Name
Abstract | ||
|---|---|---|
Drug polypharmacology or “drug promiscuity” refers to the ability of a drug to bind multiple proteins. Such studies have huge impact to the pharmaceutical industry, but in the same time require large investments on wet-lab experiments. The respective in-silico experiments have a significantly smaller cost and minimize the expenses for the subsequent lab experiments. However, the process of finding similar protein targets for an existing drug, passes through protein structural similarity and is a highly demanding in computational resources task. In this work, we propose several algorithms that port the protein similarity task to a parallel high-performance computing environment. The differences in size and complexity of the examined protein structures raise several issues in a naive parallelization process that significantly affect the overall time and required memory. We describe several optimizations for better memory and CPU balancing which achieve faster execution times. Experimental results, on a high-performance computing environment with 512 cores and 2048GB of memory, demonstrate the effectiveness of our approach which scales well to large amounts of protein pairs. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/HPCS.2017.39 | 2017 International Conference on High Performance Computing & Simulation (HPCS) |
Keywords | Field | DocType |
pharmaceutical industry,wet-lab experiments,in-silico experiments,protein structural similarity,computational resources task,high-performance computing environment,naive parallelization process,protein pairs,large-scale drug-protein binding experiments,drug promiscuity,protein structures,multiple protein binding,protein similarity task,parallelization,memory size 2048.0 GByte,CPU | Plasma protein binding,Computer science,Parallel computing,Memory management,Software,Polypharmacology,Protein structure | Conference |
Volume | ISBN | Citations |
97 | 978-1-5386-3251-2 | 0 |
PageRank | References | Authors |
0.34 | 18 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonios Makris | 1 | 8 | 2.56 |
| Dimitrios Michail | 2 | 152 | 15.20 |
| Iraklis Varlamis | 3 | 503 | 52.08 |
| Chronis Dimitropoulos | 4 | 0 | 0.34 |
| Konstantinos Tserpes | 5 | 276 | 38.63 |
| George Tsatsaronis | 6 | 427 | 29.66 |
| Joachim Haupt | 7 | 0 | 0.34 |
| Mark Sawyer | 8 | 0 | 0.34 |