You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Chapter title |
Structure-Based Virtual Screening
|
|---|---|
| Chapter number | 5 |
| Book title |
Protein Bioinformatics
|
| Published in |
Methods in molecular biology, February 2017
|
| DOI | 10.1007/978-1-4939-6783-4_5 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6781-0, 978-1-4939-6783-4
|
| Authors |
Qingliang Li, Salim Shah |
| Editors |
Cathy H. Wu, Cecilia N. Arighi, Karen E. Ross |
| Abstract |
Structure-based virtual screening (SBVS) is a computational approach used in the early-stage drug discovery campaign to search a chemical compound library for novel bioactive molecules against a certain drug target. It utilizes the three-dimensional (3D) structure of the biological target, obtained from X-ray, NMR, or computational modeling, to dock a collection of chemical compounds into the binding site and select a subset of these compounds based on the predicted binding scores for further biological evaluation. In the present work, we illustrate the basic process of conducting a SBVS with examples using freely accessible tools and resources. |
Mendeley readers
The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 122 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 17 | 14% |
| Student > Ph. D. Student | 15 | 12% |
| Student > Master | 14 | 11% |
| Researcher | 10 | 8% |
| Student > Doctoral Student | 4 | 3% |
| Other | 13 | 11% |
| Unknown | 49 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 20 | 16% |
| Chemistry | 14 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 12 | 10% |
| Computer Science | 7 | 6% |
| Agricultural and Biological Sciences | 6 | 5% |
| Other | 10 | 8% |
| Unknown | 53 | 43% |