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.     

Specific DNA recognition by the Antp homeodomain: MD simulations of specific and nonspecific complexes

Four molecular dynamics simulation trajectories of complexes between the wild-type or a mutant Antennapedia homeodomain and 2 DNA sequences were generated in order to probe the mechanisms governing the specificity of DNA recognition. The starting point was published affinity measurements showing that a single protein mutation combined with a replacement of 2 base pairs yields a new high-affinity complex, whereas the other combinations, with changes on only 1 macromolecule, exhibited lower affinity. The simulations of the 4 complexes yielded fluctuating networks of interaction. On average, these networks differ significantly, explaining the switch of affinity caused by the alterations in the macromolecules. The network of mostly hydrogen-bonding interactions involving several water molecules, which was suggested both by X-ray and NMR structures of the wild-type homeodomain and its DNA operator sequence, could be reproduced in the trajectory. More interestingly, the high-affinity complex with alterations in both the protein and the DNA yielded again a dynamic but very tight network of intermolecular interactions, however, attributing a significantly stronger role to direct hydrophobic interactions at the expense of water bridges. The other 2 homeodomain-DNA complexes, with only 1 molecule altered, show on average over the trajectories a clearly reduced number of protein-DNA interactions. The observations from these simulations suggest specific experiments and thus close the circle formed by biochemical, structural, and computational studies. The shift from a water-dominated to a more "dry" interface may prove important in the design of proteins binding DNA in a specific manner.     

Binding Hot Spots and Amantadine Orientation in the Influenza A Virus M2 Proton Channel

Structures of truncated versions of the influenza A virus M2 proton channel have been determined recently by x-ray crystallography in the open conformation of the channel, and by NMR in the closed state. The structures differ in the position of the bound inhibitors. The x-ray structure shows a single amantadine molecule in the middle of the channel, whereas in the NMR structure four drug molecules bind at the channel's outer surface. To study this controversy we applied computational solvent mapping, a technique developed for the identification of the most druggable binding hot spots of proteins. The method moves molecular probes—small organic molecules containing various functional groups—around the protein surface, finds favorable positions using empirical free energy functions, clusters the conformations, and ranks the clusters on the basis of the average free energy. The results of the mapping show that in both structures the primary hot spot is an internal cavity overlapping the amantadine binding site seen in the x-ray structure. However, both structures also have weaker hot spots at the exterior locations that bind rimantadine in the NMR structure, although these sites are partially due to the favorable interactions with the interfacial region of the lipid bilayer. As confirmed by docking calculations, the open channel binds amantadine at the more favorable internal site, in good agreement with the x-ray structure. In contrast, the NMR structure is based on a peptide/micelle construct that is able to accommodate the small molecular probes used for the mapping, but has a too narrow pore for the rimantadine to access the internal hot spot, and hence the drug can bind only at the exterior sites.     

Molecular dynamics-solvated interaction energy studies of protein-protein interactions: the MP1-p14 scaffolding complex

Using the MP1-p14 scaffolding complex from the mitogen-activated protein kinase signaling pathway as model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. Hot spots are located by virtual alanine-scanning consensus predictions over three different energy functions and two different single-structure representations of the complex. Refined binding affinity predictions for select hot-spot mutations are carried out by applying first-principle methods such as the molecular mechanics generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) to the molecular dynamics (MD) trajectories for mutated and wild-type complexes. Here, predicted hot-spot residues were actually mutated to alanine, and crystal structures of the mutated complexes were determined. Two mutated MP1-p14 complexes were investigated, the p14(Y56A)-mutated complex and the MP1(L63A,L65A)-mutated complex. Alternative ways to generate MD ensembles for mutant complexes, not relying on crystal structures for mutated complexes, were also investigated. The SIE function, fitted on protein-ligand binding affinities, gave absolute binding affinity predictions in excellent agreement with experiment and outperformed standard MM-GBSA predictions when tested on the MD ensembles of Ras-Raf and Ras-RalGDS protein-protein complexes. For wild-type and mutant MP1-p14 complexes, SIE predictions of relative binding affinities were supported by a yeast two-hybrid assay that provided semiquantitative relative interaction strengths. Results on the MP1-mutated complex suggested that SIE predictions deteriorate if mutant MD ensembles are approximated by just mutating the wild-type MD trajectory. The SIE data on the p14-mutated complex indicated feasibility for generating mutant MD ensembles from mutated wild-type crystal structure, despite local structural differences observed upon mutation. For energetic considerations, this would circumvent costly needs to produce and crystallize mutated complexes. The sensitized protein-protein interface afforded by the p14(Y56A) mutation identified here has practical applications in screening-based discovery of first-generation small-molecule hits for further development into specific modulators of the mitogen-activated protein kinase signaling pathway.     

Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: hierarchy of structural loss from all-atom Monte Carlo simulations of p27Kip1 unfolding-unbinding and structural determinants of the binding mechanism

Conformational transitions coupled to binding are studied for the p27(Kip1) protein which undergoes a functional disorder-to-order folding transition during tertiary complex formation with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) binary complex. Temperature-induced Monte Carlo simulations of p27(Kip1) unfolding-unbinding carried out from the crystal structure of the tertiary complex have revealed a systematic trend in the hierarchy of structural loss for p27(Kip1) and a considerable difference in mobility of p27(Kip1) secondary structure elements. The most persistent interactions of p27(Kip1) at the intermolecular interface during unfolding-unbinding simulations are formed by beta-hairpin and beta-strand that on average maintain their structural integrity considerably longer than other p27(Kip1) elements. We have found that the ensemble of unfolded p27(Kip1) conformations is characterized by transitions between mostly unbound, collapsed conformations and entropically favorable p27(Kip1) conformations, which are weakly bound to the cyclin A side of the binary complex. The results of this study are consistent with the experimental evidence pointing to this region of the intermolecular interface as a potential initiation docking site during binding reaction and may reconcile conflicting experimental hypotheses on the recognition of substrate recruitment motifs.     

Structural determinants of trypsin affinity and specificity for cationic inhibitors

The binding free energies of four inhibitors to bovine beta-trypsin are calculated. The inhibitors use either ornithine, lysine, or arginine to bind to the S1 specificity site. The electrostatic contribution to binding free energy is calculated by solving the finite difference Poisson-Boltzmann equation, the contribution of nonpolar interactions is calculated using a free energy-surface area relationship and the loss of conformational entropy is estimated both for trypsin and ligand side chains. Binding free energy values are of a reasonable magnitude and the relative affinity of the four inhibitors for trypsin is correctly predicted. Electrostatic interactions are found to oppose binding in all cases. However, in the case of ornithine- and lysine-based inhibitors, the salt bridge formed between their charged group and the partially buried carboxylate of Asp189 is found to stabilize the complex. Our analysis reveals how the molecular architecture of the trypsin binding site results in highly specific recognition of substrates and inhibitors. Specifically, partially burying Asp189 in the inhibitor-free enzyme decreases the penalty for desolvation of this group upon complexation. Water molecules trapped in the binding interface further stabilize the buried ion pair, resulting in a favorable electrostatic contribution of the ion pair formed with ornithine and lysine side chains. Moreover, all side chains that form the trypsin specificity site are partially buried, and hence, relatively immobile in the inhibitor-free state, thus reducing the entropic cost of complexation. The implications of the results for the general problem of recognition and binding are considered. A novel finding in this regard is that like charged molecules can have electrostatic contributions to binding that are more favorable than oppositely charged molecules due to enhanced interactions with the solvent in the highly charged complex that is formed.     

The functional binding epitope of a high affinity variant of human growth hormone mapped by shotgun alanine-scanning mutagenesis: insights into the mechanisms responsible for improved affinity

A high-affinity variant of human growth hormone (hGH(v)) contains 15 mutations within site 1 and binds to the hGH receptor (hGHR) approximately 400-fold tighter than does wild-type (wt) hGH (hGH(wt)). We used shotgun scanning combinatorial mutagenesis to dissect the energetic contributions of individual residues within the hGH(v) binding epitope and placed them in context with previously determined structural information. In all, the effects of alanine substitutions were determined for 35 hGH(v) residues that are directly contained in or closely border the binding interface. We found that the distribution of binding energy in the functional epitope of hGH(v) differs significantly from that of hGH(wt). The residues that contributed the majority of the binding energy in the wt interaction (the so-called binding "hot spot") remain important, but their contributions are attenuated in the hGH(v) interaction, and additional binding energy is acquired from residues on the periphery of the original hotspot. Many interactions that inhibited the binding of hGH(wt) are replaced by interactions that make positive contributions to the binding of hGH(v). These changes produce an expanded and diffused hot spot in which improved affinity results from numerous small contributions distributed broadly over the interface. The mutagenesis results are consistent with previous structural studies, which revealed widespread structural differences between the wt and variant hormone-receptor interfaces. Thus, it appears that the improved binding affinity of hGH(v) site 1 was not achieved through minor adjustments to the wt interface, but rather, results from a wholesale reconfiguration of many of the original binding elements.     

Structural insight into the binding mechanism of ATP to EGFR and L858R,and T790M and L858R/T790 mutants

Abstract

The L858R mutation in EGFR is particularly responsive to small tyrosine kinase inhibitors (TKIs) such as gefitinib and erlotinib. This efficacy decreases due to drug resistance conferred by a second mutation, T790M, which subsequently produces a double mutant, L858R/T790M. Although this resistance was initially attributed to steric blocking by the T790M mutation, experimental studies have demonstrated that differences in the binding affinities of TKIs to T790M and L858R/T790M mutants are more a result of the increased sensitivity of these mutants to ATP than to a decrease in the affinity to TKIs. Regrettably, detailed information at the atomic level on the origins of the increased binding affinity of mutants for ATP is lacking. In this study, we have combined structural data and molecular dynamics simulations with the MMGBSA approach to determine how the L858R, T790M and L858R/T790 mutations impact the binding mechanism of ATP with respect to wild-type EGFR. Structural and energetic analyses provided novel information that helps to explain the increased affinity of ATP to T790M and L858R/T790 mutants with respect to L858R and wild-type systems. In addition, it was observed that dimerization of the wild-type and mutant systems exerts dissimilar effects on the ATP binding affinity characteristic of negative cooperativity.

Communicated by Ramaswamy H. Sarma     

Thermodynamic dissection of the binding energetics of KNI-272, a potent HIV-1 protease inhibitor

KNI-272 is a powerful HIV-1 protease inhibitor with a reported inhibition constant in the picomolar range. In this paper, a complete experimental dissection of the thermodynamic forces that define the binding affinity of this inhibitor to the wild-type and drug-resistant mutant V82F/184V is presented. Unlike other protease inhibitors, KNI-272 binds to the protease with a favorable binding enthalpy. The origin of the favorable binding enthalpy has been traced to the coupling of the binding reaction to the burial of six water molecules. These bound water molecules, previously identified by NMR studies, optimize the atomic packing at the inhibitor/protein interface enhancing van der Waals and other favorable interactions. These interactions offset the unfavorable enthalpy usually associated with the binding of hydrophobic molecules. The association constant to the drug resistant mutant is 100-500 times weaker. The decrease in binding affinity corresponds to an increase in the Gibbs energy of binding of 3-3.5 kcal/mol, which originates from less favorable enthalpy (1.7 kcal/mol more positive) and entropy changes. Calorimetric binding experiments performed as a function of pH and utilizing buffers with different ionization enthalpies have permitted the dissection of proton linkage effects. According to these experiments, the binding of the inhibitor is linked to the protonation/deprotonation of two groups. In the uncomplexed form these groups have pKs of 6.0 and 4.8, and become 6.6 and 2.9 in the complex. These groups have been identified as one of the aspartates in the catalytic aspartyl dyad in the protease and the isoquinoline nitrogen in the inhibitor molecule. The binding affinity is maximal between pH 5 and pH 6. At those pH values the affinity is close to 6 x 10(10) M(-1) (Kd = 16 pM). Global analysis of the data yield a buffer- and pH-independent binding enthalpy of -6.3 kcal/mol. Under conditions in which the exchange of protons is zero, the Gibbs energy of binding is -14.7 kcal/mol from which a binding entropy of 28 cal/K mol is obtained. Thus, the binding of KNI-272 is both enthalpically and entropically favorable. The structure-based thermodynamic analysis indicates that the allophenylnorstatine nucleus of KNI-272 provides an important scaffold for the design of inhibitors that are less susceptible to resistant mutations.     

Affinity enhancement of an in vivo matured therapeutic antibody using structure-based computational design

Improving the affinity of a high-affinity protein-protein interaction is a challenging problem that has practical applications in the development of therapeutic biomolecules. We used a combination of structure-based computational methods to optimize the binding affinity of an antibody fragment to the I-domain of the integrin VLA1. Despite the already high affinity of the antibody (Kd approximately 7 nM) and the moderate resolution (2.8 A) of the starting crystal structure, the affinity was increased by an order of magnitude primarily through a decrease in the dissociation rate. We determined the crystal structure of a high-affinity quadruple mutant complex at 2.2 A. The structure shows that the design makes the predicted contacts. Structural evidence and mutagenesis experiments that probe a hydrogen bond network illustrate the importance of satisfying hydrogen bonding requirements while seeking higher-affinity mutations. The large and diverse set of interface mutations allowed refinement of the mutant binding affinity prediction protocol and improvement of the single-mutant success rate. Our results indicate that structure-based computational design can be successfully applied to further improve the binding of high-affinity antibodies.     

Optimization of binding electrostatics: charge complementarity in the barnase-barstar protein complex

Theoretical and experimental studies have shown that the large desolvation penalty required for polar and charged groups frequently precludes their involvement in electrostatic interactions that contribute strongly to net stability in the folding or binding of proteins in aqueous solution near room temperature. We have previously developed a theoretical framework for computing optimized electrostatic interactions and illustrated use of the algorithm with simplified geometries. Given a receptor and model assumptions, the method computes the ligand-charge distribution that provides the most favorable balance of desolvation and interaction effects on binding. In this paper the method has been extended to treat complexes using actual molecular shapes. The barnase-barstar protein complex was investigated with barnase treated as a target receptor. The atomic point charges of barstar were varied to optimize the electrostatic binding free energy. Barnase and natural barstar form a tight complex (K(d) approximately 10(-14) M) with many charged and polar groups near the interface that make this a particularly relevant system for investigating the role of electrostatic effects on binding. The results show that sets of barstar charges (resulting from optimization with different constraints) can be found that give rise to relatively large predicted improvements in electrostatic binding free energy. Principles for enhancing the effect of electrostatic interactions in molecular binding in aqueous environments are discussed in light of the optima. Our findings suggest that, in general, the enhancements in electrostatic binding free energy resulting from modification of polar and charged groups can be substantial. Moreover, a recently proposed definition of electrostatic complementarity is shown to be a useful tool for examining binding interfaces. Finally, calculational results suggest that wild-type barstar is closer to being affinity optimized than is barnase for their mutual binding, consistent with the known roles of these proteins.     

Unraveling hot spots in binding interfaces: progress and challenges

Protein interface hot spots, as revealed by alanine scanning mutagenesis, continue to stimulate interest in the biophysical basis of molecular recognition. Although these regions apparently constitute fertile grounds for intermolecular interactions, no general algorithm has yet been developed that can predict hot spots based solely on their shape or composition. The discovery of structural plasticity in hot spot regions indicates that dynamic simulation techniques may be essential for achieving a predictive understanding of binding interface energetics. Future progress will depend as much on the application of new computational approaches for dissecting protein interfaces as on expanding our empirical databank of mutagenic substitutions and their effects. Despite our current theoretical shortcomings, recent methodological advances provide efficient experimental means of probing hot spots and enable immediate applications for hot spots in drug discovery.     

Recapitulation and design of protein binding peptide structures and sequences

An important objective of computational protein design is the generation of high affinity peptide inhibitors of protein-peptide interactions, both as a precursor to the development of therapeutics aimed at disrupting disease causing complexes, and as a tool to aid investigators in understanding the role of specific complexes in the cell. We have developed a computational approach to increase the affinity of a protein-peptide complex by designing N or C-terminal extensions which interact with the protein outside the canonical peptide binding pocket. In a first in silico test, we show that by simultaneously optimizing the sequence and structure of three to nine residue peptide extensions starting from short (1-6 residue) peptide stubs in the binding pocket of a peptide binding protein, the approach can recover both the conformations and the sequences of known binding peptides. Comparison with phage display and other experimental data suggests that the peptide extension approach recapitulates naturally occurring peptide binding specificity better than fixed backbone design, and that it should be useful for predicting peptide binding specificities from crystal structures. We then experimentally test the approach by designing extensions for p53 and dystroglycan-based peptides predicted to bind with increased affinity to the Mdm2 oncoprotein and to dystrophin, respectively. The measured increases in affinity are modest, revealing some limitations of the method. Based on these in silico and experimental results, we discuss future applications of the approach to the prediction and design of protein-peptide interactions.     

Identification of novel Nicotinamide Phosphoribosyltransferase (NAMPT) inhibitors using computational approaches

Nicotinamide Phosphoribosyltransferase (NAMPT) is a rate-limiting enzyme in the biosynthesis of NAD. Cancer cells have elevated poly [ADP-Ribose] polymerase 1 (PARP) activity as well as the immense necessity of ATP: thereby consuming NAD at a higher rate than normal tissues. The perturbation of these intracellular processes is more sensitive and highly dependent on NAMPT to maintain the required NAD levels. Functional inhibition of NAMPT is, therefore, a promising drug target in therapeutic oncology. In this study, the importance of intermolecular contacts was realized based on contact occupancy and favorable energetic from molecular dynamic simulation to discern non-critical contacts of four different classes of potential NAMPT inhibitor bound complexes. Further, pharmacophore modeling, molecular docking, a quantum mechanical properties and MD simulation, as well as active site residual network communication were employed to identify potential leads. Present studies identified two leads, 2 and 3 which have better binding free energy compared to known inhibitors and showed stable hydrogen bonding and hydrophobic contacts with β barrel cavity lining residues in the active site of the dimer interface (A′B). Lead 2 containing fluorene as central core and lead 3 having phenyl-benzamide as a core showed stable moiety which was observed from electronic property analysis. Active site residual communication in identified leads bound complex also showed similarity to known inhibitor complexes. Compounds containing these moieties were not reported until now against NAMPT inhibition and can be considered as novel cores for future development of drugs to inhibit NAMPT function.     

The role of flexibility and hydration on the sequence-specific DNA recognition by the Tn916 integrase protein: a molecular dynamics analysis

The N-terminal domain of the Tn916 integrase protein (INT-DBD) is responsible for DNA binding in the process of strand cleavage and joining reactions required for transposition of the Tn916 conjugative transposon. Site-specific association is facilitated by numerous protein-DNA contacts from the face of a three-stranded beta-sheet inserted into the major groove. The protein undergoes a subtle conformational transition and is slightly unfolded in the protein-DNA complex. The conformation of many charged residues is poorly defined by NMR data but mutational studies have indicated that removal of polar side chains decreases binding affinity, while non-polar contacts are malleable. Based on analysis of the binding enthalpy and binding heat capacity, we have reasoned that dehydration of the protein-DNA interface is incomplete. This study presents results from a molecular dynamics investigation of the INT-DBD-DNA complex aimed at a more detailed understanding of the role of conformational dynamics and hydration in site-specific binding. Comparison of simulations (total of 13 ns) of the free protein and of the bound protein conformation (in isolation or DNA-bound) reveals intrinsic flexibility in certain parts of the molecule. Conformational adaptation linked to partial unfolding appears to be induced by protein-DNA contacts. The protein-DNA hydrogen-bonding network is highly dynamic. The simulation identifies protein-DNA interactions that are poorly resolved or only surmised from the NMR ensemble. Single water molecules and water clusters dynamically optimize the complementarity of polar interactions at the 'wet' protein-DNA interface. The simulation results are useful to establish a qualitative link between experimental data on individual residue's contribution to binding affinity and thermodynamic properties of INT-DBD alone and in complex with DNA.     

Modulating calmodulin binding specificity through computational protein design

We report the computational redesign of the protein-binding interface of calmodulin (CaM), a small, ubiquitous Ca(2+)-binding protein that is known to bind to and regulate a variety of functionally and structurally diverse proteins. The CaM binding interface was optimized to improve binding specificity towards one of its natural targets, smooth muscle myosin light chain kinase (smMLCK). The optimization was performed using optimization of rotamers by iterative techniques (ORBIT), a protein design program that utilizes a physically based force-field and the Dead-End Elimination theorem to compute sequences that are optimal for a given protein scaffold. Starting from the structure of the CaM-smMLCK complex, the program considered 10(22) amino acid residue sequences to obtain the lowest-energy CaM sequence. The resulting eightfold mutant, CaM_8, was constructed and tested for binding to a set of seven CaM target peptides. CaM_8 displayed high binding affinity to the smMLCK peptide (1.3nM), similar to that of the wild-type protein (1.8nM). The affinity of CaM_8 to six other target peptides was reduced, as intended, by 1.5-fold to 86-fold. Hence, CaM_8 exhibited increased binding specificity, preferring the smMLCK peptide to the other targets. Studies of this type may increase our understanding of the origins of binding specificity in protein-ligand complexes and may provide valuable information that can be used in the design of novel protein receptors and/or ligands.     

An automated decision-tree approach to predicting protein interaction hot spots

Protein-protein interactions can be altered by mutating one or more "hot spots," the subset of residues that account for most of the interface's binding free energy. The identification of hot spots requires a significant experimental effort, highlighting the practical value of hot spot predictions. We present two knowledge-based models that improve the ability to predict hot spots: K-FADE uses shape specificity features calculated by the Fast Atomic Density Evaluation (FADE) program, and K-CON uses biochemical contact features. The combined K-FADE/CON (KFC) model displays better overall predictive accuracy than computational alanine scanning (Robetta-Ala). In addition, because these methods predict different subsets of known hot spots, a large and significant increase in accuracy is achieved by combining KFC and Robetta-Ala. The KFC analysis is applied to the calmodulin (CaM)/smooth muscle myosin light chain kinase (smMLCK) interface, and to the bone morphogenetic protein-2 (BMP-2)/BMP receptor-type I (BMPR-IA) interface. The results indicate a strong correlation between KFC hot spot predictions and mutations that significantly reduce the binding affinity of the interface.     

Topology-based modeling of intrinsically disordered proteins: balancing intrinsic folding and intermolecular interactions

Coupled binding and folding is frequently involved in specific recognition of so-called intrinsically disordered proteins (IDPs), a newly recognized class of proteins that rely on a lack of stable tertiary fold for function. Here, we exploit topology-based Gō-like modeling as an effective tool for the mechanism of IDP recognition within the theoretical framework of minimally frustrated energy landscape. Importantly, substantial differences exist between IDPs and globular proteins in both amino acid sequence and binding interface characteristics. We demonstrate that established Gō-like models designed for folded proteins tend to over-estimate the level of residual structures in unbound IDPs, whereas under-estimating the strength of intermolecular interactions. Such systematic biases have important consequences in the predicted mechanism of interaction. A strategy is proposed to recalibrate topology-derived models to balance intrinsic folding propensities and intermolecular interactions, based on experimental knowledge of the overall residual structure level and binding affinity. Applied to pKID/KIX, the calibrated Gō-like model predicts a dominant multistep sequential pathway for binding-induced folding of pKID that is initiated by KIX binding via the C-terminus in disordered conformations, followed by binding and folding of the rest of C-terminal helix and finally the N-terminal helix. This novel mechanism is consistent with key observations derived from a recent NMR titration and relaxation dispersion study and provides a molecular-level interpretation of kinetic rates derived from dispersion curve analysis. These case studies provide important insight into the applicability and potential pitfalls of topology-based modeling for studying IDP folding and interaction in general.     

Insight into the binding modes and inhibition mechanisms of adamantyl-based 1,3-disubstituted urea inhibitors in the active site of the human soluble epoxide hydrolase

Soluble epoxide hydrolase (sEH) is a promising new target for treating hypertension and inflammation. Considerable efforts have been devoted to develop novel inhibitors. In this study, the binding modes and interaction mechanisms of a series of adamantyl-based 1,3-disubstituted urea inhibitors were investigated by molecular docking, molecular dynamics simulations, binding free energy calculations, and binding energy decomposition analysis. Based on binding affinity, the most favorable binding mode was determined for each inhibitor. The calculation results indicate that the total binding free energy (ΔG_TOT, the sum of enthalpy ΔG_MM-GB/SA, and entropy ?TΔS) presents a good correlation with the experimental inhibitory activity (IC₅₀, r²?=?.99). The van der Waals energy contributes most to the total binding free energy (ΔG_TOT). A detailed discussion on the interactions between inhibitors and those residues located in the active pocket is made based on hydrogen bond and binding modes analysis. According to binding energy decomposition, the residues Asp333 and Trp334 contribute the most to binding free energy in all systems. Furthermore, Hip523 plays a major role in determining this class of inhibitor-binding orientations. Combined with the results of hydrogen bond analysis and binding free energy, we believe that the conserved hydrogen bonds play a role only in anchoring the inhibitors to the exact site for binding and the number of hydrogen bonds may not directly relate to the binding free energy. The results we obtained will provide valuable information for the design of high potency sEH inhibitors.     

Complex Structure of Engineered Modular Domains Defining Molecular Interaction between ICAM-1 and Integrin LFA-1

Intermolecular contacts between integrin LFA-1 (α(L)β(2)) and ICAM-1 derive solely from the integrin α(L) I domain and the first domain (D1) of ICAM-1. This study presents a crystal structure of the engineered complex of the α(L) I domain and ICAM-1 D1. Previously, we engineered the I domain for high affinity by point mutations that were identified by a directed evolution approach. In order to examine α(L) I domain allostery between the C-terminal α7-helix (allosteric site) and the metal-ion dependent adhesion site (active site), we have chosen a high affinity variant without mutations directly influencing either the position of the α7-helix or the active sites. In our crystal, the α(L) I domain was found to have a high affinity conformation to D1 with its α7-helix displaced downward away from the binding interface, recapitulating a current understanding of the allostery in the I domain and its linkage to neighboring domains of integrins in signaling. To enable soluble D1 of ICAM-1 to fold on its own, we also engineered D1 to be functional by mutations, which were found to be those that would convert hydrogen bond networks in the solvent-excluded core into vdW contacts. The backbone structure of the β-sandwich fold and the epitope for I domain binding of the engineered D1 were essentially identical to those of wild-type D1. Most deviations in engineered D1 were found in the loops at the N-terminal region that interacts with human rhinovirus (HRV). Structural deviation found in engineered D1 was overall in agreement with the function of engineered D1 observed previously, i.e., full capacity binding to α(L) I domain but reduced interaction with HRV.