- Title
- The role of structural bioinformatics in drug discovery via computational SNP analysis–a proposed protocol for analyzing variation at the protein level:
- Creator
- Brown, David K, Tastan Bishop, Özlem
- Date
- 2017
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/162914
- Identifier
- vital:40996
- Identifier
- doi: 10.1016/j.gheart.2017.01.009
- Description
- With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps towards an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as Genome-Wide Association Studies (GWAS) and Candidate Gene Association Studies (CGAS). However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as High Throughput Sequencing (HTS).
- Format
- 22 page, pdf
- Language
- English
- Relation
- Global Heart, Brown, D.K. and Bishop, Ö.T., 2017. The role of structural bioinformatics in drug discovery via computational SNP analysis–a proposed protocol for analyzing variation at the protein level. Global heart, 12(2), p.151, Global Heart volume 12 number 2 1 21 June 2017 2211-8179
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the National Centre for Biotechnology Information (NCBI) Statement (https://0-www.ncbi.nlm.nih.gov.wam.seals.ac.za/home/about/)
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Collections
RU Research Unit in Bioinformatics (RUBi)
Tastan Bishop, Ozlem (Prof)
RU Department of Biochemistry, Microbiology and Bioinformatics
SDG 03. Good Health and Well-Being
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