Computational detection of the binding-site hot spot at the remodeled human growth hormone-receptor interface.

A hierarchical computational approach is used to identify the engineered binding-site cavity at the remodeled intermolecular interface between the mutants of human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp). Multiple docking simulations are conducted with the remodeled hGH-hGHbp complex for a panel of potent benzimidazole-containing inhibitors that can restore the binding affinity of the wild-type complex, and for a set of known nonactive small molecules that contain different heterocyclic motifs. Structural clustering of ligand-bound conformations and binding free-energy calculations, using the AMBER force field and a continuum solvation model, can rapidly locate and screen numerous ligand-binding modes on the protein surface and detect the binding-site hot spot at the intermolecular interface.

Simulating disorder-order transitions in molecular recognition of unstructured proteins: where folding meets binding.

A microscopic study of functional disorder-order folding transitions coupled to binding is performed for the p27 protein, which derives a kinetic advantage from the intrinsically disordered unbound form on binding with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) complex. Hierarchy of structural loss during p27 coupled unfolding and unbinding is simulated by using high-temperature Monte Carlo simulations initiated from the crystal structure of the tertiary complex. Subsequent determination of the transition-state ensemble and the proposed atomic picture of the folding mechanism coupled to binding provide a microscopic rationale that reconciles the initiation recruitment of p27 at the cyclin A docking site with the kinetic benefit for a disordered alpha-helix in the unbound form of p27.

Monte Carlo simulations of the peptide recognition at the consensus binding site of the constant fragment of human immunoglobulin G: the energy landscape analysis of a hot spot at the intermolecular interface.

Monte Carlo simulations of molecular recognition at the consensus binding site of the constant fragment (Fc) of human immunoglobulin G (Ig) protein have been performed to analyze structural and thermodynamic aspects of binding for the 13-residue cyclic peptide DCAWHLGELVWCT. The energy landscape analysis of a hot spot at the intermolecular interface using alanine scanning and equilibrium-simulated tempering dynamics with the simplified, knowledge-based energy function has enabled the role of the protein hot spot residues in providing the thermodynamic stability of the native structure to be determined. We have found that hydrophobic interactions between the peptide and the Met-252, Ile-253, His-433, and His-435 protein residues are critical to guarantee the thermodynamic stability of the crystallographic binding mode of the complex.

Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective.

The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand-macromolecule interactions. Significant advances in computational structure prediction of ligand-protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes.

Hierarchy of simulation models in predicting structure and energetics of the Src SH2 domain binding to tyrosyl phosphopeptides.

Structure and energetics of the Src Src Homology 2 (SH2) domain binding with the recognition phosphopeptide pYEEI and its mutants are studied by a hierarchical computational approach. The proposed structure prediction strategy includes equilibrium sampling of the peptide conformational space by simulated tempering dynamics with the simplified, knowledge-based energy function, followed by structural clustering of the resulting conformations and binding free energy evaluation of a single representative from each cluster, a cluster center. This protocol is robust in rapid screening of low-energy conformations and recovers the crystal structure of the pYEEI peptide.