Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process

Michael Ramirez Campos; Diana C. Rodriguez; Alvaro D. Orjuela-Canon

doi:10.1109/colcaci59285.2023.10225875

Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process

Michael Ramirez Campos
, Diana C. Rodriguez
, Alvaro D. Orjuela-Canon

Research output: Chapter in Book/Inform › Conference contribution

Abstract

Tuberculosis is a contagious disease considered as world emergency by the World Health Organization. One of the common prevalent problems are associated to drug-resistant TB, because of unsuccessful treatments of using antibiotics. The use of artificial intelligence algorithms, mainly machine learning (ML) models have allowed to provided more tools for the drug discovery field. For this study, the methodology used was driven to identify new components that may contribute to the inhibition of the inhA protein. Leveraging ML models that learn from data, six regression models were implemented. Best model obtained R2 value of 0.99 and a MSE value of 1.8 e-5.

Translated title of the contribution	Propuesta de compuestos moleculares para la tuberculosis farmacorresistente en el proceso de descubrimiento de fármacos
Original language	English (US)
Title of host publication	2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)
Editors	Alvaro David Orjuela-Canon
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-5
Number of pages	5
ISBN (Electronic)	9798350316599
DOIs	https://doi.org/10.1109/colcaci59285.2023.10225875
State	Published - Jul 26 2023
Event	2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 - Bogota, Colombia Duration: Jul 26 2023 → Jul 28 2023

Publication series

Name	2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)

Conference

Conference	2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023
Country/Territory	Colombia
City	Bogota
Period	7/26/23 → 7/28/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications
Computer Vision and Pattern Recognition
Control and Optimization

Access to Document

10.1109/colcaci59285.2023.10225875

Cite this

Campos, M. R., Rodriguez, D. C., & Orjuela-Canon, A. D. (2023). Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process. In A. D. Orjuela-Canon (Ed.), 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI) (pp. 1-5). (2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/colcaci59285.2023.10225875

Campos, Michael Ramirez ; Rodriguez, Diana C. ; Orjuela-Canon, Alvaro D. / Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process. 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI). editor / Alvaro David Orjuela-Canon. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 1-5 (2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)).

@inproceedings{30e80f8b12664c889639ea6dd5d1c6c8,

title = "Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process",

abstract = "Tuberculosis is a contagious disease considered as world emergency by the World Health Organization. One of the common prevalent problems are associated to drug-resistant TB, because of unsuccessful treatments of using antibiotics. The use of artificial intelligence algorithms, mainly machine learning (ML) models have allowed to provided more tools for the drug discovery field. For this study, the methodology used was driven to identify new components that may contribute to the inhibition of the inhA protein. Leveraging ML models that learn from data, six regression models were implemented. Best model obtained R2 value of 0.99 and a MSE value of 1.8 e-5.",

author = "Campos, \{Michael Ramirez\} and Rodriguez, \{Diana C.\} and Orjuela-Canon, \{Alvaro D.\}",

note = "Funding Information: ACKNOWLEDGMENT Authors acknowledge the support of the Universidad del Rosario for funding this project. In addition, the contribution of research incubator team Semillero en Inteligencia Artificial en Salud: Semill-IAS. Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 ; Conference date: 26-07-2023 Through 28-07-2023",

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doi = "10.1109/colcaci59285.2023.10225875",

language = "English (US)",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--5",

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}

Campos, MR, Rodriguez, DC & Orjuela-Canon, AD 2023, Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process. in AD Orjuela-Canon (ed.), 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI). 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI), Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023, Bogota, Colombia, 7/26/23. https://doi.org/10.1109/colcaci59285.2023.10225875

Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process. / Campos, Michael Ramirez; Rodriguez, Diana C.; Orjuela-Canon, Alvaro D.
2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI). ed. / Alvaro David Orjuela-Canon. Institute of Electrical and Electronics Engineers Inc., 2023. p. 1-5 (2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)).

Research output: Chapter in Book/Inform › Conference contribution

TY - GEN

T1 - Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process

AU - Campos, Michael Ramirez

AU - Rodriguez, Diana C.

AU - Orjuela-Canon, Alvaro D.

N1 - Funding Information: ACKNOWLEDGMENT Authors acknowledge the support of the Universidad del Rosario for funding this project. In addition, the contribution of research incubator team Semillero en Inteligencia Artificial en Salud: Semill-IAS. Publisher Copyright: © 2023 IEEE.

PY - 2023/7/26

Y1 - 2023/7/26

N2 - Tuberculosis is a contagious disease considered as world emergency by the World Health Organization. One of the common prevalent problems are associated to drug-resistant TB, because of unsuccessful treatments of using antibiotics. The use of artificial intelligence algorithms, mainly machine learning (ML) models have allowed to provided more tools for the drug discovery field. For this study, the methodology used was driven to identify new components that may contribute to the inhibition of the inhA protein. Leveraging ML models that learn from data, six regression models were implemented. Best model obtained R2 value of 0.99 and a MSE value of 1.8 e-5.

AB - Tuberculosis is a contagious disease considered as world emergency by the World Health Organization. One of the common prevalent problems are associated to drug-resistant TB, because of unsuccessful treatments of using antibiotics. The use of artificial intelligence algorithms, mainly machine learning (ML) models have allowed to provided more tools for the drug discovery field. For this study, the methodology used was driven to identify new components that may contribute to the inhibition of the inhA protein. Leveraging ML models that learn from data, six regression models were implemented. Best model obtained R2 value of 0.99 and a MSE value of 1.8 e-5.

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M3 - Conference contribution

AN - SCOPUS:85171617479

T3 - 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)

SP - 1

EP - 5

BT - 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)

A2 - Orjuela-Canon, Alvaro David

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023

Y2 - 26 July 2023 through 28 July 2023

ER -

Campos MR, Rodriguez DC , Orjuela-Canon AD. Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process. In Orjuela-Canon AD, editor, 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI). Institute of Electrical and Electronics Engineers Inc. 2023. p. 1-5. (2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)). doi: 10.1109/colcaci59285.2023.10225875

Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

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