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Int. J. Mol. Sci. 2014, 15(9), 17035-17064; doi:10.3390/ijms150917035

Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates

1
Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela (USC), Santiago de Compostela 15782, Spain
2
Department of Pharmacology, University of Santiago de Compostela (USC), Santiago de Compostela 15782, Spain
3
Biomedical Sciences Department, Health Sciences Division, University of Quintana Roo (UQROO), Chetumal 77039, Mexico
4
Department of Organic Chemistry II, Faculty of Science and Technology, University of the Basque Country UPV/EHU, Leioa 48940, Spain
5
IKERBASQUE, Basque Foundation for Science, Bilbao 48011, Spain
*
Authors to whom correspondence should be addressed.
Received: 11 March 2014 / Revised: 19 August 2014 / Accepted: 21 August 2014 / Published: 24 September 2014
(This article belongs to the Special Issue Molecular Science for Drug Development and Biomedicine)
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Abstract

In a multi-target complex network, the links (Lij) represent the interactions between the drug (di) and the target (tj), characterized by different experimental measures (Ki, Km, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (cj). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%–90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally. View Full-Text
Keywords: CHEMBL; neuroprotective agents; rasagiline derivatives; asymmetric synthesis; multi-target drugs; molecular information measures; Shannon entropy; Markov chains; moving averages CHEMBL; neuroprotective agents; rasagiline derivatives; asymmetric synthesis; multi-target drugs; molecular information measures; Shannon entropy; Markov chains; moving averages
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Durán, F.J.R.; Alonso, N.; Caamaño, O.; García-Mera, X.; Yañez, M.; Prado-Prado, F.J.; González-Díaz, H. Prediction of Multi-Target Networks of Neuroprotective Compounds with Entropy Indices and Synthesis, Assay, and Theoretical Study of New Asymmetric 1,2-Rasagiline Carbamates. Int. J. Mol. Sci. 2014, 15, 17035-17064.

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