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When global and local molecular descriptors are more than the sum of its parts: Simple, But Not Simpler?

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Abstract

In this report, we introduce a set of aggregation operators (AOs) to calculate global and local (group and atom type) molecular descriptors (MDs) as a generalization of the classical approach of molecular encoding using the sum of the atomic (or fragment) contributions. These AOs are implemented in a new and free software denominated MD-LOVIs (http://tomocomd.com/md-lovis), which allows for the calculation of MDs from atomic weights vector and LOVIs (local vertex invariants). This software was developed in Java programming language and employed the Chemical Development Kit (CDK) library for handling chemical structures and the calculation of atomic weights. An analysis of the complexities of the algorithms presented herein demonstrates that these aspects were efficiently implemented. The calculation speed experiments show that the MD-LOVIs software has satisfactory behavior when compared to software such as Padel, CDKDescriptor, DRAGON and Bluecal software. Shannon’s entropy (SE)-based variability studies demonstrate that MD-LOVIs yields indices with greater information content when compared to those of popular academic and commercial software. A principal component analysis reveals that our approach captures chemical information orthogonal to that codified by the DRAGON, Padel and Mold2 software, as a result of the several generalizations in MD-LOVIs not used in other programs. Lastly, three QSARs were built using multiple linear regression with genetic algorithms, and the statistical parameters of these models demonstrate that the MD-LOVIs indices obtained with AOs yield better performance than those obtained when the summation operator is used exclusively. Moreover, it is also revealed that the MD-LOVIs indices yield models with comparable to superior performance when compared to other QSAR methodologies reported in the literature, despite their simplicity. The studies performed herein collectively demonstrated that MD-LOVIs software generates indices as simple as possible, but not simpler and that use of AOs enhances the diversity of the chemical information codified, which consequently improves the performance of traditional MDs.

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Availability of Software and Material

The MD-LOVIs software and the respective user manual are freely available online at http://tomocomd.com/md-lovis.

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Acknowledgements

Yoan Martínez-López thanks the program International Investigator Invited for a postdoctoral fellowship to work at USFQ in 2019. Yovani Marrero-Ponce acknowledges the support from USFQ “Chancellor Grant 2018 (Project ID13525).”

Funding

This work was partially supported from the USFQ (Project ID13525 “Chancellor Grant 2018”).

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Authors and Affiliations

  1. Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Universidad San Francisco de Quito (USFQ), Av. Interoceánica Km 12 ½ —Cumbayá, 170157, Quito, Ecuador

    Yoan Martínez-López, Yovani Marrero-Ponce, Enrique Teran & Oscar Martínez-Santiago

  2. Grupo de Investigación de Inteligencia Artificial (AIRES), Facultad de Informática, Universidad de Camagüey, Camagüey, Cuba

    Yoan Martínez-López

  3. Department of Computer Sciences, Faculty of Computer Sciences, Camagüey University, 74650, Camagüey City, Camagüey, Cuba

    Yoan Martínez-López & Oscar Martínez-Santiago

  4. Instituto de Simulación Computacional (ISC-USFQ, Universidad San Francisco de Quito (USFQ), Diego de Robles y vía Interoceánica, 17-1200-841, Quito, Ecuador

    Yovani Marrero-Ponce, Cesar H. Zambrano & F. Javier Torres

  5. Departamento de Química Física Aplicada, Facultad de Ciencias, Universidad Autónoma de Madrid (UAM), 28049, Madrid, Spain

    Stephen J. Barigye

  6. ProtoQSAR SL, Centro Europeo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia, 46980, Paterna, Valencia, Spain

    Stephen J. Barigye

  7. Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, 17-1200-841, Quito, Ecuador

    Oscar Martínez-Santiago, Cesar H. Zambrano & F. Javier Torres

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  1. Yoan Martínez-López
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Martínez-López, Y., Marrero-Ponce, Y., Barigye, S.J. et al. When global and local molecular descriptors are more than the sum of its parts: Simple, But Not Simpler?. Mol Divers 24, 913–932 (2020). https://doi.org/10.1007/s11030-019-10002-3

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