection DOAJ
description 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.
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issn 1984-6428
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publisher Universidade Federal de Mato Grosso do Sul
record_format Article
series Orbital: The Electronic Journal of Chemistry
spelling doaj-art-112a41b4fe4041dea91034b653b4b9282025-08-20T02:36:34ZengUniversidade Federal de Mato Grosso do SulOrbital: The Electronic Journal of Chemistry1984-64282024-12-0116410.17807/orbital.v16i4.21129Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel DrugsMichell O. Almeida0Artur C. G. Soares1Gustavo H. M. Sousa2Witor R. Ferraz3Gustavo Trossini4University of São PauloUniversity of São PauloUniversity of São PauloUniversity of São PauloUniversity of São Paulo 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. https://periodicos.ufms.br/index.php/orbital/article/view/21129Natural Language ProcessingMedicinal ChemistryDrug design and developmentChemoinformaticComputational chemistry
spellingShingle Michell O. Almeida
Artur C. G. Soares
Gustavo H. M. Sousa
Witor R. Ferraz
Gustavo Trossini
Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs
Orbital: The Electronic Journal of Chemistry
Natural Language Processing
Medicinal Chemistry
Drug design and development
Chemoinformatic
Computational chemistry
title Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs
title_full Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs
title_fullStr Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs
title_full_unstemmed Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs
title_short Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs
title_sort investigating the prospects of chatgpt in training medicinal chemists and the development of novel drugs
topic Natural Language Processing
Medicinal Chemistry
Drug design and development
Chemoinformatic
Computational chemistry
url https://periodicos.ufms.br/index.php/orbital/article/view/21129
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