Literature DB >> 23855599

Model for high-throughput screening of multitarget drugs in chemical neurosciences: synthesis, assay, and theoretic study of rasagiline carbamates.

Nerea Alonso1, Olga Caamaño, Francisco J Romero-Duran, Feng Luan, M Natália D S Cordeiro, Matilde Yañez, Humberto González-Díaz, Xerardo García-Mera.   

Abstract

The disappointing results obtained in recent clinical trials renew the interest in experimental/computational techniques for the discovery of neuroprotective drugs. In this context, multitarget or multiplexing QSAR models (mt-QSAR/mx-QSAR) may help to predict neurotoxicity/neuroprotective effects of drugs in multiple assays, on drug targets, and in model organisms. In this work, we study a data set downloaded from CHEMBL; each data point (>8000) contains the values of one out of 37 possible measures of activity, 493 assays, 169 molecular or cellular targets, and 11 different organisms (including human) for a given compound. In this work, we introduce the first mx-QSAR model for neurotoxicity/neuroprotective effects of drugs based on the MARCH-INSIDE (MI) method. First, we used MI to calculate the stochastic spectral moments (structural descriptors) of all compounds. Next, we found a model that classified correctly 2955 out of 3548 total cases in the training and validation series with Accuracy, Sensitivity, and Specificity values>80%. The model also showed excellent results in Computational-Chemistry simulations of High-Throughput Screening (CCHTS) experiments, with accuracy=90.6% for 4671 positive cases. Next, we reported the synthesis, characterization, and experimental assays of new rasagiline derivatives. We carried out three different experimental tests: assay (1) in the absence of neurotoxic agents, assay (2) in the presence of glutamate, and assay (3) in the presence of H2O2. Compounds 11 with 27.4%, 8 with 11.6%, and 9 with 15.4% showed the highest neuroprotective effects in assays (1), (2), and (3), respectively. After that, we used the mx-QSAR model to carry out a CCHTS of the new compounds in >400 unique pharmacological tests not carried out experimentally. Consequently, this model may become a promising auxiliary tool for the discovery of new drugs for the treatment of neurodegenerative diseases.

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Year:  2013        PMID: 23855599      PMCID: PMC3799003          DOI: 10.1021/cn400111n

Source DB:  PubMed          Journal:  ACS Chem Neurosci        ISSN: 1948-7193            Impact factor:   4.418


  67 in total

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Authors:  E Estrada; E Uriarte
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2.  TOMOCOMD-CARDD, a novel approach for computer-aided 'rational' drug design: I. Theoretical and experimental assessment of a promising method for computational screening and in silico design of new anthelmintic compounds.

Authors:  Yovani Marrero-Ponce; Juan A Castillo-Garit; Ervelio Olazabal; Hector S Serrano; Alcidez Morales; Nilo Castañedo; Froylán Ibarra-Velarde; Alma Huesca-Guillen; Elisa Jorge; Arletys del Valle; Francisco Torrens; Eduardo A Castro
Journal:  J Comput Aided Mol Des       Date:  2004-10       Impact factor: 3.686

3.  Using the TOPS-MODE approach to fit multi-target QSAR models for tyrosine kinases inhibitors.

Authors:  Giovanni Marzaro; Adriana Chilin; Adriano Guiotto; Eugenio Uriarte; Paola Brun; Ignazio Castagliuolo; Francesca Tonus; Humberto González-Díaz
Journal:  Eur J Med Chem       Date:  2011-03-11       Impact factor: 6.514

Review 4.  Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network.

Authors:  Marcos Martínez-Romero; José M Vázquez-Naya; Juan R Rabuñal; Salvador Pita-Fernández; Ramiro Macenlle; Javier Castro-Alvariño; Leopoldo López-Roses; José L Ulla; Antonio V Martínez-Calvo; Santiago Vázquez; Javier Pereira; Ana B Porto-Pazos; Julián Dorado; Alejandro Pazos; Cristian R Munteanu
Journal:  Curr Drug Metab       Date:  2010-05       Impact factor: 3.731

5.  Allo-network drugs: harnessing allostery in cellular networks.

Authors:  Ruth Nussinov; Chung-Jung Tsai; Peter Csermely
Journal:  Trends Pharmacol Sci       Date:  2011-09-16       Impact factor: 14.819

6.  Quantitative structure-toxicity relationships using TOPS-MODE. 2. Neurotoxicity of a non-congeneric series of solvents.

Authors:  E Estrada; E Molina; E Uriarte
Journal:  SAR QSAR Environ Res       Date:  2001       Impact factor: 3.000

7.  Multiplexing cell viability assays.

Authors:  Helga H J Gerets; Stéphane Dhalluin; Franck A Atienzar
Journal:  Methods Mol Biol       Date:  2011

8.  Trypano-PPI: a web server for prediction of unique targets in trypanosome proteome by using electrostatic parameters of protein-protein interactions.

Authors:  Yamilet Rodriguez-Soca; Cristian R Munteanu; Julián Dorado; Alejandro Pazos; Francisco J Prado-Prado; Humberto González-Díaz
Journal:  J Proteome Res       Date:  2010-02-05       Impact factor: 4.466

Review 9.  Amyotrophic lateral sclerosis.

Authors:  Albert C Ludolph; Johannes Brettschneider; Jochen H Weishaupt
Journal:  Curr Opin Neurol       Date:  2012-10       Impact factor: 5.710

Review 10.  Subtype-selective allosteric modulators of muscarinic receptors for the treatment of CNS disorders.

Authors:  P Jeffrey Conn; Carrie K Jones; Craig W Lindsley
Journal:  Trends Pharmacol Sci       Date:  2009-02-07       Impact factor: 14.819

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  6 in total

1.  Multi-output model with Box-Jenkins operators of linear indices to predict multi-target inhibitors of ubiquitin-proteasome pathway.

Authors:  Gerardo M Casañola-Martin; Huong Le-Thi-Thu; Facundo Pérez-Giménez; Yovani Marrero-Ponce; Matilde Merino-Sanjuán; Concepción Abad; Humberto González-Díaz
Journal:  Mol Divers       Date:  2015-03-10       Impact factor: 2.943

2.  PTML modeling for peptide discovery: in silico design of non-hemolytic peptides with antihypertensive activity.

Authors:  Valeria V Kleandrova; Julio A Rojas-Vargas; Marcus T Scotti; Alejandro Speck-Planche
Journal:  Mol Divers       Date:  2021-11-21       Impact factor: 3.364

3.  Prediction of multi-target networks of neuroprotective compounds with entropy indices and synthesis, assay, and theoretical study of new asymmetric 1,2-rasagiline carbamates.

Authors:  Francisco J Romero Durán; Nerea Alonso; Olga Caamaño; Xerardo García-Mera; Matilde Yañez; Francisco J Prado-Prado; Humberto González-Díaz
Journal:  Int J Mol Sci       Date:  2014-09-24       Impact factor: 5.923

4.  Computer-Aided Drug Design Applied to Marine Drug Discovery: Meridianins as Alzheimer's Disease Therapeutic Agents.

Authors:  Laura Llorach-Pares; Alfons Nonell-Canals; Melchor Sanchez-Martinez; Conxita Avila
Journal:  Mar Drugs       Date:  2017-11-27       Impact factor: 5.118

Review 5.  Neuroprotective Function of Rasagiline and Selegiline, Inhibitors of Type B Monoamine Oxidase, and Role of Monoamine Oxidases in Synucleinopathies.

Authors:  Makoto Naoi; Wakako Maruyama; Masayo Shamoto-Nagai
Journal:  Int J Mol Sci       Date:  2022-09-21       Impact factor: 6.208

6.  Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents.

Authors:  Amit Kumar Halder; Amal Kanta Giri; Maria Natália Dias Soeiro Cordeiro
Journal:  Molecules       Date:  2019-10-30       Impact factor: 4.411

  6 in total

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