Expediting the Design, Discovery, and Development of Anticancer Drugs using Computational Approaches
Owner/Developer: Current Medicinal Chemistry
| Country: | United States of America |
|---|---|
| Languages: | English |
| Url: | http://www.ncbi.nlm.nih.gov/pubmed/27593958 |
| Description: |
Cancer is considered as one of the world's leading cause of morbidity and mortality. Over the past four decades, spectacular advances in molecular and cellular biology have led to major breakthroughs in the field of cancer research. However, the design and development of anticancer drugs proves to be an intricate, expensive, and time-consuming process. To overcome these limitations and manage large amounts of emerging data, computer-aided drug discovery/design (CADD) methods have been developed. Computational methods can be employed to help and design experiments, and more importantly, elucidate structure-activity relationships to drive drug discovery and lead optimization methods. [...] In this review, we aim to provide a comprehensive view on the state-of-the-art technologies for computer-assisted anticancer drug development with thriving models from literature. The limitations associated with each traditional in silico method have also been discussed, which helps the reader to rationale the best computational tool for their analysis. |
| Category: | Publication |
| Channel: | Website |
| Audience: | Researchers - Scientists |
| User access: | Restricted access |
| Updating frequency: | 2016 |
| Relevance: | Replacement |
| Purpose: | Documentation and information |
| Technology/Tools: | Non-testing methods (in silico) |
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