This submission belongs to the session c. Bioorganic Chemistry and Natural Products of the event The 10th International Electronic Conference on Synthetic Organic Chemistry
Published date
30 Nov, 2006
Citation
Alfredo Meneses-Marcel, Oscar M. Rivera-Borroto, Yovani Marrero-Ponce, Alina Montero, Yanetsy Machado Tugores, José Antonio Escario, Alicia Gómez Barrio, David Montero Pereira, Juann José Nogal, Vladimir V. Kouznetsov, Cristian Ochoa Puentes, Arnold R. Bohórquez, Ricardo Grau, Nilo Castañedo Cancio, Francisco Torrens, Froylán Ibarra-Velarde, Richard Rotondo, Ysaias J. Alvarado, Christian Vogel, Lizet Rodriguez-Machin, Bond-Based Quadratic TOMOCOMD-CARDD Molecular Indices & Statistical Techniques for New Antitrichomonal Drug-like Compounds Discovery, in Proceedings of The 10th International Electronic Conference on Synthetic Organic Chemistry, 1 November–30 November 2006, MDPI: Basel, Switzerland, doi: 10.3390/ecsoc-10-01419
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Bond-Based Quadratic TOMOCOMD-CARDD Molecular Indices & Statistical Techniques for New Antitrichomonal Drug-like Compounds Discovery
Alfredo Meneses-Marcel 1,2
Oscar M. Rivera-Borroto 1,3
Yovani Marrero-Ponce 1,4
Alina Montero 1
Yanetsy Machado Tugores 1
José Antonio Escario 2
Alicia Gómez Barrio 2
David Montero Pereira 2
Juann José Nogal 2
Vladimir V. Kouznetsov 5
Cristian Ochoa Puentes 5
Arnold R. Bohórquez 5
Ricardo Grau 3
Nilo Castañedo Cancio 1
Francisco Torrens 4
Froylán Ibarra-Velarde 6
Richard Rotondo 7
Ysaias J. Alvarado 8
Christian Vogel 9
Lizet Rodriguez-Machin 1
1. Unit of Computer-Aided Molecular “Biosilico” Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy and Department of Drug Design, Chemical Bioactive Center. Central University of Las Villas, Santa Clara, 54830, Villa Clara, C
2. Departamento de Parasitología, Facultad de Farmacia, UCM, Pza. Ramón y Cajal s/n, 28040 Madrid
3. Bioinformatics Group, Center of Studies on Bioinformatics (CEI), Faculty of Mathematics, Physics and Computer Science. Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba
4. Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain
5. Laboratorio de Química Orgánica y Biomolecular, Escuela de Química, UIS. Bucaramanga, Colombia
6. Department of Parasitology, Faculty of Veterinarian Medicinal and Zootecnic, UNAM, Mexico, D.F. 04510, Mexico
7. Mediscovery, Inc. Suite 1050, 601 Carlson Parkway, Minnetonka, MN 55305, USA
8. Laboratorio de Electrónica Molecular, Departamento de Química, Modulo II, grano de Oro, Facultad Experimental de Ciencias, La Universidad del Zulia (LUZ), Venezuela
9. Universität Rostock, Institut für Chemie, Abteilung für Organische Chemie, Albert-Einstein-Straße 3a, 18059 Rostock
Abstract
New antitrichomonal agents are needed to combat emerging metronidazoleresistant trichomoniasis and reduce the side-effects associated with currently available drugs. Toward this end, bond-based quadratic indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic total and bond-type quadratic indices for heteroatoms. The obtained LDA-based QSAR models, using non-stochastic and stochastic indices, were able to classify correctly 87.91% (87.50%) and 89.01% (84.38%) of the chemicals in training (test) sets, respectively. They showed large Matthews’ correlation coefficients (C) of 0.75 (0.71) and 0.78 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidenced the robustness of the obtained models. Later, both models were applied to the virtual screening of 12 compounds already proved against TrichomonasVaginalis (Tv). As a result, they correctly classified 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is a more important criterion for validating the models. In addition, these classification functions were also applied to a library of twenty-one chemicals in order to find new lead antitrichomonal agents. These compounds were synthesized and tested for in vitro activity against Tv. As expected, theoretical results almost coincided with experimental ones since there was obtained a correct classification for both models of 95.24% (20 out of 21) of the chemicals. Out of the twenty-one compounds that were screened, and synthesized, two molecules (chemicals G-1, UC-245), showed high to moderate cytocidal activity at the concentration of 10µg/ml, other two compounds (G-0 and CRIS-148) showed high cytocidal activity only at the concentration of 100µg/ml, and the remaining chemicals (from CRIS-105 to CRIS-153 except CRIS-148) were inactive at these assayed concentrations. Finally, the best candidate, G-1 (cytocidal activity of 100% at 10µg/ml) was in vivo assayed in ovariectomized Wistar rats achieving promissory results as a trichomonacidal drug-like compound. The LDA-based QSAR models presented here can be considered as a computer-assisted system that could potentially significantly reduce the number of synthesized and tested compounds and increase the chance of finding new chemical entities with antitrichomonal activity.
Keywords
<i>TOMOCOMD-CARDD</i> Software
Bond-based Quadratic Indices
LDA-based QSAR Model
Virtual Screening
Lead Generation
Trichomonacidal
Cytostatic and Cytocidal Activity
Quick Access to Potential Trichomonacidals through Bond Linear Indices-Trained Ligand-Based virtual Screening Models
Unify QSAR approach to antibacterial activity of organic drugs against different species