184 research outputs found
Virtual screening for inhibitors of the human TSLP:TSLPR interaction
The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Ra), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP: TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP: alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP: TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-ofprinciple for use of fragments in the inhibition of TSLP: TSLPR complexation
Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows
We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.Fil: Goncearenco, Alexander. National Institutes of Health; Estados UnidosFil: Li, Minghui. Soochow University; China. National Institutes of Health; Estados UnidosFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Shoemaker, Benjamin A. National Institutes of Health; Estados UnidosFil: Panchenko, Anna R. National Institutes of Health; Estados Unido
A direct physical interaction between Nanog and Sox2 regulates embryonic stem cell self-renewal
Embryonic stem (ES) cell self-renewal efficiency is determined by the Nanog protein level. However, the protein partners of Nanog that function to direct self-renewal are unclear. Here, we identify a Nanog interactome of over 130 proteins including transcription factors, chromatin modifying complexes, phosphorylation and ubiquitination enzymes, basal transcriptional machinery members, and RNA processing factors. Sox2 was identified as a robust interacting partner of Nanog. The purified Nanog–Sox2 complex identified a DNA recognition sequence present in multiple overlapping Nanog/Sox2 ChIP-Seq data sets. The Nanog tryptophan repeat region is necessary and sufficient for interaction with Sox2, with tryptophan residues required. In Sox2, tyrosine to alanine mutations within a triple-repeat motif (S X T/S Y) abrogates the Nanog–Sox2 interaction, alters expression of genes associated with the Nanog-Sox2 cognate sequence, and reduces the ability of Sox2 to rescue ES cell differentiation induced by endogenous Sox2 deletion. Substitution of the tyrosines with phenylalanine rescues both the Sox2–Nanog interaction and efficient self-renewal. These results suggest that aromatic stacking of Nanog tryptophans and Sox2 tyrosines mediates an interaction central to ES cell self-renewal
Intestinal CFTR expression alleviates meconium ileus in cystic fibrosis pigs
published_or_final_versio
Identification of hot-spot residues in protein-protein interactions by computational docking
<p>Abstract</p> <p>Background</p> <p>The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'). These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex.</p> <p>Results</p> <p>We have applied here normalized interface propensity (<it>NIP</it>) values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value), and the advantage of not requiring any prior structural knowledge of the complex.</p> <p>Conclusion</p> <p>The <it>NIP </it>values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.</p
Anchored Design of Protein-Protein Interfaces
Few existing protein-protein interface design methods allow for extensive backbone rearrangements during the design process. There is also a dichotomy between redesign methods, which take advantage of the native interface, and de novo methods, which produce novel binders.Here, we propose a new method for designing novel protein reagents that combines advantages of redesign and de novo methods and allows for extensive backbone motion. This method requires a bound structure of a target and one of its natural binding partners. A key interaction in this interface, the anchor, is computationally grafted out of the partner and into a surface loop on the design scaffold. The design scaffold's surface is then redesigned with backbone flexibility to create a new binding partner for the target. Careful choice of a scaffold will bring experimentally desirable characteristics into the new complex. The use of an anchor both expedites the design process and ensures that binding proceeds against a known location on the target. The use of surface loops on the scaffold allows for flexible-backbone redesign to properly search conformational space.This protocol was implemented within the Rosetta3 software suite. To demonstrate and evaluate this protocol, we have developed a benchmarking set of structures from the PDB with loop-mediated interfaces. This protocol can recover the correct loop-mediated interface in 15 out of 16 tested structures, using only a single residue as an anchor
Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
10.1186/1471-2105-15-57BMC Bioinformatics151-BBMI
Protein binding hot spots and the residue-residue pairing preference: a water exclusion perspective
<p>Abstract</p> <p>Background</p> <p>A protein binding hot spot is a small cluster of residues tightly packed at the center of the interface between two interacting proteins. Though a hot spot constitutes a small fraction of the interface, it is vital to the stability of protein complexes. Recently, there are a series of hypotheses proposed to characterize binding hot spots, including the pioneering O-ring theory, the insightful 'coupling' and 'hot region' principle, and our 'double water exclusion' (DWE) hypothesis. As the perspective changes from the O-ring theory to the DWE hypothesis, we examine the physicochemical properties of the binding hot spots under the new hypothesis and compare with those under the O-ring theory.</p> <p>Results</p> <p>The requirements for a cluster of residues to form a hot spot under the DWE hypothesis can be mathematically satisfied by a biclique subgraph if a vertex is used to represent a residue, an edge to indicate a close distance between two residues, and a bipartite graph to represent a pair of interacting proteins. We term these hot spots as DWE bicliques. We identified DWE bicliques from crystal packing contacts, obligate and non-obligate interactions. Our comparative study revealed that there are abundant <it>unique </it>bicliques to the biological interactions, indicating specific biological binding behaviors in contrast to crystal packing. The two sub-types of biological interactions also have their own signature bicliques. In our analysis on residue compositions and residue pairing preferences in DWE bicliques, the focus was on interaction-preferred residues (ipRs) and interaction-preferred residue pairs (ipRPs). It is observed that hydrophobic residues are heavily involved in the ipRs and ipRPs of the obligate interactions; and that aromatic residues are in favor in the ipRs and ipRPs of the biological interactions, especially in those of the non-obligate interactions. In contrast, the ipRs and ipRPs in crystal packing are dominated by hydrophilic residues, and most of the anti-ipRs of crystal packing are the ipRs of the obligate or non-obligate interactions.</p> <p>Conclusions</p> <p>These ipRs and ipRPs in our DWE bicliques describe a diverse binding features among the three types of interactions. They also highlight the specific binding behaviors of the biological interactions, sharply differing from the artifact interfaces in the crystal packing. It can be noted that DWE bicliques, especially the unique bicliques, can capture deep insights into the binding characteristics of protein interfaces.</p
The Caenorhabditis elegans HNF4α Homolog, NHR-31, Mediates Excretory Tube Growth and Function through Coordinate Regulation of the Vacuolar ATPase
Nuclear receptors of the Hepatocyte Nuclear Factor-4 (HNF4) subtype have been linked to a host of developmental and metabolic functions in animals ranging from worms to humans; however, the full spectrum of physiological activities carried out by this nuclear receptor subfamily is far from established. We have found that the Caenorhabditis elegans nuclear receptor NHR-31, a homolog of mammalian HNF4 receptors, is required for controlling the growth and function of the nematode excretory cell, a multi-branched tubular cell that acts as the C. elegans renal system. Larval specific RNAi knockdown of nhr-31 led to significant structural abnormalities along the length of the excretory cell canal, including numerous regions of uncontrolled growth at sites near to and distant from the cell nucleus. nhr-31 RNAi animals were sensitive to acute challenge with ionic stress, implying that the osmoregulatory function of the excretory cell was also compromised. Gene expression profiling revealed a surprisingly specific role for nhr-31 in the control of multiple genes that encode subunits of the vacuolar ATPase (vATPase). RNAi of these vATPase genes resulted in excretory cell defects similar to those observed in nhr-31 RNAi animals, demonstrating that the influence of nhr-31 on excretory cell growth is mediated, at least in part, through coordinate regulation of the vATPase. Sequence analysis revealed a stunning enrichment of HNF4α type binding sites in the promoters of both C. elegans and mouse vATPase genes, arguing that coordinate regulation of the vATPase by HNF4 receptors is likely to be conserved in mammals. Our study establishes a new pathway for regulation of excretory cell growth and reveals a novel role for HNF4-type nuclear receptors in the development and function of a renal system
Prediction of binding hot spot residues by using structural and evolutionary parameters
In this work, we present a method for predicting hot spot residues by using a set of structural and evolutionary parameters. Unlike previous studies, we use a set of parameters which do not depend on the structure of the protein in complex, so that the predictor can also be used when the interface region is unknown. Despite the fact that no information concerning proteins in complex is used for prediction, the application of the method to a compiled dataset described in the literature achieved a performance of 60.4%, as measured by F-Measure, corresponding to a recall of 78.1% and a precision of 49.5%. This result is higher than those reported by previous studies using the same data set
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