Deep learning methods outperform classical methods on sidechain prediction

Summary

Deep learning sidechain prediction methods outperform classical energy function-based methods ((1), Heo and (2,3)). SCWRL4, which is a classical method that uses force fields, did not sample outlier rotamers as often as alternative DL-based method (Heo and (2)).

Figures

	RMSD (Å) ↓			χ-MAE (°) ↓				RR (%) ↑	Steric Clashes (#) ↓
Tool Name	All	Core	Surface	χ1	χ2	χ3	χ4	χ1-4	100%	90%	80%
---	---	---	---	---	---	---	---	---	---	---	---
CASP14 (n = 66)
FlowPacker	0.80	0.40	1.01	23.02	25.82	46.09	52.80	57.1	102.0	21.7	6.4
PIPPack	0.79	0.43	0.99	21.57	25.25	41.93	51.27	58.1	131.2	36.2	14.4
DiffPack	0.79	0.41	0.98	22.92	25.23	46.97	55.33	57.6	104.2	26.8	9.8
AttnPacker	0.79	0.44	0.98	24.19	28.79	48.34	50.37	51.3	84.6	22.8	8.1
DLPacker	0.90	0.50	1.11	27.45	30.03	52.82	70.34	50.6	83.2	16.8	5.1
FASPR	1.03	0.62	1.24	31.97	31.27	49.43	55.74	47.8	152.9	41.8	13.0
PyRosetta Packer	1.00	0.55	1.23	30.98	31.29	49.31	55.58	48.9	104.3	22.1	8.4
SCWRL4	1.04	0.61	1.26	32.22	31.65	50.21	55.10	47.5	158.3	40.2	11.8
CASP15 (n = 71)
FlowPacker	0.69	0.33	0.90	18.99	22.04	40.93	52.62	66.4	100.8	14.6	3.3
PIPPack	0.70	0.34	0.91	18.27	22.16	40.21	53.36	66.1	129.0	30.5	10.9
DiffPack	0.68	0.34	0.87	18.29	22.47	42.91	56.88	65.7	95.3	20.3	7.2
AttnPacker	0.71	0.37	0.90	20.29	26.10	47.09	54.68	59.2	96.4	25.5	9.5
DLPacker	0.76	0.38	0.97	21.88	26.29	50.86	67.53	59.5	89.4	14.0	3.2
FASPR	0.92	0.52	1.14	27.12	29.07	50.39	59.05	55.8	160.5	37.4	9.7
PyRosetta Packer	0.87	0.43	1.12	25.84	27.57	47.95	55.32	58.0	98.5	13.5	3.1
SCWRL4	0.94	0.50	1.17	27.89	29.12	49.81	57.25	55.5	168.3	36.3	7.7

Ref (3)

1.

Visani GM, Galvin W, Pun M, Nourmohammad A. H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing. In: Machine Learning in Computational Biology. PMLR; 2024. p. 230–49. Available from: https://proceedings.mlr.press/v240/visani24a.html

2.

Heo L, Feig M. One particle per residue is sufficient to describe all-atom protein structures. openRxiv; 2023. Available from: https://doi.org/10.1101/2023.05.22.541652

3.

Vangaru S, Bhattacharya D. To pack or not to pack: revisiting protein side-chain packing in the post-AlphaFold era. Briefings in Bioinformatics. 2025;26(3). Available from: https://doi.org/10.1093/bib/bbaf297