Multivalent-Interaction-Driven Assembly of Discrete,Flexible, and Asymmetric Supramolecular Protein Nano-Prisms

Current approaches to design monodisperse protein assemblies require rigid, tight, and symmetric interactions between oligomeric protein units. Herein, we introduce a new multivalent-interaction-driven assembly strategy that allows flexible, spaced, and asymmetric assembly between protein oligomers. We discovered that two polygonal protein oligomers (ranging from triangle to hexagon) dominantly form a discrete and stable two-layered protein prism nanostructure via multivalent interactions between fused binding pairs. We demonstrated that protein nano-prisms with long flexible peptide linkers (over 80 amino acids) between protein oligomer layers could be discretely formed. Oligomers with different structures could also be monodispersely assembled into two-layered but asymmetric protein nano-prisms. Furthermore, producing higher-order architectures with multiple oligomer layers, for example, 3-layered nano-prisms or nanotubes, was also feasible.     

Aromaticity in stable tiara nickel thiolates: computational and structural analysis

Quantum chemical calculations as well as crystallographic analyses show that the Ni(n) rings in the tiara Ni thiolates, [NiS2]n and [Ni(SR)2]n (n = 3-6), have highly symmetric polygonal structures. We find that such structural features primarily arise from the effective delocalization of the d-orbital electrons across the Ni(n) rings leading to bond length equalization and thereby aromaticity. We introduce the d-orbital aromaticity for the first time to explain the experimentally observed polygonal structures of these cyclic metal rings bridged by thiol linkages.     

Inter-domain linker prediction using amino acid compositional index

Protein chains are generally long and consist of multiple domains. Domains are distinct structural units of a protein that can evolve and function independently. The accurate and reliable prediction of protein domain linkers and boundaries is often considered to be the initial step of protein tertiary structure and function predictions. In this paper, we introduce CISA as a method for predicting inter-domain linker regions solely from the amino acid sequence information. The method first computes the amino acid compositional index from the protein sequence dataset of domain-linker segments and the amino acid composition. A preference profile is then generated by calculating the average compositional index values along the amino acid sequence using a sliding window. Finally, the protein sequence is segmented into intervals and a simulated annealing algorithm is employed to enhance the prediction by finding the optimal threshold value for each segment that separates domains from inter-domain linkers. The method was tested on two standard protein datasets and showed considerable improvement over the state-of-the-art domain linker prediction methods.     

Single molecule force spectroscopy using polyproteins

In recent years single molecule force spectroscopy has emerged as a powerful new tool to explore the mechanical stability and folding pathways of individual proteins. This technique is used to apply a stretching force between two points of a protein, unfolding the protein to an extended state. By measuring the unfolding and folding trajectories of individual proteins, insight can be gained into the physical mechanisms of protein folding. In this tutorial review we introduce the reader to single molecule force spectroscopy using the atomic force microscope (AFM), and explain the two main modes of operation of the AFM for force spectroscopy: force-extension and force-clamp. We introduce the approach of using polyproteins to obtain a clear mechanical fingerprint for monitoring the response of proteins to an applied mechanical force. In addition, we provide an informative and representative review of recent research on proteins using single molecule force spectroscopy. We focus on areas which have made a significant contribution to the single molecule protein folding field and highlight emerging areas of research which have wider implications for the general scientific community.     

Collision‐free poisson motion planning in ultra high‐dimensional molecular conformation spaces

The function of protein, RNA, and DNA is modulated by fast, dynamic exchanges between three‐dimensional conformations. Conformational sampling of biomolecules with exact and nullspace inverse kinematics, using rotatable bonds as revolute joints and noncovalent interactions as holonomic constraints, can accurately characterize these native ensembles. However, sampling biomolecules remains challenging owing to their ultra‐high dimensional configuration spaces, and the requirement to avoid (self‐) collisions, which results in low acceptance rates. Here, we present two novel mechanisms to overcome these limitations. First, we introduce temporary constraints between near‐colliding links. The resulting constraint varieties instantaneously redirect the search for collision‐free conformations, and couple motions between distant parts of the linkage. Second, we adapt a randomized Poisson‐disk motion planner, which prevents local oversampling and widens the search, to ultra‐high dimensions. Tests on several model systems show that the sampling acceptance rate can increase from 16% to 70%, and that the conformational coverage in loop modeling measured as average closeness to existing loop conformations doubled. Correlated protein motions identified with our algorithm agree with those from MD simulations. © 2018 Wiley Periodicals, Inc.     

Core and peripheral connectivity based cluster analysis over PPI network

A number of methods have been proposed in the literature of protein–protein interaction (PPI) network analysis for detection of clusters in the network. Clusters are identified by these methods using various graph theoretic criteria. Most of these methods have been found time consuming due to involvement of preprocessing and post processing tasks. In addition, they do not achieve high precision and recall consistently and simultaneously. Moreover, the existing methods do not employ the idea of core-periphery structural pattern of protein complexes effectively to extract clusters. In this paper, we introduce a clustering method named CPCA based on a recent observation by researchers that a protein complex in a PPI network is arranged as a relatively dense core region and additional proteins weakly connected to the core. CPCA uses two connectivity criterion functions to identify core and peripheral regions of the cluster. To locate initial node of a cluster we introduce a measure called DNQ (Degree based Neighborhood Qualification) index that evaluates tendency of the node to be part of a cluster. CPCA performs well when compared with well-known counterparts. Along with protein complex gold standards, a co-localization dataset has also been used for validation of the results.     

Critical assessment of side-chain conformational space sampling procedures designed for quantifying the effect of side-chain environment

We introduce a family of procedures designed to sample side-chain conformational space at particular locations in protein structures. These procedures (CRSP) use intensive cycles of random assignment of side-chain conformations followed by minimization to determine all the conformations that a group of side-chains can adopt simultaneously. First, we consider a procedure evolving in the dihedral space (dCRSP). Our results suggest that it can accurately map low-energy conformations adopted by clusters of side-chains of a protein. dCRSP is relatively insensitive to various important parameters, and it is sufficiently accurate to capture efficiently the constraint induced by the environment on the conformations a particular side-chain can adopt. Our results show that dCRSP, compared with molecular dynamics (MD), can overcome the problem of the limited set of conformations reached in a reasonable amount of simulations. Next, we introduce procedures (vCRSP) in which valence angles are relaxed, and we assess how efficiently they quantify the conformational entropy of side-chains in the protein native state. For simple peptides, entropies obtained with vCRSP are fully compatible with those obtained with a Monte Carlo procedure. For side-chains in a protein environment, however, vCRSP appears of limited use. Finally, we consider a two-step procedure that combines dCRSP and vCRSP. Our tests suggest that it is able to overcome the limitations of vCRSP. We also note that dCRSP provides a reasonable initial approximation. This family of procedures offers promise in quantifying the contribution of conformational entropy to the energetics of protein structures.     

Folding DNA into a Lipid‐Conjugated Nanobarrel for Controlled Reconstitution of Membrane Proteins

Building upon DNA origami technology, we introduce a method to reconstitute a single membrane protein into a self‐assembled DNA nanobarrel that scaffolds a nanodisc‐like lipid environment. Compared with the membrane‐scaffolding‐protein nanodisc technique, our approach gives rise to defined stoichiometry, controlled sizes, as well as enhanced stability and homogeneity in membrane protein reconstitution. We further demonstrate potential applications of the DNA nanobarrels in the structural analysis of membrane proteins.     

Synthesis and Thermal Responses of Polygonal Poly(ethylene glycol) Analogues

As a new type of topological poly(ethylene glycol) (PEG) analogue, a series of polygonal PEGs with digonal to hexagonal structures were developed. Polygonal PEGs with structures between the digonal and tetragonal types showed molecular‐level dispersion in water at 20 °C, whereas the pentagonal and hexagonal PEGs aggregated, which is suggestive of enhanced hydrophobicity by ring expansion. Heating induced conformational changes in the polygonal PEGs and increased their hydrophobicity. Among the polygonal PEGs, only the trigonal and hexagonal PEGs showed a distinct thermal response to form and increase the size of the aggregates, respectively. Given that tetragonal and pentagonal PEGs only marginally responded to heat treatment, the thermal responses are likely due to a topological effect. At low temperatures, the larger polygonal PEGs are more restricted despite the expanded rings. The trigonal PEG showed the largest change in mobility, whereas the tetragonal PEG exhibited the smallest change. Hence, the topology of the polygonal PEGs influences the intramolecular packing and the local dynamics.     

Label-free analysis in chip electrophoresis applying deep UV fluorescence lifetime detection

Herein we introduce deep UV fluorescence lifetime detection in microfluidics applied for label-free detection and identification of various aromatic analytes in chip electrophoresis. For this purpose, a frequency quadrupled Nd:YAG (neodymium-doped yttrium aluminum garnet) picosecond laser at 266 nm was incorporated into an inverse fluorescence microscope setup with time-correlated single photon counting detection. This allowed recording of photon timing with sub-nanosecond precision. Thereby fluorescence decay curves are gathered on-the-fly and average lifetimes can be determined for each substance in the electropherogram. The aromatic compounds serotonin, propranolol, 3-phenoxy-1,2-propanediol and tryptophan were electrophoretically separated using a fused-silica microchip. Average lifetimes were independently determined for each compound via bi-exponential tail fitting. Time-correlated single photon counting also allows the discrimination of background fluorescence in the time domain. This results in improved signal-to-noise-ratios as demonstrated for the above model analytes. Microchip electrophoretic separations with fluorescence lifetime detection were also performed with a protein mixture containing lysozyme, trypsinogen and chymotrypsinogen emphasizing the potential for biopolymer analysis.     

Application of capillary electrophoresis/ electrospray ionization-mass spectrometry to subcellular proteomics of Escherichia coli ribosomal proteins

We introduce capillary electrophoresis-mass spectrometry (CE-MS) as an efficient means for the on-line separation and identification of protein mixtures. It was found that while CE/electrospray ionization (ESI)-MS analysis of whole-cell lysate was too complicated for the one-dimensional CE-MS analysis, the technique was useful for the analysis of protein mixtures of moderate complexity (approximately 50 intact proteins). CE/ESI-MS was applied to the subcellular proteomics of ribosomal Escherichia coli. 55 out of the 56 ribosomal proteins were detected with ease by using only approximately 3.4 ng of ribosomal proteins. In addition, it was found that the mass accuracy of the conventional MS (such as quadrupole ion traps) was good enough to identify many post-translational modifications of the intact proteins by simply comparing their measured average molecular weight with the average molecular weight predicted from gene banks.     

Drug development: longer-lived proteins

Protein therapeutics represent a powerful class of clinically approved drugs for the prevention and treatment of various diseases. Once administered, the biological fate of protein therapeutics is governed by the body's various complex biochemical and biophysical clearance mechanisms, several of which may decrease the drug's circulation time and efficiency. In this tutorial review, we introduce the concepts of physiological protein clearance from the body, and describe several chemical modification and protein engineering approaches used to improve the life span of administered protein therapeutics.     

Antibody Activation using DNA‐Based Logic Gates

Oligonucleotide‐based molecular circuits offer the exciting possibility to introduce autonomous signal processing in biomedicine, synthetic biology, and molecular diagnostics. Here we introduce bivalent peptide–DNA conjugates as generic, noncovalent, and easily applicable molecular locks that allow the control of antibody activity using toehold‐mediated strand displacement reactions. Employing yeast as a cellular model system, reversible control of antibody targeting is demonstrated with low nM concentrations of peptide–DNA locks and oligonucleotide displacer strands. Introduction of two different toehold strands on the peptide–DNA lock allowed signal integration of two different inputs, yielding logic OR‐ and AND‐gates. The range of molecular inputs could be further extended to protein‐based triggers by using protein‐binding aptamers.     

Statistically based reduced representation of amino acid side chains

Preferred conformations of amino acid side chains have been well established through statistically obtained rotamer libraries. Typically, these provide bond torsion angles allowing a side chain to be traced atom by atom. In cases where it is desirable to reduce the complexity of a protein representation or prediction, fixing all side-chain atoms may prove unwieldy. Therefore, we introduce a general parametrization to allow positions of representative atoms (in the present study, these are terminal atoms) to be predicted directly given backbone atom coordinates. Using a large, culled data set of amino acid residues from high-resolution protein crystal structures, anywhere from 1 to 7 preferred conformations were observed for each terminal atom of the non-glycine residues. Side-chain length from the backbone C(alpha) is one of the parameters determined for each conformation, which should itself be useful. Prediction of terminal atoms was then carried out for a second, nonredundant set of protein structures to validate the data set. Using four simple probabilistic approaches, the Monte Carlo style prediction of terminal atom locations given only backbone coordinates produced an average root mean-square deviation (RMSD) of approximately 3 A from the experimentally determined terminal atom positions. With prediction using conditional probabilities based on the side-chain chi(1) rotamer, this average RMSD was improved to 1.74 A. The observed terminal atom conformations therefore provide reasonable and potentially highly accurate representations of side-chain conformation, offering a viable alternative to existing all-atom rotamers for any case where reduction in protein model complexity, or in the amount of data to be handled, is desired. One application of this representation with strong potential is the prediction of charge density in proteins. This would likely be especially valuable on protein surfaces, where side chains are much less likely to be fixed in single rotamers. Prediction of ensembles of structures provides a method to determine the probability density of charge and atom location; such a prediction is demonstrated graphically.     

Rigorous determination of the stoichiometry of protein phosphorylation using mass spectrometry

Quantification of the stoichiometry of phosphorylation is usually achieved using a mixture of phosphatase treatment and differential isotopic labeling. Here, we introduce a new approach to the concomitant determination of absolute protein concentration and the stoichiometry of phosphorylation at predefined sites. The method exploits QconCAT to quantify levels of phosphorylated and nonphosphorylated peptide sequences in a phosphoprotein. The nonphosphorylated sequence is used to determine the absolute protein quantity and serves as a reference to calculate the extent of phosphorylation at the second peptide. Thus, the stoichiometry of phosphorylation and the absolute protein concentration can be determined accurately in a single experiment.     

基于微流控技术的蛋白质结晶及其筛选方法的研究进展

微流控技术以其高通量、 低消耗和集成化等优点成为蛋白质结晶微型化研究的重要手段. 本文综述了基于微流控技术的蛋白质结晶技术和方法, 主要包括微泵微阀、 液滴(Droplet)、 滑动芯片(SlipChip)以及液滴实验室(DropLab)等技术. 此外, 还针对当前膜蛋白在结构生物学研究中的重要地位, 综述了应用于膜蛋白结晶的微流控技术的研究进展.     

基于微流控技术的蛋白质结晶及其筛选方法的研究进展简

微流控技术以其高通量、低消耗和集成化等优点成为蛋白质结晶微型化研究的重要手段. 本文综述了基于微流控技术的蛋白质结晶技术和方法,主要包括微泵微阀、液滴(Droplet)、滑动芯片(SlipChip)以及液滴实验室(DropLab)等技术. 此外,还针对当前膜蛋白在结构生物学研究中的重要地位,综述了应用于膜蛋白结晶的微流控技术的研究进展.     

The ensemble performance index: an improved measure for assessing ensemble pose prediction performance

We present a theoretical study on the performance of ensemble docking methodologies considering multiple protein structures. We perform a theoretical analysis of pose prediction experiments which is completely unbiased, as we make no assumptions about specific scoring functions, search paradigms, protein structures, or ligand data sets. We introduce a novel interpretable measure, the ensemble performance index (EPI), for the assessment of scoring performance in ensemble docking, which will be applied to simulated and real data sets.