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.

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. Thermodynamics of the peptide-SH2 domain binding is analyzed by computing the average energy contributions over conformations from the clusters, structurally similar to the predicted peptide bound structure. Using this approach, the binding thermodynamics for a panel of studied peptides is predicted in a better agreement with the experiment than previously suggested models. However, the overall correlation between computed and experimental binding affinity remains rather modest. The results of this study show that small differences in binding free energies between the Ala and Gly mutants of the pYEEI peptide are considerably more difficult to predict than the structure of the bound peptides, indicating that accurate computational prediction of binding affinities still remains a major methodological and technical challenge.

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.

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. (C) 1999 John Wiley & Sons, Inc.

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.

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 © 1999 John Wiley & Sons, Ltd.