Energy landscape and dynamics of the beta-hairpin G peptide and its isomers: Topology and sequences.
We have investigated free energy landscape [MM/PBSA + normal modes entropy] of permutations in the G peptide (41-56) from the protein G B1 domain by studying six isomers corresponding to moving the hydrophobic cluster along the beta-strands (toward the turn: T1, AGEWTYDDKTFTVTET; T2, GEDTWDYATFTVTKTE; T3, GEDDWTYATFTVTKTE; toward the end: E1, WTYDDAGETKTFTVT; E2, WEYTGDDATKTETFTV; E3, WTYEGDDATKTETFTV). The free energy terms include molecular mechanics energy, Poisson-Boltzmann electrostatic solvation energy, surface area solvation energy, and conformational entropy estimated by using normal mode analysis. From the wild type to T1, then T3, and finally T2, we see a progressively changing energy landscape, toward a less stable beta-hairpin structure. Moving the hydrophobic cluster outside toward the end region causes a greater change in the energy landscape. alpha-Helical instead of a beta-hairpin structure was the most stable form for the E2 isomer. However, no matter how much the sequence changes, for all variants studied, ideal "native" beta-hairpin topologies remain as minima (regardless of whether global or local) in the energy landscape. In general, we find that the energy landscape is dependent on the hydrophobic cluster topology and on the sequence. Our present study indicates that the key is the relative conformational energies of the different conformations. Changes in the sequence strongly modulate the relative stabilities of topologically similar regions in the energy landscape, rather than redefine the topology space. This finding is consistent with a population redistribution in the process of protein folding. The limited variation of topological space, compared with the number of possible sequence changes, may relate to the observation that the number of known protein folds are far less than the sequential allowance.
Ma
Buyong
B
Basic Research Program, SAIC-Frederick, Inc, Laboratory of Experimental and Computational Biology, National Cancer Institute at Frederick, Frederick, Maryland 21702, USA.
Nussinov
Ruth
R
D000595:Amino Acid Sequence; D019277:Entropy; D006860:Hydrogen Bonding; D008958:Models, Molecular; D015233:Models, Statistical; D008969:Molecular Sequence Data; D009419:Nerve Tissue Proteins / Q000737:chemistry*; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D017510:Protein Folding; D020033:Protein Isoforms; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D017386:Sequence Homology, Amino Acid; D012984:Software; D013816:Thermodynamics
C029152:G-substrate; D009419:Nerve Tissue Proteins; D010455:Peptides; D020033:Protein Isoforms