Chapter title |
Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows
|
---|---|
Chapter number | 15 |
Book title |
Proteomics for Drug Discovery
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-7201-2_15 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7200-5, 978-1-4939-7201-2
|
Authors |
Alexander Goncearenco, Minghui Li, Franco L. Simonetti, Benjamin A. Shoemaker, Anna R. Panchenko |
Abstract |
We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 50 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 18% |
Researcher | 9 | 18% |
Student > Bachelor | 5 | 10% |
Student > Doctoral Student | 4 | 8% |
Student > Master | 4 | 8% |
Other | 7 | 14% |
Unknown | 12 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 14 | 28% |
Chemistry | 5 | 10% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 8% |
Computer Science | 3 | 6% |
Immunology and Microbiology | 2 | 4% |
Other | 6 | 12% |
Unknown | 16 | 32% |