https://github.com/lightonai/newma-md
Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)
https://github.com/lightonai/newma-md
change-point-detection covid-19 molecular-dynamics newma photonic-computing
Last synced: 10 months ago
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Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)
- Host: GitHub
- URL: https://github.com/lightonai/newma-md
- Owner: lightonai
- License: mit
- Created: 2020-03-24T12:55:41.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2022-06-22T01:31:23.000Z (almost 4 years ago)
- Last Synced: 2023-03-05T14:12:30.167Z (over 3 years ago)
- Topics: change-point-detection, covid-19, molecular-dynamics, newma, photonic-computing
- Language: Jupyter Notebook
- Homepage: https://medium.com/@LightOnIO
- Size: 590 KB
- Stars: 15
- Watchers: 4
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 
Conformational exploration SARS-CoV-2 (coronavirus responsible for COVID-19)
[](LICENSE) [](https://twitter.com/LightOnIO)
This repository contains the script to reproduce the results of the blog post [**Coronavirus “SARS-CoV-2” conformational change-points detected with optical random features**](https://medium.com/@LightOnIO/accelerating-sars-cov2-molecular-dynamics-studies-with-optical-random-features-b8cffdb99b01) as well as the results of [**Optical Random Features versus SARS-CoV-2 Glycoprotein Trajectory: Round#2**](https://medium.com/@LightOnIO/optical-random-features-versus-sars-cov-2-glycoprotein-trajectory-round-2-adcf04d6036d).
##
## Requirements
We advise creating a `virtualenv` before running these commands. You can create one with `python3 -m venv `. Activate it with source `/bin/activate` before proceeding. We used `python 3.7`for all the simulations.
- Clone the repository and then do `pip install -r requirements.txt`.
- Download the dataset from [this page](https://figshare.com/articles/6_molecular_dynamics_simulations_of_coronavirus_2019-nCoV_protease_model_in_complex_with_different_conformations_of_lopinavir_/11764158). You should put the dataset in the same folder as the repository. Otherwise, make sure to update the variable `path traj`.
##
## Replicate our results
For replicating the results of [**Coronavirus “SARS-CoV-2” conformational change-points detected with optical random features**](https://medium.com/@LightOnIO/accelerating-sars-cov2-molecular-dynamics-studies-with-optical-random-features-b8cffdb99b01): start by running
```
python newma_coronavirus.py
```
This outputs a numpy zipped archive. To analyse the results and create your own plot, use the notebook `notebooks/corona_exploration.ipynb`.
For replicating the results of [**Optical Random Features versus SARS-CoV-2 Glycoprotein Trajectory: Round#2**](https://medium.com/@LightOnIO/optical-random-features-versus-sars-cov-2-glycoprotein-trajectory-round-2-adcf04d6036d): start by running
```
python newma_coronavirus_DESRES.py
```
This outputs a numpy zipped archive. To analyse the results and create your own plot, use the notebook `notebooks/corona_exploration_DESRES.ipynb`.
## 
Access to Optical Processing Units
To request access to LightOn Cloud and try our photonic co-processor, please visit:
For researchers, we also have a LightOn Cloud for Research program, please visit for more information.
##
## Hardware Specifications
All our results were obtains on a Intel(R) Xeon(R) Gold 6128 CPU @3.40GHz with 12 cores.