Computer-Aided Discovery in Antimicrobial Research: In Silico Model for Virtual Screening of Potent and Safe Anti-Pseudomonas Agents

• Type: Article in International Scientific Journal
• Date: 2015

Authors

Speck Planche, A (Author) Other; Natalia N D S Cordeiro (Author) FCUP

Journal

Title: Combinatorial Chemistry and High Throughput Screening

Vol. 18

Pages: 305-314

ISSN: 1386-2073

Publisher: Bentham

Indexing

ISI Web of Knowledge - 20 Citations

Scopus - 22 Citations

Other information

Authenticus ID: P-00G-4B0

Abstract (EN): Resistance of bacteria to current antibiotics is an alarming health problem. In this sense, Pseudomonas represents a genus of Gram-negative pathogens, which has emerged as one of the most dangerous species causing nosocomial infections. Despite the effort of the scientific community, drug resistant strains of bacteria belonging to Pseudomonas spp. prevail. The high costs associated to drug discovery and the urgent need for more efficient antimicrobial chemotherapies envisage the fact that computer-aided methods can rationalize several stages involved in the development of a new drug. In this work, we introduce a chemoinformatic methodology devoted to the construction of a multitasking model for quantitative-structure biological effect relationships (mtk-QSBER). The purpose of this model was to perform simultaneous predictions of anti-Pseudomonas activities and ADMET (absorption, distribution, metabolism, elimination, and toxicity) properties of organic compounds. The mtk-QSBER model was created from a large and heterogeneous dataset (more than 54000 cases) and displayed accuracies higher than 90% in both training and prediction sets. In order to demonstrate the applicability of our mtk-QSBER model, we used the investigational antibacterial drug delafloxacin as a case of study, for which experimental results were recently reported. The predictions performed for many biological effects of this drug exhibited a remarkable convergence with the experimental assays, confirming that our model can serve as useful tool for virtual screening of potent and safer anti-Pseudomonas agents.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10