Translational Bioinformatics: Data-driven Drug Discovery and Development
ABSTRACT Internet-accessible computing power and data-sharing mandates now enable researchers to interrogate thousands of publicly available databases containing molecular, clinical, and epidemiological data. With emerging new approaches, translational bioinformatics can now provide answers to previously untouchable questions, ranging from detecting population signals of adverse drug reactions to clinical interpretation of the whole genome. There are challenges, including lack of access to some data sources and software, but there are also overwhelming doses of hopes and expectations.
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- "However, as a first step, here we have tested the single-label system. Many studies have indicated that cheminformatics , mutagenesis , molecular docking  , predicting drug-target interaction , and bioinformatics   can timely provide very useful information and insights for drug development and hence are widely welcomed by the scientific community. "
ABSTRACT: Antibiotic resistance continues to pose a significant problem in the management of bacterial infections, despite advances in antimicrobial chemotherapy and supportive care. Here, we suggest a simple, inexpensive, and easy-to-perform assay to screen antimicrobial compounds from natural products or synthetic chemical libraries for their potential to work in tandem with the available antibiotics against multiple drug-resistant bacteria. The aqueous extract of Juglans regia tree bark was tested against representative multiple drug-resistant bacteria in the aforementioned assay to determine whether it potentiates the activity of selected antibiotics. The aqueous extract of J. regia bark was added to Mueller-Hinton agar, followed by a lawn of multiple drug-resistant bacteria, Salmonella typhi or enteropathogenic E. coli. Next, filter paper discs impregnated with different classes of antibiotics were placed on the agar surface. Bacteria incubated with extract or antibiotics alone were used as controls. The results showed a significant increase (>30%) in the zone of inhibition around the aztreonam, cefuroxime, and ampicillin discs compared with bacteria incubated with the antibiotics/extract alone. In conclusion, our assay is able to detect either synergistic or additive action of J. regia extract against multiple drug-resistant bacteria when tested with a range of antibiotics.06/2013; 2013:927323. DOI:10.1155/2013/927323
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ABSTRACT: This article introduces fundamental concepts to guide the analysis and interpretation of drug-target interaction networks. An overview of the generation and integration of interaction networks is followed by key strategies for extracting biologically meaningful information. The article highlights how this information can enable novel translational and clinically motivated applications. Important advances for the discovery of new treatments and for the detection of adverse drug effects are discussed. Examples of applications and findings originating from cardiovascular research are presented. The review ends with a discussion of crucial challenges and opportunities.Cardiovascular Research 09/2012; 97(4). DOI:10.1093/cvr/cvs289 · 5.81 Impact Factor
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ABSTRACT: The management of genitourinary malignancies requires a multidisciplinary care team composed of urologists, medical oncologists, and radiation oncologists. A genitourinary (GU) oncology clinical database is an invaluable resource for patient care and research. Although electronic medical records provide a single web-based record used for clinical care, billing, and scheduling, information is typically stored in a discipline-specific manner and data extraction is often not applicable to a research setting. A GU oncology database may be used for the development of multidisciplinary treatment plans, analysis of disease-specific practice patterns, and identification of patients for research studies. Despite the potential utility, there are many important considerations that must be addressed when developing and implementing a discipline-specific database.Urologic Oncology 02/2013; 32(1). DOI:10.1016/j.urolonc.2012.11.019 · 3.36 Impact Factor