Browsing by Author "Marrero-Ponce, Y."

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In silico antibacterial activity modeling based on the TOMOCOMD-CARDD approach
(Sociedade Brasileira de Quimica, 2015) Castillo-Garit, J.A.; Marrero-Ponce, Y.; Barigye, S.J.; Medina-Marrero, R.; Bernal, M.G.; De La Vega, J.M.G.; Torrens, F.; Arán, V.J.; Pérez-Giménez, F.; García-Domenech, R.; Acevedo Barrios, Rosa
In the recent times, the race to cope with the increasing multidrug resistance of pathogenic bacteria has lost much of its momentum and health professionals are grasping for solutions to deal with the unprecedented resistance levels. As a result, there is an urgent need for a concerted effort towards the development of new antimicrobial drugs to stay ahead in the fight against the ever adapting bacteria. In the present report, antibacterial classification functions (models) based on the topological molecular computational design-computer aided "rational" drug design (TOMOCOMD-CARDD) atom-based non-stochastic and stochastic bilinear indices are presented. These models were built using the linear discriminant analysis (LDA) method over a balanced chemical compounds dataset of 2230 molecular structures, with a diverse range of structural and molecular mechanism modes. The results of this study indicated that the non-stochastic and stochastic bilinear indices provided excellent classification of the chemical compounds (with accuracies of 86.31% and 84.92%, respectively, in the training set). These models were further externally validated yielding correct classification percentages of 86.55% and 87.91% for the non-stochastic and stochastic bilinear models, respectively. Additionally, the obtained models were compared with those reported in the literature and demonstrated comparable results, although the latter were built over much smaller datasets and with much higher degrees of freedom. Finally, simulated ligand-based virtual screening of 116 compounds, recently identified as potential antibacterials, was performed yielding 86.21% and 83.62% of correct classification, respectively, and thus demonstrating the utility of the obtained TOMOCOMD-CARDD models in the search of novel compounds with desirable antibacterial activity. © 2015 Sociedade Brasileira de Química.
Overlap and diversity in antimicrobial peptide databases: Compiling a non-redundant set of sequences
(Oxford University Press, 2015) Marrero-Ponce, Y.; Marrero-Ponce, Y.; Tellez-Ibarra, R.; Llorente-Quesada, M.T.; Salgado, J.; Barigye, S.J.; Liu, J.
Motivation: The large variety of antimicrobial peptide (AMP) databases developed to date are characterized by a substantial overlap of data and similarity of sequences. Our goals are to analyze the levels of redundancy for all available AMP databases and use this information to build a new nonredundant sequence database. For this purpose, a new software tool is introduced. Results: A comparative study of 25 AMP databases reveals the overlap and diversity among them and the internal diversity within each database. The overlap analysis shows that only one database (Peptaibol) contains exclusive data, not present in any other, whereas all sequences in the LAMP-Patent database are included in CAMP-Patent. However, the majority of databases have their own set of unique sequences, as well as some overlap with other databases. The complete set of non-duplicate sequences comprises 16 990 cases, which is almost half of the total number of reported peptides. On the other hand, the diversity analysis identifies the most and least diverse databases and proves that all databases exhibit some level of redundancy. Finally, we present a new parallel-free software, named Dover Analyzer, developed to compute the overlap and diversity between any number of databases and compile a set of non-redundant sequences. These results are useful for selecting or building a suitable representative set of AMPs, according to specific needs. © The Author 2015. Published by Oxford University Press. All rights reserved.
Physico-Chemical and structural interpretation of discrete derivative indices on N-tuples atoms
(MDPI AG, 2016) Martínez-Santiago, O.; Marrero-Ponce, Y.; Barigye, S.J.; Thu, H.L.T.; Torres, Javier; Zambrano, C.H.; Muñiz Olite, J.L.; Cruz-Monteagudo, M.; Vivas-Reyes, R.; Infante, L.V.; Artiles Martínez, L.M.
This report examines the interpretation of the Graph Derivative Indices (GDIs) from three different perspectives (i.e., in structural, steric and electronic terms). It is found that the individual vertex frequencies may be expressed in terms of the geometrical and electronic reactivity of the atoms and bonds, respectively. On the other hand, it is demonstrated that the GDIs are sensitive to progressive structural modifications in terms of: size, ramifications, electronic richness, conjugation effects and molecular symmetry. Moreover, it is observed that the GDIs quantify the interaction capacity among molecules and codify information on the activation entropy. A structure property relationship study reveals that there exists a direct correspondence between the individual frequencies of atoms and Hückel’s Free Valence, as well as between the atomic GDIs and the chemical shift in NMR, which collectively validates the theory that these indices codify steric and electronic information of the atoms in a molecule. Taking in consideration the regularity and coherence found in experiments performed with the GDIs, it is possible to say that GDIs possess plausible interpretation in structural and physicochemical terms. © 2016 by the authors; licensee MDPI, Basel, Switzerland.