BMC Structural Biology最新文献

The ESX-1 type VII secretion system is an important determinant of virulence in pathogenic mycobacteria, including Mycobacterium tuberculosis. This complicated molecular machine secretes folded proteins through the mycobacterial cell envelope to subvert the host immune response. Despite its important role in disease very little is known about the molecular architecture of the ESX-1 secretion system.

This study characterizes the structures of the soluble domains of two conserved core ESX-1 components – EccB₁ and EccD₁. The periplasmic domain of EccB₁ consists of 4 repeat domains and a central domain, which together form a quasi 2-fold symmetrical structure. The repeat domains of EccB₁ are structurally similar to a known peptidoglycan binding protein suggesting a role in anchoring the ESX-1 system within the periplasmic space. The cytoplasmic domain of EccD₁has a ubiquitin-like fold and forms a dimer with a negatively charged groove.

These structures represent a major step towards resolving the molecular architecture of the entire ESX-1 assembly and may contribute to ESX-1 targeted tuberculosis intervention strategies.

Multimeric naphthoquinones are redox-active compounds that exhibit antineoplastic, antiprotozoal, and antiviral activities. Due to their multimodal effect on perturbation of cellular oxidative state, these compounds hold great potential as therapeutic agents against highly proliferative neoplastic cells. In our previous work, we developed a series of novel dimeric naphthoquinones and showed that they were selectively cytotoxic to human acute myeloid leukemia (AML), breast and prostate cancer cell lines. We subsequently identified the oxidoreductase NAD(P)H dehydrogenase, quinone 1 (NQO1) as the major target of dimeric naphthoquinones and proposed a mechanism of action that entailed induction of a futile redox cycling.

Here, for the first time, we describe a direct physical interaction between the bromohydroxy dimeric naphthoquinone E6a and NQO1. Moreover, our studies reveal an extensive binding interface between E6a and the isoalloxazine ring of the flavin adenine dinucleotide (FAD) cofactor of NQO1 in addition to interactions with protein side chains in the active site. We also present biochemical evidence that dimeric naphthoquinones affect the redox state of the FAD cofactor of NQO1. Comparison of the mode of binding of E6a with those of other chemotherapeutics reveals unique characteristics of the interaction that can be leveraged in future drug optimization efforts.

The first structure of a dimeric naphthoquinone-NQO1 complex was reported, which can be used for design and synthesis of more potent next generation dimeric naphthoquinones to target NQO1 with higher affinity and specificity.

Many β-strands are not flat but bend and/or twist. However, although almost all β-strands have a twist, not all have a bend, suggesting that the underlying force(s) driving β-strand bending is distinct from that for the twist. We, therefore, investigated the physical origin(s) of β-strand bends.

We calculated rotation, twist and bend angles for a four-residue short frame. Fixed-length fragments consisting of six residues found in three consecutive short frames were used to evaluate the twist and bend angles of full-length β-strands.

We calculated and statistically analyzed the twist and bend angles of β-strands found in globular proteins with known three-dimensional structures. The results show that full-length β-strand bend angles are related to the nearby aromatic residue content, whereas local bend angles are related to the nearby aliphatic residue content. Furthermore, it appears that β-strands bend to maximize their hydrophobic contacts with an abutting hydrophobic surface or to form a hydrophobic side-chain cluster when an abutting hydrophobic surface is absent.

We conclude that the dominant driving force for full-length β-strand bends is the hydrophobic interaction involving aromatic residues, whereas that for local β-strand bends is the hydrophobic interaction involving aliphatic residues.

Sec4p is a small monomeric Ras-related GTP-binding protein (23?kDa) that regulates polarized exocytosis in S. cerevisiae. In this study we examine the structural effects of a conserved serine residue in the P-loop corresponding to G12 in Ras.

We show that the Sec4p residue serine 29 forms a hydrogen bond with the nucleotide. Mutations of this residue have a different impact than equivalent mutations in Ras and can form stable associations with the exchange factor allowing us to elucidate the structure of a complex of Sec4p bound to the exchange factor Sec2p representing an early stage of the exchange reaction.

Our structural investigation of the Sec4p-Sec2p complex reveals the role of the Sec2p coiled-coil domain in facilitating the fast kinetics of the exchange reaction. For Ras-family GTPases, single point mutations that impact the signaling state of the molecule have been well described however less structural information is available for equivalent mutations in the case of Rab proteins. Understanding the structural properties of mutants such as the one described here, provides useful insights into unique aspects of Rab GTPase function.

Over the last two decades, many approaches have been developed in bioinformatics that aim at one of the most promising, yet unsolved problems in modern life sciences - prediction of structural features of a protein. Such tasks addressed to transmembrane protein structures provide valuable knowledge about their three-dimensional structure. For this reason, the analysis of membrane proteins is essential in genomic and proteomic-wide investigations. Thus, many in-silico approaches have been utilized extensively to gain crucial advances in understanding membrane protein structures and functions.

It turned out that amino acid covariation within interacting sequence parts, extracted from a evolutionary sequence record of α-helical membrane proteins, can be used for structure prediction. In a recent study we discussed the significance of short membrane sequence motifs widely present in nature that act as stabilizing ’building blocks’ during protein folding and in retaining the three-dimensional fold. In this work, we used motif data to define evolutionary interaction pattern pairs. These were obtained from different pattern alignments and were used to evaluate which coupling mechanisms the evolution provides. It can be shown that short interaction patterns of homologous sequence records are membrane protein family-specific signatures. These signatures can provide valuable information for structure prediction and protein classification. The results indicate a good agreement with recent studies.

Generally, it can be shown how the evolution contributes to realize covariation within discriminative interaction patterns to maintain structure and function. This points to their general importance for α-helical membrane protein structure formation and interaction mediation. In the process, no fundamentally energetic approaches of previous published works are considered. The low-cost rapid computational methods postulated in this work provides valuable information to classify unknown α-helical transmembrane proteins and to determine their structural similarity.

A commonly recurring problem in structural protein studies, is the determination of all heavy atom positions from the knowledge of the central α-carbon coordinates.

We employ advances in virtual reality to address the problem. The outcome is a 3D visualisation based technique where all the heavy backbone and side chain atoms are treated on equal footing, in terms of the C_α coordinates. Each heavy atom is visualised on the surfaces of a different two-sphere, that is centered at another heavy backbone and side chain atoms. In particular, the rotamers are visible as clusters, that display a clear and strong dependence on the underlying backbone secondary structure.

We demonstrate that there is a clear interdependence between rotameric states and secondary structure. Our method easily detects those atoms in a crystallographic protein structure which are either outliers or have been likely misplaced, possibly due to radiation damage. Our approach forms a basis for the development of a new generation, visualization based side chain construction, validation and refinement tools. The heavy atom positions are identified in a manner which accounts for the secondary structure environment, leading to improved accuracy.

Hirudin is an anti-coagulation protein produced by the salivary glands of the medicinal leech Hirudomedicinalis. It is a powerful and specific thrombin inhibitor. The novel recombinant hirudin, RGD-hirudin, which contains an RGD motif, competitively inhibits the binding of fibrinogen to GPIIb/IIIa on platelets, thus inhibiting platelet aggregation while maintaining its anticoagulant activity.

Recombinant RGD-hirudin and six mutant variants (Y3A, S50A, Q53A, D55A, E57A and I59A), designed based on molecular simulations, were expressed in Pichia pastoris. The proteins were refolded and purified to homogeneity as monomers by gel filtration and anion exchange chromatography. The anti-thrombin activity of the six mutants and RGD-hirudin was tested. Further, we evaluated the binding of the mutant variants and RGD-hirudin to thrombin using BIAcore surface plasmon resonance analysis (SPR). Kinetics and affinity constants showed that the K_D values of all six mutant proteins were higher than that of RGD-hirudin.

These findings contribute to a novel understanding of the interaction between RGD-hirudin and thrombin.

Thanks to the growth in sequence and structure databases, more than 50 million sequences are now available in UniProt and 100,000 structures in the PDB. Rich information about protein-protein interfaces can be obtained by a comprehensive study of protein contacts in the PDB, their sequence conservation and geometric features.

An automated computational pipeline was developed to run our Evolutionary protein-protein Interface Classifier (EPPIC) software on the entire PDB and store the results in a relational database, currently containing > 800,000 interfaces. This allows the analysis of interface data on a PDB-wide scale. Two large benchmark datasets of biological interfaces and crystal contacts, each containing about 3000 entries, were automatically generated based on criteria thought to be strong indicators of interface type. The BioMany set of biological interfaces includes NMR dimers solved as crystal structures and interfaces that are preserved across diverse crystal forms, as catalogued by the Protein Common Interface Database (ProtCID) from Xu and Dunbrack. The second dataset, XtalMany, is derived from interfaces that would lead to infinite assemblies and are therefore crystal contacts. BioMany and XtalMany were used to benchmark the EPPIC approach. The performance of EPPIC was also compared to classifications from the Protein Interfaces, Surfaces, and Assemblies (PISA) program on a PDB-wide scale, finding that the two approaches give the same call in about 88% of PDB interfaces. By comparing our safest predictions to the PDB author annotations, we provide a lower-bound estimate of the error rate of biological unit annotations in the PDB. Additionally, we developed a PyMOL plugin for direct download and easy visualization of EPPIC interfaces for any PDB entry. Both the datasets and the PyMOL plugin are available at http://www.eppic-web.org/ewui/#downloads.

Our computational pipeline allows us to analyze protein-protein contacts and their sequence conservation across the entire PDB. Two new benchmark datasets are provided, which are over an order of magnitude larger than existing manually curated ones. These tools enable the comprehensive study of several aspects of protein-protein contacts in the PDB and represent a basis for future, even larger scale studies of protein-protein interactions.

This paper provides a simple and rapid method for a protein-clustering strategy. The basic idea implemented here is to use computational geometry methods to predict and characterize ligand-binding pockets of a given protein structure. In addition to geometrical characteristics of the protein structure, we consider some simple biochemical properties that help recognize the best candidates for pockets in a protein’s active site.

Our results are shown to produce good agreement with known empirical results.

The method presented in this paper is a low-cost rapid computational method that could be used to classify proteins and other biomolecules, and furthermore could be useful in reducing the cost and time of drug discovery.