Research Article
Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects
Table 1
Characteristics of the operations of the drug discovery pipeline.
| | TI | VS | ER | LO |
| Functional | | | | |
Number ofcores | ≥16 | ≥8 | ≥32 | ≥4 | Network | — | — | Infiniband | — | RAM (GB) | ≥32 | ≥16 | ≥64 | ≥16 | HDD (GB) | — | ≥500 | ≥1000 | — | Reference Amazon EC21 virtual cluster | 20 D | 10 2 D | 1–10 2 D | 1 C | Non functional | | | | | Security | Low | Medium | Medium | High | Availability/Resiliency | Low | Medium | Medium | Low | Operations parameters | | | | | Input data and size | 10 K–100 K Parameter simulations | 5 K–10 K Compounds | 1–10 Simulations 50 K–250 K Atoms 5–300 Nanoseconds | 5–10 Compounds | Service demand time () with respect to the reference Amazon EC2 virtual cluster | 16–160 h | 8–16 h | 2–1200 h | 1–6 h | Arrival rate () per year per research group | 4 | 3/4 | 2/3 | 1/2 | Packages | | | | | Commercial | MATLAB | FlexX, Glide, ICM | AMBER, CHARMM | MacroModel, Medstere | Free/open source | R | Dock, Autodock | GROMACS, NAMD | Omega |
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See Table 2.
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