A Generic Self-Assembly Process in Microcompartments and Synthetic Protein Nanotubes

Bacterial microcompartments enclose a biochemical pathway and reactive intermediate within a protein envelope formed by the shell proteins. Herein, the orientation of the propanediol?utilization (Pdu) microcompartment shell protein PduA in bacterial microcompartments and in synthetic nanotubes, and the orientation of PduB in synthetic nanotubes are revealed. When produced individually, PduA hexamers and PduB trimers, tessellate to form flat sheets in the crystal, or they can self?assemble to form synthetic protein nanotubes in solution. Modelling the orientation of PduA in the 20 nm nanotube so as to preserve the shape complementarity and key interactions seen in the crystal structure suggests that the concave surface of the PduA hexamer faces out. This orientation is confirmed experimentally in synthetic nanotubes and in the bacterial microcompartment produced in vivo. The PduB nanotubes described here have a larger diameter, 63 nm, with the concave surface of the trimer again facing out. The conserved concave surface out characteristic of these nano?structures reveals a generic assembly process that causes the interface between adjacent subunits to bend in a common direction that optimizes shape complementarity and minimizes steric clashes. This understanding underpins engineering strategies for the biotechnological application of protein nanotubes

Structural analysis on mutation residues and interfacial water molecules for human TIM disease understanding

10.1186/1471-2105-14-S16-S11BMC Bioinformatics14SUPPL16-BBMI

BALL - biochemical algorithms library 1.3

<p>Abstract</p> <p>Background</p> <p>The Biochemical Algorithms Library (BALL) is a comprehensive rapid application development framework for structural bioinformatics. It provides an extensive C++ class library of data structures and algorithms for molecular modeling and structural bioinformatics. Using BALL as a programming toolbox does not only allow to greatly reduce application development times but also helps in ensuring stability and correctness by avoiding the error-prone reimplementation of complex algorithms and replacing them with calls into the library that has been well-tested by a large number of developers. In the ten years since its original publication, BALL has seen a substantial increase in functionality and numerous other improvements.</p> <p>Results</p> <p>Here, we discuss BALL's current functionality and highlight the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics.</p> <p>Conclusions</p> <p>BALL is available for all major operating systems, including Linux, Windows, and MacOS X. It is available free of charge under the Lesser GNU Public License (LPGL). Parts of the code are distributed under the GNU Public License (GPL). BALL is available as source code and binary packages from the project web site at <url>http://www.ball-project.org</url>. Recently, it has been accepted into the debian project; integration into further distributions is currently pursued.</p

A Steered Molecular Dynamics Study of Binding and Translocation Processes in the GABA Transporter

The entire substrate translocation pathway in the human GABA transporter (GAT-1) was explored for the endogenous substrate GABA and the anti-convulsive drug tiagabine. Following a steered molecular dynamics (SMD) approach, in which a harmonic restraining potential is applied to the ligand, dissociation and re-association of ligands were simulated revealing events leading to substrate (GABA) translocation and inhibitor (tiagabine) mechanism of action. We succeeded in turning the transporter from the outward facing occluded to the open-to-out conformation, and also to reorient the transporter to the open-to-in conformation. The simulations are validated by literature data and provide a substrate pathway fingerprint in terms of which, how, and in which sequence specific residues are interacted with. They reveal the essential functional roles of specific residues, e.g. the role of charged residues in the extracellular vestibule including two lysines (K76 (TM1) and K448 (TM10)) and a TM6-triad (D281, E283, and D287) in attracting and relocating substrates towards the secondary/interim substrate-binding site (S2). Likewise, E101 is highlighted as essential for the relocation of the substrate from the primary substrate-binding site (S1) towards the cytoplasm

Bayesian inference of protein structure from chemical shift data

Protein chemical shifts are routinely used to augment molecular mechanics force fields in protein structure simulations, with weights of the chemical shift restraints determined empirically. These weights, however, might not be an optimal descriptor of a given protein structure and predictive model, and a bias is introduced which might result in incorrect structures. In the inferential structure determination framework, both the unknown structure and the disagreement between experimental and back-calculated data are formulated as a joint probability distribution, thus utilizing the full information content of the data. Here, we present the formulation of such a probability distribution where the error in chemical shift prediction is described by either a Gaussian or Cauchy distribution. The methodology is demonstrated and compared to a set of empirically weighted potentials through Markov chain Monte Carlo simulations of three small proteins (ENHD, Protein G and the SMN Tudor Domain) using the PROFASI force field and the chemical shift predictor CamShift. Using a clustering-criterion for identifying the best structure, together with the addition of a solvent exposure scoring term, the simulations suggests that sampling both the structure and the uncertainties in chemical shift prediction leads more accurate structures compared to conventional methods using empirical determined weights. The Cauchy distribution, using either sampled uncertainties or predetermined weights, did, however, result in overall better convergence to the native fold, suggesting that both types of distribution might be useful in different aspects of the protein structure prediction

Structural and Functional Insights into Endoglin Ligand Recognition and Binding

Endoglin, a type I membrane glycoprotein expressed as a disulfide-linked homodimer on human vascular endothelial cells, is a component of the transforming growth factor (TGF)-β receptor complex and is implicated in a dominant vascular dysplasia known as hereditary hemorrhagic telangiectasia as well as in preeclampsia. It interacts with the type I TGF-β signaling receptor activin receptor-like kinase (ALK)1 and modulates cellular responses to Bone Morphogenetic Protein (BMP)-9 and BMP-10. Structurally, besides carrying a zona pellucida (ZP) domain, endoglin contains at its N-terminal extracellular region a domain of unknown function and without homology to any other known protein, therefore called the orphan domain (OD). In this study, we have determined the recognition and binding ability of full length ALK1, endoglin and constructs encompassing the OD to BMP-9 using combined methods, consisting of surface plasmon resonance and cellular assays. ALK1 and endoglin ectodomains bind, independently of their glycosylation state and without cooperativity, to different sites of BMP-9. The OD comprising residues 22 to 337 was identified among the present constructs as the minimal active endoglin domain needed for partner recognition. These studies also pinpointed to Cys350 as being responsible for the dimerization of endoglin. In contrast to the complete endoglin ectodomain, the OD is a monomer and its small angle X-ray scattering characterization revealed a compact conformation in solution into which a de novo model was fitted

Optimal assignment methods for ligand-based virtual screening

<p>Abstract</p> <p>Background</p> <p>Ligand-based virtual screening experiments are an important task in the early drug discovery stage. An ambitious aim in each experiment is to disclose active structures based on new scaffolds. To perform these "scaffold-hoppings" for individual problems and targets, a plethora of different similarity methods based on diverse techniques were published in the last years. The optimal assignment approach on molecular graphs, a successful method in the field of quantitative structure-activity relationships, has not been tested as a ligand-based virtual screening method so far.</p> <p>Results</p> <p>We evaluated two already published and two new optimal assignment methods on various data sets. To emphasize the "scaffold-hopping" ability, we used the information of chemotype clustering analyses in our evaluation metrics. Comparisons with literature results show an improved early recognition performance and comparable results over the complete data set. A new method based on two different assignment steps shows an increased "scaffold-hopping" behavior together with a good early recognition performance.</p> <p>Conclusion</p> <p>The presented methods show a good combination of chemotype discovery and enrichment of active structures. Additionally, the optimal assignment on molecular graphs has the advantage to investigate and interpret the mappings, allowing precise modifications of internal parameters of the similarity measure for specific targets. All methods have low computation times which make them applicable to screen large data sets.</p