pKaDatabase for Stacking Gaussian Processes to Improve pKa Predictions in the SAMPL7 Challenge

A curated a database of small molecules with experimentally measured pKa values. This pickle file can be loaded into memory using Pandas. In the code block below we will print out the columns of the DataFrame: <pre><code class="language-python">import pandas as pd df = pd.load("pKaDatabase.pkl") print(df.keys()). # print the columns</code></pre> ['deprotonated microstate ID', 'protonated microstate ID', 'deprotonated microstate smiles', 'protonated microstate smiles', 'AM1BCC partial charge (prot. atom)', 'AM1BCC partial charge (deprot. atom)', 'AM1BCC partial charge (prot. atoms 1 bond away)', 'AM1BCC partial charge (deprot. atoms 1 bond away)', 'AM1BCC partial charge (prot. atoms 2 bond away)', 'AM1BCC partial charge (deprot. atoms 2 bond away)', 'Gasteiger partial charge (prot. atom)', 'Gasteiger partial charge (deprot. atom)', 'Gasteiger partial charge (prot. atoms 1 bond away)', 'Gasteiger partial charge (deprot. atoms 1 bond away)', 'Gasteiger partial charge (prot. atoms 2 bond away)', 'Gasteiger partial charge (deprot. atoms 2 bond away)', 'Extented Hückel partial charge (prot. atom)', 'Extented Hückel partial charge (deprot. atom)', 'Extented Hückel partial charge (prot. atoms 1 bond away)', 'Extented Hückel partial charge (deprot. atoms 1 bond away)', 'Extented Hückel partial charge (prot. atoms 2 bond away)', 'Extented Hückel partial charge (deprot. atoms 2 bond away)', '∆G_solv (kJ/mol) (prot-deprot)', 'SASA (Shrake)', 'SASA (Lee)', 'Bond Order', 'Change in Enthalpy (kJ/mol) (prot-deprot)', 'pKa','href', 'num ionizable groups', 'Weight', 'pKa source'] For more information regarding feature calculations, please read the following paper: Raddi, Robert, and Vincent Voelz. "Stacking Gaussian Processes to Improve pKa Predictions in the SAMPL7 Challenge." (2021). 10.26434/chemrxiv.14650302.v1