Quantitative liquid chromatography tandem mass spectrometry analysis of macromolecules using signature peptides in biological fluids

Targeted protein quantification using peptide surrogates has increasingly become important to the validation of biomarker candidates and development of protein therapeutics. These approaches have been proposed and employed as alternatives to immunoassays in biological fluids. Technological advances over the last 20 years in biochemistry and mass spectrometry have prompted the use of peptides as surrogates to quantify enzyme digested proteins using triple quadrupole mass spectrometers. Multiple sample preparation processes are often incorporated to achieve quantification of target proteins using these signature peptides. This review article focuses on these processes or hyphenated techniques for quantification of proteins with peptide surrogates. The most recent advances and strategies involved with hyphenated techniques are discussed.     

Molecular Dynamics Simulation of Peptide Folding

The simulation of peptide folding with atomic resolution has evolved remarkably during the last 7 years, i.e., from absolute skepticism on the capability of classical molecular dynamics (MD) methodology to reproduce complex biological phenomena such as the folding of even simple oligopeptides (6–15 residues) to the seemingly realistic representation of the thermodynamics and kinetics of folding of a rapidly increasing number of polypeptides (over 20 residues). Four factors permitted this rapid progress: the breakthrough of a second generation of force fields, a rapid and steady increase of (commodity) computer performance, a move from local computational resources to large distributed clusters and, last but not less important, a decision of particular groups to spend a large computational effort on projects that most other groups trusted unrealizable at the time. The present account goes over some aspects of peptide folding and its simulation with MD techniques while sweeping through the simulation landmarks of the last 7 years and conjecturing on the future.     

Molecular views and measurements of hemostatic processes using atomic force microscopy

Hemostasis and thrombosis are highly complex and coordinated interfacial responses to vascular injury. In recent years, atomic force microscopy (AFM) has proven to be a very useful approach for studying hemostatic processes under near physiologic conditions. In this report, we review recent progress in the use of AFM for studying hemostatic processes, including molecular level visualization of plasma proteins, protein aggregation and multimer assembly, and structural and morphological details of vascular cells under aqueous conditions. AFM offers opportunities for visualizing surface-dependent molecular and cellular interactions in three dimensions on a nanoscale and for sensitive, picoNewton level, measurements of intermolecular forces. AFM has been used to obtain molecular and sub-molecular, resolution of many biological molecules and assemblies, including coagulation proteins and cell surfaces. Surface-dependent molecular processes including protein adsorption, conformational changes, and subsequent interactions with cellular components have been described. This review outlines the basic principles and utility of AFM for imaging and force measurements, and offers objective perspectives on both the advantages and disadvantages. We focus primarily on molecular level events related to hemostasis and thrombosis, particularly coagulation proteins, and blood platelets, but also explore the use of AFM in force measurements and surface property mapping.     

Stochastic dynamic simulation of a protein

The internal motions of a small protein, the bovine pancreatic trypsin inhibitor (BPTI) in solution, are investigated in the framework of the Langevin equation. In this approach, the effects of the solvent molecules are incorporated by suitably defining the friction and random forces. The friction coefficients are determined from a molecular dynamics simulation. The details of the rapid fluctuations of protein atoms obtained by stochastic and molecular dynamics simulation techniques are compared by calculating the generalized density of states obtained via an incoherent neutron scattering. Presently, our stochastic dynamics simulation is one order of magnitude faster than the molecular dynamics simulation with the explicit inclusion of the water molecules. Generalizations of the present stochastic dynamics approach for studying the large-scale motion in proteins are briefly outlined and the probability of a further speedup by an additional order of magnitude is discussed.     

Membrane localization and flexibility of a lipidated ras peptide studied by molecular dynamics simulations

Lipid-modified membrane-binding proteins are essential in signal transduction events of the cell, a typical example being the GTPase ras. Recently, membrane binding of a doubly lipid-modified heptapeptide from the C-terminus of the human N-ras protein was studied by spectroscopic techniques. It was found that membrane binding is mainly due to lipid chain insertion, but it is also favored by interactions between apolar side chains and the hydrophobic region of the membrane. Here, 10 explicit solvent molecular dynamics simulations for a total time of about 150 ns are used to investigate the atomic details of the peptide-membrane association. The 16:0 peptide lipid chains are more mobile than the 14:0 phospholipid chains, which is in agreement with (2)H NMR experiments. Peptide-lipid and peptide-solvent interactions, backbone and side-chain distributions, as well as the effects of lipidated peptide insertion onto the structure, and dynamics of a 1,2-dimyristoylglycero-3-phosphocholine bilayer are described. The simulation results validate the structural model proposed by the analysis of spectroscopic data and highlight the main aspects of the insertion mechanism. The peptide in the membrane is rather rigid over the simulation time scale of about 10 ns, but different partially extended conformations devoid of backbone hydrogen bonds are observed in different trajectories.     

Computational Characterization of Nanosystems

Nanosystems play an important role in many applications. Due to their complexity, it is challenging to accurately characterize their structure and properties. An important means to reach such a goal is computational simulation, which is grounded on ab initio electronic structure calculations. Low scaling and accurate electronic-structure algorithms have been developed in recent years. Especially, the efficiency of hybrid density functional calculations for periodic systems has been significantly improved. With electronic structure information, simulation methods can be developed to directly obtain experimentally comparable data. For example, scanning tunneling microscopy images can be effectively simulated with advanced algorithms. When the system we are interested in is strongly coupled to environment, such as the Kondo effect, solving the hierarchical equations of motion turns out to be an effective way of computational characterization. Furthermore, the first principles simulation on the excited state dynamics rapidly emerges in recent years, and nonadiabatic molecular dynamics method plays an important role. For nanosystem involved chemical processes, such as graphene growth, multiscale simulation methods should be developed to characterize their atomic details. In this review, we review some recent progresses in methodology development for computational characterization of nanosystems. Advanced algorithms and software are essential for us to better understand of the nanoworld.     

Recent advances in the chemical synthesis and semi-synthesis of poly-ubiquitin-based proteins and probes

Ubiquitination, a key and extensive posttranslational modification of proteins, has profound effects on a variety of physiological and pathological processes. The inherent complexity of ubiquitin conjugates makes it highly challenging to study the functional and structural mechanisms of ubiquitination. To address these challenges, accesses to sufficient poly-ubiquitin chains or ubiquitinated proteins are urgently needed. Over the last decade, synthetic protein chemists have developed several novel peptide ligation methods for the preparation of ubiquitin conjugates with precise control over the atomic structure. In this review, we summarize the recent breakthroughs and potential challenges in the chemical synthesis and semi-synthesis of ubiquitin conjugates with respect to the preparation of poly-ubiquitin-based proteins and ubiquitin-based probes.     

Ligand Rearrangements at Fe/S Cofactors: Slow Isomerization of a Biomimetic [2Fe‐2S] Cluster

Ligand exchange plays an important role in the biogenesis of Fe/S clusters, most prominently during cluster transfer from a scaffold protein to its target protein. Although in vivo and in vitro studies have provided some insight into this process, the microscopic details of the ligand exchange steps are mostly unknown. In this work, the kinetics of the ligand rearrangement in a biomimetic [2Fe‐2S] cluster with mixed S/N capping ligands have been studied. Two geometrical isomers of the cluster are present in solution, and mechanistic insight into the isomerization process was obtained by variable‐temperature ¹H NMR spectroscopy. Combined experimental and computational results reveal that this is an associative process that involves the coordination of a solvent molecule to one of the ferric ions. The cluster isomerizes at least two orders of magnitude faster in its protonated and mixed‐valent states. These findings may contribute to a deeper understanding of cluster transfer and sensing processes occurring in Fe/S cluster biogenesis.     

Uncovering molecular processes in crystal nucleation and growth by using molecular simulation

Exploring nucleation processes by molecular simulation provides a mechanistic understanding at the atomic level and also enables kinetic and thermodynamic quantities to be estimated. However, whilst the potential for modeling crystal nucleation and growth processes is immense, there are specific technical challenges to modeling. In general, rare events, such as nucleation cannot be simulated using a direct "brute force" molecular dynamics approach. The limited time and length scales that are accessible by conventional molecular dynamics simulations have inspired a number of advances to tackle problems that were considered outside the scope of molecular simulation. While general insights and features could be explored from efficient generic models, new methods paved the way to realistic crystal nucleation scenarios. The association of single ions in solvent environments, the mechanisms of motif formation, ripening reactions, and the self-organization of nanocrystals can now be investigated at the molecular level. The analysis of interactions with growth-controlling additives gives a new understanding of functionalized nanocrystals and the precipitation of composite materials.     

Impact of atomic force microscopy on interface and colloid science

Since its invention twenty years ago the atomic force microscope (AFM) has become one of the most important tools in colloid and interface science. The reason for this impact is that the AFM allows doing experiments on length, time, force, and energy scales, which are not accessible by any other technique. These experiments can be carried out under natural conditions, for example in liquid environments. In this paper we specify the length and time scales involved, give examples where by using the AFM relevant questions in colloid and interface science have been solved, and we discuss future perspectives.     

Elucidating Peptide and Protein Structure and Dynamics: UV Resonance Raman Spectroscopy

UV resonance Raman spectroscopy (UVRR) is a powerful method that has the requisite selectivity and sensitivity to incisively monitor biomolecular structure and dynamics in solution. In this perspective, we highlight applications of UVRR for studying peptide and protein structure and the dynamics of protein and peptide folding. UVRR spectral monitors of protein secondary structure, such as the Amide III(3) band and the C(α)-H band frequencies and intensities can be used to determine Ramachandran Ψ angle distributions for peptide bonds. These incisive, quantitative glimpses into conformation can be combined with kinetic T-jump methodologies to monitor the dynamics of biomolecular conformational transitions. The resulting UVRR structural insight is impressive in that it allows differentiation of, for example, different α-helix-like states that enable differentiating π- and 3(10)- states from pure α-helices. These approaches can be used to determine the Gibbs free energy landscape of individual peptide bonds along the most important protein (un)folding coordinate. Future work will find spectral monitors that probe peptide bond activation barriers that control protein (un)folding mechanisms. In addition, UVRR studies of sidechain vibrations will probe the role of side chains in determining protein secondary, tertiary and quaternary structures.     

Charge distribution and hydrogen bonding of a collagen α2‐chain in vacuum,hydrated, neutral,and charged structural models

A challenging task in computational biophysics is to ascertain the solvent effect on the electronic structure and interatomic bonding at the atomistic level. Simulations must be carried out on reasonably large biomolecules for accurate calculations to yield valid results. We report the results of a calculation on collagen model in the form of a peptide under three different environments: vacuum, solvated and with neutral and charged sites. Quantitative results and analysis of the partial charge (PC) distribution on each amino acid are discussed. A significant charge transfer of more than 1 electron from protein to water molecules is found with similar results when the model contains charged sites. The main contributions to the interatomic bonding are from hydrogen bonds (HBs) between water‐water and water‐protein pairs. A connection between PC and HBs can be established since the nonpolar amino acids form no HBs and have the smallest PC and vice versa. The ab initio PC obtained are used in the NAMD simulation showing significant improvement over the default values as reflected in the root mean square deviation of atomic positions in the MD steps and the total free energy in energy minimization. These results could facilitate the interpretation of data on interaction of various ligands in charged proteins in relation to isoelectric points. © 2016 Wiley Periodicals, Inc.     

Mass Spectrometric Characterization of Protein Structure Details Refines the Proteome Signature for Invasive Ductal Breast Carcinoma

Early diagnosis as well as individualized therapies are necessary to reduce the mortality of breast cancer, and personalized patient care strategies rely on novel prognostic or predictive factors. In this study, with six breast cancer patients, 2D gel analysis was applied for studying protein expression differences in order to distinguish invasive ductal breast carcinoma, the most frequent breast tumor subtype, from control samples. In total, 1203 protein spots were assembled in a 2D reference gel. Differentially abundant spots were subjected to peptide mass fingerprinting for protein identification. Twenty proteins with their corresponding 38 differentially expressed 2D gel spots were contained in our previously reported proteome signature, suggesting that distinct protein forms were contributing. In-depth MS/MS measurements enabled analyses of protein structure details of selected proteins. In protein spots that significantly contributed to our signature, we found that glyceraldehyde-3-phosphate dehydrogenase was N-terminally truncated, pyruvate kinase M2 and nucleoside diphosphate kinase A but not other isoforms of these proteins were of importance, and nucleophosmin phosphorylation at serine residues 106 and 125 were clearly identified. Principle component analysis and hierarchical clustering with normalized quantitative data from the 38 spots resulted in accurate separation of tumor from control samples. Thus, separation of tissue samples as in our initial proteome signature could be confirmed even with a different proteome analysis platform. In addition, detailed protein structure investigations enabled refining our proteome signature for invasive ductal breast carcinoma, opening the way to structure-/function studies with respect to disease processes and/or therapeutic intervention.     

Fluorescent protein barrel fluctuations and oxygen diffusion pathways in mCherry

Fluorescent proteins (FPs) are valuable tools as biochemical markers for studying cellular processes. Red fluorescent proteins (RFPs) are highly desirable for in vivo applications because they absorb and emit light in the red region of the spectrum where cellular autofluorescence is low. The naturally occurring fluorescent proteins with emission peaks in this region of the spectrum occur in dimeric or tetrameric forms. The development of mutant monomeric variants of RFPs has resulted in several novel FPs known as mFruits. Though oxygen is required for maturation of the chromophore, it is known that photobleaching of FPs is oxygen sensitive, and oxygen-free conditions result in improved photostabilities. Therefore, understanding oxygen diffusion pathways in FPs is important for both photostabilites and maturation of the chromophores. In this paper, we use molecular dynamics calculations to investigate the protein barrel fluctuations in mCherry, which is one of the most useful monomeric mFruit variant. We employ implicit ligand sampling to determine oxygen pathways from the bulk solvent into the mCherry chromophore in the interior of the protein. We also show that these pathways can be blocked or altered and barrel fluctuations can be reduced by strategic amino acid substitutions.     

Preferential solvation dynamics in liquids: how geodesic pathways through the potential energy landscape reveal mechanistic details about solute relaxation in liquids

It is not obvious that many-body phenomena as collective as solute energy relaxation in liquid solution should ever have identifiable molecular mechanisms, at least not in the sense of the well-defined sequence of molecular events one often attributes to chemical reactions. What can define such mechanisms, though, are the most efficient relaxation paths that solutions take through their potential energy landscapes. When liquid dynamics is dominated by slow diffusive processes, there are mathematically precise and computationally accessible routes to searching for such paths. We apply this observation to the dynamics of preferential solvation, the relaxation around a newly excited solute by a solvent composed of different components with different solvating abilities. The slow solvation seen experimentally in these mixtures stems from the dual needs to compress the solvent and to do solvent-solvent exchanges near the solute. By studying the geodesic (most efficient) paths for this combined process in a simple atomic liquid mixture, we show that the mechanism for preferential solvation features a reasonably sharp onset for slow diffusion, and that this diffusion involves a sequential, rather than concerted, series of solvent exchanges.     

Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues

Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C^α and C^β atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of ‘hard’ degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.     

Electrochemical Technologies to Decrease the Chemical Risk of Hospital Wastewater and Urine

The inefficiency of conventional biological processes to remove pharmaceutical compounds (PhCs) in wastewater is leading to their accumulation in aquatic environments. These compounds are characterized by high toxicity, high antibiotic activity and low biodegradability, and their presence is causing serious environmental risks. Because much of the PhCs consumed by humans are excreted in the urine, hospital effluents have been considered one of the main routes of entry of PhCs into the environment. In this work, a critical review of the technologies employed for the removal of PhCs in hospital wastewater was carried out. This review provides an overview of the current state of the developed technologies for decreasing the chemical risks associated with the presence of PhCs in hospital wastewater or urine in the last years, including conventional treatments (filtration, adsorption, or biological processes), advanced oxidation processes (AOPs) and electrochemical advanced oxidation processes (EAOPs).     

Geometric algorithms for the conformational analysis of long protein loops

The efficient filtering of unfeasible conformations would considerably benefit the exploration of the conformational space when searching for minimum energy structures or during molecular simulation. The most important conditions for filtering are the maintenance of molecular chain integrity and the avoidance of steric clashes. These conditions can be seen as geometric constraints on a molecular model. In this article, we discuss how techniques issued from recent research in robotics can be applied to this filtering. Two complementary techniques are presented: one for conformational sampling and another for computing conformational changes satisfying such geometric constraints. The main interest of the proposed techniques is their application to the structural analysis of long protein loops. First experimental results demonstrate the efficacy of the approach for studying the mobility of loop 7 in amylosucrase from Neisseria polysaccharea. The supposed motions of this 17-residue loop would play an important role in the activity of this enzyme.     

准确快速计算含多肽酰胺和核酸碱基的氢键复合物的氢键强度和氢键作用势能曲线

N-H···O=C、C-H···O=C、N-H···N和C-H···N等氢键作用是蛋白质a-螺旋结构、b-折叠结构和DNA双螺旋结构形成的主要因素,在生物分子识别、蛋白质复制以及遗传信息传递等过程中起重要作用。准确快速计算生物体系中存在的N-H···O=C、C-H···O=C、N-H···N和C-H···N等氢键作用强度以及氢键强度随分子几何结构(距离和角度)变化的势能曲线对正确模拟(从而正确认识和理解)蛋白质折叠机制和DNA双螺旋结构形成机制等生物过程意义重大,对设计合成具有特殊功能的生物分子材料有重要指导价值。本文主要介绍了近年来建立的偶极-偶极氢键作用模型及其在快速预测多肽-多肽分子间和核酸碱基-多肽分子间氢键作用强度和氢键作用势能曲线方面的应用。