MIND-BEST: Web Server for Drugs and Target Discovery; Design, Synthesis, and Assay of MAO-B Inhibitors and Theoretical-Experimental Study of G3PDH Protein from Trichomonas gallinae

被引:78
作者
Gonzalez-Diaz, Humberto [1 ]
Prado-Prado, Francisco [2 ]
Garcia-Mera, Xerardo [2 ]
Alonso, Nerea [2 ]
Abeijon, Paula [2 ]
Caamano, Olga [2 ]
Yanez, Matilde [3 ]
Munteanu, Cristian R. [4 ]
Pazos, Alejandro [4 ]
Auxiliadora Dea-Ayuela, Maria [5 ]
Teresa Gomez-Munoz, Maria [6 ]
Magdalena Garijo, M. [6 ]
Sansano, Jose [6 ]
Ubeira, Florencio M. [1 ]
机构
[1] Univ Santiago de Compostela, Dept Microbiol & Parasitol, Santiago De Compostela 15782, Spain
[2] Univ Santiago de Compostela, Dept Organ Chem, Santiago De Compostela 15782, Spain
[3] Univ Santiago de Compostela, Dept Pharmacol, Santiago De Compostela 15782, Spain
[4] Univ A Coruna, Fac Comp Sci, Dept Informat & Commun Technol, La Coruna 15071, Spain
[5] Univ Cardenal Herrera CEU, Dept Chem Biochem & Mol Biol, Valencia 46113, Spain
[6] Univ Cardenal Herrera CEU, Dept Anim Hlth & Prod, Valencia 46113, Spain
关键词
Drug-protein interaction; protein structure complex networks; Trichomonas gallinae proteome; rasagiline inhibitors of MAO enzymes; multitarget QSAR; Markov model; ALIGNMENT-FREE PREDICTION; SINGLE-CHANNEL CURRENTS; LIGAND-BINDING SITES; TOPOLOGICAL INDEXES; MASS-SPECTROMETRY; COMPLEX NETWORKS; QSAR MODEL; 2-DIMENSIONAL ELECTROPHORESIS; PHARMACEUTICAL DESIGN; MEDICINAL CHEMISTRY;
D O I
10.1021/pr101009e
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Many drugs with very different affinity to a large number of receptors are described. Thus, in this work, we selected drug target pairs (DTPs/nDTPs) of drugs with high affinity/nonaffinity for different targets. Quantitative structure activity relationship (QSAR) models become a very useful tool in this context because they substantially reduce time and resource-consuming experiments. Unfortunately, most QSAR models predict activity against only one protein target and/or they have not been implemented on a public Web server yet, freely available online to the scientific community. To solve this problem, we developed a multitarget QSAR (mt-QSAR) classifier combining the MARCH-INSIDE software for the calculation of the structural parameters of drug and target with the linear discriminant analysis (LDA) method in order to seek the best model. The accuracy of the best LDA model was 94.4% (3,859/4,086 cases) for training and 94.9% (1,909/2,012 cases) for the external validation series. In addition, we implemented the model into the Web portal Bio-AIMS as an online server entitled MARCH-INSIDE Nested Drug-Bank Exploration & Screening Tool (MIND-BEST), located at http://miaja.tic.udc.es/BioAIMS/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 for the first time a MIND-BEST prediction, synthesis, characterization, and MAO-A and MAO-B pharmacological assay of eight rasagiline derivatives, promising for anti-Parkinson drug design. In experiment 2, we report sampling, parasite culture, sample preparation, 2-DE, MALDI-TOF and TOF/TOF MS, MASCOT search, 3D structure modeling with LOMETS, and MIND-BEST prediction for different peptides as new protein of the found in the proteome of the bird parasite Trichomonas gallinae, which is promising for antiparasite drug targets discovery.
引用
收藏
页码:1698 / 1718
页数:21
相关论文
共 159 条
[1]   Alignment-Free Prediction of Polygalacturonases with Pseudofolding Topological Indices: Experimental Isolation from Coffea arabica and Prediction of a New Sequence [J].
Agueero-Chapin, Guillermin ;
Varona-Santos, Javier ;
de la Riva, Gustavo A. ;
Antunes, Agostinho ;
Gonzalez-Villa, Tomas ;
Uriarte, Eugenio ;
Gonzalez-Diaz, Humberto .
JOURNAL OF PROTEOME RESEARCH, 2009, 8 (04) :2122-2128
[2]   Statistical mechanics of complex networks [J].
Albert, R ;
Barabási, AL .
REVIEWS OF MODERN PHYSICS, 2002, 74 (01) :47-97
[3]  
[Anonymous], 2002, STAT DAT AN SOFTW SY
[4]   Network biology:: Understanding the cell's functional organization [J].
Barabási, AL ;
Oltvai, ZN .
NATURE REVIEWS GENETICS, 2004, 5 (02) :101-U15
[5]   Network medicine -: From obesity to the "Diseasome'' [J].
Barabasi, Albert-Laszlo .
NEW ENGLAND JOURNAL OF MEDICINE, 2007, 357 (04) :404-407
[6]   Very fast prediction and rationalization of pKa values for protein-ligand complexes [J].
Bas, Delphine C. ;
Rogers, David M. ;
Jensen, Jan H. .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2008, 73 (03) :765-783
[7]   PROTEIN DATA BANK - COMPUTER-BASED ARCHIVAL FILE FOR MACROMOLECULAR STRUCTURES [J].
BERNSTEIN, FC ;
KOETZLE, TF ;
WILLIAMS, GJB ;
MEYER, EF ;
BRICE, MD ;
RODGERS, JR ;
KENNARD, O ;
SHIMANOUCHI, T ;
TASUMI, M .
JOURNAL OF MOLECULAR BIOLOGY, 1977, 112 (03) :535-542
[8]   Supervised prediction of drug-target interactions using bipartite local models [J].
Bleakley, Kevin ;
Yamanishi, Yoshihiro .
BIOINFORMATICS, 2009, 25 (18) :2397-2403
[9]   Cellular automata modelling of biomolecular networks dynamics [J].
Bonchev, D. ;
Thomas, S. ;
Apte, A. ;
Kier, L. B. .
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2010, 21 (1-2) :77-102
[10]   Overall molecular descriptors. 3. Overall Zagreb indices [J].
Bonchev, D ;
Trinajstic, N .
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2001, 12 (1-2) :213-236