Highly negative total score

[Anonymous]

I have performed a docking between a protein and a 15 residue peptide using flex pep dock. I have got a total score of around -1347, is this considered as good docking ? I am unable to predict whether the docking can be considered or not. Please help me. Thanks in advance:

The total score and other factors are as follows:

total_score	I_sc	fa_atr	fa_dun	fa_pair	fa_rep	fa_sol	hbond_sc	pep_sc	pep_sc_noref	rama	rmsALL_if	rmsBB	rmsBB_if	startRMSbb	description
-1347.095	-14.720	-5007.113	1134.600	-85.068	776.773	2460.776	-39.201	-8.295	-19.405	141.836	2.842	2.680	2.430	0.000	top_1.pdb
-1343.080	-11.662	-4997.305	1134.889	-84.667	773.714	2457.896	-39.826	-5.309	-16.419	142.413	2.411	1.188	1.205	0.000	top_2.pdb
-1342.016	-17.091	-5003.941	1132.832	-84.844	782.667	2459.289	-39.885	-10.117	-21.227	142.670	2.212	1.501	1.516	0.000	top_3.pdb
-1341.815	-14.740	-5012.769	1136.692	-83.429	778.716	2465.664	-39.519	-8.820	-19.930	142.253	2.434	2.203	2.015	0.000	top_4.pdb
-1341.156	-17.032	-5004.029	1137.124	-84.009	776.288	2461.377	-39.548	-8.928	-20.038	142.564	2.178	1.044	1.057	0.000	top_5.pdb
-1340.566	-15.159	-5013.151	1136.656	-83.377	779.321	2466.008	-40.593	-6.833	-17.943	142.152	2.704	2.653	2.466	0.000	top_6.pdb
-1340.552	-13.753	-5011.181	1139.277	-84.528	776.843	2467.074	-39.732	-8.951	-20.061	141.948	1.898	1.583	1.467	0.000	top_7.pdb
-1340.207	-14.188	-5003.347	1136.732	-84.222	781.371	2456.592	-39.093	-7.809	-18.919	141.985	6.767	5.835	6.127	0.000	top_8.pdb
-1339.185	-14.238	-5018.549	1144.341	-85.171	780.477	2469.711	-39.545	-7.569	-18.679	141.185	1.937	1.613	1.484	0.000	top_9.pdb
-1339.054	-15.704	-5007.212	1138.056	-83.308	778.395	2462.201	-39.708	-8.215	-19.325	142.234	2.347	0.831	0.865	0.000	top_10.pdb

[Anonymous]

Hello,

In docking experiments it is common to sort your models for an acceptably good total_score in order to remove models with clashes and other poor properties and then sort these good models based on the interface score. In your case, model 3 and 5 are the best to look at based on secondary sorting by I_sc (interface score). A good rule of thumb is to select the top 10% by total_score then sort these by I_sc and look at these top scoring models.

Take a look at these docs as well if you haven’t already. The advice I give is in the last paragraph of the Analyzing Results doc, written a little differently, of course. 

https://www.rosettacommons.org/docs/latest/getting_started/Analyzing-Results

https://www.rosettacommons.org/docs/latest/getting_started/Rosetta-on-different-scales

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