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Sun L, Li M, Yang J, Li J. Cell Membrane-Coated Nanoparticles for Management of Infectious Diseases: A Review. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Lizhong Sun
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Cariology and Endodontics, West China Hospital of Stomatology, Sichuan University, Chengdu 610065, China
| | - Meng Li
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Cariology and Endodontics, West China Hospital of Stomatology, Sichuan University, Chengdu 610065, China
| | - Jiaojiao Yang
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Cariology and Endodontics, West China Hospital of Stomatology, Sichuan University, Chengdu 610065, China
| | - Jiyao Li
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Cariology and Endodontics, West China Hospital of Stomatology, Sichuan University, Chengdu 610065, China
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Santos HLC, Rebello KM. An Overview of Mucosa-Associated Protozoa: Challenges in Chemotherapy and Future Perspectives. Front Cell Infect Microbiol 2022; 12:860442. [PMID: 35548465 PMCID: PMC9084232 DOI: 10.3389/fcimb.2022.860442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 03/29/2022] [Indexed: 11/13/2022] Open
Abstract
Parasitic infections caused by protozoans that infect the mucosal surfaces are widely neglected worldwide. Collectively, Entamoeba histolytica, Giardia lamblia, Cryptosporidium spp. and Trichomonas vaginalis infect more than a billion people in the world, being a public health problem mainly in developing countries. However, the exact incidence and prevalence data depend on the population examined. These parasites ultimately cause pathologies that culminate in liver abscesses, malabsorption syndrome, vaginitis, and urethritis, respectively. Despite this, the antimicrobial agents currently used to treat these diseases are limited and often associated with adverse side effects and refractory cases due to the development of resistant parasites. The paucity of drug treatments, absence of vaccines and increasing problems of drug resistance are major concerns for their control and eradication. Herein, potential candidates are reviewed with the overall aim of determining the knowledge gaps and suggest future perspectives for research. This review focuses on this public health problem and focuses on the progress of drug repositioning as a potential strategy for the treatment of mucosal parasites.
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Affiliation(s)
- Helena Lucia Carneiro Santos
- Laboratório de Estudos Integrados em Protozoologia, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Brazil
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Zanni R, Galvez-Llompart M, Garcia-Domenech R, Galvez J. What place does molecular topology have in today’s drug discovery? Expert Opin Drug Discov 2020; 15:1133-1144. [DOI: 10.1080/17460441.2020.1770223] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Riccardo Zanni
- Molecular Topology and Drug Design Unit, Department of Physical Chemistry, University of Valencia, Valencia, Spain
- Departamento de Microbiologia, Facultad de Ciencias, Universidad de Malaga, Málaga, Spain
| | - Maria Galvez-Llompart
- Molecular Topology and Drug Design Unit, Department of Physical Chemistry, University of Valencia, Valencia, Spain
- Instituto de Tecnología Química, UPV-CSIC, Universidad Politécnica de Valencia, Valencia, Spain
| | - Ramon Garcia-Domenech
- Molecular Topology and Drug Design Unit, Department of Physical Chemistry, University of Valencia, Valencia, Spain
| | - Jorge Galvez
- Molecular Topology and Drug Design Unit, Department of Physical Chemistry, University of Valencia, Valencia, Spain
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Mora JR, Marrero-Ponce Y, García-Jacas CR, Suarez Causado A. Ensemble Models Based on QuBiLS-MAS Features and Shallow Learning for the Prediction of Drug-Induced Liver Toxicity: Improving Deep Learning and Traditional Approaches. Chem Res Toxicol 2020; 33:1855-1873. [PMID: 32406679 DOI: 10.1021/acs.chemrestox.0c00030] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Drug-induced liver injury (DILI) is a key safety issue in the drug discovery pipeline and a regulatory concern. Thus, many in silico tools have been proposed to improve the hepatotoxicity prediction of organic-type chemicals. Here, classifiers for the prediction of DILI were developed by using QuBiLS-MAS 0-2.5D molecular descriptors and shallow machine learning techniques, on a training set composed of 1075 molecules. The best ensemble model build, E13, was obtained with good statistical parameters for the learning series, namely, the following: accuracy = 0.840, sensibility = 0.890, specificity = 0.761, Matthew's correlation coefficient = 0.660, and area under the ROC curve = 0.904. The model was also satisfactorily evaluated with Y-scrambling test, and repeated k-fold cross-validation and repeated k-holdout validation. In addition, an exhaustive external validation was also carried out by using two test sets and five external test sets, with an average accuracy value equal to 0.854 (±0.062) and a coverage equal to 98.4% according to its applicability domain. A statistical comparison of the performance of the E13 model, with regard to results and tools (e.g., Padel DDPredictor Software, Deep Learning DILIserver, and Vslead) reported in the literature, was also performed. In general, E13 presented the best global performance in all experiments. The sum of the ranking differences procedure provided a very similar grouping pattern to that of the M-ANOVA statistical analysis, where E13 was identified as the best model for DILI predictions. A noncommercial and fully cross-platform software for the DILI prediction was also developed, which is freely available at http://tomocomd.com/apps/ptoxra. This software was used for the screening of seven data sets, containing natural products, leads, toxic materials, and FDA approved drugs, to assess the usefulness of the QSAR models in the DILI labeling of organic substances; it was found that 50-92% of the evaluated molecules are positive-DILI compounds. All in all, it can be stated that the E13 model is a relevant method for the prediction of DILI risk in humans, as it shows the best results among all of the methods analyzed.
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Affiliation(s)
- Jose R Mora
- Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito (USFQ), Quito 17-1200-841, Ecuador.,Instituto de Simulación Computacional (ISC-USFQ), Universidad San Francisco de Quito (USFQ), Diego de Robles y Vía Interoceánica, Quito 17-1200-841, Ecuador
| | - Yovani Marrero-Ponce
- Instituto de Simulación Computacional (ISC-USFQ), Universidad San Francisco de Quito (USFQ), Diego de Robles y Vía Interoceánica, Quito 17-1200-841, Ecuador.,Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, and Instituto de Simulación Computacional (ISC-USFQ), Universidad San Francisco de Quito (USFQ), Diego de Robles y vía Interoceánica, Quito, Pichincha 170157, Ecuador
| | - César R García-Jacas
- Cátedras Conacyt-Departamento de Ciencias de la Computación, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), Ensenada, Baja California 22860, México
| | - Amileth Suarez Causado
- Grupo de Investigación Prometeus & Biomedicina Aplicada a las Ciencias Clínicas, Área de Bioquímica, Campus de Zaragocilla, Facultad de Medicina, Universidad de Cartagena, Cartagena de Indias 130001, Colombia
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García-Jacas CR, Marrero-Ponce Y, Cortés-Guzmán F, Suárez-Lezcano J, Martinez-Rios FO, García-González LA, Pupo-Meriño M, Martinez-Mayorga K. Enhancing Acute Oral Toxicity Predictions by using Consensus Modeling and Algebraic Form-Based 0D-to-2D Molecular Encodes. Chem Res Toxicol 2019; 32:1178-1192. [PMID: 31066547 DOI: 10.1021/acs.chemrestox.9b00011] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Quantitative structure-activity relationships (QSAR) are introduced to predict acute oral toxicity (AOT), by using the QuBiLS-MAS (acronym for quadratic, bilinear and N-Linear maps based on graph-theoretic electronic-density matrices and atomic weightings) framework for the molecular encoding. Three training sets were employed to build the models: EPA training set (5931 compounds), EPA-full training set (7413 compounds), and Zhu training set (10 152 compounds). Additionally, the EPA test set (1482 compounds) was used for the validation of the QSAR models built on the EPA training set, while the ProTox (425 compounds) and T3DB (284 compounds) external sets were employed for the assessment of all the models. The k-nearest neighbor, multilayer perceptron, random forest, and support vector machine procedures were employed to build several base (individual) models. The base models with REPA-training ≥ 0.75 ( R = correlation coefficient) and MAEEPA-training ≤ 0.5 (MAE = mean absolute error) were retained to build consensus models. As a result, two consensus models based on the minimum operator and denoted as M19 and M22, as well as a consensus model based on the weighted average operator and denoted as M24, were selected as the best ones for each training set considered. According to the applicability domain (AD) analysis performed, model M19 (built on the EPA training set) has MAEtest-AD = 0.4044, MAEProTox-AD = 0.4067 and MAET3DB-AD = 0.2586 on the EPA test set, ProTox external set, and T3DB external set, respectively; whereas model M22 (built on the EPA-full set) and model M24 (built on the Zhu set) present MAEProTox-AD = 0.3992 and MAET3DB-AD = 0.2286, and MAEProTox-AD = 0.3773 and MAET3DB-AD = 0.2471 on the two external sets accounted for, respectively. These outcomes were compared and statistically validated with respect to 14 QSAR methods (e.g., admetSAR, ProTox-II) from the literature. As a result, model M22 presents the best overall performance. In addition, a retrospective study on 261 withdrawn drugs due to their toxic/side effects was performed, to assess the usefulness of prospectively using the QSAR models proposed in the labeling of chemicals. A comparison with regard to the methods from the literature was also made. As a result, model M22 has the best ability of labeling a compound as toxic according to the globally harmonized system of classification and labeling of chemicals. Therefore, it can be concluded that the models proposed, especially model M22, constitute prominent tools for studying AOT, at providing the best results among all the methods examined. A freely available software was also developed to be used in virtual screening tasks ( http://tomocomd.com/apps/ptoxra ).
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Affiliation(s)
- César R García-Jacas
- Departamento de Ciencias de la Computación , Centro de Investigación Científica y de Educación Superior de Ensenada , Ensenada , Baja California , México
| | - Yovani Marrero-Ponce
- Universidad San Francisco de Quito, Grupo de Medicina Molecular y Traslacional, Colegio de Ciencias de la Salud , Escuela de Medicina, Edificio de Especialidades Médicas , Quito , Pichincha , Ecuador.,Grupo de Investigación Ambiental, Programas Ambientales, Facultad de Ingenierías , Fundacion Universitaria Tecnologico Comfenalco-Cartagena , Cr44 DN 30 A, 91 , Cartagena , Bolívar , Colombia
| | - Fernando Cortés-Guzmán
- Instituto de Química , Universidad Nacional Autónoma de México , Ciudad de México , México
| | - José Suárez-Lezcano
- Pontificia Universidad Católica del Ecuador Sede Esmeraldas , Esmeraldas , Ecuador
| | | | - Luis A García-González
- Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas , La Habana , Cuba
| | - Mario Pupo-Meriño
- Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas , La Habana , Cuba
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García-Jacas CR, Cabrera-Leyva L, Marrero-Ponce Y, Suárez-Lezcano J, Cortés-Guzmán F, Pupo-Meriño M, Vivas-Reyes R. Choquet integral-based fuzzy molecular characterizations: when global definitions are computed from the dependency among atom/bond contributions (LOVIs/LOEIs). J Cheminform 2018; 10:51. [PMID: 30362050 PMCID: PMC6755596 DOI: 10.1186/s13321-018-0306-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Accepted: 10/15/2018] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Several topological (2D) and geometric (3D) molecular descriptors (MDs) are calculated from local vertex/edge invariants (LOVIs/LOEIs) by performing an aggregation process. To this end, norm-, mean- and statistic-based (non-fuzzy) operators are used, under the assumption that LOVIs/LOEIs are independent (orthogonal) values of one another. These operators are based on additive and/or linear measures and, consequently, they cannot be used to encode information from interrelated criteria. Thus, as LOVIs/LOEIs are not orthogonal values, then non-additive (fuzzy) measures can be used to encode the interrelation among them. RESULTS General approaches to compute fuzzy 2D/3D-MDs from the contribution of each atom (LOVIs) or covalent bond (LOEIs) within a molecule are proposed, by using the Choquet integral as fuzzy aggregation operator. The Choquet integral-based operator is rather different from the other operators often used for the 2D/3D-MDs calculation. It performs a reordering step to fuse the LOVIs/LOEIs according to their magnitudes and, in addition, it considers the interrelation among them through a fuzzy measure. With this operator, fuzzy definitions can be derived from traditional or recent MDs; for instance, fuzzy Randic-like connectivity indices, fuzzy Balaban-like indices, fuzzy Kier-Hall connectivity indices, among others. To demonstrate the feasibility of using this operator, the QuBiLS-MIDAS 3D-MDs were used as study case and, as a result, a module was built into the corresponding software to compute them ( http://tomocomd.com/qubils-midas ). Thus, it is the only software reported in the literature that can be employed to determine Choquet integral-based fuzzy MDs. Moreover, regression models were created on eight chemical datasets. In this way, a comparison between the results achieved by the models based on the non-fuzzy QuBiLS-MIDAS 3D-MDs with regard to the ones achieved by the models based on the fuzzy QuBiLS-MIDAS 3D-MDs was made. As a result, the models built with the fuzzy QuBiLS-MIDAS 3D-MDs achieved the best performance, which was statistically corroborated through the Wilcoxon signed-rank test. CONCLUSIONS All in all, it can be concluded that the Choquet integral constitutes a prominent alternative to compute fuzzy 2D/3D-MDs from LOVIs/LOEIs. In this way, better characterizations of the compounds can be obtained, which will be ultimately useful in enhancing the modelling ability of existing traditional 2D/3D-MDs.
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Affiliation(s)
- César R. García-Jacas
- Instituto de Química, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, México
| | - Lisset Cabrera-Leyva
- Grupo de Investigación de Inteligencia Artificial (AIRES), Facultad de Informática, Universidad de Camagüey, Camagüey, Cuba
| | - Yovani Marrero-Ponce
- Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Universidad San Francisco de Quito (USFQ), Quito, Pichincha Ecuador
- Grupo de Investigación Ambiental (GIA), Programas Ambientales, Facultad de Ingenierías, Fundacion Universitaria Tecnologico Comfenalco – Cartagena, Cr 44 DN 30 A, 91, Cartagena, Bolívar Colombia
| | - José Suárez-Lezcano
- Pontificia Universidad Católica del Ecuador Sede Esmeraldas (PUCESE), Esmeraldas, Ecuador
| | - Fernando Cortés-Guzmán
- Instituto de Química, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, México
| | - Mario Pupo-Meriño
- Grupo de Investigación de Bioinformática, Universidad de las Ciencias Informáticas (UCI), La Habana, Cuba
| | - Ricardo Vivas-Reyes
- Grupo de Química Cuántica y Teórica, Facultad de Ciencias Exactas y Naturales, Programa de Química, Universidad de Cartagena, Campus de San Pablo, Cartagena, Colombia
- Grupo CipTec, Facultad de Ingenierias, Fundacion Universitaria Tecnologico Comfenalco – Cartagena, Cr 44 DN 30 A, 91, Cartagena, Bolívar Colombia
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