Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

Table 3

The energy and RMSD values achieved by different algorithms using BM energy model. The bold-faced values indicate the winner. For both energy and RMSD values, the higher the better.

Protein size			Hybrid [12]			Heuristics [13] (𝑟)			Our GA (𝑡)				Our Rel. Imp.
and H-Count			BM En		RMSD	BM En		RMSD	BM En		RMSD		RI w.r.t [13]
Seq	Size	H	Best	Avg	Avg	Best	Avg	Avg	Best	Avg	Best	Avg	Energy	RMSD
4RXN	54	27	−157.70	−140.13	9.99	−165.21	−156.32	6.29	−166.88	−162.72	4.70	5.41	4.09%	13.99%
1ENH	54	19	−154.24	−141.99	10.04	−168.75	−146.69	6.61	−153.79	−151.65	4.57	5.22	3.01%	21.03%
4PTI	58	32	−213.70	−196.23	11.92	−219.52	−198.42	7.07	−210.29	−204.56	5.97	6.46	3.09%	36.92%
2IGD	61	25	−184.29	−157.20	13.30	−187.20	−174.19	9.33	−183.18	−176.83	6.85	7.81	1.12%	16.26%
1YPA	64	38	−221.11	−208.10	13.42	−249.90	−239.98	7.53	−256.95	−253.09	5.42	6.29	5.46%	16.47%
1R69	69	30	−180.62	−165.11	14.78	−213.04	−204.17	6.47	−216.37	−208.79	4.68	5.17	2.26%	20.09%
1CTF	74	42	−204.88	−195.23	12.65	−224.29	−213.81	7.23	−233.51	−225.43	4.69	5.28	5.43%	26.97%
3MX7	90	44	—	—	—	−328.12	−311.56	8.18	−340.05	−325.45	7.31	7.94	4.46%	2.93%
3NBM	108	56	—	—	—	−418.60	−401.99	8.58	−436.76	−419.25	5.58	6.46	4.29%	24.71%
3MQO	120	68	—	—	—	−465.74	−455.27	8.86	−486.05	−472.78	6.17	6.84	3.85%	22.80%
3MRO	142	63	—	—	—	−445.33	−430.29	10.02	−479.36	−447.77	7.65	8.72	4.06%	12.97%
3PNX	160	84	—	—	—	−601.23	−571.13	9.38	−615.82	−592.25	7.50	8.51	3.70%	9.28%