Table 1.

Modeling results by CR-I-TASSER and other methods on 778 benchmark test proteins involving different density map types and resolutions. P-values are calculated using two-tailed Student’s t-tests between the TM-scores produced by CR-I-TASSER and the other methods. Bold fonts highlight the performer which obtained the best average result in each category.

Methods	$\langle \mathbf{T}\mathbf{M}\mathbf{˗}\mathbf{s}\mathbf{c}\mathbf{o}\mathbf{r}\mathbf{e}\rangle$	N (TM>TM0)4	$\langle \mathbf{R}\mathbf{M}\mathbf{S}\mathbf{D}\rangle$ (Å)	P-value
301 Hard targets with high-resolution density map (resolution in 2–5 Å) (TM0=0.5)
I-TASSER1	0.345	27	12.0	8.0×10−91
Flex-EM2	0.318	22	12.4	3.8×10−96
iMODFIT2	0.340	25	11.9	6.6×10−91
MDFF2	0.331	26	12.1	3.4×10−91
EM-Refiner2	0.315	18	12.2	6.9×10−96
Rosetta-Ref2	0.297	30	14.0	1.2×10−99
MAINMAST3	0.438	121	10.2	9.8×10−47
Rosetta-dn3	0.419	94	12.2	8.7×10−52
Phenix3	0.466	134	8.6	8.7×10−42
CR-I-TASSER3	0.772	251	4.4	--
229 Easy targets with high-resolution density map (resolution in 2–5 Å) (TM0=0.9)
I-TASSER1	0.762	16	5.1	8.4×10−75
Flex-EM2	0.824	66	4.4	4.6×10−35
iMODFIT2	0.799	43	4.7	5.6×10−48
MDFF2	0.857	104	4.1	4.8×10−21
EM-Refiner2	0.846	76	4.0	3.5×10−37
Rosetta-Ref2	0.851	103	4.0	6.9×10−21
MAINMAST3	0.439	9	11.8	5.7×10−78
Rosetta-dn3	0.474	17	12.0	8.0×10−77
Phenix3	0.493	8	8.4	1.4×10−76
CR-I-TASSER3	0.950	198	1.4	--
301 Hard targets with low-resolution density map (resolution in 5–15 Å) (TM0=0.5)
I-TASSER1	0.345	27	12.0	2.0×10−48
Flex-EM2	0.303	13	12.3	1.2×10−61
iMODFIT2	0.316	23	12.0	2.0×10−56
MDFF2	0.319	29	11.8	6.8×10−55
EM-Refiner2	0.305	19	12.1	2.3×10−60
Rosetta-Ref2	0.268	18	13.9	1.6×10−70
MAINMAST3	0.204	3	14.3	2.1×10−86
Rosetta-dn3	0.201	7	14.6	6.7×10−91
Phenix3	0.180	0	12.5	5.5×10−95
CR-I-TASSER3	0.597	191	6.3	--
229 Easy targets with low-resolution density map (resolution in 5–15 Å) (TM0=0.9)
I-TASSER1	0.762	16	5.1	8.4×10−75
Flex-EM2	0.666	0	5.3	3.5×10−90
iMODFIT2	0.767	34	4.4	4.0×10−29
MDFF2	0.788	46	4.3	5.5×10−23
EM-Refiner2	0.739	21	4.7	5.3×10−42
Rosetta-Ref2	0.714	14	4.9	7.5×10−49
MAINMAST3	0.202	0	15.6	5.7×10−311
Rosetta-dn3	0.225	1	9.2	1.5×10−238
Phenix3	0.174	0	13.8	3.2×10−309
CR-I-TASSER3	0.898	137	2.1	--
178 targets with experimental density map (resolution in 2–5 Å) (TM0=0.9)
I-TASSER1	0.647	6	8.3	4.0×10−15
Flex-EM2	0.681	24	8.5	3.6×10−9
iMODFIT2	0.695	19	7.8	6.8×10−8
MDFF2	0.709	37	7.3	4.9×10−6
EM-Refiner2	0.690	32	8.3	2.5×10−7
Rosetta-Ref2	0.688	40	8.5	7.1×10−7
MAINMAST3	0.323	2	15.2	7.4×10−72
Rosetta-dn3	0.353	5	15.7	1.4×10−60
Phenix3	0.349	1	13.3	2.7×10−63
CR-I-TASSER3	0.810	75	4.9	--
70 targets with experimental density map (resolution in 5–10 Å) (TM0=0.5)
I-TASSER1	0.612	49	9.2	2.7×10−3
Flex-EM2	0.546	45	9.3	4.3×10−7
iMODFIT2	0.603	48	8.9	1.7×10−3
MDFF2	0.573	46	8.7	5.9×10−5
EM-Refiner2	0.576	45	8.8	9.7×10−5
Rosetta-Ref2	0.554	43	9.3	9.7×10−6
MAINMAST3,5	0.221	0	16.1	2.0×10−31
Rosetta-dn3	0.176	1	15.6	5.4×10−41
Phenix3	0.118	0	18.3	1.5×10−43
CR-I-TASSER3	0.714	63	6.2	--

¹Protein structure prediction methods

²Cryo-EM based structure refinement methods

³Cryo-EM based de novo structure modeling methods

⁴TM₀=0.5 for simulated Hard targets and low-resolution experimental targets, =0.9 for simulated Easy targets or high-resolution experimental targets

⁵Only 61 targets are solved with MAINMAST, probably due to the low resolution and experimental noise