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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 AND QSAR IN ENVIRONMENTAL RESEARCH 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] [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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González-Castañeda Y, Marrero-Ponce Y, Guerra JO, Echevarría-Díaz Y, Pérez N, Pérez-Giménez F, Simonet AM, Macías FA, Nogueiras CM, Olazabal E, Serrano H. Computational discovery of novel anthelmintic natural compounds from Agave Brittoniana trel. Spp. Brachypus. BIONATURA 2022. [DOI: 10.21931/rb/2022.07.04.53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Helminth infections are a medical problem in the world nowadays. This report used bond-based 2D quadratic indices, a bond-level QuBiLs-MAS molecular descriptor family, and Linear Discriminant Analysis (LDA) to obtain a quantitative linear model that discriminates between anthelmintic and non-anthelmintic drug-like organic-compounds. The model obtained correctly classified 87.46% and 81.82% of the training and external data sets, respectively. The developed model was used in a virtual screening to predict the biological activity of all chemicals (19) previously obtained and chemically characterized by some authors of this report from Agave brittoniana Trel. spp. Brachypus. The model identified several metabolites (12) as possible anthelmintics, and a group of 5 novel natural products was tested in an in vitro assay against Fasciola hepatica (100% effectivity at 500 µg/mL). Finally, the two best hits were evaluated in vivo in bald/c mice and the same helminth parasite using a 25 mg/kg dose. Compound 8 (Karatavinoside A) showed an efficacy of 92.2% in vivo. It is important to remark that this natural compound exhibits similar-to-superior activity as triclabendazole, the best human fasciolicide available in the market against Fasciola hepatica, resulting in a novel lead scaffold with anti-helminthic activity.
Keywords: TOMOCOMD-CARDD Software; QuBiLs-MAS, nonstochastic and stochastic bond-based quadratic indices; LDA-based QSAR model; Computational Screening, Anthelmintic Agent; Agave brittoniana Trel. spp. Brachypus, Fasciola hepatica.
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Affiliation(s)
- Yeniel González-Castañeda
- Universidad San Francisco de Quito, Grupo de Medicina Molecular y Traslacional (MeM&T), Escuela de Medicina, Colegio de Ciencias de la Salud (COCSA)
| | - Yovani Marrero-Ponce
- Universidad San Francisco de Quito, Grupo de Medicina Molecular y Traslacional (MeM&T), Escuela de Medicina, Colegio de Ciencias de la Salud (COCSA), Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Valencia, Spain
| | - Jose O. Guerra
- Chemistry Department, Faculty of Chemistry-Pharmacy. Universidad Central “Marta Abreu” de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Yunaimy Echevarría-Díaz
- Universidad San Francisco de Quito, Grupo de Medicina Molecular y Traslacional (MeM&T), Escuela de Medicina, Colegio de Ciencias de la Salud (COCSA), Departamento de Ciencias de la Computación, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE)
| | - Noel Pérez
- Colegio de Ciencias e Ingenierías “El Politécnico”, Universidad San Francisco de Quito (USFQ), Quito, Ecuador
| | - Facundo Pérez-Giménez
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Valencia, Spain
| | - Ana M. Simonet
- Grupo de Alelopatía, Departamento de Química Orgánica, Facultad de Ciencias, Universidad de Cádiz
| | - Francisco A. Macías
- Grupo de Alelopatía, Departamento de Química Orgánica, Facultad de Ciencias, Universidad de Cádiz
| | - Clara M. Nogueiras
- Departamento de Química Orgánica, Facultad de Química, Universidad de La Habana
| | - Ervelio Olazabal
- Chemical Bioactive Center. Universidad Central “Marta Abreu” de Las Villas, Santa Clara
| | - Hector Serrano
- Chemical Bioactive Center. Universidad Central “Marta Abreu” de Las Villas, Santa Clara
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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 AND QSAR IN ENVIRONMENTAL RESEARCH 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] [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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An approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking. ARAB J CHEM 2019. [DOI: 10.1016/j.arabjc.2016.10.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Martínez-López Y, Barigye SJ, Martínez-Santiago O, Marrero-Ponce Y, Green J, Castillo-Garit JA. Prediction of aquatic toxicity of benzene derivatives using molecular descriptor from atomic weighted vectors. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2017; 56:314-321. [PMID: 29091819 DOI: 10.1016/j.etap.2017.10.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 10/09/2017] [Accepted: 10/11/2017] [Indexed: 06/07/2023]
Abstract
Several descriptors from atom weighted vectors are used in the prediction of aquatic toxicity of set of organic compounds of 392 benzene derivatives to the protozoo ciliate Tetrahymena pyriformis (log(IGC50)-1). These descriptors are calculated using the MD-LOVIs software and various Aggregation Operators are examined with the aim comparing their performances in predicting aquatic toxicity. Variability analysis is used to quantify the information content of these molecular descriptors by means of an information theory-based algorithm. Multiple Linear Regression with Genetic Algorithms is used to obtain models of the structure-toxicity relationships; the best model shows values of Q2=0.830 and R2=0.837 using six variables. Our models compare favorably with other previously published models that use the same data set. The obtained results suggest that these descriptors provide an effective alternative for determining aquatic toxicity of benzene derivatives.
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Affiliation(s)
- Yoan Martínez-López
- Department of Computer Sciences, Faculty of Informatics, Camaguey University, Camaguey City, 74650, Camaguey, Cuba; Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Martha Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Stephen J Barigye
- Departamento de Química, Universidade Federal de Lavras, CP 3037, 37200-000, Lavras, MG, Brazil
| | - Oscar Martínez-Santiago
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Martha Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - 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, Av. Interoceánica Km 12 ½, Cumbayá, Ecuador
| | - James Green
- Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Juan A Castillo-Garit
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Martha Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada; Unidad de Toxicologia Experimental, Universidad de Ciencias Médicas de Villa Clara Santa Clara, 50200, Villa Clara, Cuba.
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García-Jacas CR, Marrero-Ponce Y, Hernández-Ortega T, Martinez-Mayorga K, Cabrera-Leyva L, Ledesma-Romero JC, Aguilera-Fernández I, Rodríguez-León AR. Tensor algebra-based geometric methodology to codify central chirality on organic molecules. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2017; 28:541-556. [PMID: 28705027 DOI: 10.1080/1062936x.2017.1344729] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 06/16/2017] [Indexed: 06/07/2023]
Abstract
A novel mathematical procedure to codify chiral features of organic molecules in the QuBiLS-MIDAS framework is introduced. This procedure constitutes a generalization to that commonly used to date, where the values 1 and -1 (correction factor) are employed to weight the molecular vectors when each atom is labelled as R (rectus) or S (sinister) according to the Cahn-Ingold-Prelog rules. Therefore, values in the range [Formula: see text] with steps equal to 0.25 may be accounted for. The atoms labelled R or S can have negative and positive values assigned (e.g. -3 for an R atom and 1 for an S atom, or vice versa), opposed values (e.g. -3 for an R atom and 3 for an S atom, or vice versa), positive values (e.g. 3 for an R atom and 1 for an S atom) or negative values (e.g. -3 for an R atom and -1 for an S atom). These proposed Chiral QuBiLS-MIDAS 3D-MDs are real numbers, non-symmetric and reduced to 'classical' (non-chiral) QuBiLS-MIDAS 3D-MDs when symmetry is not codified (correction factor equal to zero). In this report, only the factors with opposed values were considered with the purpose of demonstrating the feasibility of this proposal. From QSAR modelling carried out on four chemical datasets (Cramer's steroids, fenoterol stereoisomer derivatives, N-alkylated 3-(3-hydroxyphenyl)-piperidines, and perindoprilat stereoisomers), it was demonstrated that the use of several correction factors contributes to the building of models with greater robustness and predictive ability than those reported in the literature, as well as with respect to the models exclusively developed with QuBiLS-MIDAS 3D-MDs based on the factor 1 | -1. In conclusion, it can be stated that this novel strategy constitutes a suitable alternative to computed chirality-based descriptors, contributing to the development of good models to predict properties depending on symmetry.
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Affiliation(s)
- C R García-Jacas
- a Instituto de Química, Universidad Nacional Autónoma de México (UNAM) , Ciudad de México , México
- b Escuela de Sistemas y Computación , Pontificia Universidad Católica del Ecuador Sede Esmeraldas (PUCESE) , Esmeraldas , Ecuador
- g Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas (UCI) , La Habana , Cuba
| | - Y Marrero-Ponce
- c Computer-Aided Molecular "Biosilico" Discovery and Bioinformatics Research International Network (CAMD-BIR IN) , Quito , Ecuador
- d Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina , Quito , Pichincha , Ecuador
- e Universidad San Francisco de Quito (USFQ), Instituto de Simulación Computacional (ISC-USFQ) , Quito , Pichincha , Ecuador
- f Grupo de Investigación Ambiental (GIA) , Programas Ambientales, Facultad de Ingenierías, Fundación Universitaria Tecnológico de Comfenalco (COMFENALCO) , Cartagena de Indias , Bolívar , Colombia
| | - T Hernández-Ortega
- g Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas (UCI) , La Habana , Cuba
| | - K Martinez-Mayorga
- a Instituto de Química, Universidad Nacional Autónoma de México (UNAM) , Ciudad de México , México
| | - L Cabrera-Leyva
- h Grupo de Investigación de Inteligencia Artificial (AIRES), Facultad de Informática , Universidad de Camagüey , Camagüey , Cuba
| | - J C Ledesma-Romero
- g Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas (UCI) , La Habana , Cuba
| | - I Aguilera-Fernández
- g Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas (UCI) , La Habana , Cuba
| | - A R Rodríguez-León
- g Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas (UCI) , La Habana , Cuba
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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] [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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Toropov AA, Toropova AP, Rasulev BF, Benfenati E, Gini G, Leszczynska D, Leszczynski J. Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical. J Comput Chem 2012; 33:1902-6. [DOI: 10.1002/jcc.23022] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2012] [Revised: 04/12/2012] [Accepted: 04/16/2012] [Indexed: 12/18/2022]
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9
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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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Toropova AP, Toropov AA, Rasulev BF, Benfenati E, Gini G, Leszczynska D, Leszczynski J. QSAR models for ACE-inhibitor activity of tri-peptides based on representation of the molecular structure by graph of atomic orbitals and SMILES. Struct Chem 2012. [DOI: 10.1007/s11224-012-9996-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Ligand-based discovery of novel trypanosomicidal drug-like compounds: In silico identification and experimental support. Eur J Med Chem 2011; 46:3324-30. [DOI: 10.1016/j.ejmech.2011.04.057] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Revised: 04/26/2011] [Accepted: 04/26/2011] [Indexed: 01/08/2023]
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