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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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2
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Abstract
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For decades now, compounds in the cycloartane-type series have been shown to
have versatile pharmacological activities. However, no extensive review has been written
to summarize these health-beneficial activities. Therefore, the purpose of this paper is to
systematically highlight the biological activities of these compounds, including their antitumor
and anti-osteoporosis effects, their effects on receptors, cytokine release, and
chronic renal failure, as well as their tyrosinase inhibitory, anticomplement, anti-parasite,
anti-HIV, and antituberculosis activities. In this review, we have summarized the structures
of over 200 compounds based on their characteristics and described their structureactivity
relationships (SARs), and potential mechanisms of action.
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Affiliation(s)
- Wenyan Gao
- Key Laboratory of Neuropsychiatric Drug, Research of Zhejiang Province, Institute of Materia Medica, Zhejiang Academy of Medical Sciences & Hangzhou Medical College, Hangzhou, 310013, China
| | - Xiaoyan Dong
- Department of Pharmacy and Medicine Pharmacy, Jiang Su College of Nursing, Huian, 223003, China
| | - Taiming Wei
- College of Pharmacy, Harbin Medical University (Daqing), Daqing 163319, China
| | - Wenmin Xing
- Zhejiang Provincial Key Lab of Geriatrics, Department of Geriatrics, Zhejiang Hospital, Hangzhou, 310013, China
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3
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Fragment-based in silico modeling of multi-target inhibitors against breast cancer-related proteins. Mol Divers 2017; 21:511-523. [PMID: 28194627 DOI: 10.1007/s11030-017-9731-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Accepted: 01/16/2017] [Indexed: 10/20/2022]
Abstract
Breast cancer is the most frequent cancer reported in women, being responsible for hundreds of thousands of deaths. Chemotherapy has proven to be effective against this malignant neoplasm depending on different biological factors such as the histopathology, grade, and stage, among others. However, breast cancer cells have become resistant to current chemotherapeutic regimens, urging the discovery of new anti-breast cancer drugs. Computational approaches have the potential to offer promising alternatives to accelerate the search for potent and versatile anti-breast cancer agents. In the present work, we introduce the first multitasking (mtk) computational model devoted to the in silico fragment-based design of new molecules with high inhibitory activity against 19 different proteins involved in breast cancer. The mtk-computational model was created from a dataset formed by 24,285 cases, and it exhibited accuracy around 93% in both training and prediction (test) sets. Several molecular fragments were extracted from the molecules present in the dataset, and their quantitative contributions to the inhibitory activities against all the proteins under study were calculated. The combined use of the fragment contributions and the physicochemical interpretations of the different molecular descriptors in the mtk-computational model allowed the design of eight new molecular entities not reported in our dataset. These molecules were predicted as potent multi-target inhibitors against all the proteins, and they exhibited a desirable druglikeness according to the Lipinski's rule of five and its variants.
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Kang MH, Moon SU, Sung JH, Kim JW, Lee KW, Lee HS, Lee JS, Kim JH. Antitumor Activity of HM781-36B, alone or in Combination with Chemotherapeutic Agents, in Colorectal Cancer Cells. Cancer Res Treat 2015; 48:355-64. [PMID: 25761479 PMCID: PMC4720083 DOI: 10.4143/crt.2014.260] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Accepted: 12/19/2014] [Indexed: 01/01/2023] Open
Abstract
Purpose HM781-36B is a novel and irreversible pan-human epidermal growth factor receptor
(HER) inhibitor with TEC cytoplasmic kinase inhibition. The aim of this study is
to evaluate the antitumor activity and mechanism of action for HM781-36B in CRC
cell lines. Materials and Methods The CRC cell lines were exposed to HM781-36B and/or oxaliplatin (L-OHP),
5-fluorouracil (5-FU), SN-38. The cell viability was examined by Cell Titer-Glo
luminescent cell viability assay kit. Change in the cell cycle and protein
expression was determined by flow cytometry and immunoblot analysis, respectively.
Synergism between 2 drugs was evaluated by the combination index. Results The addition of HM781-36B induced potent growth inhibition in both DiFi cells with
EGFR overexpression and SNU-175 cells (IC50 = 0.003 and 0.005
μM, respectively). Furthermore, HM781-36B induced G1 arrest of the cell
cycle and apoptosis, and reduced the levels of HER family and downstream signaling
molecules, pERK and pAKT, as well as nonreceptor/cytoplasmic tyrosine kinase, BMX.
The combination of HM781-36B with 5-FU, L-OHP, or SN-38 showed an additive or
synergistic effect in most CRC cells. Conclusion These findings suggest the potential roles of HM781-36B as the treatment for
EGFR-overexpressing colon cancer, singly or in combination with chemotherapeutic
agents. The role of BMX expression as a marker of response to HM781-36B should be
further explored.
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Affiliation(s)
- Mi Hyun Kang
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea ; Biomedical Research Institute, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sung Ung Moon
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea ; Biomedical Research Institute, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Ji Hea Sung
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea ; Biomedical Research Institute, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jin Won Kim
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Keun Wook Lee
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Hye Seung Lee
- Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jong Seok Lee
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Jee Hyun Kim
- Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
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Discovery of highly potent tyrosinase inhibitor, T1, with significant anti-melanogenesis ability by zebrafish in vivo assay and computational molecular modeling. Sci Rep 2015; 5:7995. [PMID: 25613357 PMCID: PMC4303873 DOI: 10.1038/srep07995] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 12/29/2014] [Indexed: 01/30/2023] Open
Abstract
Tyrosinase is involved in melanin biosynthesis and the abnormal accumulation of melanin pigments leading to hyperpigmentation disorders that can be treated with depigmenting agents. A natural product T1, bis(4-hydroxybenzyl)sulfide, isolated from the Chinese herbal plant, Gastrodia elata, is a strong competitive inhibitor against mushroom tyrosinase (IC50 = 0.53 μM, Ki = 58 ± 6 nM), outperforms than kojic acid. The cell viability and melanin quantification assay demonstrate that 50 μM of T1 apparently attenuates 20% melanin content of human normal melanocytes without significant cell toxicity. Moreover, the zebrafish in vivo assay reveals that T1 effectively reduces melanogenesis with no adverse side effects. The acute oral toxicity study evidently confirms that T1 molecule is free of discernable cytotoxicity in mice. Furthermore, the molecular modeling demonstrates that the sulfur atom of T1 coordinating with the copper ions in the active site of tyrosinase is essential for mushroom tyrosinase inhibition and the ability of diminishing the human melanin synthesis. These results evident that T1 isolated from Gastrodia elata is a promising candidate in developing pharmacological and cosmetic agents of great potency in skin-whitening.
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6
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A QSPR-like model for multilocus genotype networks of Fasciola hepatica in Northwest Spain. J Theor Biol 2014; 343:16-24. [DOI: 10.1016/j.jtbi.2013.11.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2013] [Revised: 11/08/2013] [Accepted: 11/11/2013] [Indexed: 11/23/2022]
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7
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The Rücker–Markov invariants of complex Bio-Systems: Applications in Parasitology and Neuroinformatics. Biosystems 2013; 111:199-207. [DOI: 10.1016/j.biosystems.2013.02.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Accepted: 02/11/2013] [Indexed: 11/23/2022]
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8
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Bazl R, Ganjali MR, Derakhshankhah H, Saboury AA, Amanlou M, Norouzi P. Prediction of tyrosinase inhibition for drug design using the genetic algorithm–multiple linear regressions. Med Chem Res 2013. [DOI: 10.1007/s00044-012-0440-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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9
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Sun W, Wendt M, Klebe G, Röhm KH. On the interpretation of tyrosinase inhibition kinetics. J Enzyme Inhib Med Chem 2013; 29:92-9. [PMID: 23323989 DOI: 10.3109/14756366.2012.755621] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract Tyrosinases (monophenol monooxygenases, EC 1.14.18.1) utilize a reaction mechanism that involves two intertwined catalytic cycles and at least three different ligand-binding enzyme forms. Therefore a variety of different inhibition types may arise in inhibition experiments, depending on the binding mode of the compound studied. Here we discuss a steady-state equation that describes inhibition of the diphenolase cycle of tyrosinase catalysis in a general way. In addition, we employ numerical simulations to explore the kinetic outcome of various binding schemes. As the full equation is far too complex to be applicable for data evaluation by curve fitting, we propose to use the general modifier scheme of Botts-Morales for fitting and demonstrate that especially the value of parameter α of the equation allows conclusions about the binding mode of the inhibitor. The approach is exemplified by selected data describing the inhibition of human tyrosinase by typical inhibitors.
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Affiliation(s)
- Wei Sun
- Institute of Pharmaceutical Chemistry and
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10
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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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11
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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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2010] [Accepted: 03/25/2010] [Indexed: 11/05/2022]
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12
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Ford KA, Gulevich AG, Swenson TL, Casida JE. Neonicotinoid insecticides: oxidative stress in planta and metallo-oxidase inhibition. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2011; 59:4860-7. [PMID: 21476569 DOI: 10.1021/jf200485k] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Neonicotinoids not only control insect pests but also sometimes independently alter plant growth and response to stress. We find that imidacloprid, thiacloprid, acetamiprid, thiamethoxam, and clothianidin but not nitenpyram and dinotefuran induce foliar lesions and peroxidative damage in soybean ( Glycine max ) seedlings assayed with the 3,3'-diaminobenzidine stain. The chloropyridinyl-carboxylic acid (COOH) but not the -carboxaldehyde (CHO) metabolites induce peroxidative damage but in a different pattern. Surprisingly, the chlorothiazolyl -CHO and -COOH metabolites induce chlorosis but no clear superimposable peroxidative damage or cell death. Four metallo-oxidases known to modulate reactive oxygen species were not sensitive in vitro to the parent neonicotinoid itself but were to several CHO and COOH metabolites and related compounds, with a sensitivity order of CHO > COOH and tyrosinase > xanthine oxidase and aldehyde oxidase > catalase. Although metallo-oxidase inhibition does not correlate overall with lesion formation, it may play an as yet unknown role in plant response to neonicotinoids.
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Affiliation(s)
- Kevin A Ford
- Environmental Chemistry and Toxicology Laboratory, Department of Environmental Science, Policy and Management, University of California, Berkeley, California 94720-3112, United States
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13
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Agüero-Chapin G, de la Riva GA, Molina-Ruiz R, Sánchez-Rodríguez A, Pérez-Machado G, Vasconcelos V, Antunes A. Non-linear models based on simple topological indices to identify RNase III protein members. J Theor Biol 2010; 273:167-78. [PMID: 21192951 DOI: 10.1016/j.jtbi.2010.12.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2010] [Revised: 11/15/2010] [Accepted: 12/13/2010] [Indexed: 01/27/2023]
Abstract
Alignment-free classifiers are especially useful in the functional classification of protein classes with variable homology and different domain structures. Thus, the Topological Indices to BioPolymers (TI2BioP) methodology (Agüero-Chapin et al., 2010) inspired in both the TOPS-MODE and the MARCH-INSIDE methodologies allows the calculation of simple topological indices (TIs) as alignment-free classifiers. These indices were derived from the clustering of the amino acids into four classes of hydrophobicity and polarity revealing higher sequence-order information beyond the amino acid composition level. The predictability power of such TIs was evaluated for the first time on the RNase III family, due to the high diversity of its members (primary sequence and domain organization). Three non-linear models were developed for RNase III class prediction: Decision Tree Model (DTM), Artificial Neural Networks (ANN)-model and Hidden Markov Model (HMM). The first two are alignment-free approaches, using TIs as input predictors. Their performances were compared with a non-classical HMM, modified according to our amino acid clustering strategy. The alignment-free models showed similar performances on the training and the test sets reaching values above 90% in the overall classification. The non-classical HMM showed the highest rate in the classification with values above 95% in training and 100% in test. Although the higher accuracy of the HMM, the DTM showed simplicity for the RNase III classification with low computational cost. Such simplicity was evaluated in respect to HMM and ANN models for the functional annotation of a new bacterial RNase III class member, isolated and annotated by our group.
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Affiliation(s)
- Guillermin Agüero-Chapin
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas, 177, 4050-123 Porto, Portugal
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14
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Rescigno A, Casañola-Martin GM, Sanjust E, Zucca P, Marrero-Ponce Y. Vanilloid derivatives as tyrosinase inhibitors driven by virtual screening-based QSAR models. Drug Test Anal 2010; 3:176-81. [PMID: 21125547 DOI: 10.1002/dta.187] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2010] [Revised: 08/19/2010] [Accepted: 08/19/2010] [Indexed: 11/06/2022]
Abstract
A number of vanilloids have been tested as tyrosinase inhibitors using Ligand-Based Virtual Screening (LBVS) driven by QSAR (Quantitative Structure-Activity Relationship) models as the multi-agent classification system. A total of 81 models were used to screen this family. Then, a preliminary cluster analysis of the selected chemicals was carried out based on their bioactivity to detect possible similar substructural features among these compounds and the active database used in the QSAR model construction. The compounds identified were tested in vitro to corroborate the results obtained in silico. Among them, two chemicals, isovanillin (K(M) (app) = 1.08 mM) near to kojic acid (reference drug) in one cluster and isovanillyl alcohol (K(M) (app) = 0.88 mM) at the same distance as hydroquinone (reference drug) in another cluster showed inhibitory activity against tyrosinase. The algorithm proposed here could result in a suitable approach for faster and more effective identification of hit and/or lead compounds with tyrosinase inhibitory activity, helping to shorten the long pipeline in the research of novel depigmenting agents to treat skin disorders.
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Affiliation(s)
- Antonio Rescigno
- Dipartimento di Scienze e Tecnologie Biomediche, Università di Cagliari, Cittadella Universitaria, Monserrato (CA), Italy
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Casañola-Martin GM, Marrero-Ponce Y, Khan MTH, Khan SB, Torrens F, Pérez-Jiménez F, Rescigno A, Abad C. Bond-based 2D quadratic fingerprints in QSAR studies: virtual and in vitro tyrosinase inhibitory activity elucidation. Chem Biol Drug Des 2010; 76:538-45. [PMID: 20964806 DOI: 10.1111/j.1747-0285.2010.01032.x] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In this report, we show the results of quantitative structure-activity relationship (QSAR) studies of tyrosinase inhibitory activity, by using the bond-based quadratic indices as molecular descriptors (MDs) and linear discriminant analysis (LDA), to generate discriminant functions to predict the anti-tyrosinase activity. The best two models [Eqs (6) and (12)] out of the total 12 QSAR models developed here show accuracies of 93.51% and 91.21%, as well as high Matthews correlation coefficients (C) of 0.86 and 0.82, respectively, in the training set. The validation external series depicts values of 90.00% and 89.44% for these best two equations (6) and (12), respectively. Afterwards, a second external prediction data are used to perform a virtual screening of compounds reported in the literature as active (tyrosinase inhibitors). In a final step, a series of lignans is analysed using the in silico-developed models, and in vitro corroboration of the activity is carried out. An issue of great importance to remark here is that all compounds present greater inhibition values than Kojic acid (standard tyrosinase inhibitor: IC₅₀ = 16.67 μm). The current obtained results could be used as a framework to increase the speed, in the biosilico discovery of leads for the treatment of skin disorders.
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Le-Thi-Thu H, Casañola-Martín GM, Marrero-Ponce Y, Rescigno A, Saso L, Parmar VS, Torrens F, Abad C. Novel coumarin-based tyrosinase inhibitors discovered by OECD principles-validated QSAR approach from an enlarged, balanced database. Mol Divers 2010; 15:507-20. [PMID: 20814821 DOI: 10.1007/s11030-010-9274-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2010] [Accepted: 08/16/2010] [Indexed: 12/16/2022]
Abstract
The present work is devoted to the development and application of a multi-agent Quantitative Structure-Activity Relationship (QSAR) classification system for tyrosinase inhibitor identification, in which the individual QSAR outputs are the inputs of a fusion approach based on the voting mechanism. The individual models are based on TOMOCOMD-CARDD (TOpological Molecular COMputational Design-Computer Aided Rational Drug Design) atom-based bilinear descriptors and Linear Discriminant Analysis (LDA) on a novel enlarged, balanced database of 1,429 compounds within 701 greatly dissimilar molecules presenting anti-tyrosinase activity. A total of 21 adequate models are obtained taking into account the requirements of the Organization for Economic Cooperation and Development (OECD) principles for QSAR validation and present global accuracies (Q) above 84.50 and 79.27% in the training and test sets, respectively. The resulted fusion system is used for the in silico identification of synthesized coumarin derivatives as novel tyrosinase inhibitors. The 7-hydroxycoumarin (compound C07) shows potent activity for the inhibition of monophenolase activity of mushroom tyrosinase giving a value of inhibition percentage close to 100% in vitro assays, by means of spectrophotometric analysis. The current report could help to shed some clues in the identification of new chemicals that inhibit tyrosinase enzyme, for entering in the pipeline of drug discovery development.
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Affiliation(s)
- Huong Le-Thi-Thu
- Unit of Computer-Aided Molecular Biosilico Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara, Villa Clara, 54830, Cuba
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17
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García I, Fall Y, Gómez G. Using topological indices to predict anti-Alzheimer and anti-parasitic GSK-3 inhibitors by multi-target QSAR in silico screening. Molecules 2010; 15:5408-22. [PMID: 20714305 PMCID: PMC6257681 DOI: 10.3390/molecules15085408] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2010] [Revised: 07/27/2010] [Accepted: 08/02/2010] [Indexed: 01/20/2023] Open
Abstract
Plasmodium falciparum, Leishmania, Trypanosomes, are the causers of diseases such as malaria, leishmaniasis and African trypanosomiasis that nowadays are the most serious parasitic health problems worldwide. The great number of deaths and the few drugs available against these parasites, make necessary the search for new drugs. Some of these antiparasitic drugs also are GSK-3 inhibitors. GSKI-3 are candidates to develop drugs for the treatment of Alzheimer's disease. In this work topological descriptors for a large series of 3,370 active/non-active compounds were initially calculated with the ModesLab software. Linear Discriminant Analysis was used to fit the classification function and it predicts heterogeneous series of compounds like paullones, indirubins, meridians, etc. This study thus provided a general evaluation of these types of molecules.
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Affiliation(s)
- Isela García
- Department of Organic Chemistry, Faculty of Chemistry, University of Vigo, Spain.
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18
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Ortega-Broche SE, Marrero-Ponce Y, Díaz YE, Torrens F, Pérez-Giménez F. tomocomd-camps and protein bilinear indices - novel bio-macromolecular descriptors for protein research: I. Predicting protein stability effects of a complete set of alanine substitutions in the Arc repressor. FEBS J 2010; 277:3118-46. [DOI: 10.1111/j.1742-4658.2010.07711.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Castillo-Garit JA, Vega MC, Rolon M, Marrero-Ponce Y, Kouznetsov VV, Torres DFA, Gómez-Barrio A, Bello AA, Montero A, Torrens F, Pérez-Giménez F. Computational discovery of novel trypanosomicidal drug-like chemicals by using bond-based non-stochastic and stochastic quadratic maps and linear discriminant analysis. Eur J Pharm Sci 2009; 39:30-6. [PMID: 19854271 DOI: 10.1016/j.ejps.2009.10.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2009] [Revised: 10/01/2009] [Accepted: 10/13/2009] [Indexed: 11/28/2022]
Abstract
Herein we present results of a quantitative structure-activity relationship (QSAR) studies to classify and design, in a rational way, new antitrypanosomal compounds by using non-stochastic and stochastic bond-based quadratic indices. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop QSAR models based on linear discriminant analysis (LDA). Non-stochastic model correctly classifies more than 93% and 95% of chemicals in both training and external prediction groups, respectively. On the other hand, the stochastic model shows an accuracy of about the 87% for both series. As an experiment of virtual lead generation, the present approach is finally satisfactorily applied to the virtual evaluation of 9 already synthesized in house compounds. The in vitro antitrypanosomal activity of this series against epimastigote forms of Trypanosoma cruzi is assayed. The model is able to predict correctly the behaviour for the majority of these compounds. Four compounds (FER16, FER32, FER33 and FER 132) showed more than 70% of epimastigote inhibition at a concentration of 100 microg/mL (86.74%, 78.12%, 88.85% and 72.10%, respectively) and two of these chemicals, FER16 (78.22% of AE) and FER33 (81.31% of AE), also showed good activity at a concentration of 10 microg/mL. At the same concentration, compound FER16 showed lower value of cytotoxicity (15.44%), and compound FER33 showed very low value of 1.37%. Taking into account all these results, we can say that these three compounds can be optimized in forthcoming works, but we consider that compound FER33 is the best candidate. Even though none of them resulted more active than Nifurtimox, the current results constitute a step forward in the search for efficient ways to discover new lead antitrypanosomals.
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Affiliation(s)
- Juan Alberto Castillo-Garit
- Applied Chemistry Research Center, Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba.
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Variations in IC(50) values with purity of mushroom tyrosinase. Int J Mol Sci 2009; 10:3811-3823. [PMID: 19865520 PMCID: PMC2769143 DOI: 10.3390/ijms10093811] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2009] [Revised: 08/19/2009] [Accepted: 08/31/2009] [Indexed: 11/16/2022] Open
Abstract
The effects of various inhibitors on crude, commercial and partially purified commercial mushroom tyrosinase were examined by comparing IC(50) values. Kojic acid, salicylhydroxamic acid, tropolone, methimazole, and ammonium tetrathiomolybdate had relatively similar IC(50) values for the crude, commercial and partially purified enzyme. 4-Hexylresorcinol seemed to have a somewhat higher IC(50) value using crude extracts, compared to commercial or purified tyrosinase. Some inhibitors (NaCl, esculetin, biphenol, phloridzin) showed variations in IC(50) values between the enzyme samples. In contrast, hydroquinone, lysozyme, Zn(2+), and anisaldehyde showed little or no inhibition in concentration ranges reported to be effective inhibitors. Organic solvents (DMSO and ethanol) had IC(50) values that were similar for some of the tyrosinase samples. Depending of the source of tyrosinase and choice of inhibitor, variations in IC(50) values were observed.
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Nucleotide's bilinear indices: novel bio-macromolecular descriptors for bioinformatics studies of nucleic acids. I. Prediction of paromomycin's affinity constant with HIV-1 Psi-RNA packaging region. J Theor Biol 2009; 259:229-41. [PMID: 19272394 DOI: 10.1016/j.jtbi.2009.02.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2008] [Revised: 02/24/2009] [Accepted: 02/25/2009] [Indexed: 02/03/2023]
Abstract
A new set of nucleotide-based bio-macromolecular descriptors are presented. This novel approach to bio-macromolecular design from a linear algebra point of view is relevant to nucleic acids quantitative structure-activity relationship (QSAR) studies. These bio-macromolecular indices are based on the calculus of bilinear maps on Re(n)[b(mk)(x (m),y (m)):Re(n) x Re(n)-->Re] in canonical basis. Nucleic acid's bilinear indices are calculated from kth power of non-stochastic and stochastic nucleotide's graph-theoretic electronic-contact matrices, M(m)(k) and (s)M(m)(k), respectively. That is to say, the kth non-stochastic and stochastic nucleic acid's bilinear indices are calculated using M(m)(k) and (s)M(m)(k) as matrix operators of bilinear transformations. Moreover, biochemical information is codified by using different pair combinations of nucleotide-base properties as weightings (experimental molar absorption coefficient epsilon(260) at 260 nm and pH=7.0, first (Delta E(1)) and second (Delta E(2)) single excitation energies in eV, and first (f(1)) and second (f(2)) oscillator strength values (of the first singlet excitation energies) of the nucleotide DNA-RNA bases. As example of this approach, an interaction study of the antibiotic paromomycin with the packaging region of the HIV-1 Psi-RNA have been performed and it have been obtained several linear models in order to predict the interaction strength. The best linear model obtained by using non-stochastic bilinear indices explains about 91% of the variance of the experimental Log K (R=0.95 and s=0.08 x 10(-4)M(-1)) as long as the best stochastic bilinear indices-based equation account for 93% of the Log K variance (R=0.97 and s=0.07 x 10(-4)M(-1)). The leave-one-out (LOO) press statistics, evidenced high predictive ability of both models (q(2)=0.86 and s(cv)=0.09 x 10(-4)M(-1) for non-stochastic and q(2)=0.91 and s(cv)=0.08 x 10(-4)M(-1) for stochastic bilinear indices). The nucleic acid's bilinear indices-based models compared favorably with other nucleic acid's indices-based approaches reported nowadays. These models also permit the interpretation of the driving forces of the interaction process. In this sense, developed equations involve short-reaching (k<or=3), middle-reaching (4<k<9), and far-reaching (k=10 or greater) nucleotide's bilinear indices. This situation points to electronic and topologic nucleotide's backbone interactions control of the stability profile of paromomycin-RNA complexes. Consequently, the present approach represents a novel and rather promising way to theoretical-biology studies.
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Agüero-Chapín G, Antunes A, Ubeira FM, Chou KC, González-Díaz H. Comparative study of topological indices of macro/supramolecular RNA complex networks. J Chem Inf Model 2009; 48:2265-77. [PMID: 18937437 DOI: 10.1021/ci8001809] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
RNA function annotation is often based on alignment to a previously studied template. In contrast to the study of proteins, there are not many alignment-free methods to predict RNA functions if alignment fails. The use of topological indices (TIs) of RNA complex networks (CNs) to find quantitative structure-activity relationships (QSAR) may be an alternative to incorporate secondary structure or sequence-to-sequence similarity. Here, we introduce new QSAR-like techniques using RNA macromolecular CNs (mmCNs), where nodes are nucleotides, or RNA supramolecular CNs (smCNs), where nodes are RNA sequences. We studied a data set of 198 sequences including 18S-rRNAs (important phylogenetic molecular biomarkers). We constructed three types of RNA mmCNs: sequence-linear (SL), Cartesian-lattice (CL), and sequence-folding CNs (SF-CNs) and two smCNs: sequence-sequence disagreement CN (SSD) and sequence-sequence similarity (SSS-smCN). We reported the first comparative QSAR study with all these CIs and CNs, which includes: (i) spectral moments ( ( i )micro d ( w)) of SL-mmCNs (accuracy = 75.3%), (ii) electrostatic CIs (xi d ) of CL-mmCNs (>90%), (iii) thermodynamic parameters (Delta G, Delta H, Delta S, and T m) of SF-mmCNs (64.7%), (iv) disagreement-distribution moments ( M k ) of the SSD-smCN (79.3%), and (v) node centralities of the SSD-smCN (78.0%). Furthermore, we reported the experimental isolation of a new RNA sequence from Psidum guajava leaf tissue and its QSAR and BLAST prediction to illustrate the practical use of these methods. We also investigated the use of these CNs to explore rRNA diversity on bacteria, plants, and parasites from the Dactylogyrus genus. The HPL-mmCNs model was the best of all found. All the CNs and TIs, except SF-mmCNs, were introduced here by the first time for the QSAR study of RNA, which allowed a comparative study for RNA classification.
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Affiliation(s)
- Guillermín Agüero-Chapín
- Department of Microbiology & Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Santiago de Compostela 15782, Spain.
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García I, Munteanu CR, Fall Y, Gómez G, Uriarte E, González-Díaz H. QSAR and complex network study of the chiral HMGR inhibitor structural diversity. Bioorg Med Chem 2009; 17:165-75. [DOI: 10.1016/j.bmc.2008.11.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2008] [Revised: 10/31/2008] [Accepted: 11/06/2008] [Indexed: 10/21/2022]
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Dea-Ayuela MA, Pérez-Castillo Y, Meneses-Marcel A, Ubeira FM, Bolas-Fernández F, Chou KC, González-Díaz H. HP-Lattice QSAR for dynein proteins: experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence. Bioorg Med Chem 2008; 16:7770-6. [PMID: 18662882 DOI: 10.1016/j.bmc.2008.07.023] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2008] [Revised: 06/23/2008] [Accepted: 07/02/2008] [Indexed: 10/21/2022]
Abstract
The toxicity and inefficacy of actual organic drugs against Leishmaniosis justify research projects to find new molecular targets in Leishmania species including Leishmania infantum (L. infantum) and Leishmaniamajor (L. major), both important pathogens. In this sense, quantitative structure-activity relationship (QSAR) methods, which are very useful in Bioorganic and Medicinal Chemistry to discover small-sized drugs, may help to identify not only new drugs but also new drug targets, if we apply them to proteins. Dyneins are important proteins of these parasites governing fundamental processes such as cilia and flagella motion, nuclear migration, organization of the mitotic splinde, and chromosome separation during mitosis. However, despite the interest for them as potential drug targets, so far there has been no report whatsoever on dyneins with QSAR techniques. To the best of our knowledge, we report here the first QSAR for dynein proteins. We used as input the Spectral Moments of a Markov matrix associated to the HP-Lattice Network of the protein sequence. The data contain 411 protein sequences of different species selected by ClustalX to develop a QSAR that correctly discriminates on average between 92.75% and 92.51% of dyneins and other proteins in four different train and cross-validation datasets. We also report a combined experimental and theoretic study of a new dynein sequence in order to illustrate the utility of the model to search for potential drug targets with a practical example. First, we carried out a 2D-electrophoresis analysis of L. infantum biological samples. Next, we excised from 2D-E gels one spot of interest belonging to an unknown protein or protein fragment in the region M<20,200 and pI<4. We used MASCOT search engine to find proteins in the L. major data base with the highest similarity score to the MS of the protein isolated from L. infantum. We used the QSAR model to predict the new sequence as dynein with probability of 99.99% without relying upon alignment. In order to confirm the previous function annotation we predicted the sequences as dynein with BLAST and the omniBLAST tools (96% alignment similarity to dyneins of other species). Using this combined strategy, we have successfully identified L. infantum protein containing dynein heavy chain, and illustrated the potential use of the QSAR model as a complement to alignment tools.
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Flurkey A, Cooksey J, Reddy A, Spoonmore K, Rescigno A, Inlow J, Flurkey WH. Enzyme, protein, carbohydrate, and phenolic contaminants in commercial tyrosinase preparations: potential problems affecting tyrosinase activity and inhibition studies. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2008; 56:4760-4768. [PMID: 18500813 DOI: 10.1021/jf800109a] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Commercial mushroom tyrosinase contains other proteins, enzymes, carbohydrates, and phenolic material besides tyrosinase. Carbohydrate and phenolic material comprise a large percentage of the powder resuspensions derived from Agaricus bisporus. Enzyme assays identified the presence of tyrosinase, laccase, beta-glucosidase, beta-galactosidase, beta-xylosidase, cellulase, chitinase, xylanase, and mannanase in the commercial tyrosinase. Protein sequencing indicated the presence of tyrosinase, a lectin, and a putative mannanase as well as 10 unidentified protein/peptides in the commercial tyrosinase preparations. Characteristics of tyrosinase isoforms were similar in two different commercial tyrosinase sources. Inhibition studies indicated that I 50 values for some tyrosinase inhibitors were different when the crude powder was compared to a partially purified tyrosinase. The presence of these contaminants has the potential to affect studies using commercial tyrosinase.
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Affiliation(s)
- Allison Flurkey
- Department of Chemistry, Indiana State University, Terre Haute, Indiana 47809, USA.
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Prado-Prado FJ, González-Díaz H, de la Vega OM, Ubeira FM, Chou KC. Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds. Bioorg Med Chem 2008; 16:5871-80. [PMID: 18485714 DOI: 10.1016/j.bmc.2008.04.068] [Citation(s) in RCA: 104] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2008] [Revised: 04/22/2008] [Accepted: 04/25/2008] [Indexed: 10/22/2022]
Abstract
Several pathogen parasite species show different susceptibilities to different antiparasite drugs. Unfortunately, almost all structure-based methods are one-task or one-target Quantitative Structure-Activity Relationships (ot-QSAR) that predict the biological activity of drugs against only one parasite species. Consequently, multi-tasking learning to predict drugs activity against different species by a single model (mt-QSAR) is vitally important. In the two previous works of the present series we reported two single mt-QSAR models in order to predict the antimicrobial activity against different fungal (Bioorg. Med. Chem.2006, 14, 5973-5980) or bacterial species (Bioorg. Med. Chem.2007, 15, 897-902). These mt-QSARs offer a good opportunity (unpractical with ot-QSAR) to construct drug-drug similarity Complex Networks and to map the contribution of sub-structures to function for multiple species. These possibilities were unattended in our previous works. In the present work, we continue this series toward other important direction of chemotherapy (antiparasite drugs) with the development of an mt-QSAR for more than 500 drugs tested in the literature against different parasites. The data were processed by Linear Discriminant Analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 212 out of 244 (87.0%) cases in training series and 207 out of 243 compounds (85.4%) in external validation series. In order to illustrate the performance of the QSAR for the selection of active drugs we carried out an additional virtual screening of antiparasite compounds not used in training or predicting series; the model recognized 97 out of 114 (85.1%) of them. We also give the procedures to construct back-projection maps and to calculate sub-structures contribution to the biological activity. Finally, we used the outputs of the QSAR to construct, by the first time, a multi-species Complex Networks of antiparasite drugs. The network predicted has 380 nodes (compounds), 634 edges (pairs of compounds with similar activity). This network allows us to cluster different compounds and identify on average three known compounds similar to a new query compound according to their profile of biological activity. This is the first attempt to calculate probabilities of antiparasitic action of drugs against different parasites.
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Casañola-Martín GM, Marrero-Ponce Y, Khan MTH, Ather A, Khan KM, Torrens F, Rotondo R. Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays. Eur J Med Chem 2007; 42:1370-81. [PMID: 17637486 DOI: 10.1016/j.ejmech.2007.01.026] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2006] [Revised: 01/18/2007] [Accepted: 01/19/2007] [Indexed: 10/23/2022]
Abstract
QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors employing Dragon descriptors and linear discriminant analysis (LDA) are presented here. A data set of 653 compounds, 245 with tyrosinase inhibitory activity and 408 having other clinical uses were used. The active data set was processed by k-means cluster analysis in order to design training and prediction series. Seven LDA-based QSAR models were obtained. The discriminant functions applied showed a globally good classification of 99.79% for the best model Class=-96.067+1.988 x 10(2)X0Av +9 1.907 BIC3 + 6.853 CIC1 in the training set. External validation processes to assess the robustness and predictive power of the obtained model were carried out. This external prediction set had an accuracy of 99.44%. After that, the developed models were used in ligand-based virtual screening of tyrosinase inhibitors from the literature and never considered in either training or predicting series. In this case, all screened chemicals were correctly classified by the LDA-based QSAR models. As a final point, these fitted models were used in the screening of new bipiperidine series as new tyrosinase inhibitors. These methods are an adequate alternative to the process of selection/identification of new bioactive compounds. The biosilico assays and in vitro results of inhibitory activity on mushroom tyrosinase showed good correspondence. It is important to stand out that compound BP4 (IC(50)=1.72 microM) showed higher activity in the inhibition against the enzyme than reference compound kojic acid (IC(50)=16.67 microM) and l-mimosine (IC(50)=3.68 microM). These results support the role of biosilico algorithm for the identification of new tyrosinase inhibitor compounds.
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Affiliation(s)
- Gerardo M Casañola-Martín
- Unit of Computer-Aided Molecular Biosilico Discovery and Bioinformatic Research (CAMD-BIR Unit), Department of Pharmacy, Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara, 54830 Villa Clara, Cuba
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