Design of cyclic and d‐amino acids containing peptidomimetics for inhibition of protein‐protein interactions of HER2‐HER3

HER2 receptors are surface proteins belonging to the epidermal growth factor family of receptors. Their numbers are elevated in breast, lung, and ovarian cancers. HER2‐positive cancers are aggressive, have higher mortality rate, and have a poor prognosis. We have designed peptidomimetics that bind to HER2 and block the HER2‐mediated dimerization of epidermal growth factor family of receptors. Among these, a symmetrical cyclic peptidomimetic (compound 18 ) exhibited antiproliferative activity in HER2‐overexpressing lung cancer cell lines with IC₅₀ values in the nanomolar concentration range. To improve the stability of the peptidomimetic, d ‐amino acids were introduced into the peptidomimetic, and several analogs of compound 18 were designed. Among the analogs of compound 18 , compound 32 , a cyclic, d ‐amino acid‐containing peptidomimetic, was found to have an IC₅₀ value in the nanomolar range in HER2‐overexpressing cancer cell lines. The antiproliferative activity of compound 32 was also measured by using a 3D cell culture model that mimics the in vivo conditions. The binding of compound 32 to the HER2 protein was studied by surface plasmon resonance. In vitro stability studies indicated that compound 32 was stable in serum for 48 hours and intact peptide was detectable in vivo for 12 hours. Results from our studies indicated that 1 of the d ‐amino acid analogs of 18 , compound 32 , binds to the HER2 extracellular domain, inhibiting the phosphorylation of kinase of HER2.     

A rapid fluorogenic GPCR–β‐arrestin interaction assay

Detection of protein–protein interactions involved in signal transduction in live cells and organisms has a variety of important applications. We report a fluorogenic assay for G protein‐coupled receptor (GPCR)–β‐arrestin interaction that is genetically encoded, generalizes to multiple GPCRs, and features high signal‐to‐noise because fluorescence is absent until its components interact upon GPCR activation. Fluorescence after protease‐activated receptor‐1 activation developed in minutes and required specific serine–threonine residues in the receptor carboxyl tail, consistent with a classical G protein‐coupled receptor kinase dependent β‐arrestin recruitment mechanism. This assay provides a useful complement to other in vivo assays of GPCR activation.     

Structure‐guided design of a reversible fluorogenic reporter of protein‐protein interactions

A reversible green fluorogenic protein‐fragment complementation assay was developed based on the crystal structure of UnaG, a recently discovered fluorescent protein. In living mammalian cells, the nonfluorescent fragments complemented and rapidly became fluorescent upon rapamycin‐induced FKBP and Frb protein interaction, and lost fluorescence when the protein interaction was inhibited. This reversible fluorogenic reporter, named uPPI [UnaG‐based protein‐protein interaction (PPI) reporter], uses bilirubin (BR) as the chromophore and requires no exogenous cofactor. BR is an endogenous molecule in mammalian cells and is not fluorescent by itself. uPPI may have many potential applications in visualizing spatiotemporal dynamics of PPIs.     

A non‐redundant protein–RNA docking benchmark version 2.0

We present an updated version of the protein–RNA docking benchmark, which we first published four years back. The non‐redundant protein–RNA docking benchmark version 2.0 consists of 126 test cases, a threefold increase in number compared to its previous version. The present version consists of 21 unbound–unbound cases, of which, in 12 cases, the unbound RNAs are taken from another complex. It also consists of 95 unbound–bound cases where only the protein is available in the unbound state. Besides, we introduce 10 new bound–unbound cases where only the RNA is found in the unbound state. Based on the degree of conformational change of the interface residues upon complex formation the benchmark is classified into 72 rigid‐body cases, 25 semiflexible cases and 19 full flexible cases. It also covers a wide range of conformational flexibility including small side chain movement to large domain swapping in protein structures as well as flipping and restacking in RNA bases. This benchmark should provide the docking community with more test cases for evaluating rigid‐body as well as flexible docking algorithms. Besides, it will also facilitate the development of new algorithms that require large number of training set. The protein–RNA docking benchmark version 2.0 can be freely downloaded from http://www.csb.iitkgp.ernet.in/applications/PRDBv2 . Proteins 2017; 85:256–267. © 2016 Wiley Periodicals, Inc.     

Mitotic spindle association of TACC3 requires Aurora‐A‐dependent stabilization of a cryptic α‐helix

Aurora‐A regulates the recruitment of TACC3 to the mitotic spindle through a phospho‐dependent interaction with clathrin heavy chain (CHC). Here, we describe the structural basis of these interactions, mediated by three motifs in a disordered region of TACC3. A hydrophobic docking motif binds to a previously uncharacterized pocket on Aurora‐A that is blocked in most kinases. Abrogation of the docking motif causes a delay in late mitosis, consistent with the cellular distribution of Aurora‐A complexes. Phosphorylation of Ser558 engages a conformational switch in a second motif from a disordered state, needed to bind the kinase active site, into a helical conformation. The helix extends into a third, adjacent motif that is recognized by a helical‐repeat region of CHC, not a recognized phospho‐reader domain. This potentially widespread mechanism of phospho‐recognition provides greater flexibility to tune the molecular details of the interaction than canonical recognition motifs that are dominated by phosphate binding.     

A Novel Core‐Attachment–Based Method to Identify Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

Cellular functions are always performed by protein complexes. At present, many approaches have been proposed to identify protein complexes from protein–protein interaction (PPI) networks. Some approaches focus on detecting local dense subgraphs in PPI networks which are regarded as protein‐complex cores, then identify protein complexes by including local neighbors. However, from gene expression profiles at different time points or tissues it is known that proteins are dynamic. Therefore, identifying dynamic protein complexes should become very important and meaningful. In this study, a novel core‐attachment–based method named CO‐DPC to detect dynamic protein complexes is presented. First, CO‐DPC selects active proteins according to gene expression profiles and the 3‐sigma principle, and constructs dynamic PPI networks based on the co‐expression principle and PPI networks. Second, CO‐DPC detects local dense subgraphs as the cores of protein complexes and then attach close neighbors of these cores to form protein complexes. In order to evaluate the method, the method and the existing algorithms are applied to yeast PPI networks. The experimental results show that CO‐DPC performs much better than the existing methods. In addition, the identified dynamic protein complexes can match very well and thus become more meaningful for future biological study.     

Discovery of binding proteins for a protein target using protein–protein docking‐based virtual screening

Target structure‐based virtual screening, which employs protein‐small molecule docking to identify potential ligands, has been widely used in small‐molecule drug discovery. In the present study, we used a protein–protein docking program to identify proteins that bind to a specific target protein. In the testing phase, an all‐to‐all protein–protein docking run on a large dataset was performed. The three‐dimensional rigid docking program SDOCK was used to examine protein–protein docking on all protein pairs in the dataset. Both the binding affinity and features of the binding energy landscape were considered in the scoring function in order to distinguish positive binding pairs from negative binding pairs. Thus, the lowest docking score, the average Z‐score, and convergency of the low‐score solutions were incorporated in the analysis. The hybrid scoring function was optimized in the all‐to‐all docking test. The docking method and the hybrid scoring function were then used to screen for proteins that bind to tumor necrosis factor‐α (TNFα), which is a well‐known therapeutic target for rheumatoid arthritis and other autoimmune diseases. A protein library containing 677 proteins was used for the screen. Proteins with scores among the top 20% were further examined. Sixteen proteins from the top‐ranking 67 proteins were selected for experimental study. Two of these proteins showed significant binding to TNFα in an in vitro binding study. The results of the present study demonstrate the power and potential application of protein–protein docking for the discovery of novel binding proteins for specific protein targets. Proteins 2014; 82:2472–2482. © 2014 Wiley Periodicals, Inc.     

Identification of key stabilizing interactions of amyloid-β oligomers based on fragment molecular orbital calculations on macrocyclic β-hairpin peptides

Analyzing the electronic states and inter-/intra-molecular interactions of amyloid oligomers expand our understanding of the molecular basis of Alzheimer's disease and other amyloid diseases. In the current study, several high-resolution crystal structures of oligomeric assemblies of Aβ-derived peptides have been studied by the ab initio fragment molecular orbital (FMO) method. The FMO method provides comprehensive details of the molecular interactions between the residues of the amyloid oligomers at the quantum mechanical level. Based on the calculations, two sequential aromatic residues (F19 and F20) and negatively charged E22 on the central region of Aβ have been identified as key residues in oligomer stabilization and potential interesting pharmacophores for preventing oligomer formation.     

Temperature‐dependent study reveals that dynamics of hydrophobic residues plays an important functional role in the mitochondrial Tim9–Tim10 complex

Protein–protein interaction is a fundamental process in all major biological processes. The hexameric Tim9–Tim10 (translocase of inner membrane) complex of the mitochondrial intermembrane space plays an essential chaperone‐like role during import of mitochondrial membrane proteins. However, little is known about the functional mechanism of the complex because the interaction is weak and transient. This study investigates how electrostatic and hydrophobic interactions affect the conformation and function of the complex at physiological temperatures, using both experimental and computational methods. The results suggest that, first, different complex conformational states exist at equilibrium, and the major difference between these states is the degree of hydrophobic interactions. Second, the conformational change mimics the biological activity of the complex as measured by substrate binding at the same temperatures. Finally, molecular dynamics simulation and detailed energy decomposition analysis provided supporting evidence at the atomic level for the presence of an excited state of the complex, the formation of which is largely driven by the disruption of hydrophobic interactions. Taken together, this study indicates that the dynamics of the hydrophobic residues plays an important role in regulating the function of the Tim9–Tim10 complex. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Cation–π, amino–π, π–π, and H‐bond interactions stabilize antigen–antibody interfaces

The identification of immunogenic regions on the surface of antigens, which are able to stimulate an immune response, is a major challenge for the design of new vaccines. Computational immunology aims at predicting such regions—in particular B‐cell epitopes—but is far from being reliably applicable on a large scale. To gain understanding into the factors that contribute to the antigen–antibody affinity and specificity, we perform a detailed analysis of the amino acid composition and secondary structure of antigen and antibody surfaces, and of the interactions that stabilize the complexes, in comparison with the composition and interactions observed in other heterodimeric protein interfaces. We make a distinction between linear and conformational B‐cell epitopes, according to whether they consist of successive residues along the polypeptide chain or not. The antigen–antibody interfaces were shown to differ from other protein–protein interfaces by their smaller size, their secondary structure with less helices and more loops, and the interactions that stabilize them: more H‐bond, cation–π, amino–π, and π–π interactions, and less hydrophobic packing; linear and conformational epitopes can clearly be distinguished. Often, chains of successive interactions, called cation/amino–π and π–π chains, are formed. The amino acid composition differs significantly between the interfaces: antigen–antibody interfaces are less aliphatic and more charged, polar and aromatic than other heterodimeric protein interfaces. Moreover, paratopes and epitopes—albeit to a lesser extent—have amino acid compositions that are distinct from general protein surfaces. This specificity holds promise for improving B‐cell epitope prediction. Proteins 2014; 82:1734–1746. © 2014 Wiley Periodicals, Inc.     

Detection of membrane protein–protein interaction in planta based on dual‐intein‐coupled tripartite split‐GFP association

Despite the great interest in identifying protein–protein interactions (PPIs) in biological systems, only a few attempts have been made at large‐scale PPI screening in planta. Unlike biochemical assays, bimolecular fluorescence complementation allows visualization of transient and weak PPIs in vivo at subcellular resolution. However, when the non‐fluorescent fragments are highly expressed, spontaneous and irreversible self‐assembly of the split halves can easily generate false positives. The recently developed tripartite split‐GFP system was shown to be a reliable PPI reporter in mammalian and yeast cells. In this study, we adapted this methodology, in combination with the β‐estradiol‐inducible expression cassette, for the detection of membrane PPIs in planta. Using a transient expression assay by agroinfiltration of Nicotiana benthamiana leaves, we demonstrate the utility of the tripartite split‐GFP association in plant cells and affirm that the tripartite split‐GFP system yields no spurious background signal even with abundant fusion proteins readily accessible to the compartments of interaction. By validating a few of the Arabidopsis PPIs, including the membrane PPIs implicated in phosphate homeostasis, we proved the fidelity of this assay for detection of PPIs in various cellular compartments in planta. Moreover, the technique combining the tripartite split‐GFP association and dual‐intein‐mediated cleavage of polyprotein precursor is feasible in stably transformed Arabidopsis plants. Our results provide a proof‐of‐concept implementation of the tripartite split‐GFP system as a potential tool for membrane PPI screens in planta.     

nNOS–CAPON interaction mediates amyloid‐β‐induced neurotoxicity,especially in the early stages

In neurons, increased protein–protein interactions between neuronal nitric oxide synthase (nNOS) and its carboxy‐terminal PDZ ligand (CAPON) contribute to excitotoxicity and abnormal dendritic spine development, both of which are involved in the development of Alzheimer's disease. In models of Alzheimer's disease, increased nNOS–CAPON interaction was detected after treatment with amyloid‐β in vitro, and a similar change was found in the hippocampus of APP/PS1 mice (a transgenic mouse model of Alzheimer's disease), compared with age‐matched background mice in vivo. After blocking the nNOS–CAPON interaction, memory was rescued in 4‐month‐old APP/PS1 mice, and dendritic impairments were ameliorated both in vivo and in vitro. Furthermore, we demonstrated that S‐nitrosylation of Dexras1 and inhibition of the ERK–CREB–BDNF pathway might be downstream of the nNOS–CAPON interaction.