Peter W. Rose

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 α-helix in the unbound form of p27. The emerging structural polarization in the ensemble of unfolding/unbinding trajectories and in the computationally determined transition-state ensemble is not determined by the intrinsic folding preferences of p27 but rather is attributed to the topological requirements of the native intermolecular interface to order β-hairpin and β-strand of p27 that could be critical for nucleating rapid folding transition coupled to binding. In agreement with the experimental data, the disorder–order folding transition for p27 is largely determined by the functional requirement to form a specific intermolecular interface that ultimately dictates the folding mechanism and overwhelms any local folding preferences for creating a stable α-helix in the p27 structure before overcoming the major free energy barrier.

Computer Simulations of Ligand)Protein Binding with Ensembles of Protein Conformations: A Monte Carlo Study of HIV-1 Protease Binding Energy Landscapes

We present the results of molecular docking simulations with HIV-1 protease for the sb203386 and skf107457 inhibitors by Monte Carlo simulated annealing. A simplified piecewise linear energy function, the standard AMBER force field, and the AMBER force field with solvation and a soft-core smoothing component are employed in simulations with a single-protein conformation to determine the relationship between docking simulations with a simple energy function and more realistic force fields. The temperature-dependent binding free energy profiles of the inhibitors interacting with a single protein conformation provide a detailed picture of relative thermodynamic stability and a distribution of ligand binding modes in agreement with experimental crystallographic data. Using the simplified piecewise linear energy function, we also performed Monte Carlo docking simulations with an ensemble of protein conformations employing preferential biased sampling of low-energy protein conformations, and the results are analyzed in connection with the free energy profiles. Q 1999 John Wiley & Sons, Inc. Int J Quant Chem 72: 73)84, 1999

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. Binding free energy calculations, using a molecular mechanics force field and a solvation energy model, combined with alanine scanning have been conducted to determine the energetic contribution of the protein hot spot residues in binding affinity. The conserved Asn‐434, Ser‐254, and Tyr‐436 protein residues contribute significantly to the binding affinity of the peptide–protein complex, serving as an energetic hot spot at the intermolecular interface. The results suggest that evolutionary conserved hot spot protein residues at the intermolecular interface may be partitioned in fulfilling thermodynamic stability of the native binding mode and contributing to the binding affinity of the complex. Proteins 2002;48:539–557.

Towards understanding the mechanisms of molecular recognition by computer simulations of ligand-protein interactions.

The thermodynamic and kinetic aspects of molecular recognition for the methotrexate (MTX)–dihydrofolate reductase (DHFR) ligand–protein system are investigated by the binding energy landscape approach. The impact of ‘hot’ and ‘cold’ errors in ligand mutations on the thermodynamic stability of the native MTX–DHFR complex is analyzed, and relationships between the molecular recognition mechanism and the degree of ligand optimization are discussed. The nature and relative stability of intermediates and thermodynamic phases on the ligand–protein association pathway are studied, providing new insights into connections between protein folding and molecular recognition mechanisms, and cooperativity of ligand–protein binding. The results of kinetic docking simulations are rationalized based on the thermodynamic properties determined from equilibrium simulations and the shape of the underlying binding energy landscape. We show how evolutionary ligand selection for a receptor active site can produce well‐optimized ligand–protein systems such as MTX–DHFR complex with the thermodynamically stable native structure and a direct transition mechanism of binding from unbound conformations to the unique native structure. Copyright

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. Structural orientation of the benzimidazole motif in the binding‐site cavity closely mimics the position of the hot spot residue W104 in the crystal structure of the wild‐type complex, which is recognized as an important structural requirement for restoring binding affinity. Despite numerous pockets on the protein surface of the mutant hGH–hGHbp complex, the binding‐site cavity presents the energetically favorable hot spot for the benzimidazole‐containing inhibitors, whereas for a set of nonactive molecules, the lowest energy ligand conformations do not necessarily bind in the engineered cavity. The results reveal a dominant role of the intermolecular van der Waals interactions in providing favorable ligand–protein energetics in the redesigned interface, in agreement with the experimental and computational alanine scanning of the hGH–hGHbp complex. Proteins 2003.

Parallel simulated tempering dynamics of ligand-protein binding with ensembles of protein conformations

Abstract Simulated tempering dynamics with the simplified energy model and the ensemble of protein conformations have been performed for the SB203386 inhibitor binding with HIV-1 protease. Equilibrium simulations with multiple protein conformations implicitly incorporate protein flexibility and rank HIV-1 protease conformations according to the average ligand–protein interaction energies. Subsequent energy refinement with a molecular mechanics force field accurately quantifies the energetics of the low-energy ligand binding modes. The results suggest that the mobility of the SB203386 inhibitor is effectively restricted to two symmetry-related binding modes and this may prevent the inhibitor from adapting to distorted binding sites in mutant conformations.

Discovering high-affinity ligands from the computationally predicted structures and affinities of small molecules bound to a target: A virtual screening approach

We describe a ‘virtual NMR screening’ method to assist in the design of inhibitors that occupy different sites within a target. We dock small molecules into the active site of an enzyme and score them. Keeping the tightest-binding lead fixed in space, we dock and score other small molecules in its presence. Using this approach, linker groups are used to join the compounds together to form a high-affinity inhibitor. We present validation of our computational approach by reproducing experimental results for FKBP and stromelysin. Docking simulations are not subject to experimental problems such as proteolysis, protein or compound insolubility, or enzyme size. Because docking is fast and our scoring method can distinguish between high- and low-affinity inhibitors, this docking procedure shows promise as integral part of a drug-design strategy.

Hierarchy of simulation models in predicting molecular recognition mechanisms from the binding energy landscapes: Structural analysis of the peptide complexes with SH2 domains

Computer simulations using the simplified energy function and simulated tempering dynamics have accurately determined the native structure of the pYVPML, SVLpYTAVQPNE, and SPGEpYVNIEF peptides in the complexes with SH2 domains. Structural and equilibrium aspects of the peptide binding with SH2 domains have been studied by generating temperature‐dependent binding free energy landscapes. Once some native peptide–SH2 domain contacts are constrained, the underlying binding free energy profile has the funnel‐like shape that leads to a rapid and consistent acquisition of the native structure. The dominant native topology of the peptide–SH2 domain complexes represents an extended peptide conformation with strong specific interactions in the phosphotyrosine pocket and hydrophobic interactions of the peptide residues C‐terminal to the pTyr group. The topological features of the peptide–protein interface are primarily determined by the thermodynamically stable phosphotyrosyl group. A diversity of structurally different binding orientations has been observed for the amino‐terminal residues to the phosphotyrosine. The dominant native topology for the peptide residues carboxy‐terminal to the phosphotyrosine is tolerant to flexibility in this region of the peptide–SH2 domain interface observed in equilibrium simulations. The energy landscape analysis has revealed a broad, entropically favorable topology of the native binding mode for the bound peptides, which is robust to structural perturbations. This could provide an additional positive mechanism underlying tolerance of the SH2 domains to hydrophobic conservative substitutions in the peptide specificity region. Proteins 2001;45:456–470.

Navigating ligand–protein binding free energy landscapes: universality and diversity of protein folding and molecular recognition mechanisms

Abstract Thermodynamic and kinetic aspects of ligand–protein binding are studied for the methotrexate–dihydrofolate reductase system from the binding free energy profile constructed as a function of the order parameter. Thermodynamic stability of the native complex and a cooperative transition to the unique native structure suggest the nucleation kinetic mechanism at the equilibrium transition temperature. Structural properties of the transition state ensemble and the ensemble of nucleation conformations are determined by kinetic simulations of the transmission coefficient and ligand–protein association pathways. Structural analysis of the transition states and the nucleation conformations reconciles different views on the nucleation mechanism in protein folding.

Thermodynamics and kinetics of ligand-protein binding studied with the weighted histogram analysis method and simulated annealing.

The thermodynamics of ligand-protein molecular recognition is investigated by the energy landscape approach for two systems: methotrexate(MTX)--dihydrofolate reductase(DHFR) and biotin-streptavidin. The temperature-dependent binding free energy profile is determined using the weighted histogram analysis method. Two different force fields are employed in this study: a simplified model of ligand-protein interactions and the AMBER force field with a soft core smoothing component, used to soften the repulsive part of the potential. The results of multiple docking simulations are rationalized from the shape of the binding free energy profile that characterizes the thermodynamics of the binding process.