Table 4: The effect of using HP energy model within a macro-mutation operator. The bold-faced values indicate the winner. The lower the energy value, the better the performance.

Protein details Best of 50 runs Average of 50 runs Rel. Imp. RI
Seq Size H HP BM BD BH HP( ) BM( ) BD BH( ) HP BM

4RXN 5427−135.43 −167.90−162.81 −166.88−124.32−159.92−155.64 −162.7230.89%1.75%
1ENH 5419−134.97 −155.49−150.07−153.79−125.52−147.42−144.47 −151.6520.82%2.87%
4PTI 5832−171.28 −213.05−202.33−210.29−156.43−201.12−196.86 −204.5630.77%1.71%
2IGD 6125−153.00−181.93−177.19 −183.18−140.59−173.62−170.79 −176.8325.78%1.85%
1YPA 6438−232.94−255.40−251.78 −256.95−220.35−247.17−242.89 −253.0914.86%2.4%
1R69 6930−181.44−212.35−213.34 −216.37−171.79−203.26−199.65 −208.7921.54%2.72%
1CTF 7442−202.06−225.59−225.37 −233.51−190.31−217.02−212.05 −225.4218.45%3.87%

3MX7 9044−295.16−333.74−323.67 −340.05−281.99−317.11−311.92 −325.4515.41%2.63%
3NBM 10856−380.20−426.35−424.10 −436.76−364.99−406.11−400.17 −419.2514.87%3.24%
3MQO 12068−443.84−472.15−464.09 −486.05−420.38−452.32−443.08 −472.7812.46%4.52%
3MRO 14263−420.65−445.19−444.99 −479.36−401.32−420.86−421.61 −447.7711.57%6.39%
3PNX 16084−576.77−584.17−576.09 −615.82−549.03−542.68−535.40−592.257.87%9.13%