Computer-aided discovery in antimicrobial research: In silico model for virtual screening of potent and safe anti-pseudomonas agents.

Computer-aided discovery in antimicrobial research: In silico model for virtual screening of potent and safe anti-pseudomonas agents. Comb Chem High Throughput Screen. 2015 Mar 5; Authors: Speck-Planche A, Cordeiro MN Abstract 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. prevails. Drug discovery is a very expensive process in terms of time and financial resources. For this reason, there is an urgent need of searching for more efficient antimicrobial chemotherapies. Computer-aided methodologies could rationalize several stages involved in the development of a new drug. In this work, we introduce a computational 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 prediction of anti-Pseudomonas activities and ADMET (absorption, distribution, metabolism, elimination, and toxicity) properties of organic compounds. The mtk-QSBER model used a large and heterogeneous dataset (more than 54000 cases), showing an accuracy higher than 90%. In order to demonstrate the accuracy and applicability of our mtk-QSBER m...
Source: Combinatorial Chemistry and High Throughput Screening - Category: Chemistry Authors: Tags: Comb Chem High Throughput Screen Source Type: research