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

JOURNAL OF THEORETICAL BIOLOGY

卷:276

Article

Gonzalez-Diaz, Humberto¹  Prado-Prado, Francisco²  Sobarzo-Sanchez, Eduardo³  Haddad, Mohamed^4,5,6  Chevalley, Severine Maurel^4,5  Valentin, Alexis^4,5  Quetin-Leclercq, Joelle⁶  Dea-Ayuela, Maria A.⁷  Teresa Gomez-Munos, Maria⁸  Munteanu, Cristian R.⁹  Jose Torres-Labandeira, Juan³  Garcia-Mera, Xerardo²  Tapia, Ricardo A.¹⁰  Ubeira, Florencio M.¹ 

[1] USC, Dept Microbiol & Parasitol, Santiago De Compostela 15782, Galicia, Spain

[2] USC, Dept Organ Chem, Santiago De Compostela 15782, Galicia, Spain

[3] USC, Dept Pharm & Pharmaceut Technol, Fac Pharm, Santiago De Compostela 15782, Galicia, Spain

[4] Univ Toulouse, UPS, INP, INSA,LPSNPR, F-31062 Toulouse 9, France

[5] LPSNPR, IRD, F-31062 Toulouse, France

[6] Catholic Univ Louvain, Lab Pharmacognosie, Unite Anal Chim & Physicochim Medicaments, B-1200 Brussels, Belgium

[7] Univ CEU Cardenal Herrera, Dept Chem Biochem & Mol Biol, Valencia 46113, Spain

[8] Univ CEU Cardenal Herrera, Dept Anim Hlth & Prod, Valencia 46113, Spain

[9] Univ A Coruna, Dept Informat & Commun Technol, Fac Comp Sci, La Coruna 15071, Spain

[10] Pontific Catholic Univ Chile, Dept Organ Chem, Fac Chem, Santiago 6094411, Chile

关键词: Ligands-protein interaction;    Drugs-targets prediction;    Protein structure networks;    Multi-target QSAR;    Markov model;   

DOI  :  10.1016/j.jtbi.2011.01.010

来源: Elsevier

【 摘 要 】

There 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.

【 授权许可】

Free