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Hsiao NW, Tseng TS, Lee YC, Chen WC, Lin HH, Chen YR, Wang YT, Hsu HJ, Tsai KC. Serendipitous discovery of short peptides from natural products as tyrosinase inhibitors. J Chem Inf Model 2014; 54:3099-111. [PMID: 25317506 DOI: 10.1021/ci500370x] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Tyrosinase, which is the crucial copper-containing enzyme involved in melanin synthesis, is strongly associated with hyperpigmentation disorders, cancer, and neurodegenerative disease; thus, it has attracted considerable interest in the fields of medicine and cosmetics. The known tyrosinase inhibitors show numerous adverse side effects, and there is a lack of safety regulations governing their use. As a result, there is a need to develop novel inhibitors with no toxicity and long-term stability. In this study, we use molecular docking and pharmacophore modeling to construct a reasonable and reliable pharmacophore model, called Hypo 1, that could be used for identifying potent natural products with crucial complementary functional groups for mushroom tyrosinase inhibition. It was observed that, out of 47,263 natural compounds, A5 structurally resembles a dipeptide (WY) and natural compound B16 is the equivalent of a tripeptide (KFY), revealing that the C-terminus tyrosine residues play a key role in tyrosinase inhibition. Tripeptides RCY and CRY, which show high tyrosinase inhibitory potency, revealed a positional and functional preference for the cysteine residue at the N-terminus of the tripeptides, essentially determining the capacity of tyrosinase inhibition. CRY and RCY used the thiol group of cysteine residues to coordinate with the Cu ions in the active site of tyrosinase and showed reduced tyrosinase activity. We discovered the novel tripeptide CRY that shows the most striking inhibitory potency against mushroom tyrosinase (IC50 = 6.16 μM); this tripeptide is more potent than the known oligopeptides and comparable with kojic acid-tripeptides. Our study provides an insight into the structural and functional roles of key amino acids of tripeptides derived from the natural compound B16, and the results are expected to be useful for the development of tyrosinase inhibitors.
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Affiliation(s)
- Nai-Wan Hsiao
- Institute of Biotechnology, National Changhua University of Education , Changhua 500, Taiwan
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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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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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Speck-Planche A, Kleandrova VV, Luan F, Cordeiro MND. Fragment-based QSAR model toward the selection of versatile anti-sarcoma leads. Eur J Med Chem 2011; 46:5910-6. [DOI: 10.1016/j.ejmech.2011.09.055] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2011] [Revised: 09/24/2011] [Accepted: 09/29/2011] [Indexed: 12/17/2022]
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Speck-Planche A, Kleandrova VV, Luan F, Cordeiro MND. Multi-target drug discovery in anti-cancer therapy: Fragment-based approach toward the design of potent and versatile anti-prostate cancer agents. Bioorg Med Chem 2011; 19:6239-44. [DOI: 10.1016/j.bmc.2011.09.015] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2011] [Revised: 07/24/2011] [Accepted: 09/08/2011] [Indexed: 11/25/2022]
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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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Speck-Planche A, Guilarte-Montero L, Yera-Bueno R, Rojas-Vargas JA, García-López A, Uriarte E, Molina-Pérez E. Rational design of new agrochemical fungicides using substructural descriptors. PEST MANAGEMENT SCIENCE 2011; 67:438-445. [PMID: 21394877 DOI: 10.1002/ps.2082] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2010] [Revised: 09/28/2010] [Accepted: 09/29/2010] [Indexed: 05/30/2023]
Abstract
BACKGROUND The increasing resistance of several phytopathogenic fungal species to existing agrochemical fungicides has alarmed the worldwide scientific community. In an attempt to overcome this problem, a discriminant model based on substructural descriptors was developed from a heterogeneous database of compounds for the design of, search for and prediction of agrochemical fungicides. RESULTS The discriminant model classifies correctly 81.95% of the fungicides and 81.54% of the inactive compounds in the training series, with an accuracy of 81.72%. In the prediction series, the percentage of correct classification was 80.59 and 85.56% for fungicides and inactive compounds respectively, with an accuracy of 83.44%. Some fragments were extracted and their contributions were calculated. From the fragments that were determined to make positive contributions to the fungicidal activity, new molecules such as pyrrole derivatives were designed and the probabilities of their being fungicides were calculated. These molecules were correctly classified as potential fungicides. CONCLUSION The discriminant model based on substructural descriptors provides a promising methodology for the development of molecular patterns to be used in the design of, search for and prediction of agrochemical fungicides of wide spectrum. This constitutes an alternative for the discovery of compounds that are able to decrease crop losses caused by phytopathogenic fungal species.
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Affiliation(s)
- Alejandro Speck-Planche
- Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Santiago de Compostela, Spain.
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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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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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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 J, Marrero-Ponce Y, Torrens F, García-Domenech R, Rodríguez-Borges J. Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification. ACTA ACUST UNITED AC 2009. [DOI: 10.1002/qsar.200960085] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Prado-Prado FJ, Martinez de la Vega O, Uriarte E, Ubeira FM, Chou KC, González-Díaz H. Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug-drug complex networks. Bioorg Med Chem 2008; 17:569-75. [PMID: 19112024 DOI: 10.1016/j.bmc.2008.11.075] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2008] [Revised: 11/24/2008] [Accepted: 11/28/2008] [Indexed: 11/18/2022]
Abstract
One limitation of almost all antiviral Quantitative Structure-Activity Relationships (QSAR) models is that they predict the biological activity of drugs against only one species of virus. Consequently, the development of multi-tasking QSAR models (mt-QSAR) to predict drugs activity against different species of virus is of the major vitally important. These mt-QSARs offer also a good opportunity to construct drug-drug Complex Networks (CNs) that can be used to explore large and complex drug-viral species databases. It is known that in very large CNs we can use the Giant Component (GC) as a representative sub-set of nodes (drugs) and but the drug-drug similarity function selected may strongly determines the final network obtained. In the three previous works of the present series we reported mt-QSAR models to predict the antimicrobial activity against different fungi [Gonzalez-Diaz, H.; Prado-Prado, F. J.; Santana, L.; Uriarte, E. Bioorg.Med.Chem.2006, 14, 5973], bacteria [Prado-Prado, F. J.; Gonzalez-Diaz, H.; Santana, L.; Uriarte E. Bioorg.Med.Chem.2007, 15, 897] or parasite species [Prado-Prado, F.J.; González-Díaz, H.; Martinez de la Vega, O.; Ubeira, F.M.; Chou K.C. Bioorg.Med.Chem.2008, 16, 5871]. However, including these works, we do not found any report of mt-QSAR models for antivirals drug, or a comparative study of the different GC extracted from drug-drug CNs based on different similarity functions. In this work, we used Linear Discriminant Analysis (LDA) to fit a mt-QSAR model that classify 600 drugs as active or non-active against the 41 different tested species of virus. The model correctly classifies 143 of 169 active compounds (specificity=84.62%) and 119 of 139 non-active compounds (sensitivity=85.61%) and presents overall training accuracy of 85.1% (262 of 308 cases). Validation of the model was carried out by means of external predicting series, classifying the model 466 of 514, 90.7% of compounds. In order to illustrate the performance of the model in practice, we develop a virtual screening recognizing the model as active 92.7%, 102 of 110 antivirus compounds. These compounds were never use in training or predicting series. Next, we obtained and compared the topology of the CNs and their respective GCs based on Euclidean, Manhattan, Chebychey, Pearson and other similarity measures. The GC of the Manhattan network showed the more interesting features for drug-drug similarity search. We also give the procedure for the construction of Back-Projection Maps for the contribution of each drug sub-structure to the antiviral activity against different species.
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Affiliation(s)
- Francisco J Prado-Prado
- Department of Microbiology and Parasitology, Faculty of Pharmacy, University of Santiago de Compostela, Santiago de Compostela 15782, Spain
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Rivera-Borroto O, Marrero-Ponce Y, Meneses-Marcel A, Escario J, Gómez Barrio A, Arán V, Martins Alho M, Montero Pereira D, Nogal J, Torrens F, Ibarra-Velarde F, Montenegro Y, Huesca-Guillén A, Rivera N, Vogel C. Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors. ACTA ACUST UNITED AC 2008. [DOI: 10.1002/qsar.200610165] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Casañola-Martín GM, Marrero-Ponce Y, Tareq Hassan Khan M, Torrens F, Pérez-Giménez F, Rescigno A. Atom- and bond-based 2D TOMOCOMD-CARDD approach and ligand-based virtual screening for the drug discovery of new tyrosinase inhibitors. ACTA ACUST UNITED AC 2008; 13:1014-24. [PMID: 19015291 DOI: 10.1177/1087057108326078] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Two-dimensional atom- and bond-based TOMOCOMD-CARDD descriptors and linear discriminant analysis (LDA) are used in this report to perform a quantitative structure-activity relationship (QSAR) study of tyrosinase-inhibitory activity. A database of inhibitors of the enzyme is collected for this study, within 246 highly dissimilar molecules presenting antityrosinase activity. In total, 7 discriminant functions are obtained by using the whole set of atom- and bond-based 2D indices. All the LDA-based QSAR models show accuracies above 90% in the training set and values of the Matthews correlation coefficient (C) varying from 0.85 to 0.90. The external validation set shows globally good classifications between 89% and 91% and C values ranging from 0.75 to 0.81. Finally, QSAR models are used in the selection/identification of the 20 new dicoumarins subset to search for tyrosinase inhibitory activity. Theoretical and experimental results show good correspondence between one another. It is important to remark that most compounds in this series exhibit a more potent inhibitory activity against the mushroom tyrosinase enzyme than the reference compound, Kojic acid (IC(50) = 16.67 muM), resulting in a novel nucleus base (lead) with antityrosinase activity, and this could serve as a starting point for the drug discovery of novel tyrosinase inhibitor lead compounds. ( Journal of Biomolecular Screening 2008:1014-1024).
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