Ranking Peptide Binders by Affinity with AlphaFold**

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.     

Direct observations of conformational distributions of intrinsically disordered p53 peptides using UV Raman and explicit solvent simulations

We report the first experimental measurements of Ramachandran Ψ-angle distributions for intrinsically disordered peptides: the N-terminal peptide fragment of tumor suppressor p53 and its P27S mutant form. To provide atomically detailed views of the conformational distributions, we performed classical, explicit-solvent molecular dynamics simulations on the microsecond time scale. Upon binding its partner protein, MDM2, wild-type p53 peptide adopts an α-helical conformation. Mutation of Pro27 to serine results in the highest affinity yet observed for MDM2-binding of the p53 peptide. Both UV resonance Raman spectroscopy (UVRR) and simulations reveal that the P27S mutation decreases the extent of PPII helical content and increases the probability for conformations that are similar to the α-helical MDM2-bound conformation. In addition, UVRR measurements were performed on peptides that were isotopically labeled at the Leu26 residue preceding the Pro27 in order to determine the conformational distributions of Leu26 in the wild-type and mutant peptides. The UVRR and simulation results are in quantitative agreement in terms of the change in the population of non-PPII conformations involving Leu26 upon mutation of Pro27 to serine. Finally, our simulations reveal that the MDM2-bound conformation of the peptide is significantly populated in both the wild-type and mutant isolated peptide ensembles in their unbound states, suggesting that MDM2 binding of the p53 peptides may involve conformational selection.     

SEC–MS as an Approach to Isolate and Directly Identifying Small Molecular GPCR–Ligands from Complex Mixtures Without Labeling

G protein coupled receptors (GPCRs) belong to the most successful targets in drug discovery. However, the development of assays with an appropriately labeled high affinity reporter compound is laborious. In the present study an MS-based binding assay is described using the rat histamine receptor 2 (rH2) as a model GPCR system. Instead of using a purified receptor it is demonstrated that it is possible to use an unpurified receptor to extract active compounds from a solution or small mixture of compounds. By using SEC it is possible to separate the bound ligand from the unbound ligand. The major advantage of this approach is that there is no labeling of ligands required (direct monitoring based on the appropriate m/z values).     

Solid-state NMR evidence for a protonation switch in the binding pocket of the H1 receptor upon binding of the agonist histamine

G protein coupled receptors (GPCRs) represent a major superfamily of transmembrane receptor proteins that are crucial in cellular signaling and are major pharmacological targets. While the activity of GPCRs can be modulated by agonist binding, the mechanisms that link agonist binding to G protein coupling are poorly understood. Here we present a method to accurately examine the activity of ligands in their bound state, even at low affinity, by solid-state NMR dipolar correlation spectroscopy and confront this method with the human H1 receptor. The analysis reveals two different charge states of the bound agonist, dicationic with a charged imidazole ring and monocationic with a neutral imidazole ring, with the same overall conformation. The combination of charge difference and pronounced heterogeneity agrees with converging evidence that the active and inactive states of the GPCR represent a dynamic equilibrium of substates and that proton transfer between agonist and protein side chains can shift this equilibrium by stabilizing the active receptor population relative to the inactive one. In fact, the data suggest a global functional analogy between H1 receptor activation and the meta I/meta II charge/discharge equilibrium in rhodopsin (GPCR). This corroborates current ideas on unifying principles in GPCR structure and function.     

Peptide mimetics as enzyme inhibitors: Use of free energy perturbation calculations to evaluate isosteric replacement for amide bonds in a potent HIV protease inhibitor

Summary We present the application of free energy perturbation theory/molecular dynamics to predict the consequence of replacing each of the seven peptide bonds in the potent HIV protease inhibitor JG365: ACE (acetyl)-Ser-Leu-Asn-HEA (hydroxyethylamine analog of Phe-Pro)-Ile-Val-NME (N-methyl) by ethylene or fluoroethylene isosteres. Replacing two of these bonds may well lead to significantly tighter binding; replacing two others is predicted to significantly diminish the binding affinity. Also, for three of the peptide bonds fluoroethylene replacements could lead to increased binding of free energies of the inhibitors. Our results should be considered as predictive since there are, as yet, no experimental results on such peptide replacements as enzyme inhibitors.     

Universality of the Sodium Ion Binding Mechanism in Class A G‐Protein‐Coupled Receptors

The allosteric modulation of G‐protein‐coupled receptors (GPCRs) by sodium ions has received significant attention as crystal structures of several receptors show Na⁺ ions bound to the inactive conformations at the conserved Asp^2.50. To date, structures from 24 families of GPCRs have been determined, though mechanistic insights into Na⁺ binding to the allosteric site are limited. We performed hundreds‐of‐microsecond long simulations of 18 GPCRs and elucidated their Na⁺ binding mechanism. In class A GPCRs, the Na⁺ ion binds to the conserved residue 2.50 whereas in class B receptors, it binds at 3.43b, 6.53b, and 7.49b. Using Markov state models, we obtained the free energy profiles and kinetics of Na⁺ binding to the allosteric site, which reveal a conserved mechanism of Na⁺ binding for GPCRs and show the residues that act as major barriers for ion diffusion. Furthermore, we also show that the Na⁺ ion can bind to GPCRs from the intracellular side when the allosteric site is inaccessible from the extracellular side.     

Unwinding of the C‐Terminal Residues of Neuropeptide Y is critical for Y2 Receptor Binding and Activation

Despite recent breakthroughs in the structural characterization of G‐protein‐coupled receptors (GPCRs), there is only sparse data on how GPCRs recognize larger peptide ligands. NMR spectroscopy, molecular modeling, and double‐cycle mutagenesis studies were integrated to obtain a structural model of the peptide hormone neuropeptide Y (NPY) bound to its human G‐protein‐coupled Y₂ receptor (Y₂R). Solid‐state NMR measurements of specific isotope‐labeled NPY in complex with in vitro folded Y₂R reconstituted into phospholipid bicelles provided the bioactive structure of the peptide. Guided by solution NMR experiments, it could be shown that the ligand is tethered to the second extracellular loop by hydrophobic contacts. The C‐terminal α‐helix of NPY, which is formed in a membrane environment in the absence of the receptor, is unwound starting at T³² to provide optimal contacts in a deep binding pocket within the transmembrane bundle of the Y₂R.     

Atomistic insights into rhodopsin activation from a dynamic model

Rhodopsin, the light sensitive receptor responsible for blue-green vision, serves as a prototypical G protein-coupled receptor (GPCR). Upon light absorption, it undergoes a series of conformational changes that lead to the active form, metarhodopsin II (META II), initiating a signaling cascade through binding to the G protein transducin (G(t)). Here, we first develop a structural model of META II by applying experimental distance restraints to the structure of lumi-rhodopsin (LUMI), an earlier intermediate. The restraints are imposed by using a combination of biased molecular dynamics simulations and perturbations to an elastic network model. We characterize the motions of the transmembrane helices in the LUMI-to-META II transition and the rearrangement of interhelical hydrogen bonds. We then simulate rhodopsin activation in a dynamic model to study the path leading from LUMI to our META II model for wild-type rhodopsin and a series of mutants. The simulations show a strong correlation between the transition dynamics and the pharmacological phenotypes of the mutants. These results help identify the molecular mechanisms of activation in both wild type and mutant rhodopsin. While static models can provide insights into the mechanisms of ligand recognition and predict ligand affinity, a dynamic model of activation could be applicable to study the pharmacology of other GPCRs and their ligands, offering a key to predictions of basal activity and ligand efficacy.     

Virtual screen for ligands of orphan G protein-coupled receptors

This paper describes a virtual screening methodology that generates a ranked list of high-binding small molecule ligands for orphan G protein-coupled receptors (oGPCRs), circumventing the requirement for receptor three-dimensional structure determination. Features representing the receptor are based only on physicochemical properties of primary amino acid sequence, and ligand features use the two-dimensional atomic connection topology and atomic properties. An experimental screen comprised nearly 2 million hypothetical oGPCR-ligand complexes, from which it was observed that the top 1.96% predicted affinity scores corresponded to "highly active" ligands against orphan receptors. Results representing predicted high-scoring novel ligands for many oGPCRs are presented here. Validation of the method was carried out in several ways: (1) A random permutation of the structure-activity relationship of the training data was carried out; by comparing test statistic values of the randomized and nonshuffled data, we conclude that the value obtained with nonshuffled data is unlikely to have been encountered by chance. (2) Biological activities linked to the compounds with high cross-target binding affinity were analyzed using computed log-odds from a structure-based program. This information was correlated with literature citations where GPCR-related pathways or processes were linked to the bioactivity in question. (3) Anecdotal, out-of-sample predictions for nicotinic targets and known ligands were performed, with good accuracy in the low-to-high "active" binding range. (4) An out-of-sample consistency check using the commercial antipsychotic drug olanzapine produced "active" to "highly-active" predicted affinities for all oGPCRs in our study, an observation that is consistent with documented findings of cross-target affinity of this compound for many different GPCRs. It is suggested that this virtual screening approach may be used in support of the functional characterization of oGPCRs by identifying potential cognate ligands. Ultimately, this approach may have implications for pharmaceutical therapies to modulate the activity of faulty or disease-related cellular signaling pathways. In addition to application to cell surface receptors, this approach is a generalized strategy for discovery of small molecules that may bind intracellular enzymes and involve protein-protein interactions.     

Identification of a Conformational Equilibrium That Determines the Efficacy and Functional Selectivity of the μ‐Opioid Receptor

G‐protein‐coupled receptor (GPCR) ligands impart differing degrees of signaling in the G‐protein and arrestin pathways, in phenomena called “biased signaling”. However, the mechanism underlying the biased signaling of GPCRs is still unclear, although crystal structures of GPCRs bound to the G protein or arrestin are available. In this study, we observed the NMR signals from methionine residues of the μ‐opioid receptor (μOR) in the balanced‐ and biased‐ligand‐bound states. We found that the intracellular cavity of μOR exists in an equilibrium between closed and multiple open conformations with coupled conformational changes on the transmembrane helices 3, 5, 6, and 7, and that the population of each open conformation determines the G‐protein‐ and arrestin‐mediated signaling levels in each ligand‐bound state. These findings provide insight into the biased signaling of GPCRs and will be helpful for development of analgesics that stimulate μOR with reduced tolerance and dependence.     

Relative energies of binding for antibody-carbohydrate-antigen complexes computed from free-energy simulations

Free-energy perturbation (FEP) simulations have been applied to a series of analogues of the natural trisaccharide epitope of Salmonella serotype B bound to a fragment of the monoclonal anti-Salmonella antibody Se155-4. This system was selected in order to assess the ability of free-energy perturbation (FEP) simulations to predict carbohydrate-protein interaction energies. The ultimate goal is to use FEP simulations to aid in the design of synthetic high affinity ligands for carbohydrate-binding proteins. The molecular dynamics (MD) simulations were performed in the explicit presence of water molecules, at room temperature. The AMBER force field, with the GLYCAM parameter set for oligosaccharides, was employed. In contrast to many modeling protocols, FEP simulations are capable of including the effects of entropy, arising from differential ligand flexibilities and solvation properties. The experimental binding affinities are all close in value, resulting in small relative free energies of binding. Many of the DeltaDeltaG values are on the order of 0-1 kcal mol(-1), making their accurate calculation particularly challenging. The simulations were shown to reasonably reproduce the known geometries of the ligands and the ligand-protein complexes. A model for the conformational behavior of the unbound antigen is proposed that is consistent with the reported NMR data. The best agreement with experiment was obtained when histidine 97H was treated as fully protonated, for which the relative binding energies were predicted to well within 1 kcal mol(-1). To our knowledge this is the first report of FEP simulations applied to an oligosaccharide-protein complex.     

Biological properties of opioid peptides replacing Tyr at position 1 by 2,6-dimethyl-Tyr.

To understand the effect of the replacement of Tyr residue at position 1 in opioid peptides by 2,6-dimethyl-Tyr (Dmt) on the biological property, chiral (D or L) Dmt1 analogs of Leu-enkephalin (Enk) and Tyr-D-Arg-Phe-beta Ala-NH2 (YRFB) were synthesized and their enzymatic stabilities, in vitro bioactivities and receptor binding affinities compared with those of parent peptides. [L-Dmt1]Enk (1) exhibited 4-fold higher stability against aminopeptidase-M and possessed dramatically increased activities in guinea pig ilium (GPI) (187-fold) and mouse vas deferens (MVD) (131-fold) assays, and in rat brain receptor binding assays (356-fold at mu receptor and 46-fold at delta receptor) as compared to Enk. [L-Dmt1]YRFB (3) also exhibited increased activities in GPI (46-fold) and MVD (177-fold) assays, and in the binding assays (69-fold at mu receptro and 341-fold at delta receptor) as compared to the parent peptide. [D-Dmt1]Enk (2) and [D-Dmt1]YRFB (4) exhibited activities with diminished or lesser potency than the parent peptide in all assays. These results indicate that there is a tendency for mu affinity to be enhanced more than delta affinity with introduction of L-Dmt into delta ligand peptide (Enk), and for delta affinity to be enhanced more than mu affinity in case of mu ligand peptide (YRFB), resulting in reduced receptor selectivities at the receptors.     

Nanobody‐Enabled Reverse Pharmacology on G‐Protein‐Coupled Receptors

The conformational complexity of transmembrane signaling of G‐protein‐coupled receptors (GPCRs) is a central hurdle for the design of screens for receptor agonists. In their basal states, GPCRs have lower affinities for agonists compared to their G‐protein‐bound active state conformations. Moreover, different agonists can stabilize distinct active receptor conformations and do not uniformly activate all cellular signaling pathways linked to a given receptor (agonist bias). Comparative fragment screens were performed on a β₂‐adrenoreceptor–nanobody fusion locked in its active‐state conformation by a G‐protein‐mimicking nanobody, and the same receptor in its basal‐state conformation. This simple biophysical assay allowed the identification and ranking of multiple novel agonists and permitted classification of the efficacy of each hit in agonist, antagonist, or inverse agonist categories, thereby opening doors to nanobody‐enabled reverse pharmacology.     

Fragment‐based quantum mechanical calculation of protein–protein binding affinities

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE‐GMFCC) method has been successfully utilized for efficient linear‐scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE‐GMFCC method for calculation of binding affinity of Endonuclease colicin–immunity protein complex. The binding free energy changes between the wild‐type and mutants of the complex calculated by EE‐GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6‐31G*‐D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein–protein binding affinities. Moreover, the self‐consistent calculation of PB solvation energy is required for accurate calculations of protein–protein binding free energies. This study demonstrates that the EE‐GMFCC method is capable of providing reliable prediction of relative binding affinities for protein–protein complexes. © 2018 Wiley Periodicals, Inc.     

Biological applications of the receptor mimetic peptide mastoparan

The receptor mimetic and mast cell degranulating peptide mastoparan (MP) translocates cell membranes as an amphipathic alpha-helix, a feature that is undoubtedly a major determinant of bioactivity through the activation of heterotrimeric G proteins. Chimeric combinations of MP with G protein-coupled receptor (GPCR) ligands has produced peptides that exhibit biological activities distinct from their composite components. Thus, chimeric peptides such as galparan and M391 differentially modulate GTPase activity, display altered binding affinities for appropriate GPCRs and possess disparate secretory properties. MP and MP-containing chimerae also bind and modulate the activities of various other intracellular protein targets and are valuable tools to manipulate and study enzymatic activity, calcium homeostasis and apoptotic signalling pathways. In addition, charge delocalisation within the hydrophilic face of MP has produced analogues, including [Lys5, Lys8,Aib10]MP, that differentially regulate mast cell secretion and/or cytotoxicity. Finally, the identification of cell penetrant variants of MP chimerae has enabled the effective intracellular delivery of non-permeable biomolecules and presents an opportunity to target novel intracellular therapeutic loci.     

Molecular dynamics simulations of CXCL-8 and its interactions with a receptor peptide, heparin fragments, and sulfated linked cyclitols

CXCL-8 (Interleukin 8) is a CXC chemokine with a central role in the human immune response. We have undertaken extensive in silico analyses to elucidate the interactions of CXCL-8 with its various binding partners, which are crucial for its biological function. Sequence and structure analyses showed that residues in the thirdq β-sheet and basic residues in the heparin binding site are highly variable, while residues in the second β-sheet are highly conserved. Molecular dynamics simulations in aqueous solution of dimeric CXCL-8 have been performed with starting geometries from both X-ray and NMR structures showed shearing movements between the two antiparallel C-terminal helices. Dynamic conservation analyses of these simulations agreed with experimental data indicating that structural differences between the two structures at quaternary level arise from changes in the secondary structure of the N-terminal loop, the 3(10)-helix, the 30s, 40s, and 50s loops and the third β-sheet, resulting in a different interhelical separation. Nevertheless, the observation of these different states indicates that CXCL-8 has the potential to undergo conformational changes, and it seems likely that this feature is relevant to the mode of binding of glycosaminoglycan (GAG) mimetics such as cyclitols. Simulations of the receptor peptide fragment-CXCL-8 complex identified several specific interactions of the receptor peptide with CXCL-8 that could be exploited in the structure-based design of competitive peptides and nonpeptidic molecules targeting CXCL-8 for combating inflammatory diseases. Simulations of the CXCL-8 dimer complexed with a 24-mer heparin fragment and of the CXCL-8-receptor peptide complex revealed that Arg60, Lys64, and Arg68 in the dimer bind to cyclitols in a horseshoe pattern, defining a region which is spatially distinct from the receptor binding site. There appears to be an optimum number of sulfates and an optimum length of alkyl spacers required for the interaction of cyclitol inhibitors with the dimeric form of CXCL-8. Calculation of the binding affinities of cyclitol inhibitors reflected satisfactorily the ranking of experimentally determined inhibitory potencies. The findings of these molecular modeling studies will help in the search for inhibitors which can modulate various CXCL-8 biological activities and serve as an excellent model system to study CXC-inhibitor interactions.     

Structural and energetic insight into the interactions between the benzolactam inhibitors and tumor marker HSP90α

The heat shock protein 90α (HSP90α) provides a promising molecular target for cancer therapy. A series of novel benzolactam inhibitors exhibited distinct inhibitory activity for HSP90α. However, the structural basis for the impact of distinct R₁ substituent groups of nine benzolactam inhibitors on HSP90α binding affinities remains unknown. In this study, we carried out molecular docking, molecular dynamics (MD) simulations, and molecular mechanics and generalized Born/surface area (MM–GBSA) binding free energy calculations to address the differences. Molecular docking studies indicated that all nine compounds presented one conformation in the ATP-binding site of HSP90α N-terminal domain. MD simulations and subsequent MM–GBSA calculations revealed that the hydrophobic interactions between all compounds and HSP90α contributed the most to the binding affinity and a good linear correlation was obtained between the calculated and the experimental binding free energies (R = 0.88). The per residue decomposition revealed that the most remarkable differences of residue contributions were found in the residues Ala55, Ile96, and Leu107 defining a hydrophobic pocket for the R₁ group, consistent with the analysis of binding modes. This study may be helpful for the future design of novel HSP90α inhibitors.     

Monitoring the Reversibility of GPCR Signaling by Combining Photochromic Ligands with Label-free Impedance Analysis

G protein-coupled cell surface receptors (GPCR) trigger complex intracellular signaling cascades upon agonist binding. Classic pharmacological assays provide information about binding affinities, activation or blockade at different stages of the signaling cascade, but real time dynamics and reversibility of these processes remain often disguised. We show that combining photochromic NPY receptor ligands, which can be toggled in their receptor activation ability by irradiation with light of different wavelengths, with whole cell label-free impedance assays allows observing the cell response to receptor activation and its reversibility over time. The concept demonstrated on NPY receptors may be well applicable to many other GPCRs providing a deeper insight into the time course of intracellular signaling processes.     

Differences between G‐Protein‐Stabilized Agonist–GPCR Complexes and their Nanobody‐Stabilized Equivalents

Protein nanobodies have been used successfully as surrogates for unstable G‐proteins in order to crystallize G‐protein‐coupled receptors (GPCRs) in their active states. We used molecular dynamics (MD) simulations, including metadynamics enhanced sampling, to investigate the similarities and differences between GPCR–agonist ternary complexes with the α‐subunits of the appropriate G‐proteins and those with the protein nanobodies (intracellular binding partners, IBPs) used for crystallization. In two of the three receptors considered, the agonist‐binding mode differs significantly between the two alternative ternary complexes. The ternary‐complex model of GPCR activation entails enhancement of ligand binding by bound IBPs: Our results show that IBP‐specific changes can alter the agonist binding modes and thus also the criteria for designing GPCR agonists.     

Homodimerization of neurotensin 1 receptor involves helices 1, 2, and 4: insights from quaternary structure predictions and dimerization free energy estimations

A computational approach based upon rigid-body docking, ad hoc filtering, and cluster analysis has been combined with a protocol for dimerization free energy estimations to predict likely interfaces in the neurotensin 1 receptor (NTS1) homodimers. The results of this study suggest that the likely intermonomer interfaces compatible with in vitro binding affinity constants essentially involve helices 1, 2, and 4 and do not include disulfide bridges. The correlative model initially developed on Glycophorin A and herein extended to a G protein-Coupled Receptor (GPCR) appears to be a useful tool for estimating the association free energies of transmembrane proteins independent of the size and shape of the interface. In the desirable future cases, in which in vitro intermonomer binding affinities will be available for other GPCRs, such a correlative model will work as an additional criterion for helping in the selection of the most likely dimers.