Author: Shawar, Ribhi ; Seid, Mehran ; Chu, Daniel T. ; Desai, Manoj C. ; Barker, Lynn ; Burger, Matthew T. ; Hiebert, Christy ; Kidney, Jolene ; Plattner, Jacob J. ; Langhorne, Mike

A novel series of C(12) ethyl erythromycin derivatives have been discovered which exhibit in vitro and in vivo potency against key respiratory pathogens, including those resistant to erythromycin. The C(12) modification involves replacing the natural C(12) methyl group in the erythromycin core with an ethyl group via chemical synthesis. From the C(12) ethyl macrolide core, a series of C(12) ethyl ketolides were prepared and tested for antibacterial activity against a panel of relevant clinical isolates. Several compounds were found to be potent against macrolide-sensitive and -resistant bacteria, whether resistance was due to ribosome methylation (erm) or efflux (mef). In particular, the C(12) ethyl ketolides 4k,4s,4q,4m, and 4t showed a similar antimicrobial spectrum and comparable activity to the commercial ketolide telithromycin. The in vivo efficacy of several C(12) ethyl ketolides was demonstrated in a mouse infection model with Streptococcus pneumoniae as pathogen.

01 Feb 2006·Journal of Molecular Modeling

Non-stochastic and stochastic linear indices of the molecular pseudograph’s atom-adjacency matrix: a novel approach for computational in silico screening and “rational” selection of new lead antibacterial agents

Article

Author: Martinez, Yamile ; Zaldivar, Vicente Romero ; Bernal, Milagros Garcia ; Marrero-Ponce, Yovani ; Castro, Eduardo A. ; Abalo, Ricardo Grau ; Marrero, Ricardo Medina ; Torrens, Francisco

A novel approach (TOMOCOMD-CARDD) to computer-aided "rational" drug design is illustrated. This approach is based on the calculation of the non-stochastic and stochastic linear indices of the molecular pseudograph's atom-adjacency matrix representing molecular structures. These TOMOCOMD-CARDD descriptors are introduced for the computational (virtual) screening and "rational" selection of new lead antibacterial agents using linear discrimination analysis. The two structure-based antibacterial-activity classification models, including non-stochastic and stochastic indices, classify correctly 91.61% and 90.75%, respectively, of 1525 chemicals in training sets. These models show high Matthews correlation coefficients (MCC=0.84 and 0.82). An external validation process was carried out to assess the robustness and predictive power of the model obtained. These QSAR models permit the correct classification of 91.49% and 89.31% of 505 compounds in an external test set, yielding MCCs of 0.84 and 0.79, respectively. The TOMOCOMD-CARDD approach compares satisfactorily with respect to nine of the most useful models for antimicrobial selection reported to date. Finally, an in silico screening of 87 new chemicals reported in the anti-infective field with antibacterial activities is developed showing the ability of the TOMOCOMD-CARDD models to identify new lead antibacterial compounds.

01 Apr 2005·Bioorganic & Medicinal Chemistry

Atom, atom-type, and total nonstochastic and stochastic quadratic fingerprints: a promising approach for modeling of antibacterial activity

Article

Author: Castro, Eduardo A. ; Martinez, Yamile ; Marrero-Ponce, Yovani ; Romero-Zaldivar, Vicente ; Medina-Marrero, Ricardo ; Torrens, Francisco

The TOpological MOlecular COMputer Design (TOMOCOMD-CARDD) approach has been introduced for the classification and design of antimicrobial agents using computer-aided molecular design. For this propose, atom, atom-type, and total quadratic indices have been generalized to codify chemical structure information. In this sense, stochastic quadratic indices have been introduced for the description of the molecular structure. These stochastic fingerprints are based on a simple model for the intramolecular movement of all valence-bond electrons. In this work, a complete data set containing 1006 antimicrobial agents is collected and presented. Two structure-based antibacterial activity classification models have been generated. The models (including nonstochastic and stochastic indices) classify correctly more than 90% of 1525 compounds in training sets. These models permit the correct classification of 92.28% and 89.31% of 505 compounds in an external test sets. The TOMOCOMD-CARDD approach, also, satisfactorily compares with respect to nine of the most useful models for antimicrobial selection reported to date. Finally, a virtual screening of 87 new compounds reported in the antiinfective field with antibacterial activities is developed showing the ability of the TOMOCOMD-CARDD models to identify new leads as antibacterial.

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Indication	Highest Phase	Country/Location	Organization	Date
Bacterial Infections	Preclinical	Japan	-	-
Bacterial Infections	Preclinical	Japan	-	-

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