Generation of a flexible loop structural ensemble and its application to induced-fit structural changes following ligand binding

Abstract

Molecular recognition is often mediated by flexible loops that have widely fluctuating structures and are sometimes disordered, but that form particular complex structures following ligand binding. In fact, many loop structures found in the PDB database are too flexible to be determined precisely. A new loop modeling method was therefore developed using force-biased multicanonical molecular dynamics with the implicit solvent model to generate an ensemble of putative loop structures with low free energy values. The method was then used to create ensembles for several flexible loops that were compared with the corresponding NMR and X-ray structures. The induced-fit structural change of dihydrofolate reductase (DHFR) was also predicted from a structural ensemble of ligand-free M20 loop conformations and successive docking simulations.

Computer-aided antibody design

“…For that purpose, Shirai et al (1998 ) and Kim et al (1999 ) performed the multicanonical molecular dynamics simulations ( Nakajima et al , 1997 ; Higo et al , 2012 ) to probe the free energy landscapes, and they obtained the stable structural ensembles of the CDR-H3 loops at 300 K, which were found to include the corresponding crystal structures. In addition, characterizing the free energy landscapes should aid in predicting structural changes of CDR-H3 upon antigen binding based on the ‘population shift’ principle that suggests that bound conformations should be relatively close in free energy to the unbound state ( Watanabe et al , 2006 ; Okazaki and Takada, 2008 ). Higo et al (2011 ) recently observed both the population shift and the induced fit mechanisms during the coupled folding and binding in an intrinsically disordered protein.…”

Molecular Dynamics Simulation Study on Allosteric Regulation of CD44-Hyaluronan Binding as a Force Sensing Mechanism

“…To elucidate the interactions between the HA molecule and each residue of protein in the complex models, the binding free energy was decomposed into the interaction energy of the single residue and the HA molecule pair by the MM-generalized-Born (GB) SA method. − Total 6000 snapshots around the energy minima on the free energy landscape generated by PCA were chosen for the estimation of the interaction energy.…”

Investigation on substrate specificity and catalytic activity of serine protease neuropsin

“…The binding free energies of the substrates were calculated on the basis of the one-state end-point approach with the MM-Poisson-Bolzmann (PB) SA methods [50][51][52][53][54][55]. In addition to the binding energy estimations, to elucidate the key interaction among each residue in the ligand recognition, the binding free energy was decomposed into the interaction energy of single residue pair by MM-generalized-Born (GB) SA method [56][57][58][59][60][61][62][63][64]. The GB method is one of the approximations of the PB method by modifying the pairwise electrostatic interaction between two atoms.…”