Preparation of MEH‐PPV/nanosized titania hybrids via in situ sol–gel reaction of titanium alkoxide: Optical property

Homogenously dispersed organic (MEH‐PPV)/inorganic (nanosized titania) hybrids were successfully synthesized. The method of preparation was based on a simple one‐step in situ sol–gel technique using titanium isopropoxide (TIP) as the precursor. The key benefit of this preparation was that TIP interacted with both 2‐chlorophenol and MEH‐PPV, so that the degree of aggregation and phase separation could be kept to a minimum with a suitable recipe. MEH‐PPV/TIP/H₂O/2‐chlorophenol of various weight ratios were synthesized to examine the morphology as well as optical properties of the MEH‐PPV/TIP(titania) hybrid. The observation of MEH‐PPV gelation and Fourier transform infrared results verified the interaction existing between MEH‐PPV and TIP. SEM photographs showed that TIP(titania) were homogenously dispersed in the MEH‐PPV film if the hybrid solution was clear from the use of a suitable recipe. UV–vis absorption measurements showed that the addition of TIP decreased the conjugation length of MEH‐PPV. A redshift in the photoluminescence (PL) emission was observed in almost all the hybrids in the solution state, because of the aggregation of MEH‐PPV. However, it was found that spinning destroyed the aggregation of MEH‐PPV, resulting in a blueshift in the PL emission of the hybrids. © 2007 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 46: 515–529, 2008     

Benchmarking the thermodynamic analysis of water molecules around a model beta sheet

Water molecules play a vital role in biological and engineered systems by controlling intermolecular interactions in the aqueous phase. Inhomogeneous fluid solvation theory provides a method to quantify solvent thermodynamics from molecular dynamics or Monte Carlo simulations and provides an insight into intermolecular interactions. In this study, simulations of TIP4P‐2005 and TIP5P‐Ewald water molecules around a model beta sheet are used to investigate the orientational correlations and predicted thermodynamic properties of water molecules at a protein surface. This allows the method to be benchmarked and provides information about the effect of a protein on the thermodynamics of nearby water molecules. The results show that the enthalpy converges with relatively little sampling, but the entropy and thus the free energy require considerably more sampling to converge. The two water models yield a very similar pattern of hydration sites, and these hydration sites have very similar thermodynamic properties, despite notable differences in their orientational preferences. The results also predict that a protein surface affects the free energy of water molecules to a distance of approximately 4.0 Å, which is in line with previous work. In addition, all hydration sites have a favorable free energy with respect to bulk water, but only when the water–water entropy term is included. A new technique for calculating this term is presented and its use is expected to be very important in accurately calculating solvent thermodynamics for quantitative application. © 2012 Wiley Periodicals, Inc.     

The role of TEOS‐TIP within a pentablock ionomer: Morphology,physical properties,and ion transport

Inorganic–organic nanocomposites were created using tetraethylorthosilicate (TEOS), titanium isopropoxide (TIP), and poly(t‐butylstyrene‐b‐hydrogenated isoprene‐b‐sulfonated styrene‐b‐hydrogenated isoprene‐b‐t‐butylstyrene) or pentablock copolymer (PBC). A TEOS–TIP–H₂O ternary phase diagram was generated to create homogenous sol solutions with designable condensation reactions that led to controllable materials. An inorganic TEOS–TIP network was synthesized using sol–gel chemistry within the organic PBC domain. All TEOS–TIP–PBC films exhibited higher water sorption than unmodified PBC ionomer that was attributed to a change in morphology. Proton conductivity increased up to 80% due to TEOS–TIP within the nanocomposite film. This can be attributed to ion domain redistribution and partial charge transfer from the titanate's inorganic domains to sulfonate groups that promote acid dissociation. PBC had a microphase‐separated morphology that changed with increasing TIP concentration, which was observed from atomic force microscopy and small‐angle X‐ray scattering results. Finally, thermal gravimetric analysis revealed a decrease in degradation temperature, and dynamic mechanical analysis results demonstrated reduced polymer chain mobility caused by inorganic–organic interactions. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017 , 55, 575–586     

The Application of Fluorine‐Containing Reagents in Structural Proteomics

Structural proteomics refers to large‐scale mapping of protein structures in order to understand the relationship between protein sequence, structure, and function. Chemical labeling, in combination with mass‐spectrometry (MS) analysis, have emerged as powerful tools to enable a broad range of biological applications in structural proteomics. The key to success is a biocompatible reagent that modifies a protein without affecting its high‐order structure. Fluorine, well‐known to exert profound effects on the physical and chemical properties of reagents, should have an impact on structural proteomics. In this Minireview, we describe several fluorine‐containing reagents that can be applied in structural proteomics. We organize their applications around four MS‐based techniques: a) affinity labeling, b) activity‐based protein profiling (ABPP), c) protein footprinting, and d) protein cross‐linking. Our aim is to provide an overview of the research, development, and application of fluorine‐containing reagents in protein structural studies.     

Cluster expansion models for flexible‐backbone protein energetics

Protein structure prediction and design often involve discrete modeling of side‐chain conformations on structural templates. Introducing backbone flexibility into such models has proven important in many different applications. Backbone flexibility improves model accuracy and provides access to larger sequence spaces in computational design, although at a cost in complexity and time. Here, we show that the influence of backbone flexibility on protein conformational energetics can be treated implicitly, at the level of sequence, using the technique of cluster expansion. Cluster expansion provides a way to convert structure‐based energies into functions of sequence alone. It leads to dramatic speed‐ups in energy evaluation and provides a convenient functional form for the analysis and optimization of sequence‐structure relationships. We show that it can be applied effectively to flexible‐backbone structural models using four proteins: α‐helical coiled‐coil dimers and trimers, zinc fingers, and Bcl‐x_L/peptide complexes. For each of these, low errors for the sequence‐based models when compared with structure‐based evaluations show that this new way of treating backbone flexibility has considerable promise, particularly for protein design. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

A Bayesian statistical approach of improving knowledge‐based scoring functions for protein–ligand interactions

Knowledge‐based scoring functions are widely used for assessing putative complexes in protein–ligand and protein–protein docking and for structure prediction. Even with large training sets, knowledge‐based scoring functions face the inevitable problem of sparse data. Here, we have developed a novel approach for handling the sparse data problem that is based on estimating the inaccuracies in knowledge‐based scoring functions. This inaccuracy estimation is used to automatically weight the knowledge‐based scoring function with an alternative, force‐field‐based potential (FFP) that does not rely on training data and can, therefore, provide an improved approximation of the interactions between rare chemical groups. The current version of STScore, a protein–ligand scoring function using our method, achieves a binding mode prediction success rate of 91% on the set of 100 complexes by Wang et al., and a binding affinity correlation of 0.514 with the experimentally determined affinities in PDBbind. The method presented here may be used with other FFPs and other knowledge‐based scoring functions and can also be applied to protein–protein docking and protein structure prediction. © 2014 Wiley Periodicals, Inc.     

A Versatile Method to Prepare Protein Nanoclusters for Drug Delivery

Nanocarriers based on natural biomaterials such as peptides and proteins have shown great advantages in the field of nanomedicine. However, the complicated preparation process and possible denaturation of proteins may limit their further applications. Herein, a novel method is developed to prepare protein nanocluster drug delivery system based on the self‐aggregated property of proteins under the isoelectric point condition. The crosslinked protein nanoclusters, prepared by adding modified natural crosslinking agent polysaccharide, exhibit excellent stability and autofluorescent property in physiological conditions. Hemoglobin, a model protein, is chosen for preparation of drug‐loaded nanoclusters. The as‐prepared nanoclusters demonstrate a pH‐responsive drug release behavior and can successfully deliver drugs into cancer cells. Moreover, this approach can be extended to various proteins, exemplifying the universal applicability of our new preparation method for protein‐based nanoparticles.     

Fast and accurate grid representations for atom‐based docking with partner flexibility

Macromolecular docking methods can broadly be divided into geometric and atom‐based methods. Geometric methods use fast algorithms that operate on simplified, grid‐like molecular representations, while atom‐based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid‐based and atom‐based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom‐based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid‐based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse‐grained forcefield, the average speed improvement was >100x. Grid‐based representations may allow atom‐based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc.     

Identifying and reducing error in cluster‐expansion approximations of protein energies

Protein design involves searching a vast space for sequences that are compatible with a defined structure. This can pose significant computational challenges. Cluster expansion is a technique that can accelerate the evaluation of protein energies by generating a simple functional relationship between sequence and energy. The method consists of several steps. First, for a given protein structure, a training set of sequences with known energies is generated. Next, this training set is used to expand energy as a function of clusters consisting of single residues, residue pairs, and higher order terms, if required. The accuracy of the sequence‐based expansion is monitored and improved using cross‐validation testing and iterative inclusion of additional clusters. As a trade‐off for evaluation speed, the cluster‐expansion approximation causes prediction errors, which can be reduced by including more training sequences, including higher order terms in the expansion, and/or reducing the sequence space described by thecluster expansion. This article analyzes the sources of error and introduces a method whereby accuracy can be improved by judiciously reducing the described sequence space. The method is applied to describe the sequence–stability relationship for several protein structures: coiled‐coil dimers and trimers, a PDZ domain, and T4 lysozyme as examples with computationally derived energies, and SH3 domains in amphiphysin‐1 and endophilin‐1 as examples where the expanded pseudo‐energies are obtained from experiments. Our open‐source software package Cluster Expansion Version 1.0 allows users to expand their own energy function of interest and thereby apply cluster expansion to custom problems in protein design. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Whey protein: A functional and promising material for drug delivery systems recent developments and future prospects

Natural polymers have been extensively utilized in the past decades due to their outstanding features. Among these natural excipients, protein‐based polymers have superb features owing to their high drug binding capacity and biodegradability. Whey protein is a versatile protein‐based vehicle for drug delivery systems. It has been shown to be nontoxic, biocompatible, and biodegradable. Therefore, it has been considered as an ideal biomaterial for the design of advanced drug delivery systems. Protein‐based cargo acts as synthetic polymers counterpart for innovative delivery systems. The current review is mainly focused on application of whey proteins as an emerging carrier in drug delivery systems, achieved during the past.     

A Synthetic Adenylation‐Domain‐Based tRNA‐Aminoacylation Catalyst

The incorporation of non‐proteinogenic amino acids represents a major challenge for the creation of functionalized proteins. The ribosomal pathway is limited to the 20–22 proteinogenic amino acids while nonribosomal peptide synthetases (NRPSs) are able to select from hundreds of different monomers. Introduced herein is a fusion‐protein‐based design for synthetic tRNA‐aminoacylation catalysts based on combining NRPS adenylation domains and a small eukaryotic tRNA‐binding domain (Arc1p‐C). Using rational design, guided by structural insights and molecular modeling, the adenylation domain PheA was fused with Arc1p‐C using flexible linkers and achieved tRNA‐aminoacylation with both proteinogenic and non‐proteinogenic amino acids. The resulting aminoacyl‐tRNAs were functionally validated and the catalysts showed broad substrate specificity towards the acceptor tRNA. Our strategy shows how functional tRNA‐aminoacylation catalysts can be created for bridging the ribosomal and nonribosomal worlds. This opens up new avenues for the aminoacylation of tRNAs with functional non‐proteinogenic amino acids.     

Assessment of biomolecular force fields for molecular dynamics simulations in a protein crystal

Different biomolecular force fields (OPLS‐AA, AMBER03, and GROMOS96) in conjunction with SPC, SPC/E and TIP3P water models are assessed for molecular dynamics simulations in a tetragonal lysozyme crystal. The root mean square deviations for the C_a atoms of lysozymes are about 0.1 to 0.2 nm from OPLS‐AA and AMBER03, smaller than 0.4 nm from GROMOS96. All force fields exhibit similar pattern in B‐factors, whereas OPLS‐AA and AMBER03 accurately reproduce experimental measurements. Despite slight variations, the primary secondary structures are well conserved using different force fields. Water diffusion in the crystal is approximately ten‐fold slower than in bulk phase. The directional and average water diffusivities from OPLS‐AA and AMBER03 along with SPC/E model match fairly well with experimental data. Compared to GROMOS96, OPLS‐AA and AMBER03 predict larger hydrophilic solvent‐accessible surface area of lysozyme, more hydrogen bonds between lysozyme and water, and higher percentage of water in hydration shell. SPC, SPC/E and TIP3P water models have similar performance in most energetic and structural properties, but SPC/E outperforms in water diffusion. While all force fields overestimate the mobility and electrical conductivity of NaCl, a combination of OPLS‐AA for lysozyme and the Kirkwood‐Buff model for ions is superior to others. As attributed to the steric restraints and surface interactions, the mobility and conductivity in the crystal are reduced by one to two orders of magnitude from aqueous solution. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

“Stainomics”: Identification of mitotracker labeled proteins in mammalian cells

Organelle‐specific cell‐permeable fluorescent dyes are invaluable tools in cell biology as they reveal intracellular dynamics in living cells. Mitrotracker is a family of dyes that strongly label the mitochondrion, a key organelle associated with many crucial cellular functions. Despite the popularity of these dyes, little is known about the molecular mechanism behind their staining specificity. Here, we aimed to identify the protein targets of one member of this dye family, mitotracker red (MTR), by 2DE and MS. MTR bound to cellular proteins covalently, and its fluorescence persisted even after cell lysis, protein solubilization, denaturation, and electrophoresis. This enabled us to display MTR‐labeled proteins by 2DE. The MTR‐specific fluorescent signals on the gel revealed the spots that contained MTR‐conjugated proteins. These spots were analyzed by MS, resulting into the identification of ten proteins. We discovered that one major target is the mitochondrial protein HSP60 and that MTR staining could induce production of HSP60, predisposing cells to heat shock‐like responses. The identification of the molecular targets of biological dyes, or “stainomics,” can help correlate their intracellular staining properties with biochemical affinities. We believe this approach can be applied to a wide range of fluorescent probes.     

Covalent Protein Labeling by Enzymatic Phosphocholination

We present a new protein labeling method based on the covalent enzymatic phosphocholination of a specific octapeptide amino acid sequence in intact proteins. The bacterial enzyme AnkX from Legionella pneumophila has been established to transfer functional phosphocholine moieties from synthetically produced CDP‐choline derivatives to N‐termini, C‐termini, and internal loop regions in proteins of interest. Furthermore, the covalent modification can be hydrolytically removed by the action of the Legionella enzyme Lem3. Only a short peptide sequence (eight amino acids) is required for efficient protein labeling and a small linker group (PEG‐phosphocholine) is introduced to attach the conjugated cargo.     

Cross‐Linking/Mass Spectrometry for Studying Protein Structures and Protein–Protein Interactions: Where Are We Now and Where Should We Go from Here?

Structural mass spectrometry (MS) is gaining increasing importance for deriving valuable three‐dimensional structural information on proteins and protein complexes, and it complements existing techniques, such as NMR spectroscopy and X‐ray crystallography. Structural MS unites different MS‐based techniques, such as hydrogen/deuterium exchange, native MS, ion‐mobility MS, protein footprinting, and chemical cross‐linking/MS, and it allows fundamental questions in structural biology to be addressed. In this Minireview, I will focus on the cross‐linking/MS strategy. This method not only delivers tertiary structural information on proteins, but is also increasingly being used to decipher protein interaction networks, both in vitro and in vivo. Cross‐linking/MS is currently one of the most promising MS‐based approaches to derive structural information on very large and transient protein assemblies and intrinsically disordered proteins.     

Incorporating support vector machine for identifying protein tyrosine sulfation sites

Tyrosine sulfation is a post‐translational modification of many secreted and membrane‐bound proteins. It governs protein‐protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty‐two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five‐fold cross‐validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in five‐fold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

Module Assembly for Designing Multivalent Mid‐Sized Inhibitors of Protein‐Protein Interactions

Developing clinically relevant synthetic agents that are capable of disrupting protein‐protein interactions (PPIs) is now a major goal of scientific research. In an effort to explore new methodologies that are applicable to the design of synthetic PPI inhibitors, we examined a strategy based on the assembly of small module compounds to create multivalent mid‐sized agents. This personal account describes three particular approaches based on module assembly: metal‐chelating‐based ligand assembly, covalent chemical ligation templated by a targeted protein, and bivalent inhibitor design for simultaneous targeting of the active pocket and protein surface. These strategies were shown to be useful for synthesizing minimally sized synthetic agents for targeting PPIs and may enable development of agents that are applicable to inhibition of intracellular PPIs.     

Solution‐blown nylon 6–chitosan core–shell nanofiber for highly efficient affinity adsorption

A facile spinning‐based strategy was developed to fabricate chitosan (CS) surface nanofiber‐based affinity membranes for protein adsorption. The core–shell nanofiber mat of nylon 6–CS was prepared via coaxial solution blowing process. The nanofibers have a diameter range of 60–300 nm. The core–shell structure was confirmed by transmission electron microscopy, and CS was observed as a thin layer that uniformly adhered to the core. The dye ligand of cibacron blue F3GA (CB F3GA) was further covalently immobilized on the nanofibers with a content of 425 µmol/g. The pristine and CB F3GA‐attached mats were studied in protein adsorption. High bovine serum albumin adsorption capacities of 91.9 and 219.6 mg/g were obtained for pristine and CB F3GA‐attached mats, respectively. Given its properties of high flux rate and low pressure drop, CB F3GA‐attached nylon 6–CS nanofiber mat meets the requirements of highly effective affinity membrane chromatography. Copyright © 2016 John Wiley & Sons, Ltd.     

Decoding the components of dynamics in three‐domain proteins

In this study, we examine the feasibility and limitations of describing the motional behavior of three‐domain proteins in which the domains are linearly connected. In addition to attempting the determination of the internal and overall reorientational correlation times, we investigate the existence of correlations in the motions between the three domains. Since in linearly arranged three‐domain proteins, there are typically no experimental data that can directly report on motional correlation between the first and the third domain, we address this question by dynamics simulations. Two limiting cases occur: (1) for weak repulsive potentials and (2) when strong repulsive potentials are applied between sequential domains. The motions of the terminal domains become correlated in the case of strong interdomain repulsive potentials when these potentials do not allow the angle between the sequential domains to be smaller than about 60°. Using the model‐free (MF) and extended MF formalisms of Lipari and Szabo, we find that the motional behavior can be separated into two components; the first component represents the concerted overall motion of the three domains, and the second describes the independent component of the motion of each individual domain. We find that this division of the motional behavior of the protein is maintained only when their timescales are distinct and can be made when the angles between sequential domains remain between 60° and 160°. In this work, we identify and quantify interdomain motional correlations. © 2013 Wiley Periodicals, Inc.