Binding Affinity

import pandas as pd
import moldyn as md

hga.affinity.hist("COLVAR", [1, 2], ["Centers of Mass", "Oxygenes"])

hga.affinity.sample("COLVAR", "count.obj", [1, 0.5], [2, 0.46], is_force=True)

hga.affinity.number("count.obj", 298.15, 31.3707e-27)

	kJ/mol	kcal/mol
dG	-14.028719	-3.351099
dG_O1	-14.022662	-3.349652
dG_O2	0.882953	0.210915

tables = [hga.affinity.time("data/cyclodextrin/count.obj", cutoff, 298.15, 31.3707e-27) for cutoff in [100*x for x in range(11)]]

table = pd.concat(tables)

display(table)

	Cutoff (ps)	dG (kJ/mol)	dG (kcal/mol)	k_on (dm^3/mol/s)	k_off (1/s)
0	0	-14.035023	-3.352605	1.073377e+10	3.729713e+07
0	100	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	200	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	300	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	400	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	500	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	600	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	700	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	800	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	900	-8.353826	-1.995514	3.106633e+08	1.068000e+07
0	1000	-8.353826	-1.995514	3.106633e+08	1.068000e+07