NL MIND-BEST: A web server for ligands and proteins discovery-Theoretic-experimental study of proteins of Giardia lamblia and new compounds active against Plasmodium falciparum

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dc.contributor.authorGonzalez Diaz, Humberto
dc.contributor.authorPrado Prado, Francisco
dc.contributor.authorSobarzo Sanchez, Eduardo
dc.contributor.authorHaddad, Mohamed
dc.contributor.authorChevalley, Severine Maurel
dc.contributor.authorValentin, Alexis
dc.contributor.authorQuetin Leclercq, Joelle
dc.contributor.authorDea Ayuela, Maria A.
dc.contributor.authorTeresa Gomez Munos, Maria
dc.contributor.authorMunteanu, Cristian R.
dc.contributor.authorJose Torres Labandeira, Juan
dc.contributor.authorGarcia Mera, Xerardo
dc.contributor.authorTapia, Ricardo A.
dc.contributor.authorUbeira, Florencio M.
dc.date.accessioned2024-01-10T12:40:52Z
dc.date.available2024-01-10T12:40:52Z
dc.date.issued2011
dc.description.abstractThere are many protein ligands and/or drugs described with very different affinity to a large number of target proteins or receptors. In this work, we selected Ligands or Drug-target pairs (DTPs/nDTPs) of drugs with high affinity/non-affinity for different targets. Quantitative Structure-Activity Relationships (QSAR) models become a very useful tool in this context to substantially reduce time and resources consuming experiments. Unfortunately most QSAR models predict activity against only one protein target and/or have not been implemented in the form of public web server freely accessible online to the scientific community. To solve this problem, we developed here a multi-target QSAR (mt-QSAR) classifier using the MARCH-INSIDE technique to calculate structural parameters of drug and target plus one Artificial Neuronal Network (ANN) to seek the model. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 20:20-15-1:1. This MLP classifies correctly 611 out of 678 DTPs (sensitivity=90.12%) and 3083 out of 3408 nDTPs (specificity=90.46%), corresponding to training accuracy=90.41%. The validation of the model was carried out by means of external predicting series. The model classifies correctly 310 out of 338 DTPs (sensitivity=91.72%) and 1527 out of 1674 nDTP (specificity = 91.22%) in validation series, corresponding to total accuracy = 91.30% for validation series (predictability). This model favorably compares with other ANN models developed in this work and Machine Learning classifiers published before to address the same problem in different aspects. We implemented the present model at web portal Bio-AIMS in the form of an online server called: Non-Linear MARCH-INSIDE Nested Drug-Bank Exploration & Screening Tool (NL MIND-BEST), which is located at URL: http://miaja.tic.udc.es/Bio-AIMS/NL-MIND-BEST.php. This online tool is based on PHP/HTML/Python and MARCH-INSIDE routines. Finally we illustrated two practical uses of this server with two different experiments. In experiment 1, we report by first time Quantum QSAR study, synthesis, characterization, and experimental assay of antiplasmodial and cytotoxic activities of oxoisoaporphine alkaloids derivatives as well as NL MIND-BEST prediction of potential target proteins. In experiment 2, we report sampling, parasite culture, sample preparation, 2-DE, MALDI-TOF, and -TOF/TOF MS, MASCOT search, MM/MD 3D structure modeling, and NL MIND-BEST prediction for different peptides a new protein of the found in the proteome of the human parasite Giardia lamblia, which is promising for anti-parasite drug-targets discovery. (c) 2011 Elsevier Ltd. All rights reserved.
dc.description.funderprogram Isidro Parga Pondal, Xunta de Galicia
dc.description.funderUniversity of Santiago de Compostela
dc.fechaingreso.objetodigital01-04-2024
dc.format.extent21 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.jtbi.2011.01.010
dc.identifier.eissn1095-8541
dc.identifier.issn0022-5193
dc.identifier.pubmedidMEDLINE:21277861
dc.identifier.urihttps://doi.org/10.1016/j.jtbi.2011.01.010
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/77357
dc.identifier.wosidWOS:000289543400026
dc.information.autorucQuímica;Tapia R;S/I;47801
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final249
dc.pagina.inicio229
dc.publisherACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
dc.revistaJOURNAL OF THEORETICAL BIOLOGY
dc.rightsacceso restringido
dc.subjectLigands-protein interaction
dc.subjectDrugs-targets prediction
dc.subjectProtein structure networks
dc.subjectMulti-target QSAR
dc.subjectMarkov model
dc.subjectALIGNMENT-FREE PREDICTION
dc.subjectSINGLE-CHANNEL CURRENTS
dc.subjectAMINO-ACID-COMPOSITION
dc.subjectUNIFIED QSAR APPROACH
dc.subjectCOMPUTATIONAL CHEMISTRY
dc.subjectTOPOLOGICAL INDEXES
dc.subjectCELLULAR-AUTOMATA
dc.subject2-DIMENSIONAL ELECTROPHORESIS
dc.subjectFASCIOLA-HEPATICA
dc.subjectMASS-SPECTROMETRY
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleNL MIND-BEST: A web server for ligands and proteins discovery-Theoretic-experimental study of proteins of Giardia lamblia and new compounds active against Plasmodium falciparum
dc.typeartículo
dc.volumen276
sipa.codpersvinculados47801
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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