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. © 2003 Wiley‐Liss, Inc.

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.

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.

Energy landscapes of molecular recognition are explored by performing "semi-rigid" docking of FK-506 and rapamycin with the Fukisawa binding protein (FKBP-12), and flexible docking simulations of the Ro-31-8959 and AG-1284 inhibitors with HIV-1 protease by a genetic algorithm. The requirements of a molecular recognition model to meet thermodynamic and kinetic criteria of ligand-protein docking simultaneously are investigated using a family of simple molecular recognition energy functions. The critical factor that determines the success rate in predicting the structure of ligand-protein complexes is found to be the roughness of the binding energy landscape, in accordance with a minimal frustration principle. The results suggest that further progress in structure prediction of ligand-protein complexes can be achieved by designing molecular recognition energy functions that generate binding landscapes with reduced frustration.

Background: An important prerequisite for computational structure-based drug design is prediction of the structures of ligand-protein complexes that have not yet been experimentally determined by X-ray crystallography or NMR. For this task, docking of rigid ligands is inadequate because it assumes knowledge of the conformation of the bound Ligand. Docking of flexible ligands would be desirable, but requires one to search an enormous conformational space. We set out to develop a strategy for flexible docking by, combining a simple model of ligand-protein interactions for molecular recognition with an evolutionary programming search technique.Results: We have developed an intermolecular energy function that incorporates steric and hydrogen-bonding terms. The parameters in this function were obtained by docking in three different protein systems. The effectiveness of this method was demonstrated by conformationally flexible docking of the inhibitor AG-1343, a potential new drug against AIDS, into HIV-1 protease. For this molecule, which has nine rotatable bonds, the crystal structure was reproduced within 1.5 Angstrom root-mean-square deviation 34 times in 100 simulations, each requiring eight minutes on a Silicon Graphics R4400 workstation. The energy function correctly evaluates the crystal structure as the global energy minimum.Conclusions: We believe that a solution of the docking problem may be achieved by matching a simple model of molecular recognition with an efficient search procedure. The necessary ingredients of a molecular recognition model include only steric and hydrogen-bond interaction terms. Although these terms are not necessarily sufficient to predict binding affinity, they describe ligand-protein interactions faithfully enough to enable a docking program to predict the structure of the bound ligand. This docking strategy thus provides an important tool for the interdisciplinary field of rational drug design.

A new computational method for the in situ generation of small molecules within the binding site of a protein is described. The method has been evaluated using two well-studied systems, dihydrofolate reductase and thymidylate synthase. The method has also been used to guide improvements to inhibitors of HIV-1 protease. One such improvement resulted in a compound selected for preclinical studies as an antiviral agent against AIDS.

The steadily increasing number of high-resolution human immunodeficiency virus (HIV) 1 protease complexes has been the impetus for the elaboration of knowledge-based mean field ligand-protein interaction potentials. These potentials have been linked with the hydrophobicity and conformational entropy scales developed originally to explain protein folding and stability. Empirical free energy calculations of a diverse set of HIV-1 protease crystallographic complexes have enabled a detailed analysis of binding thermodynamics. The thermodynamic consequences of conformational changes that HIV-1 protease undergoes upon binding to all inhibitors, and a substantial concomitant loss of conformational entropy by the part of HIV-1 protease that forms the ligand-protein interface, have been examined. The quantitative breakdown of the entropy-driven changes occurring during ligand-protein association, such as the hydrophobic contribution, the conformational entropy term and the entropy loss due to a reduction of rotational and translational degrees of freedom, of a system composed to ligand, protein and crystallographic water molecules at the ligand-protein interface has been carried out. The proposed approach provides reasonable estimates of distinctions in binding affinity and gives an insight into the nature of enthalpyentropy compensation factors detected in the binding process.

Publisher Summary The use of the (F o – F c ) synthesis for crystal structure refinement demonstrates that protein crystal structures can be crystallographically refined by the same techniques that are successful for small structures. F o – F c Fourier refinement is mathematically equivalent to least-squares refinement in which the residuals are weighted by the reciprocal of the unitary atomic scattering factor, and may be carried out on a small computer. Although F­ – F c Fourier refinement is economical and provides direct visual representation of the correction of the trial structure, it has been largely supplanted by least-squares refinement which can be more easily automated, has more realistic weighting, can easily accommodate stereochemical constraints directly into the refinement process, and can provide a direct estimate of errors in the atomic parameters of the trial structure. The input to any cycle of F o – F c Fourier refinement is a trial structure (atomic coordinates and thermal parameters) together with the structure factors computed from it, and the output is a new trial structure and new calculated structure factors.

The structure of chicken liver dihydrofolate reductase (5,6,7,8-tetrahydrofolate:NADP+ oxidoreductase (EC 1.5.1.3)),in a ternary complex with NADPH and a phenyltriazine inhibitor, has been determined at a nominal resolution of 2.9 A. Overall backbone chain folding is very similar to that observed in Escherichia coli and Lactobacillus casei dihydrofolate reductases.About 70% of the additional residues present in the avian enzyme occur in three loops far removed from the substrate and cofactor binding sites.The most dramatic structural difference is at one edge of the central j3 sheet, where a stretch of six residues is inserted near the NHz-terminal end of strand BG.This insertion produces a looped out region of 11 residues that do not participate in classical antiparallel interchain hydrogen bonding.The triazine ring of the phenyltriazine inhibitor is in a position analogous to that occupied by the pyrimidine portion of methotrexate when the latter binds to bacterial dihydrofolate reductase.A hydrogen-bonded charge-charge interaction occurs between the carboxylate side chain of Glu-30 and the inhibitor's N1 and 2amino group.This interaction closely resembles a similar one between Asp-27 (E.coli) and the pteridine ring of methotrexate.The inhibitor's phenyl ring occupies a space analogous to that utilized for binding the pyrazine and C9-NlO portion of methotrexate.NADPH lies in a long shallow groove winding across one face of the enzyme molecule.As in L. casei dihydrofolate reductase, the cofactor is held in an extended conformation by numerous hydrophobic, hydrogenbonded, and ionic interactions.Changes in enzyme structure induced by phenyltriazine binding to the holoenzyme have been studied by difference Fourier methods.Large movements (greater than 3 A) are observed for the side chains of Glu-30 and Tyr-31.Other features in the difference map can be attributed to a variety of minor adjustments of secondary and tertiary structure, and to the displacement or rearrangement of bound solvent molecules.Two side chains, Cys-11 and Asn-13, which are 12 A from the active site, have also moved by more than 3 A. How-

The three-dimensional conformation of yeast cytochrome c peroxidase has been determined from a 2.5

On November 28 and 29, 1978, a group of X-ray crystallographers and other interested parties gathered at the University of California at San Diego to discuss computer programming for protein crystallographic applications.This meeting was sponsored jointly by the Computer Resource for

The NADPH molecule binds to dihydrofolate reductase in an extended conformation. Several of the individual dihedral angles, especially in the adenine mononucleotide portion of the coenzyme, differ from their minimum energy conformations. The ribose phosphate portions of the coenzyme are involved in numerous specific hydrogen-bonded and charge-charge interactions. The adenine ring resides in an apparently nonspecific hydrophobic cleft and the nicotinamide ring is bound within an intricately constructed cavity, one wall of which includes the pyrazine ring of bound methotrexate. Two rather extended loops (residues 10 to 24 and 117 to 135) connecting beta A to alpha B and beta F to beta G, respectively, move 2 to 3 A when NADPH binds to dihydrofolate reductase. No overall structural homology is evident between the dinucleotide binding domains of dihydrofolate reductase on the one hand and the four NAD+-dependent dehydrogenases of known structure on the other. However, binding does occur in both cases at the carboxyl edge of a region of parallel beta sheet flanked by a pair of alpha helices.

The three-dimensional molecular structure of Lactobacillus casei dihydrofolate reductase complexed with NADPH and methotrexate has been used to interpret published magnetic resonance spectra for this enzyme. Proton resonances from histidine residues and 19F resonances from fluorine-labeled fluorotyrosine and fluorotryptophan dihydrofolate reductase have been assigned in several cases to specific amino acids in the primary sequence. Furthermore, the 31P signals from the pyrophosphate moiety of bound NADPH have been assigned and the large upfield shift for 13C-labeled (at the carboxamide carbon) NADP+ upon binding to the reductase has been explained in terms of desolvation effects.