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Cañizares-Carmenate Y, Perera-Sardiña Y, Marrero-Ponce Y, Díaz-Amador R, Torrens F, Castillo-Garit JA. Ligand and structure-based discovery of phosphorus-containing compounds as potential metalloproteinase inhibitors. SAR QSAR Environ Res 2024; 35:219-240. [PMID: 38380444 DOI: 10.1080/1062936x.2024.2314103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/29/2024] [Indexed: 02/22/2024]
Abstract
In this study, a methodology is proposed, combining ligand- and structure-based virtual screening tools, for the identification of phosphorus-containing compounds as inhibitors of zinc metalloproteases. First, we use Dragon molecular descriptors to develop a Linear Discriminant Analysis classification model, which is widely validated according to the OECD principles. This model is simple, robust, stable and has good discriminating power. Furthermore, it has a defined applicability domain and it is used for virtual screening of the DrugBank database. Second, docking experiments are carried out on the identified compounds that showed good binding energies to the enzyme thermolysin. Considering the potential toxicity of phosphorus-containing compounds, their toxicological profile is evaluated according to Protox II. Of the five molecules evaluated, two show carcinogenic and mutagenic potential at small LD50, not recommended as drugs, while three of them are classified as non-toxic, and could constitute a starting point for the development of new vasoactive metalloprotease inhibitor drugs. According to molecular dynamics simulation, two of them show stable interactions with the active site maintaining coordination with the metal. A high agreement is evident between QSAR, docking and molecular dynamics results, demonstrating the potentialities of the combination of these tools.
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Affiliation(s)
- Y Cañizares-Carmenate
- Unit of Computer-Aided Molecular ''Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Departamento de Farmacia, Facultad de Química-Farmacia, Universidad Central ''Marta Abreu" de Las Villas, Santa Clara, Cuba
| | - Y Perera-Sardiña
- Departamento de Ciencias Básicas Biomédicas, Facultad de Ciencias de la Salud, Universidad de Talca, Talca, Chile
| | - Y Marrero-Ponce
- Grupo de Medicina Molecular Y Traslacional (MeM & T), Escuela de Medicina, Universidad San Francisco de Quito, Edificio de Especialidades Médicas, Quito, Ecuador
| | - R Díaz-Amador
- Laboratorio de Bioinformática y Química Computacional, Escuela de Química y Farmacia, Facultad de Medicina, Universidad Católica de Maule, Maule, Chile
| | - F Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, València, Spain
| | - J A Castillo-Garit
- Instituto Universitario de Investigación y Desarrollo Tecnológico (IDT), Universidad Tecnológica Metropolitana, Santiago, Chile
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2
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Sandoval C, Torrens F, Godoy K, Reyes C, Farías J. Application of Quantitative Structure-Activity Relationships in the Prediction of New Compounds with Anti-Leukemic Activity. Int J Mol Sci 2023; 24:12258. [PMID: 37569634 PMCID: PMC10418467 DOI: 10.3390/ijms241512258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/13/2023] Open
Abstract
Leukemia invades the bone marrow progressively and, through unknown mechanisms, outcompetes healthy hematopoiesis. Protein arginine methyltransferases 1 (PRMT1) are found in prokaryotes and eukaryotes cells. They are necessary for a number of biological processes and have been linked to several human diseases, including cancer. Small compounds that target PRMT1 have a significant impact on both functional research and clinical disease treatment. In fact, numerous PRMT1 inhibitors targeting the S-adenosyl-L-methionine binding region have been studied. Through topographical descriptors, quantitative structure-activity relationships (QSAR) were developed in order to identify the most effective PRMT1 inhibitors among 17 compounds. The model built using linear discriminant analysis allows us to accurately classify over 90% of the investigated active substances. Antileukemic activity is predicted using a multilinear regression analysis, and it can account for more than 56% of the variation. Both analyses are validated using an internal "leave some out" test. The developed model could be utilized in future preclinical experiments with novel drugs.
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Affiliation(s)
- Cristian Sandoval
- Escuela de Tecnología Médica, Facultad de Salud, Universidad Santo Tomás, Los Carreras 753, Osorno 5310431, Chile
- Departamento de Ingeniería Química, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Temuco 4811230, Chile
- Departamento de Ciencias Preclínicas, Facultad de Medicina, Universidad de La Frontera, Temuco 4811230, Chile
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, 46071 València, Spain;
| | - Karina Godoy
- Nucleo Científico y Tecnológico en Biorecursos (BIOREN), Universidad de La Frontera, Temuco 4811230, Chile;
| | - Camila Reyes
- Carrera de Tecnología Médica, Facultad de Medicina, Universidad de La Frontera, Temuco 4811230, Chile;
| | - Jorge Farías
- Departamento de Ingeniería Química, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Temuco 4811230, Chile
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Sandoval C, Torrens F, Godoy K, Reyes C, Farías J. Application of Quantitative Structure-Activity Relationships in the Prediction of New Compounds with Anti-Leukemic Activity. Int J Mol Sci 2023; 24:12258. [DOI: https:/doi.org/10.3390/ijms241512258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023] Open
Abstract
Leukemia invades the bone marrow progressively and, through unknown mechanisms, outcompetes healthy hematopoiesis. Protein arginine methyltransferases 1 (PRMT1) are found in prokaryotes and eukaryotes cells. They are necessary for a number of biological processes and have been linked to several human diseases, including cancer. Small compounds that target PRMT1 have a significant impact on both functional research and clinical disease treatment. In fact, numerous PRMT1 inhibitors targeting the S-adenosyl-L-methionine binding region have been studied. Through topographical descriptors, quantitative structure-activity relationships (QSAR) were developed in order to identify the most effective PRMT1 inhibitors among 17 compounds. The model built using linear discriminant analysis allows us to accurately classify over 90% of the investigated active substances. Antileukemic activity is predicted using a multilinear regression analysis, and it can account for more than 56% of the variation. Both analyses are validated using an internal “leave some out” test. The developed model could be utilized in future preclinical experiments with novel drugs.
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Affiliation(s)
- Cristian Sandoval
- Escuela de Tecnología Médica, Facultad de Salud, Universidad Santo Tomás, Los Carreras 753, Osorno 5310431, Chile
- Departamento de Ingeniería Química, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Temuco 4811230, Chile
- Departamento de Ciencias Preclínicas, Facultad de Medicina, Universidad de La Frontera, Temuco 4811230, Chile
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, 46071 València, Spain
| | - Karina Godoy
- Nucleo Científico y Tecnológico en Biorecursos (BIOREN), Universidad de La Frontera, Temuco 4811230, Chile
| | - Camila Reyes
- Carrera de Tecnología Médica, Facultad de Medicina, Universidad de La Frontera, Temuco 4811230, Chile
| | - Jorge Farías
- Departamento de Ingeniería Química, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Temuco 4811230, Chile
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Castillo-Garit JA, Cañizares-Carmenate Y, Pham-The H, Pérez-Doñate V, Torrens F, Pérez-Giménez F. A Review of Computational Approaches Targeting SARS-CoV-2 Main Protease to the Discovery of New Potential Antiviral Compounds. Curr Top Med Chem 2023; 23:3-16. [PMID: 35473544 DOI: 10.2174/2667387816666220426133555] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 03/05/2022] [Accepted: 03/12/2022] [Indexed: 11/22/2022]
Abstract
The new pandemic caused by the coronavirus (SARS-CoV-2) has become the biggest challenge that the world is facing today. It has been creating a devastating global crisis, causing countless deaths and great panic. The search for an effective treatment remains a global challenge owing to controversies related to available vaccines. A great research effort (clinical, experimental, and computational) has emerged in response to this pandemic, and more than 125000 research reports have been published in relation to COVID-19. The majority of them focused on the discovery of novel drug candidates or repurposing of existing drugs through computational approaches that significantly speed up drug discovery. Among the different used targets, the SARS-CoV-2 main protease (Mpro), which plays an essential role in coronavirus replication, has become the preferred target for computational studies. In this review, we examine a representative set of computational studies that use the Mpro as a target for the discovery of small-molecule inhibitors of COVID-19. They will be divided into two main groups, structure-based and ligand-based methods, and each one will be subdivided according to the strategies used in the research. From our point of view, the use of combined strategies could enhance the possibilities of success in the future, permitting to development of more rigorous computational studies in future efforts to combat current and future pandemics.
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Affiliation(s)
- Juan A Castillo-Garit
- Department Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba.,Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Spain
| | - Yudith Cañizares-Carmenate
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Hai Pham-The
- Department of Medicinal Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi, Viet-nam
| | | | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain
| | - Facundo Pérez-Giménez
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Spain
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Resino-Ruiz D, Gonzalez-Madariaga Y, Nieto L, Linares YM, León JOG, Martín AV, Díaz AV, Torrens F, Castillo-Garit JA. Anti-inflammatory Activity: In silico and In vivo of Sapogenins Present in Agave brittoniana subsp. brachypus (Trel.). Antiinflamm Antiallergy Agents Med Chem 2023; 22:42-48. [PMID: 37114792 DOI: 10.2174/1871523022666230419103027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/08/2023] [Accepted: 02/27/2023] [Indexed: 04/29/2023]
Abstract
BACKGROUND Agave brittoniana subsp. brachypus is an endemic plant of Cuba, which contains different steroidal sapogenins with anti-inflammatory effects. This work aims to develop computational models which allow the identification of new chemical compounds with potential anti-inflammatory activity. METHODS The in vivo anti-inflammatory activity was evaluated in two rat models: carrageenaninduced paw edema and cotton pellet-induced granuloma. In each study, we used 30 Sprague Dawley male rats divided into five groups containing six animals. The products isolated and administrated were fraction rich in yuccagenin and sapogenins crude. RESULTS The obtained model, based on a classification tree, showed an accuracy value of 86.97% for the training set. Seven compounds (saponins and sapogenins) were identified as potential antiinflammatory agents in the virtual screening. According to in vivo studies, the yuccagenin-rich fraction was the greater inhibitor of the evaluated product from Agave. CONCLUSION The evaluated metabolites of the Agave brittoniana subsp. Brachypus showed an interesting anti-inflammatory effect.
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Affiliation(s)
- Dayana Resino-Ruiz
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba
| | - Yisel Gonzalez-Madariaga
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba
| | - Leisy Nieto
- Departamento de Farmacia, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Yilka Mena Linares
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba
| | - Jose Orestes Guerra León
- Departamento de Química, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Arlena Vázquez Martín
- Departamento de Química, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Arianna Valido Díaz
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain
| | - Juan A Castillo-Garit
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain
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Cañizares-Carmenate Y, Díaz-Amador R, Mayra M, Tran T, Torrens F, Alberto J. Virtual screening of flavonoids from Jatropha gossypiifolia L. as potential drugs for diabetic complications. Tradit Med Res 2022. [DOI: 10.53388/tmr20220131261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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7
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Cañizares-Carmenate Y, Nam NH, Díaz-Amador R, Thuan NT, Dung PTP, Torrens F, Pham-The H, Perez-Gimenez F, Castillo-Garit JA. Ligand-based discovery of new potential acetylcholinesterase inhibitors for Alzheimer's disease treatment. SAR QSAR Environ Res 2022; 33:49-61. [PMID: 35048766 DOI: 10.1080/1062936x.2022.2025615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/02/2022] [Indexed: 06/14/2023]
Abstract
The enzyme acetylcholinesterase (AChE) is currently a therapeutic target for the treatment of neurodegenerative diseases. These diseases have highly variable causes but irreversible evolutions. Although the treatments are palliative, they help relieve symptoms and allow a better quality of life, so the search for new therapeutic alternatives is the focus of many scientists worldwide. In this study, a QSAR-SVM classification model was developed by using the MATLAB numerical computation system and the molecular descriptors implemented in the Dragon software. The obtained parameters are adequate with accuracy of 88.63% for training set, 81.13% for cross-validation experiment and 81.15% for prediction set. In addition, its application domain was determined to guarantee the reliability of the predictions. Finally, the model was used to predict AChE inhibition by a group of quinazolinones and benzothiadiazine 1,1-dioxides obtained by chemical synthesis, resulting in 14 drug candidates with in silico activity comparable to acetylcholine.
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Affiliation(s)
- Y Cañizares-Carmenate
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Cuba
| | - N-H Nam
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - R Díaz-Amador
- Department of Computer Science, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Cuba
| | - N T Thuan
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - P T P Dung
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - F Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, València, Spain
| | - H Pham-The
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - F Perez-Gimenez
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Valencia, Spain
| | - J A Castillo-Garit
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Valencia, Spain
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, Cuba
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Torrens F, Castellano G. Structure-Activity Relationships of Cytotoxic Lactones as Inhibitors and Mechanisms of Action. Curr Drug Discov Technol 2021; 17:166-182. [PMID: 30621564 DOI: 10.2174/1570163816666190101113434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 11/06/2018] [Accepted: 12/14/2018] [Indexed: 11/22/2022]
Abstract
BACKGROUND Some lactones prevent protein Myb-dependent gene expression. OBJECTIVE The object is to calculate inhibitors of Myb-brought genetic manifestation. METHODS Linear quantitative structure-potency relations result expanded, among sesquiterpene lactones of a variety of macrocycles (pseudoguaianolides, guaianolides, eudesmanolides and germacranolides), to establish which part of the molecule constitutes their pharmacophore, and predict their inhibitory potency on Myb-reliant genetic manifestation, which may result helpful as leads for antileukaemic therapies with a new mechanism of action. RESULTS Several count indices are connected with structure-activity. The α-methylene-γ-lactone ML functional groups increase, whereas OH groups decrease the activity. Hydrophobicity provides to increase cell toxicity. Four counts (ML, number of α, β-unsaturated CO groups, etc.), connected with the number of oxygens, present a positive association, owing to the partial negative charge of oxygen. The s-trans-strans- germacranolide molecule presents maximal potency. The OH groups decrease the potency owing to the positive charge of hydrogen. The numbers of π-systems and atoms, and polarizability increase the potency. Following least squares, every standard error of the coefficients is satisfactory in every expression. The most predictive linear expressions for lactones, pseudoguaianolides and germacranolides are corroborated by leave-group-out cross-validation. Quadratic equations do not make the correlation better. CONCLUSION Likely action mechanisms for lactones are argued with a diversity of functional groups in the lactone annulus, including artemisinin with its uncommon macrocycle characteristic, 1,2,4-trioxane cycle (pharmacophoric peroxide linkage -O1-O2- in endoperoxide ring), which results in the foundation for its sole antimalarial potency.
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Affiliation(s)
- Francisco Torrens
- Institut Universitari de Ciencia Molecular, Universitat de Valencia, Edifici d'Instituts de Paterna, P. O. Box 22085, E-46071 Valencia, Spain
| | - Gloria Castellano
- Departamento de Ciencias Experimentales y Matematicas, Facultad de Veterinaria y Ciencias Experimentales, Universidad Catolica de Valencia San Vicente Martir, Guillem de Castro-94, E-46001 Valencia, Spain
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Cañizares-Carmenate Y, Mena-Ulecia K, MacLeod Carey D, Perera-Sardiña Y, Hernández-Rodríguez EW, Marrero-Ponce Y, Torrens F, Castillo-Garit JA. Machine learning approach to discovery of small molecules with potential inhibitory action against vasoactive metalloproteases. Mol Divers 2021; 26:1383-1397. [PMID: 34216326 DOI: 10.1007/s11030-021-10260-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 06/17/2021] [Indexed: 11/26/2022]
Abstract
With the advancement of combinatorial chemistry and big data, drug repositioning has boomed. In this sense, machine learning and artificial intelligence techniques offer a priori information to identify the most promising candidates. In this study, we combine QSAR and docking methodologies to identify compounds with potential inhibitory activity of vasoactive metalloproteases for the treatment of cardiovascular diseases. To develop this study, we used a database of 191 thermolysin inhibitor compounds, which is the largest as far as we know. First, we use Dragon's molecular descriptors (0-3D) to develop classification models using Bayesian networks (Naive Bayes) and artificial neural networks (Multilayer Perceptron). The obtained models are used for virtual screening of small molecules in the international DrugBank database. Second, docking experiments are carried out for all three enzymes using the Autodock Vina program, to identify possible interactions with the active site of human metalloproteases. As a result, high-performance artificial intelligence QSAR models are obtained for training and prediction sets. These allowed the identification of 18 compounds with potential inhibitory activity and an adequate oral bioavailability profile, which were evaluated using docking. Four of them showed high binding energies for the three enzymes, and we propose them as potential dual ACE/NEP inhibitors for the control of blood pressure. In summary, the in silico strategies used here constitute an important tool for the early identification of new antihypertensive drug candidates, with substantial savings in time and money.
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Affiliation(s)
- Yudith Cañizares-Carmenate
- Unit of Computer-Aided Molecular ''Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Facultad de Química-Farmacia, Universidad Central ''Marta Abreu" de Las Villas, 54830, Santa Clara, Villa Clara, Cuba
| | - Karel Mena-Ulecia
- Departamento de Ciencias Biológicas Y Químicas, Facultad de Recursos Naturales, Universidad Católica de Temuco, Ave. Rudecindo Ortega, 02950, Temuco, Chile
- Núcleo de Investigación en Bioproductos Y Materiales Avanzados (BIOMA), Facultad de Ingeniería, Universidad Católica de Temuco, Ave. Rudecindo Ortega, 02950, Temuco, Chile
| | - Desmond MacLeod Carey
- Facultad de Ingeniería, Inorganic Chemistry and Molecular Materials Center, Instituto de Ciencias Químicas Aplicadas, Universidad Autónoma de Chile, El Llano Subercaseaux, San Miguel, 2801, Santiago, Chile
| | - Yunier Perera-Sardiña
- Laboratorio de Bioinformática Y Química Computacional, Escuela de Química Y Farmacia, Facultad de Medicina, Universidad Católica de Maule, Talca, Chile
| | - Erix W Hernández-Rodríguez
- Laboratorio de Bioinformática Y Química Computacional, Escuela de Química Y Farmacia, Facultad de Medicina, Universidad Católica de Maule, Talca, Chile
| | - Yovani Marrero-Ponce
- Grupo de Medicina Molecular Y Traslacional (MeM & T), Escuela de Medicina, Universidad San Francisco de Quito, Edificio de Especialidades Médicas, Av. Interoceánica Km 12½, Quito, Ecuador
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici D'Instituts de Paterna, P.O. Box 22085, 46071, València, Spain
| | - Juan A Castillo-Garit
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Carretera a Acueducto Y Circunvalación, CP: 50200, Santa Clara, Villa Clara, Cuba.
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Castillo-Garit JA, Barigye SJ, Pham-The H, Pérez-Doñate V, Torrens F, Pérez-Giménez F. Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree. SAR QSAR Environ Res 2021; 32:71-83. [PMID: 33455460 DOI: 10.1080/1062936x.2020.1863857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/10/2020] [Indexed: 06/12/2023]
Abstract
Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation procedure and through a test set, achieving accuracy values over 90.5% and 92.2%, correspondingly. The values of sensitivity and specificity were around 90% in all series; also the false alarm rate values were under 10.5% for all sets. In addition, a simulated ligand-based virtual screening for several compounds recently reported as promising anti-chagasic agents was carried out, yielding good agreement between predictions and experimental results. Finally, the present work constitutes an example of how this rational computer-based method can help reduce the cost and increase the rate in which novel compounds are developed against Chagas disease.
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Affiliation(s)
- J A Castillo-Garit
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara , Villa Clara, Cuba
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València , Valencia, Spain
| | - S J Barigye
- Departamento de Química Física Aplicada, Facultad de Ciencias, Universidad Autónoma de Madrid (UAM) , Madrid, Spain
| | - H Pham-The
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy , Hanoi, Viet-nam
| | - V Pérez-Doñate
- Departamento de Microbiología, Hospital Universitario de la Ribera , Valencia, Spain
| | - F Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna , València, Spain
| | - F Pérez-Giménez
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València , Valencia, Spain
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Cañizares-Carmenate Y, Campos Delgado LE, Torrens F, Castillo-Garit JA. Thorough evaluation of OECD principles in modelling of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine derivatives using QSARINS. SAR QSAR Environ Res 2020; 31:741-759. [PMID: 32892643 DOI: 10.1080/1062936x.2020.1810116] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 08/11/2020] [Indexed: 06/11/2023]
Abstract
The human immunodeficiency virus is a lethal pathology considered as a worldwide problem. The search for new strategies for the treatment of this disease continues to be a great challenge in the scientific community. In this study, a series of 107 derivatives of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine, previously evaluated experimentally against HIV-I reverse transcriptase, was used to model antiretroviral activity. A model of linear regression, implemented in the QSARINS software, was developed with a genetic algorithm for variable selection. The fit of its parameters was good and exhaustive validation, according to the OECD regulatory principles, was performed. Also, the applicability domain was established. In addition, its robustness (r 2 = 0.84), stability (Q 2 LOO = 0.81; Q 2 LMO = 0.80) and good predictive power (r 2 EXT = 0.85) is proved. So, it was used to predict the antiretroviral activity of eight compounds obtained by rational drug design. Finally, it can be affirmed that the proposed tools allow the rapid and economic identification of potential antiretroviral drugs.
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Affiliation(s)
- Y Cañizares-Carmenate
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas , Santa Clara, Cuba
| | - L E Campos Delgado
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas , Santa Clara, Cuba
| | - F Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna , València, Spain
| | - J A Castillo-Garit
- Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara , Santa Clara, Cuba
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Cañizares-Carmenate Y, Alcántara Cárdenas A, Roche Llerena V, Torrens F, Castillo-Garit JA. Computational approach to the discovery of potential neprilysin inhibitors compounds for cardiovascular diseases treatment. Med Chem Res 2020. [DOI: 10.1007/s00044-020-02529-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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Castillo-Garit JA, Flores-Balmaseda N, Álvarez O, Pham-The H, Pérez-Doñate V, Torrens F, Pérez-Giménez F. Computational Identification of Chemical Compounds with Potential Activity against Leishmania amazonensis using Nonlinear Machine Learning Techniques. Curr Top Med Chem 2019; 18:2347-2354. [DOI: 10.2174/1568026619666181130121558] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 10/18/2018] [Accepted: 11/17/2018] [Indexed: 11/22/2022]
Abstract
Leishmaniasis is a poverty-related disease endemic in 98 countries worldwide, with morbidity
and mortality increasing daily. All currently used first-line and second-line drugs for the treatment of
leishmaniasis exhibit several drawbacks including toxicity, high costs and route of administration. Consequently,
the development of new treatments for leishmaniasis is a priority in the field of neglected
tropical diseases. The aim of this work is to develop computational models those allow the identification
of new chemical compounds with potential anti-leishmanial activity. A data set of 116 organic chemicals,
assayed against promastigotes of Leishmania amazonensis, is used to develop the theoretical models.
The cutoff value to consider a compound as active one was IC50≤1.5μM. For this study, we employed
Dragon software to calculate the molecular descriptors and WEKA to obtain machine learning
(ML) models. All ML models showed accuracy values between 82% and 91%, for the training set. The
models developed with k-nearest neighbors and classification trees showed sensitivity values of 97%
and 100%, respectively; while the models developed with artificial neural networks and support vector
machine showed specificity values of 94% and 92%, respectively. In order to validate our models, an
external test-set was evaluated with good behavior for all models. A virtual screening was performed
and 156 compounds were identified as potential anti-leishmanial by all the ML models. This investigation
highlights the merits of ML-based techniques as an alternative to other more traditional methods to
find new chemical compounds with anti-leishmanial activity.
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Affiliation(s)
- Juan Alberto Castillo-Garit
- Unidad de Toxicologia Experimental, Universidad de Ciencias Medicas de Villa Clara, Santa Clara, 50200, Cuba
| | - Naivi Flores-Balmaseda
- CAMD-BIR Unit, Chemistry-Pharmacy Faculty, Universidad Central de Las Villas, Santa Clara, 54830, Cuba
| | - Orlando Álvarez
- CAMD-BIR Unit, Chemistry-Pharmacy Faculty, Universidad Central de Las Villas, Santa Clara, 54830, Cuba
| | - Hai Pham-The
- Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi, Vietnam
| | | | - Francisco Torrens
- Institut Universitari de Ciencia Molecular, Universitat de València, 46071, Valencia, Spain
| | - Facundo Pérez-Giménez
- Unidad de Investigacion de Diseno de Farmacos y Conectividad Molecular, Departamento de Quimica Física, Facultad de Farmacia, Universitat de Valencia, Valencia, Spain
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Castellano G, Redondo L, Torrens F. QSAR of Natural Sesquiterpene Lactones as Inhibitors of Myb-dependent Gene Expression. Curr Top Med Chem 2018; 17:3256-3268. [PMID: 29231144 DOI: 10.2174/1568026618666171211145846] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 11/12/2017] [Accepted: 11/22/2017] [Indexed: 11/22/2022]
Abstract
BACKGROUND Protein c-Myb is a therapeutic target. Some sesquiterpene lactones suppress Myb-dependent gene expression, which results in their potential anti-cancer activity. MATERIAL & METHODS Database ChEMBL is a representative of lactones for physicochemical and physiochemical properties. Data presented for 31 natural lactones are discussed in terms of quantitative structureactivity relationships with the objective to predict inhibitors of Myb-induced gene expression. Several constitutional descriptors are related to structure-activity. α-Methylene-γ-lactone groups enhance while OH functions worsen potency. The latter feature is in agreement with the fact that the more lipophilic the lactone, the greater the cytotoxicity because of the ability to cross lipoidal biomembranes. In general, numbers of π-systems and atoms, and polarizability enhance activity. Linear and nonlinear structure-activity models are developed, between lactones of a great structural diversity, to predict inhibitors of Myb-induced gene expression. Four variables (ML, UNC, TCO+OCOR, UNC+UNA) related to ATOM show a positive correlation because of the partial anionic and H-acceptor characters of O-atom. In most, CO group is conjugated. RESULT AND CONCLUSION Term OH shows negative coefficients because of the partial cationic quality of H-atom and because OH forms H-bonds with CO, causing them to be less H-acceptor. s-trans-s-trans-Germacranolide structure is the most active. Coefficients standard errors result acceptable in almost all equations. After cross-validation, linear equations for lactones, pseudoguaianolides and germacranolides are the most predictive. Most descriptors are constitutional variables.
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Affiliation(s)
- Gloria Castellano
- Departamento de Ciencias Experimentales y Matematicas, Facultad de Veterinaria y Ciencias Experimentales, Universidad Catolica de Valencia San Vicente Martir, Guillem de Castro-94, E-46001 Valencia, Spain
| | - Lucia Redondo
- Departamento de Ciencias Experimentales y Matematicas, Facultad de Veterinaria y Ciencias Experimentales, Universidad Catolica de Valencia San Vicente Martir, Guillem de Castro-94, E-46001 Valencia, Spain
| | - Francisco Torrens
- Institut Universitari de Ciencia Molecular, Universitat de Valencia, Edifici d'Instituts de Paterna, P. O. Box 22085, E-46071 Valencia, Spain
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Redondo-Cuevas L, Castellano G, Torrens F, Raikos V. Revealing the relationship between vegetable oil composition and oxidative stability: A multifactorial approach. J Food Compost Anal 2018. [DOI: 10.1016/j.jfca.2017.12.027] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Martinez-Lopez Y, Caballero Y, Barigye SJ, Marrero-Ponce Y, Millan-Cabrera R, Madera J, Torrens F, Castillo-Garit JA. State of the Art Review and Report of New Tool for Drug Discovery. Curr Top Med Chem 2017; 17:2957-2976. [PMID: 28828995 DOI: 10.2174/1568026617666170821123856] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Revised: 05/30/2017] [Accepted: 05/30/2017] [Indexed: 11/22/2022]
Abstract
BACKGROUND There are a great number of tools that can be used in QSAR/QSPR studies; they are implemented in several programs that are reviewed in this report. The usefulness of new tools can be proved through comparison, with previously published approaches. In order to perform the comparison, the most usual is the use of several benchmark datasets such as DRAGON and Sutherland's datasets. METHODS Here, an exploratory study of Atomic Weighted Vectors (AWVs), a new tool useful for drug discovery using different datasets, is presented. In order to evaluate the performance of the new tool, several statistics and QSAR/QSPR experiments are performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by means of an information theory-based algorithm. RESULTS Principal components analysis is used to analyze the orthogonality of these descriptors, for which the new MDs from AWVs provide different information from those codified by DRAGON descriptors (0-2D). The QSAR models are obtained for every Sutherland's dataset, according to the original division into training/test sets, by means of the multiple linear regression with genetic algorithm (MLR-GA). These models have been validated and compared favorably to several previously published approaches, using the same benchmark datasets. CONCLUSION The obtained results show that this tool should be a useful strategy for the QSAR/QSPR studies, despite its simplicity.
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Affiliation(s)
- Yoan Martinez-Lopez
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatics Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara. Cuba
| | - Yaile Caballero
- Department of Computer Sciences, Faculty of Computer Sciences, Camaguey University, Camaguey city, 74650, Camaguey. Cuba
| | - Stephen J Barigye
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatics Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara. Cuba
| | - Yovani Marrero-Ponce
- Grupo de Medicina Molecular y Traslacional (MEM&T), Universidad San Francisco de Quito. Ecuador
| | - Reisel Millan-Cabrera
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatics Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara. Cuba
| | - Julio Madera
- Department of Computer Sciences, Faculty of Computer Sciences, Camaguey University, Camaguey city, 74650, Camaguey. Cuba
| | - Francisco Torrens
- Institut Universitari de Ciencia Molecular, Universitat de Valencia, E-46071, Valencia. Spain
| | - Juan A Castillo-Garit
- Unidad de Toxicologia Experimental, Universidad de Ciencias Medicas de Villa Clara, Carretera a acueducto y Circunvalacion, Santa Clara, Villa Clara, CP: 50200. Cuba
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Castillo-Garit JA, Casañola-Martin GM, Barigye SJ, Pham-The H, Torrens F, Torreblanca A. Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis. SAR QSAR Environ Res 2017; 28:735-747. [PMID: 29022372 DOI: 10.1080/1062936x.2017.1376705] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 09/01/2017] [Indexed: 06/07/2023]
Abstract
The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector machine, classification trees, and artificial neural networks, have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. They showed global accuracy values between 95.9% and 97.7% and area under Receiver Operator Curve values between 0.978 and 0.998; additionally, false alarm rate values were below 8.2% for training set. In order to validate our models, cross-validation (10-folds-out) and external test-set were performed with good behaviour in all cases. These models, obtained with ML techniques, were compared with others previously reported by other researchers, and the improvement was significant.
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Affiliation(s)
- J A Castillo-Garit
- a Unidad de Toxicología Experimental , Universidad de Ciencias Médicas de Villa Clara , Santa Clara , Villa Clara , Cuba
- b Departament de Biología Funcional i Antropología Física , Universitat de València , Burjassot , Spain
| | - G M Casañola-Martin
- c Departamento de Química Física, Facultad de FarmaciaUnidad de Investigación de Diseño de Fármacos y Conectividad Molecular , Universitat de València , Spain
| | - S J Barigye
- d Department of Chemistry , McGill University , Montréal , Québec , Canada
| | - H Pham-The
- e Hanoi University of Pharmacy , Hoan Kiem, Hanoi , Vietnam
| | - F Torrens
- f Institut Universitari de Ciència Molecular , Universitat de València, Edifici d'Instituts de Paterna , Valencia , Spain
| | - A Torreblanca
- b Departament de Biología Funcional i Antropología Física , Universitat de València , Burjassot , Spain
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Cañizares-Carmenate Y, Hernandez-Morfa M, Torrens F, Castellano G, Castillo-Garit JA. Larvicidal activity prediction against Aedes aegypti mosquito using computational tools. J Vector Borne Dis 2017; 54:164-171. [PMID: 28748838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023] Open
Abstract
BACKGROUND & OBJECTIVES Aedes aegypti is an important vector for transmission of dengue, yellow fever, chikun- gunya, arthritis, and Zika fever. According to the World Health Organization, it is estimated that Ae. aegypti causes 50 million infections and 25,000 deaths per year. Use of larvicidal agents is one of the recommendations of health organizations to control mosquito populations and limit their distribution. The aim of present study was to deduce a mathematical model to predict the larvicidal action of chemical compounds, based on their structure. METHODS A series of different compounds with experimental evidence of larvicidal activity were selected to develop a predictive model, using multiple linear regression and a genetic algorithm for the selection of variables, implemented in the QSARINS software. The model was assessed and validated using the OECDs principles. RESULTS The best model showed good value for the determination coefficient (R2 = 0.752), and others parameters were appropriate for fitting (s = 0.278 and RMSEtr = 0.261). The validation results confirmed that the model hasgood robustness (Q2LOO = 0.682) and stability (R2-Q2LOO = 0.070) with low correlation between the descriptors (KXX = 0.241), an excellent predictive power (R2 ext = 0.834) and was product of a non-random correlation R2 Y-scr = 0.100). INTERPRETATION & CONCLUSION The present model shows better parameters than the models reported earlier in the literature, using the same dataset, indicating that the proposed computational tools are more efficient in identifying novel larvicidal compounds against Ae. aegypti.
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Affiliation(s)
- Yudith Cañizares-Carmenate
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR) Unit, Facultad de Química-Farmacia, Universidad Central "Marta Abreu"
| | - Mirelys Hernandez-Morfa
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR) Unit, Facultad de Química-Farmacia, Universidad Central "Marta Abreu"
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, València, Spain
| | - Gloria Castellano
- Departamento de Ciencias Experimentales y Matemáticas, Facultad de Veterinaria y Ciencias Experimentales, Universidad Católica de Valencia "San Vicente Mártir", Guillem de Castro
| | - Juan A Castillo-Garit
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR) Unit, Facultad de Química-Farmacia, Universidad Central "Marta Abreu"; Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara, Santa Clara, Villa Clara, Cuba
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Marrero-Ponce Y, Castañeda YG, Vivas-Reyes R, Vergara FM, Arán VJ, Castillo-Garit JA, Pérez-Giménez F, Torrens F, Le-Thi-Thu H, Pham-The H, Montenegro YV, Ibarra-Velarde F. Dry selection and wet evaluation for the rational discovery of new anthelmintics. Mol Phys 2017. [DOI: 10.1080/00268976.2017.1296194] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Yovani Marrero-Ponce
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Ecuador
- Universidad San Francisco de Quito (USFQ), Instituto de Simulación Computacional (ISC-USFQ), Diego de Robles y vía Interoceánica, Quito, Ecuador
- Computer-Aided Molecular “Biosilico” Discovery and Bioinformatics Research International Network (CAMD-BIR IN), Quito, Ecuador
- GIA (Grupo de Investigación Ambiental), Fundación Universitaria Tecnológico de Comfenalco, Facultad de Ingenierías, Programa de Ingeniería de Procesos, Cartagena de Indias, Bolívar, Colombia
| | - Yeniel González Castañeda
- Computer-Aided Molecular “Biosilico” Discovery and Bioinformatics Research International Network (CAMD-BIR IN), Quito, Ecuador
| | - Ricardo Vivas-Reyes
- Grupo de Química Cuántica y Teórica, Facultad de Ciencias, Universidad de Cartagena, Cartagena de Indias, Bolívar, Colombia
- Grupo CipTec, Fundación Universitaria Tecnológico de Comfenalco, Facultad de Ingenierías, Programa de Ingeniería Industrial, Cartagena de Indias, Bolívar, Colombia
| | - Fredy Máximo Vergara
- Grupo de Química Cuántica y Teórica, Facultad de Ciencias, Universidad de Cartagena, Cartagena de Indias, Bolívar, Colombia
- Grupo CipTec, Fundación Universitaria Tecnológico de Comfenalco, Facultad de Ingenierías, Programa de Ingeniería Industrial, Cartagena de Indias, Bolívar, Colombia
| | | | - Juan A. Castillo-Garit
- Computer-Aided Molecular “Biosilico” Discovery and Bioinformatics Research International Network (CAMD-BIR IN), Quito, Ecuador
- Unidad de Toxicología Experimental, Universidad de Ciencias Medicas de Villas Clara, Santa Clara, 50200, Cuba
| | - Facundo Pérez-Giménez
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, València, Spain
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, València, Spain
| | - Huong Le-Thi-Thu
- School of Medicine and Pharmacy, Vietnam National University, Hanoi, Vietnam
| | - Hai Pham-The
- Pharmacy Department, Hanoi University of Pharmacy , 13-15 Le Thonh Tong, Hoan Kiem, Hanoi, Vietnam
| | - Yolanda Vera Montenegro
- Department of Parasitology, Faculty of Veterinarian Medicinal and Zootecnic, UNAM, Mexico, Mexico
| | - Froylán Ibarra-Velarde
- Department of Parasitology, Faculty of Veterinarian Medicinal and Zootecnic, UNAM, Mexico, Mexico
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Castillo-Garit J, Abad C, Casañola-Martin G, Barigye S, Torrens F, Torreblanca A. Prediction of Aquatic Toxicity of Benzene Derivatives to Tetrahymena pyriformis According to OECD Principles. Curr Pharm Des 2016; 22:5085-5094. [DOI: 10.2174/1381612822666160804095107] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 08/04/2016] [Indexed: 11/22/2022]
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Martínez-Santiago O, Cabrera R, Marrero-Ponce Y, Barigye S, Le-Thi-Thu H, Torres F, Zambrano C, Yaber-Goenaga I, Cruz-Monteagudo M, López Y, Giménez F, Torrens F. Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative. Curr Pharm Des 2016; 22:5095-5113. [DOI: 10.2174/1381612822666160610114148] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 06/27/2016] [Indexed: 11/22/2022]
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Le-Thi-Thu H, Canizares-Carmenate Y, Marrero-Ponce Y, Torrens F, A. Castillo-Garit J. Prediction of Caco-2 Cell Permeability Using Bilinear Indices and Multiple Linear Regression. LETT DRUG DES DISCOV 2015. [DOI: 10.2174/1570180812666150630183511] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Castellano G, Torrens F. Information entropy-based classification of triterpenoids and steroids from Ganoderma. Phytochemistry 2015; 116:305-313. [PMID: 26024957 DOI: 10.1016/j.phytochem.2015.05.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Revised: 05/11/2015] [Accepted: 05/14/2015] [Indexed: 06/04/2023]
Abstract
A set of 71 triterpenoid and steroid compounds from Ganoderma were periodically classified using a procedure based on information entropy with artificial intelligence. Six features were used in hierarchical order to classify the triterpenoids and steroids structurally. The phytochemicals belonging to the same group in the periodic table present similar antioxidant activity, and those compounds belonging to the same period exhibit maximum resemblance. The periodic classification is related to the experimental bioactivity and antioxidant potency data that are available in the literature: a steroid with a three-ketone group conjugated with two carbon-carbon double bonds in the right side of the periodic table exhibits the greatest antioxidant activity.
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Affiliation(s)
- Gloria Castellano
- Departamento de Ciencias Experimentales y Matemáticas, Facultad de Veterinaria y Ciencias Experimentales, Universidad Católica de Valencia San Vicente Mártir, Guillem de Castro-94, E-46001 València, Spain.
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, P.O. Box 22085, E-46071 València, Spain
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Castellano G, Torrens F. Quantitative Structure-Antioxidant Activity Models of Isoflavonoids: A Theoretical Study. Int J Mol Sci 2015; 16:12891-906. [PMID: 26062128 PMCID: PMC4490477 DOI: 10.3390/ijms160612891] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Revised: 06/01/2015] [Accepted: 06/03/2015] [Indexed: 11/25/2022] Open
Abstract
Seventeen isoflavonoids from isoflavone, isoflavanone and isoflavan classes are selected from Dalbergia parviflora. The ChEMBL database is representative from these molecules, most of which result highly drug-like. Binary rules appear risky for the selection of compounds with high antioxidant capacity in complementary xanthine/xanthine oxidase, ORAC, and DPPH model assays. Isoflavonoid structure-activity analysis shows the most important properties (log P, log D, pKa, QED, PSA, NH + OH ≈ HBD, N + O ≈ HBA). Some descriptors (PSA, HBD) are detected as more important than others (size measure Mw, HBA). Linear and nonlinear models of antioxidant potency are obtained. Weak nonlinear relationships appear between log P, etc. and antioxidant activity. The different capacity trends for the three complementary assays are explained. Isoflavonoids potency depends on the chemical form that determines their solubility. Results from isoflavonoids analysis will be useful for activity prediction of new sets of flavones and to design drugs with antioxidant capacity, which will prove beneficial for health with implications for antiageing therapy.
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Affiliation(s)
- Gloria Castellano
- Departamento de Ciencias Experimentales y Matemáticas, Facultad de Veterinaria y Ciencias Experimentales, Universidad Católica de Valencia San Vicente Mártir, Guillem de Castro-94, E 46001 València, Spain.
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P. O. Box 22085, E 46071 València, Spain.
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Torrens F, Castellano G. Computational Study of Nanosized Drug Delivery from Cyclodextrins, Crown Ethers and Hyaluronan in Pharmaceutical Formulations. Curr Top Med Chem 2015; 15:1901-13. [PMID: 25961520 DOI: 10.2174/1568026615666150506145619] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 03/19/2015] [Accepted: 03/24/2015] [Indexed: 11/22/2022]
Abstract
The problem in this work is the computational characterization of cyclodextrins, crown ethers and hyaluronan (HA) as hosts of inclusion complexes for nanosized drug delivery vehicles in pharmaceutical formulations. The difficulty is addressed through a computational study of some thermodynamic, geometric and topological properties of the hosts. The calculated properties of oligosaccharides of D-glucopyranoses allow these to act as co-solvents of polyanions in water. In crown ethers, the central channel is computed. Mucoadhesive polymer HA in formulations releases drugs in mucosas. Geometric, topological and fractal analyses are carried out with code TOPO. Reference calculations are performed with code GEPOL. From HA to HA·3Ca and hydrate, the hydrophilic solvent-accessible surface varies with the count of H-bonds. The fractal dimension rises. The dimension of external atoms rises resulting 1.725 for HA. It rises going to HA·3Ca and hydrate. Nonburied minus molecular dimension rises and decays. Hydrate globularity is lower than O(water), Ca(2+) and O(HA). Ca(2+) rugosity is smaller than for hydrate, O(HA) and O(water). Ca(2+) and O(water) accessibilities are greater than hydrate. Conclusions are drawn on: (1) the relative stability of linear/cyclic and shorter/larger polymers; (2) the atomic analysis of properties allows determining the atoms with maximum reactivity.
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Affiliation(s)
- Francisco Torrens
- Institut Universitari de Ciencia Molecular, Universitat de Valencia, Edifici d'Instituts de Paterna, P. O. Box 22085, E-46071 Valencia, Spain.
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Castillo-Garit JA, del Toro-Cortés O, Vega MC, Rolón M, Rojas de Arias A, Casañola-Martin GM, Escario JA, Gómez-Barrio A, Marrero-Ponce Y, Torrens F, Abad C. Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening. Eur J Med Chem 2015; 96:238-44. [PMID: 25884114 DOI: 10.1016/j.ejmech.2015.03.063] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Revised: 02/27/2015] [Accepted: 03/27/2015] [Indexed: 11/25/2022]
Abstract
Two-dimensional bond-based bilinear indices and linear discriminant analysis are used in this report to perform a quantitative structure-activity relationship study to identify new trypanosomicidal compounds. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop the theoretical models. Two discriminant models, computed using bond-based bilinear indices, are developed and both show accuracies higher than 86% for training and test sets. The stochastic model correctly indentifies nine out of eleven compounds of a set of organic chemicals obtained from our synthetic collaborators. The in vitro antitrypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi is assayed. Both models show a good agreement between theoretical predictions and experimental results. Three compounds showed IC50 values for epimastigote elimination (AE) lower than 50 μM, while for the benznidazole the IC50 = 54.7 μM which was used as reference compound. The value of IC50 for cytotoxicity of these compounds is at least 5 times greater than their value of IC50 for AE. Finally, we can say that, the present algorithm constitutes a step forward in the search for efficient ways of discovering new antitrypanosomal compounds.
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Affiliation(s)
- Juan Alberto Castillo-Garit
- Centro de Estudio de Química Aplicada, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100, Burjassot, Spain; Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain.
| | - Oremia del Toro-Cortés
- Centro de Estudio de Química Aplicada, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Maria C Vega
- Centro para el Desarrollo de la Investigacion Cientifica (CEDIC) and Fundación Moisés Bertoni/Laboratorios Díaz Gill, Pai Perez 265 casi Mariscal Estigarribia, Asuncion, Paraguay
| | - Miriam Rolón
- Centro para el Desarrollo de la Investigacion Cientifica (CEDIC) and Fundación Moisés Bertoni/Laboratorios Díaz Gill, Pai Perez 265 casi Mariscal Estigarribia, Asuncion, Paraguay
| | - Antonieta Rojas de Arias
- Centro para el Desarrollo de la Investigacion Cientifica (CEDIC) and Fundación Moisés Bertoni/Laboratorios Díaz Gill, Pai Perez 265 casi Mariscal Estigarribia, Asuncion, Paraguay
| | - Gerardo M Casañola-Martin
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100, Burjassot, Spain; Centro de Información y Gestión Tecnológica, Ministerio de Ciencia Tecnología y Medio Ambiente (CITMA), 65100, Ciego de Ávila, Cuba
| | - José A Escario
- Departamento de Parasitología, Facultad de Farmacia, UCM, Pza. Ramón y Cajal s/n, 28040, Madrid, Spain
| | - Alicia Gómez-Barrio
- Departamento de Parasitología, Facultad de Farmacia, UCM, Pza. Ramón y Cajal s/n, 28040, Madrid, Spain
| | - Yovani Marrero-Ponce
- Enviromental and Computational Chemistry Group, Facultad de Química Farmacéutica, Universidad de Cartagena,Cartagena de Indias, Bolivar, Colombia
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain
| | - Concepción Abad
- Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100, Burjassot, Spain
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Torrens F, Castellano G. Valence-Topological Charge-Transfer Indices, Dipole, Isoelectric Point and Fractal: From Homo/Heterocycles to Proteins. CURR ORG CHEM 2015. [DOI: 10.2174/1385272819666141216225353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Casanola-Martin GM, Le-Thi-Thu H, Marrero-Ponce Y, Castillo-Garit JA, Torrens F, Rescigno A, Abad C, Khan MTH. Tyrosinase enzyme: 1. An overview on a pharmacological target. Curr Top Med Chem 2015; 14:1494-501. [PMID: 24853560 DOI: 10.2174/1568026614666140523121427] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2014] [Revised: 02/10/2014] [Accepted: 02/11/2014] [Indexed: 11/22/2022]
Abstract
The tyrosinase enzyme (EC 1.14.18.1) is an oxidoreductase inside the general enzyme classification and is involved in the oxidation and reduction process in the epidermis. These chemical reactions that the enzyme catalyzes are of principal importance in the melanogenesis process. This process of melanogenesis is related to the melanin formation, a heteropolymer of indolic nature that provides the different tonalities in the skin and helps to the protection from the ultraviolet radiation. However, a pigment overproduction, come up by the action of the tyrosinase, can cause different disorders in the skin related to the hyperpigmentation. Several studies mainly focused on the characteristics of the enzyme have been reported. In this work, an approximation to general aspects related to this enzyme is made. Besides, it is treated the researches that have been published in the part of the biochemical anatomy dealing with diseases associated with this protein (melanogenesis), its active place and its physiological states, the molecular mechanism, the methods carried out to detect the inhibitory activity, and the used substrates.
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Affiliation(s)
| | | | | | | | | | | | | | - Mahmud Tareq Hassan Khan
- Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100 Burjassot, Spain.
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Torrens F, Castellano G. Mucoadhesive Polymer Hyaluronan as Biodegradable Cationic/Zwitterionic-Drug Delivery Vehicle. ADMET DMPK 2015. [DOI: 10.5599/admet.2.4.48] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Medina Marrero R, Marrero-Ponce Y, Barigye SJ, Echeverría Díaz Y, Acevedo-Barrios R, Casañola-Martín GM, García Bernal M, Torrens F, Pérez-Giménez F. QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents. SAR QSAR Environ Res 2015; 26:943-58. [PMID: 26567876 DOI: 10.1080/1062936x.2015.1104517] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correctly classify 92.16% and 87.56% of 706 compounds in an external test set. A comparison of the statistical parameters of the QuBiLs-MAS LDA-based models with those for models reported in the literature reveals comparable to superior performance, although the latter were built over much smaller and less diverse datasets, representing fewer mechanisms of action. It may therefore be inferred that the QuBiLs-MAS method constitutes a valuable tool useful in the design and/or selection of new and broad spectrum agents against life-threatening fungal infections.
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Affiliation(s)
- R Medina Marrero
- a Computer-Aided Molecular 'Biosilico' Discovery and Bioinformatic Research International Network (CAMD-BIR-IN) , Cartagena de Indias , Bolivar , Colombia
- b Department of Microbiology , Chemical Bioactive Center, Central University of Las Villas , Villa Clara , Cuba
| | - Y Marrero-Ponce
- a Computer-Aided Molecular 'Biosilico' Discovery and Bioinformatic Research International Network (CAMD-BIR-IN) , Cartagena de Indias , Bolivar , Colombia
- c Grupo de Investigación en Estudios Químicos y Biológicos, Facultad de Ciencias Básicas , Universidad Tecnológica de Bolívar , Cartagena de Indias , Bolívar , Colombia
- d Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia , Universitat de València , Valencia , Spain
- h Grupo de Investigación Microbiología y Ambiente (GIMA) . Programa de Bacteriología, Facultad Ciencias de la Salud, Universidad de San Buenaventura , Calle Real de Ternera, 130010, Cartagena (Bolivar) , Colombia
| | - S J Barigye
- a Computer-Aided Molecular 'Biosilico' Discovery and Bioinformatic Research International Network (CAMD-BIR-IN) , Cartagena de Indias , Bolivar , Colombia
- e Departamento de Química , Universidade Federal de Lavras , Lavras , MG , Brazil
| | - Y Echeverría Díaz
- a Computer-Aided Molecular 'Biosilico' Discovery and Bioinformatic Research International Network (CAMD-BIR-IN) , Cartagena de Indias , Bolivar , Colombia
| | - R Acevedo-Barrios
- c Grupo de Investigación en Estudios Químicos y Biológicos, Facultad de Ciencias Básicas , Universidad Tecnológica de Bolívar , Cartagena de Indias , Bolívar , Colombia
| | - G M Casañola-Martín
- a Computer-Aided Molecular 'Biosilico' Discovery and Bioinformatic Research International Network (CAMD-BIR-IN) , Cartagena de Indias , Bolivar , Colombia
- d Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia , Universitat de València , Valencia , Spain
- f Facultad de Ingeniería Ambiental , Universidad Estatal Amazónica , Puyo , Ecuador
| | - M García Bernal
- b Department of Microbiology , Chemical Bioactive Center, Central University of Las Villas , Villa Clara , Cuba
| | - F Torrens
- g Institut Universitari de Ciència Molecular, Universitat de València , Valencia , Spain
| | - F Pérez-Giménez
- d Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia , Universitat de València , Valencia , Spain
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Castillo-Garit JA, Marrero-Ponce Y, Barigye SJ, Medina-Marrero R, Bernal MG, Vega JMGDL, Torrens F, Arán VJ, Pérez-Giménez F, García-Domenech R, Acevedo-Barrios R. In silicoAntibacterial Activity Modeling Based on the TOMOCOMD-CARDD Approach. J BRAZIL CHEM SOC 2015. [DOI: 10.5935/0103-5053.20150087] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Martinez J, Vega-Hissi E, Andrada M, Duchowicz P, Torrens F, Estrada M. Lacosamide Derivatives with Anticonvulsant Activity as Carbonic Anhydrase Inhibitors. Molecular Modeling, Docking and QSAR Analysis. Curr Comput Aided Drug Des 2014; 10:160-7. [DOI: 10.2174/1573409910666140410123706] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2013] [Revised: 10/31/2013] [Accepted: 04/01/2014] [Indexed: 11/22/2022]
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Torrens F, Castellano G. Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides. Molecules 2014; 19:7388-414. [PMID: 24905607 PMCID: PMC6271575 DOI: 10.3390/molecules19067388] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Revised: 05/29/2014] [Accepted: 05/30/2014] [Indexed: 12/02/2022] Open
Abstract
Pesticide residues in wine were analyzed by liquid chromatography–tandem mass spectrometry. Retentions are modelled by structure–property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy–morphological determination–natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.
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Affiliation(s)
- Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071 València, Spain.
| | - Gloria Castellano
- Facultad de Veterinaria y Ciencias Experimentales, Universidad Católica de Valencia San Vicente Mártir, Guillem de Castro-94, E-46001 València, Spain.
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Casanola-Martin G, Le-Thi-Thu H, Marrero-Ponce Y, Garit J, Torrens F, Perez-Gimenez F, Abad C. Analysis of Proteasome Inhibition Prediction Using Atom-Based Quadratic Indices Enhanced by Machine Learning Classification Techniques. LETT DRUG DES DISCOV 2014. [DOI: 10.2174/1570180811666140122001144] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Torrens F, Castellano G. Cluster solvation models of carbon nanostructures: extension to fullerenes, tubes, and buds. J Mol Model 2014; 20:2263. [DOI: 10.1007/s00894-014-2263-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 04/23/2014] [Indexed: 11/28/2022]
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Castellano G, Lara A, Torrens F. Classification of stilbenoid compounds by entropy of artificial intelligence. Phytochemistry 2014; 97:62-69. [PMID: 24239224 DOI: 10.1016/j.phytochem.2013.10.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2013] [Accepted: 10/20/2013] [Indexed: 06/02/2023]
Abstract
A set of 66 stilbenoid compounds is classified into a system of periodic properties by using a procedure based on artificial intelligence, information entropy theory. Eight characteristics in hierarchical order are used to classify structurally the stilbenoids. The former five features mark the group or column while the latter three are used to indicate the row or period in the table of periodic classification. Those stilbenoids in the same group are suggested to present similar properties. Furthermore, compounds also in the same period will show maximum resemblance. In this report, the stilbenoids in the table are related to experimental data of bioactivity and antioxidant properties available in the technical literature. It should be noted that stilbenoids with glycoxyl groups esterified with benzoic acid derivatives, in the group g11000 in the extreme right of the periodic table, show the greatest antioxidant activity as confirmed by experiments in the bibliography. Moreover, the second group from the right (g10111) contains E-piceatannol, which antioxidant activity is recognized in the literature. The experiments confirm our results of the periodic classification.
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Affiliation(s)
- Gloria Castellano
- Universidad Católica de Valencia San Vicente Mártir, Guillem de Castro-94, E-46001 Valencia, Spain.
| | - Ana Lara
- Universidad Católica de Valencia San Vicente Mártir, Guillem de Castro-94, E-46001 Valencia, Spain
| | - Francisco Torrens
- Institut Universitari de Ciéncia Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071 València, Spain
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Abstract
The high-performance liquid-chromatographic retentions of red-wine pesticide residues are modeled by structure-property relationships. The effect of different types of features is analyzed: geometric, lipophilic, etc. The properties are fractal dimensions, partition coefficient, etc., in linear and nonlinear correlation models. Biological plastic evolution is an evolutionary perspective conjugating the effect of acquired characters and relations that emerge among the principles of evolutionary indeterminacy, morphological determination and natural selection. It is applied to design the co-ordination index that is used to characterize pesticide retentions. The parameters used to calculate the co-ordination index are the molar formation enthalpy, molecular weight and surface area. The morphological and co-ordination indices barely improve the correlations. The fractal dimension averaged for non‑buried atoms, partition coefficient, etc. distinguishes the pesticide molecular structures. The structural and constituent classification is based on nonplanarity, and the number of cycles, and O, S, N and Cl atoms. Different behavior depends on the number of cycles.
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Affiliation(s)
- Francisco Torrens
- a Institut Universitari de Ciència Molecular , Universitat de València, Edifici d'Instituts de Paterna , València , Spain
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Castellano G, González-Santander JL, Lara A, Torrens F. Classification of flavonoid compounds by using entropy of information theory. Phytochemistry 2013; 93:182-191. [PMID: 23642389 DOI: 10.1016/j.phytochem.2013.03.024] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2012] [Revised: 03/08/2013] [Accepted: 03/26/2013] [Indexed: 06/02/2023]
Abstract
A total of 74 flavonoid compounds are classified into a periodic table by using an algorithm based on the entropy of information theory. Seven features in hierarchical order are used to classify structurally the flavonoids. From these features, the first three mark the group or column, while the last four are used to indicate the row or period in a table of periodic classification. Those flavonoids in the same group and period are suggested to show maximum similarity in properties. Furthermore, those with only the same group will present moderate similarity. In this report, the flavonoid compounds in the table, whose experimental data in bioactivity and antioxidant properties have been previously published, are related.
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Affiliation(s)
- Gloria Castellano
- Facultad de Ciencias Experimentales, Universidad Católica de, Valéncia San Vicente Mártir, Guillem de Castro-94, E-46001 Valencia, Spain.
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Barigye S, Marrero-Ponce Y, Santiago O, Lopez Y, Perez-Gimenez F, Torrens F. Shannon’s, Mutual, Conditional and Joint Entropy Information Indices: Generalization of Global Indices Defined from Local Vertex Invariants. Curr Comput Aided Drug Des 2013; 9:164-83. [DOI: 10.2174/1573409911309020003] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2010] [Revised: 04/01/2013] [Accepted: 04/27/2013] [Indexed: 11/22/2022]
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Torrens F, Castellano G. Information theoretic entropy for molecular classification: oxadiazolamines as potential therapeutic agents. Curr Comput Aided Drug Des 2013; 9:241-53. [PMID: 23700996 DOI: 10.2174/1573409911309020009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2010] [Revised: 09/17/2012] [Accepted: 04/27/2013] [Indexed: 11/22/2022]
Abstract
In this review we present algorithms for classification and taxonomy based on information entropy, followed by structure-activity relationship (SAR) models for the inhibition of human prostate carcinoma cell line DU-145 by 26 derivatives of N-aryl-N-(3-aryl-1,2,4-oxadiazol-5-yl)amines (NNAs). The NNAs are classified using two characteristic chemical properties based on different regions of the molecules. A table of periodic properties of inhibitors of DU-145 human prostate carcinoma cell line is obtained based on structural features from the amine moiety and from the oxadiazole ring. Inhibitors in the same group and period of the periodic table are predicted to have highly similar properties, and those located only in the same group will present moderate similarity. The results of a virtual screening campaign are presented.
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Affiliation(s)
- Francisco Torrens
- Institut Universitari de Ciencia Molecular, Universitat de Valencia, Edifici d'Instituts de Paterna, PO Box 22085, E-46071 Valencia, Spain.
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Brito-Sánchez Y, Castillo-Garit JA, Le-Thi-Thu H, González-Madariaga Y, Torrens F, Marrero-Ponce Y, Rodríguez-Borges JE. Comparative study to predict toxic modes of action of phenols from molecular structures. SAR QSAR Environ Res 2013; 24:235-251. [PMID: 23437773 DOI: 10.1080/1062936x.2013.766260] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. Most of them showed global accuracy of over 90%, and false alarm rate values were below 2.9% for the training set. Cross-validation, complementary subsets and external test set were performed, with good behaviour in all cases. Our models compare favourably with other previously published models, and in general the models obtained with ML techniques show better results than those developed with linear techniques. We developed unsupervised and supervised consensus, and these results were better than our ML models, the results of rule-based approach and other ensemble models previously published. This investigation highlights the merits of ML-based techniques as an alternative to other more traditional methods for modelling MOA.
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Affiliation(s)
- Y Brito-Sánchez
- Unit of Computer-Aided Molecular Biosilico Discovery and Bioinformatic Research, Faculty of Chemistry-Pharmacy, Universidad Central Marta Abreu de Las Villas, Santa Clara, Cuba
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Barigye SJ, Marrero-Ponce Y, Martínez López Y, Martínez Santiago O, Torrens F, García Domenech R, Galvez J. Event-based criteria in GT-STAF information indices: theory, exploratory diversity analysis and QSPR applications. SAR QSAR Environ Res 2013; 24:3-34. [PMID: 23066866 DOI: 10.1080/1062936x.2012.728994] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Versatile event-based approaches for the definition of novel information theory-based indices (IFIs) are presented. An event in this context is the criterion followed in the "discovery" of molecular substructures, which in turn serve as basis for the construction of the generalized incidence and relations frequency matrices, Q and F, respectively. From the resultant F, Shannon's, mutual, conditional and joint entropy-based IFIs are computed. In previous reports, an event named connected subgraphs was presented. The present study is an extension of this notion, in which we introduce other events, namely: terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach's subgraphs, MACCs, E-state and substructure fingerprints and, finally, Ghose and Crippen atom-types for hydrophobicity and refractivity. Moreover, we define magnitude-based IFIs, introducing the use of the magnitude criterion in the definition of mutual, conditional and joint entropy-based IFIs. We also discuss the use of information-theoretic parameters as a measure of the dissimilarity of codified structural information of molecules. Finally, a comparison of the statistics for QSPR models obtained with the proposed IFIs and DRAGON's molecular descriptors for two physicochemical properties log P and log K of 34 derivatives of 2-furylethylenes demonstrates similar to better predictive ability than the latter.
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Affiliation(s)
- S J Barigye
- Faculty of Chemistry-Pharmacy, Universidad Central Marta Abreu de Las Villas, Villa Clara, Cuba
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Barigye SJ, Marrero-Ponce Y, Martínez-López Y, Torrens F, Artiles-Martínez LM, Pino-Urias RW, Martínez-Santiago O. Relations frequency hypermatrices in mutual, conditional, and joint entropy-based information indices. J Comput Chem 2012; 34:259-74. [DOI: 10.1002/jcc.23123] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2012] [Revised: 07/05/2012] [Accepted: 08/22/2012] [Indexed: 11/10/2022]
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Torrens F, Castellano G. QSPR Prediction of Retention Times of Phenylurea Herbicides by Biological Plastic Evolution. Curr Drug Saf 2012; 7:262-8. [DOI: 10.2174/157488612804096551] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2012] [Revised: 09/20/2012] [Accepted: 09/26/2012] [Indexed: 11/22/2022]
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Castillo-Garit JA, del Toro-Cortés O, Kouznetsov VV, Puentes CO, Romero Bohórquez AR, Vega MC, Rolón M, Escario JA, Gómez-Barrio A, Marrero-Ponce Y, Torrens F, Abad C. Identification In Silico and In Vitro of Novel Trypanosomicidal Drug-Like Compounds. Chem Biol Drug Des 2012; 80:38-45. [DOI: 10.1111/j.1747-0285.2012.01378.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Alberto Castillo-Garit J, Abad C, Enrique Rodriguez-Borges J, Marrero-Ponce Y, Torrens F. A Review of QSAR studies to Discover New Drug-like Compounds Actives Against Leishmaniasis and Trypanosomiasis. Curr Top Med Chem 2012; 12:852-65. [DOI: 10.2174/156802612800166756] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2011] [Accepted: 05/20/2011] [Indexed: 11/22/2022]
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Toropov AA, Nabiev OM, Duchowicz P, Castro EA, Torrens F. QSPR Modeling of Hydrocarbon Dipole Moments by Means of Correlation Weighting of Local Graph Invariants. J Theor Comput Chem 2011. [DOI: 10.1142/s0219633603000409] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Hydrocarbon dipole moments are calculated by means of correlation weighting of local graph invariants within the context of QSPR theory. This sort of flexible topological descriptor is used for several parameters: local invariants of k th vertex in the labeled hydrogen filled graph extended connectivity of zero-, first- and second-orders, number of paths of length 2 at k th vertex and valence shell of the k th vertex. The models predict hydrocarbon dipole moments in a quite sensible way. The best model is that one based upon numbers of path length 2 correlation weighting.
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Affiliation(s)
- Andrey A. Toropov
- Scientifical Research Institute "Algorithm — Engineering", F. Khodjaev Street 25, 700125 Tashkent, Uzbekistan
| | - Ozod M. Nabiev
- Scientifical Research Institute "Algorithm — Engineering", F. Khodjaev Street 25, 700125 Tashkent, Uzbekistan
| | - Pablo Duchowicz
- CEQUINOR, Departamento de Qumica, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Calles 47 y 115, C.C. 962, La Plata 1900, Argentina
| | - Eduardo A. Castro
- CEQUINOR, Departamento de Qumica, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Calles 47 y 115, C.C. 962, La Plata 1900, Argentina
| | - Francisco Torrens
- Facultad de Química, Departament de Química Física, Institut Universitari de Ciencia Molecular, Universitat de Valencia, Dr. Moliner 50, E-46100 Burjassot, Valencia, Spain
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Torrens F, Castellano G. (Co-)solvent selection for single-wall carbon nanotubes: best solvents, acids, superacids and guest-host inclusion complexes. Nanoscale 2011; 3:2494-2510. [PMID: 21331393 DOI: 10.1039/c0nr00922a] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Analysis of 1-octanol-water, cyclohexane-water and chloroform (CHCl(3))-water partition coefficients P(o-ch-cf) allows calculation of molecular lipophilicity patterns, which show that for a given atom log P(o-ch-cf) is sensitive to the presence of functional groups. Program CDHI does not properly differentiate between non-equivalent atoms. The most abundant single-wall carbon nanotube (SWNT), (10,10), presents a relatively small aqueous solubility and large elementary polarizability, P(o-ch-cf) and kinetic stability. The SWNT solubility is studied in various solvents, finding a class of non-hydrogen-bonding Lewis bases with good solubility. Solvents group into three classes. The SWNTs in some organic solvents are cationic while in water/Triton X mixture are anionic. Categorized solubility is semiquantitatively correlated with solvent parameters. The coefficient of term β is positive while the ones of ε and V negative. The electron affinity of d-glucopyranoses (d-Glcp(n)) suggests the formation of colloids of anionic SWNTs in water. Dipole moment for d-Glcp(n)-linear increases with n until four in agreement with 18-fold helix. The I(n)(z-) and SWNT(-) are proposed to form inclusion complexes with cyclodextrin (CD) and amylose (Amy). Starch, d-Glcp, CD and Amy are proposed as SWNT co-solvents. Guests-hosts are unperturbed. A central channel expansion is suggested.
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Affiliation(s)
- Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain.
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Le-Thi-Thu H, Marrero-Ponce Y, Casañola-Martin GM, Cardoso GC, Chávez M, Garcia MM, Morell C, Torrens F, Abad C. A Comparative Study of Nonlinear Machine Learning for the “In Silico” Depiction of Tyrosinase Inhibitory Activity from Molecular Structure. Mol Inform 2011; 30:527-37. [DOI: 10.1002/minf.201100021] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2010] [Accepted: 03/25/2010] [Indexed: 11/05/2022]
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