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Cancer Biology Aspects of Computational Methods & Applications in Drug Discovery
Shang-Tao Chien1, Ajay Kumar2,3, Shifa Pandey4
1Department of Pathology, Kaohsiung Armed Forces General Hospital, Kaohsiung, Taiwan.
Current Pharmaceutical Design
|November 13, 2018
Summary
Computer-aided drug discovery (CADD) accelerates the identification of effective anticancer drugs, reducing costs and time. Further research is recommended to explore CADD for various cancer types.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Cancer remains a leading global health challenge, with traditional drug development being lengthy and costly.
- Advances in molecular and cellular biology have improved outcomes, but efficient drug discovery is crucial.
- Computer-aided drug discovery (CADD) offers a solution to reduce costs and accelerate the timeline for anticancer drug development.
Purpose of the Study:
- To review computational approaches in drug discovery concerning cancer biology.
- To identify potential causes and development pathways of cancer.
- To briefly discuss cancer recovery strategies.
Main Methods:
- Review of existing research on computational methods in cancer drug discovery.
- Exploration of CADD strategies including structure-based and ligand-based drug design.
- Analysis of computational approaches for identifying cancer targets and active compounds.
Main Results:
- The study highlights the potential of CADD in streamlining drug discovery processes.
- CADD strategies can identify target sites and discover compounds with high target affinity.
- A review of computational approaches applied to cancer biology is presented.
Conclusions:
- Limited research currently exists on computational methods for cancer drug discovery.
- Further investigation into CADD for various cancers (breast, pancreatic, colon, prostate) is recommended.
- Computational methods show promise for identifying candidate drugs across diverse cancer types.
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