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WaterKit: thermodynamic profiling of protein hydration sites (3/3)

<p><strong>Overview</strong></p> <p>This archive (3/3) contains the results (kith, nram and streptavidin) for the following study:</p> <ul> <li> <p>WaterKit: thermodynamic profiling of protein hydration sites (https://doi.org/10.26434/chemrxiv-2022-grlsr)</p> </li> </ul> <p>Each zip archive contains the following files:</p> <ul> <li>charmm-gui: output from CHARMM-gui</li> <li>xx_amber: GIST output from MD simulations</li> <li>figures: convergence, predictions per waterkit model plots, etc...</li> <li>pdbbind_ligands: contains all the ligands used to define the ligand binding site</li> <li>waterkit: contains all the results from the WaterKit calculations <ul> <li>All the WaterKit parameters tested: <ul> <li>ad : acceptor/donor anchor points</li> <li>all : used all hydrogen atoms as anchor points</li> <li>vina : used O_DA vina probe for the spherical model (otherwise TIP3P model)</li> <li>300 : temperature</li> <li>3 : number of hydration layers placed during the calculations</li> <li>min_100_2.5 : 100 steps of minimization with 2.5 kcal/mol/A**2 constraints</li> </ul> </li> <li>Each directory contains: <ul> <li>output from the GIST analysis (gist-*.dx)</li> <li>cluster.pdb: All the hydration sites identified</li> <li>protein.nc : WaterKit &quot;trajectory&quot;</li> <li>protein_system.prmtop : Amber top file</li> <li>pymol_*.pse : PyMol session with all the results (WK, MD)</li> <li>results_*.png : Comparison plots between WaterKit predictions and MD simulations per hydration sites</li> </ul> </li> </ul> </li> <li>analysis_xxx.ipynb: Jupyter notebook containing all the analysis (needs utils.py file)</li> <li>protein_prepared.pdbqt: structure used for the WK calculations</li> <li>results_md.csv : contains all the raw results from the MD simulations</li> <li>results_wk.csv : contains all the raw results from the WK calculations</li> <li>results_md_md_comp_energy_*.csv : comparison results between MD simulations (energy)</li> <li>results_md_md_comp_placement_*.csv : comparison results between MD simulations (placement)</li> <li>results_md_wk_comp_energy_*.csv : comparison results between MD simulations and WK (energy)</li> <li>results_md_wk_comp_placement_*.csv : comparison results between MD simulations and WK (placement)</li> <li>results_wk_wk_comp_energy_*.csv : comparison results between WK calculations (energy)</li> <li>results_wk_wk_comp_placement_*.csv : comparison results between WK calculations (placement)</li> </ul> <p>&nbsp;</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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