semvec/pypi-packages huggingface dataset:
radical.analytics 1.103.0
('Profiling library for RADICAL-Cybertools',)
License: MIT
Requires Python: >=3.8
Keywords: radical, cybertools, utilities, profiling, analysis

# RADICAL-Analytics (RA)

[![Build Status](https://github.com/radical-cybertools/radical.analytics/actions/workflows/python-app.yml/badge.svg)](https://github.com/radical-cybertools/radical.analytics/actions/workflows/python-app.yml)
[![codecov](https://codecov.io/gh/radical-cybertools/radical.analytics/branch/devel/graph/badge.svg)](https://codecov.io/gh/radical-cybertools/radical.analytics)

[RADICAL-Analytics](https://github.com/radical-cybertools/radical.analytics) is a library supporting the analysis of data produced by the [RADICAL-Cybertools](https://radical-cybertools.github.io/). Currently, RADICAL-Analytics supports [RADICAL-Pilot (RP)](https://github.com/radical-cybertools/radical.pilot) and [RADICAl-EnsembleToolkit (EnTK)](https://github.com/radical-cybertools/radical.entk). RADICAL-Analytics supports the experimental analyses [published](http://radical.rutgers.edu/publications/) by the [RADICAL Group](http://radical.rutgers.edu/) at Rutgers University.

## Documentation
* General: https://radicalanalytics.readthedocs.io/en/latest/index.html
* API: https://radicalanalytics.readthedocs.io/en/latest/apidoc.html
unipka 0.0.6
Unoffical wrapper around UnipKa
License: MIT

### Unofficial inference wrapper around DPTech's UnipKa model

This repo provides a simple wrapper around Zheng and co's fantastic [UnipKa](https://pubs.acs.org/doi/10.1021/jacsau.4c00271) model. It refactors their [example notebook](https://www.bohrium.com/notebooks/38543442597) into a small python package. 

This repo provides:

- A macro and micro pKa calculator, including pH-adjusted free energies for each microstate
- A logD calculator following the methodology of [Rowan Sci](https://chemrxiv.org/engage/chemrxiv/article-details/68388349c1cb1ecda02ba65d), calculating the weighted average of logP values for each microstate. 
- A state penalty function, useful for calculating permeability of neutral species, also following the methodology of [Rowan Sci](https://chemrxiv.org/engage/chemrxiv/article-details/68388349c1cb1ecda02ba65d) and [Lawrenz and co](https://pubs.acs.org/doi/10.1021/acs.jcim.3c00150). 
- An aqueous solvation energy calculator that uses xTB and the ALPB implicit solvent model.
- A Kp,uu classifier built using Gsolv, logD and the state penalty as features.
- A Jupyter widget to visualise the microstate distributions across a range of pH values.

Please cite the corresponding authors if you use this wrapper in your work!

![](unipka.gif)

Install using `pip install unipka`


Please see `examples.ipynb` [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1JQXbARpmfol0R4hzGISONCS9prgH-NSq?usp=sharing) or the unit tests for example usage.


Performance on the SAMPL benchmarks (pKa prediction):

<img src="benchmarks/sampl_results.png">

Performance on logD benchmark:

<img src="benchmarks/logd_results.png" width="600">


Performance on Kpuu benchmark:

<img src="benchmarks/kpuu_results.png" width="600">

Performance on FreeSolv benchmark (solvation prediction):

<img src="benchmarks/solvation_results.png" width="600">