Recent developments in structural proteomics for protein structure determination

Multi-Omics Approaches Against Abiotic and Biotic Stress-A Review

Plants face an array of environmental stresses, including both abiotic and biotic stresses. These stresses significantly impact plant lifespan and reduce agricultural crop productivity. Abiotic stresses, such as ultraviolet (UV) radiation, high and low temperatures, salinity, drought, floods, heavy metal toxicity, etc., contribute to widespread crop losses globally. On the other hand, biotic stresses, such as those caused by insects, fungi, and weeds, further exacerbate these challenges. These stressors can hinder plant systems at various levels, including molecular, cellular, and development processes. To overcome these challenges, multi-omics computational approaches offer a significant tool for characterizing the plant's biomolecular pool, which is crucial for maintaining homeostasis and signaling response to environmental changes. Integrating multiple layers of omics data, such as proteomics, metabolomics, ionomics, interactomics, and phenomics, simplifies the study of plant resistance mechanisms. This comprehensive approach enables the development of regulatory networks and pathway maps, identifying potential targets for improving resistance through genetic engineering or breeding strategies. This review highlights the valuable insights from integrating multi-omics approaches to unravel plant stress responses to both biotic and abiotic factors. By decoding gene regulation and transcriptional networks, these techniques reveal critical mechanisms underlying stress tolerance. Furthermore, the role of secondary metabolites in bio-based products in enhancing plant stress mitigation is discussed. Genome editing tools offer promising strategies for improving plant resilience, as evidenced by successful case studies combating various stressors. On the whole, this review extensively discusses an advanced multi-omics approach that aids in understanding the molecular basis of resistance and developing novel strategies to improve crops' or organisms' resilience to abiotic and biotic stresses.

Molecular and structure-based drug design: From theory to practice

Structure-based drug design (SBDD) and molecular docking have revolutionized drug discovery by providing effective strategies for identifying and optimizing therapeutic agents. This review highlights the principles and methodologies of SBDD, which uses high-resolution structural data of biological targets to design drugs with enhanced selectivity and efficacy. Techniques like nuclear magnetic resonance (NMR) spectroscopy, cryo-electron microscopy (cryo-EM), and X-ray crystallography are key in providing the structural information necessary for SBDD. Molecular docking, a crucial component of modern drug discovery, simulates interactions between drug candidates and biological targets. By predicting how a ligand fits into a receptor's binding site, researchers can assess the strength and nature of these interactions, guiding compound selection. Advances in molecular docking have incorporated machine learning to improve scoring functions and prediction accuracy. Docking studies include search algorithms, scoring functions, and binding site identification to predict the optimal orientation of a ligand when bound to a protein. Despite its widespread use, molecular docking has limitations, such as challenges in achieving high prediction accuracy, modeling protein flexibility, and accounting for solvation effects. Improvements in computational power and the integration of machine learning techniques are addressing these issues. This review emphasizes the importance of ongoing innovation and interdisciplinary collaboration in enhancing molecular docking and its role in discovering novel therapies.

Observation of Protein Unfolding during pH Ramp Evoked by Lipase-Catalyzed Ester Hydrolysis

Studies of protein folding often involve offline experimental methods such as titrating protein samples with denaturants or equilibrating them in the presence of denaturants. Here, we demonstrate an online analytical approach in which the protein structure is perturbed by a pH ramp evoked by immobilized lipase-catalyzed ester hydrolysis. Changes in the tertiary structure of the protein in response to a pH ramp (from approximately 6.3 to 2.8) are monitored using electrospray ionization mass spectrometry and spectrofluorometry. Interestingly, we discovered a side reaction of ammonium and formate leading to the production of cyanide that occurred during the ionization process. We also found that only certain protein analytes were bound to the formed cyanide species. Nevertheless, this problem was readily overcome by carefully selecting a specific ester substrate. Overall, the alterations in the charge-state distribution and fluorescence intensity─caused by the lipase-induced pH ramp─reveal conformational transitions in different proteins. In line with previous reports, the acid-induced denaturation of holo-myoglobin occurs through a two-step mechanism, which is supported by identification of protein-unfolding intermediates and the loss of noncovalent protein ligand (heme). The results─obtained using the developed catalytic method─are also consistent with the results of equilibrium-based experiments, while sample preparation steps are substantially reduced. The proposed approach simplifies the identification of the pH range that has the greatest impact on the protein structure. Thus, it has the potential to be a useful tool for studying protein conformational transitions in the course of pH changes.

Monoclonal Antibodies as Probes to Study Ligand-Induced Conformations of Troponin Subunits

Striated muscle contraction and relaxation is regulated by Ca2+ at the myofilament level via conformational modulations of the troponin complex. To understand the structure-function relationship of troponin in normal muscle and in myopathies, it is necessary to study the functional effects of troponin isoforms and mutations at the level of allosteric conformations of troponin subunits. Traditional methodologies assessing such conformational studies are laborious and require significant amounts of purified protein, while many current methodologies require non-physiological conditions or labeling of the protein, which may affect their physiological conformation and function. To address these issues, we developed a novel approach using site-specific monoclonal antibodies (mAb) as molecular probes to detect and monitor conformational changes of proteins. Here, we present examples for its application in studies of two subunits of troponin: the Ca2+-binding subunit, TnC, and the tropomyosin-binding/thin filament-anchoring subunit, TnT. Studies using a high-throughput microplate assay are compared with that using localized surface plasmon resonance (LSPR) to demonstrate the effectiveness of using mAb probes to assess ligand-induced conformations of troponin subunits in physiological conditions. The assays utilize relatively small amounts of protein and are free of protein modification, which may bias results. Detailed methodologies using various monoclonal antibodies (mAbs) are discussed with considerations for the optimization of assay conditions and the broader application in studies of other proteins as well as in screening of therapeutic reagents that bind a specific target site with conformational and functional effects.

Liquid chromatography mass spectrometry based characterization of epitope configurations

Here we evaluate a quick and easy tool for determination of epitope configuration using immunocapture and liquid chromatography mass spectrometry (LC-MS) subsequent to pre-treatment of the target protein to disrupt its three-dimensional structure. The approach can be a valuable screening tool to identify antibodies that can be used in peptide capture by anti-protein antibodies. The experimental set-up was established using seven monoclonal antibodies (mAbs) with known linear or conformational epitope recognition. The mAbs were developed to target either of the two biomarkers, progastrin releasing peptide (ProGRP) or human chorionic gonadotropin (hCG). Best coherence with established epitope configuration was seen when using both denaturation, reduction and alkylation as pre-treatment method of the proteins (≥70% reduction in MS signal intensity compared to control) prior to immunocapture and LC-MS determination. The final method was used to determine the epitope configuration of four anti-thyroglobulin mAbs with unknown epitope configuration; all four mAbs showed configurational epitope recognition. These results were also supported by western blots of native, and reduced and alkylated protein using three of the evaluated mAbs, and by analysis native, and reduced and alkylated protein in a routine immunofluorometric assay employing the four evaluated antibodies.

Maximizing binary interactome mapping with a minimal number of assays

Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose a framework for binary protein-protein interaction (PPI) mapping based on optimally combining assays and/or assay versions to maximize detection of true positive interactions, while avoiding detection of random protein pairs. We have engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions, differing by protein expression systems and tagging configurations. The resulting union of N2H versions recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our findings should be applicable to systematic mapping of other biological landscapes.

Mass Spectrometry- and Computational Structural Biology-Based Investigation of Proteins and Peptides

Recent developments of mass spectrometry (MS) allow us to identify, estimate, and characterize proteins and protein complexes. At the same time, structural biology helps to determine the protein structure and its structure-function relationship. Together, they aid to understand the protein structure, property, function, protein-complex assembly, protein-protein interaction, and dynamics. The present chapter is organized with illustrative results to demonstrate how experimental mass spectrometry can be combined with computational structural biology for detailed studies of protein's structures. We have used tumor differentiation factor protein/peptide as ligand and Hsp70/Hsp90 as receptor protein as examples to study ligand-protein interaction. To investigate possible protein conformation, we will describe two proteins-lysozyme and myoglobin. As an application of MS-based assignment of disulfide bridges, the case of the spider venom polypeptide Phα1β will also be discussed.

An improved protein structure evaluation using a semi-empirically derived structure property

BACKGROUND

In the backdrop of challenge to obtain a protein structure under the known limitations of both experimental and theoretical techniques, the need of a fast as well as accurate protein structure evaluation method still exists to substantially reduce a huge gap between number of known sequences and structures. Among currently practiced theoretical techniques, homology modelling backed by molecular dynamics based optimization appears to be the most popular one. However it suffers from contradictory indications of different validation parameters generated from a set of protein models which are predicted against a particular target protein. For example, in one model Ramachandran Score may be quite high making it acceptable, whereas, its potential energy may not be very low making it unacceptable and vice versa. Towards resolving this problem, the main objective of this study was fixed as to utilize a simple experimentally derived output, Surface Roughness Index of concerned protein of unknown structure as an intervening agent that could be obtained using ordinary microscopic images of heat denatured aggregates of the same protein.

RESULT

It was intriguing to observe that direct experimental knowledge of the concerned protein, however simple it may be, might give insight on acceptability of its particular structural model out of a confusion set of models generated from database driven comparative technique for structure prediction. The result obtained from a widely varying structural class of proteins indicated that speed of protein structure evaluation can be further enhanced without compromising with accuracy by recruiting simple experimental output.

CONCLUSION

In this work, a semi-empirical methodological approach was provided for improving protein structure evaluation. It showed that, once structure models of a protein were obtained through homology technique, the problem of selection of a best model out of a confusion set of Pareto-optimal structures could be resolved by employing a structure agent directly obtainable through experiment with the same protein as experimental ingredient. Overall, in the backdrop of getting a reasonably accurate protein structure of pathogens causing epidemics or biological warfare, such approach could be of use as a plausible solution for fast drug design.

Emerging Diagnostic and Therapeutic Potentials of Human Hair Proteomics

The use of noninvasive human substrates to interrogate pathophysiological conditions has become essential in the post- Human Genome Project era. Due to its high turnover rate, and its long term capability to incorporate exogenous and endogenous substances from the circulation, hair testing is emerging as a key player in monitoring long term drug compliance, chronic alcohol abuse, forensic toxicology, and biomarker discovery, among other things. Novel high-throughput 'omics based approaches like proteomics have been underutilized globally in comprehending human hair morphology and its evolving use as a diagnostic testing substrate in the era of precision medicine. There is paucity of scientific evidence that evaluates the difference in drug incorporation into hair based on lipid content, and very few studies have addressed hair growth rates, hair forms, and the biological consequences of hair grooming or bleaching. It is apparent that protein-based identification using the human hair proteome would play a major role in understanding these parameters akin to DNA single nucleotide polymorphism profiling, up to single amino acid polymorphism resolution. Hence, this work seeks to identify and discuss the progress made thus far in the field of molecular hair testing using proteomic approaches, and identify ways in which proteomics would improve the field of hair research, considering that the human hair is mostly composed of proteins. Gaps in hair proteomics research are identified and the potential of hair proteomics in establishing a historic medical repository of normal and disease-specific proteome is also discussed.

Intra- and Interskeletal Proteome Variations in Fresh and Buried Bones

Proteomic methods are acquiring greater importance in archaeology and palaeontology due to the longevity of proteins in skeletal remains. There are also developing interests in forensic applications, offering the potential to shed light on post-mortem intervals and age at death estimation. However, our understanding of intra- and interskeletal proteome variations is currently severely limited. Here, we evaluated the proteomes obtained from five distinct subsamples of different skeletal elements from buried pig carcasses to ascertain the extent of variation within and between individuals. We found that reproducibility of data depends on the skeletal element used for sampling and that intrabone differences exceed those observed between the same skeletal element sampled from different individuals. Interestingly, the abundance of several serum proteins appeared to correlate with biological age with relative concentrations of alpha-1 antitrypsin and chromogranin-A increasing and those of fetuin-A decreasing. We also observed a surprising level of divergence in data from different LC-MS/MS runs on aliquots of similar samples analyzed months apart, adding constraints to the comparison of results of such methods across different studies.

Exploring biomolecular dynamics and interactions using advanced sampling methods

Molecular dynamics (MD) and Monte Carlo (MC) simulations have emerged as a valuable tool to investigate statistical mechanics and kinetics of biomolecules and synthetic soft matter materials. However, major limitations for routine applications are due to the accuracy of the molecular mechanics force field and due to the maximum simulation time that can be achieved in current simulations studies. For improving the sampling a number of advanced sampling approaches have been designed in recent years. In particular, variants of the parallel tempering replica-exchange methodology are widely used in many simulation studies. Recent methodological advancements and a discussion of specific aims and advantages are given. This includes improved free energy simulation approaches and conformational search applications.

Epitope mapping and targeted quantitation of the cardiac biomarker troponin by SID-MRM mass spectrometry

The absolute quantitation of the targeted protein using MS provides a promising method to evaluate/verify biomarkers used in clinical diagnostics. In this study, a cardiac biomarker, troponin I (TnI), was used as a model protein for method development. The epitope peptide of TnI was characterized by epitope excision followed with LC/MS/MS method and acted as the surrogate peptide for the targeted protein quantitation. The MRM-based MS assay using a stable internal standard that improved the selectivity, specificity, and sensitivity of the protein quantitation. Also, plasma albumin depletion and affinity enrichment of TnI by anti-TnI mAb-coated microparticles reduced the sample complexity, enhanced the dynamic range, and further improved the detecting sensitivity of the targeted protein in the biological matrix. Therefore, quantitation of TnI, a low abundant protein in human plasma, has demonstrated the applicability of the targeted protein quantitation strategy through its epitope peptide determined by epitope mapping method.

New insights into viral structure and virus–cell interactions through proteomics

Although genomics techniques such as DNA microarrays have been widely used in virology, much more limited use has been made of proteomics. Although difficult, proteomics can greatly contribute to an understanding of virus-cell interactions, including the ternary structure of viral receptors at the cell surface, post-translational modifications and isoforms of critical viral and cellular proteins and even to the structure of viruses. Proteomics techniques also offer the potential for discovering markers for diagnostic and prognostic tests of viral infections in vivo. This review describes the use of several proteomic approaches for the analysis of HIV-cellular receptor interactions, the molecular mechanisms of transport of herpes simplex virus within neurons, and the structure of the tegument of herpes simplex virus.

Utility of computational structural biology in mass spectrometry

Recent developments of mass spectrometry (MS) allow us to identify, estimate, and characterize proteins and protein complexes. At the same time, structural biology helps to determine the protein structure and its structure-function relationship. Together, they aid to understand the protein structure, property, function, protein-complex assembly, protein-protein interaction and dynamics. The present chapter is organized with illustrative results to demonstrate how experimental mass spectrometry can be combined with computational structural biology for detailed studies of protein's structures. We have used tumor differentiation factor protein/peptide as ligand and Hsp70/Hsp90 as receptor protein as examples to study ligand-protein interaction. To investigate possible protein conformation we will describe two proteins, lysozyme and myoglobin.

Periodontal proteomics: wonders never cease!

Proteins are vital parts of living organisms, as they are integral components of the physiological metabolic pathways of cells. Periodontal tissues comprise multicompartmental groups of interacting cells and matrices that provide continuous support, attachment, proprioception, and physical protection for the teeth. The proteome map, that is, complete catalogue of the matrix and cellular proteins expressed in alveolar bone, cementum, periodontal ligament, and gingiva, is to be explored for more in-depth understanding of periodontium. The ongoing research to understand the signalling pathways that allow cells to divide, differentiate, and die in controlled manner has brought us to the era of proteomics. Proteomics is defined as the study of all proteins including their relative abundance, distribution, posttranslational modifications, functions, and interactions with other macromolecules, in a given cell or organism within a given environment and at a specific stage in the cell cycle. Its application to periodontal science can be used to monitor health status, disease onset, treatment response, and outcome. Proteomics can offer answers to critical, unresolved questions such as the biological basis for the heterogeneity in gingival, alveolar bone, and cemental cell populations.

Identification and mapping of linear antibody epitopes in human serum albumin using high-density Peptide arrays

We have recently developed a high-density photolithographic, peptide array technology with a theoretical upper limit of 2 million different peptides per array of 2 cm². Here, we have used this to perform complete and exhaustive analyses of linear B cell epitopes of a medium sized protein target using human serum albumin (HSA) as an example. All possible overlapping 15-mers from HSA were synthesized and probed with a commercially available polyclonal rabbit anti-HSA antibody preparation. To allow for identification of even the weakest epitopes and at the same time perform a detailed characterization of key residues involved in antibody binding, the array also included complete single substitution scans (i.e. including each of the 20 common amino acids) at each position of each 15-mer peptide. As specificity controls, all possible 15-mer peptides from bovine serum albumin (BSA) and from rabbit serum albumin (RSA) were included as well. The resulting layout contained more than 200.000 peptide fields and could be synthesized in a single array on a microscope slide. More than 20 linear epitope candidates were identified and characterized at high resolution i.e. identifying which amino acids in which positions were needed, or not needed, for antibody interaction. As expected, moderate cross-reaction with some peptides in BSA was identified whereas no cross-reaction was observed with peptides from RSA. We conclude that high-density peptide microarrays are a very powerful methodology to identify and characterize linear antibody epitopes, and should advance detailed description of individual specificities at the single antibody level as well as serologic analysis at the proteome-wide level.

Analysis of secondary structure in proteins by chemical cross-linking coupled to MS

Chemical cross-linking is an attractive technique for the study of the structure of protein complexes due to its low sample consumption and short analysis time. Furthermore, distance constraints obtained from the identification of cross-linked peptides by MS can be used to construct and validate protein models. If a sufficient number of distance constraints are obtained, then determining the secondary structure of a protein can allow inference of the protein's fold. In this work, we show how the distance constraints obtained from cross-linking experiments can identify secondary structures within the protein sequence. Molecular modeling of alpha helices and beta sheets reveals that each secondary structure presents different cross-linking possibilities due to the topological distances between reactive residues. Cross-linking experiments performed with amine reactive cross-linkers with model alpha helix containing proteins corroborated the molecular modeling predictions. The cross-linking patterns established here can be extended to other cross-linkers with known lengths for the determination of secondary structures in proteins.

Advanced replica-exchange sampling to study the flexibility and plasticity of peptides and proteins

Molecular dynamics (MD) simulations are ideally suited to investigate protein and peptide plasticity and flexibility simultaneously at high spatial (atomic) and high time resolution. However, the applicability is still limited by the force field accuracy and by the maximum simulation time that can be routinely achieved in current MD simulations. In order to improve the sampling the replica-exchange (REMD) methodology has become popular and is now the most widely applied advanced sampling approach. Many variants of the REMD method have been designed to reduce the computational demand or to enhance sampling along specific sets of conformational variables. An overview on recent methodological advances and discussion of specific aims and advantages of the approaches will be given. Applications in the area of free energy simulations and advanced sampling of intrinsically disordered peptides and proteins will also be discussed. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.

Structure prediction and evolution of a halo-acid dehalogenase of Burkholderia mallei

Environmental pollutants containing halogenated organic compounds e.g. haloacid, can cause a plethora of health problems. The structural and functional analyses of the gene responsible of their degradation are an important aspect for environmental studies and are important to human well-being. It has been shown that some haloacids are toxic and mutagenic. Microorganisms capable of degrading these haloacids can be found in the natural environment. One of these, a soil-borne Burkholderia mallei posses the ability to grow on monobromoacetate (MBA). This bacterium produces a haloacid dehalogenase that allows the cell to grow on MBA, a highly toxic and mutagenic environmental pollutant. For the structural and functional analysis, a 346 amino acid encoding protein sequence of haloacid dehalogenase is retrieve from NCBI data base. Primary and secondary structure analysis suggested that the high percentage of helices in the structure makes the protein more flexible for folding, which might increase protein interactions. The consensus protein sub-cellular localization predictions suggest that dehalogenase protein is a periplasmic protein 3D2GO server, suggesting that it is mainly employed in metabolic process followed by hydrolase activity and catalytic activity. The tertiary structure of protein was predicted by homology modeling. The result suggests that the protein is an unstable protein which is also an important characteristic of active enzyme enabling them to bind various cofactors and substrate for proper functioning. Validation of 3D structure was done using Ramachandran plot ProsA-web and RMSD score. This predicted information will help in better understanding of mechanism underlying haloacid dehalogenase encoding protein and its evolutionary relationship.

High-resolution mapping of linear antibody epitopes using ultrahigh-density peptide microarrays

Antibodies empower numerous important scientific, clinical, diagnostic, and industrial applications. Ideally, the epitope(s) targeted by an antibody should be identified and characterized, thereby establishing antibody reactivity, highlighting possible cross-reactivities, and perhaps even warning against unwanted (e.g. autoimmune) reactivities. Antibodies target proteins as either conformational or linear epitopes. The latter are typically probed with peptides, but the cost of peptide screening programs tends to prohibit comprehensive specificity analysis. To perform high-throughput, high-resolution mapping of linear antibody epitopes, we have used ultrahigh-density peptide microarrays generating several hundred thousand different peptides per array. Using exhaustive length and substitution analysis, we have successfully examined the specificity of a panel of polyclonal antibodies raised against linear epitopes of the human proteome and obtained very detailed descriptions of the involved specificities. The epitopes identified ranged from 4 to 12 amino acids in size. In general, the antibodies were of exquisite specificity, frequently disallowing even single conservative substitutions. In several cases, multiple distinct epitopes could be identified for the same target protein, suggesting an efficient approach to the generation of paired antibodies. Two alternative epitope mapping approaches identified similar, although not necessarily identical, epitopes. These results show that ultrahigh-density peptide microarrays can be used for linear epitope mapping. With an upper theoretical limit of 2,000,000 individual peptides per array, these peptide microarrays may even be used for a systematic validation of antibodies at the proteomic level.

Homology modeling of an antifungal metabolite plipastatin synthase from the Bacillus subtilis 168

Lipopeptides have a widespread role in different pathways of Bacillus subtilis; they can act as antagonists, spreader and immunostimulators. Plipastatin, an antifungal antibiotic, is one of the most important lipopeptide nonribosomly produced by Bacillus subtilis. Plipastatin has strong fungitoxic activity and involve in inhibition of phospholipase A2 and biofilm formation. For better understanding of the molecule and pathway by which lipopeptide plipastatin is synthesized, we present a computationally predicted structure of plipastatin using homology modeling. Primary and secondary structure analysis suggested that ppsD is a hydrophilic protein containing a significant proportion of alpha helices, and subcellular localization predictions suggested it is a cytoplasmic protein. The tertiary structure of protein (plipastatin synthase subunit D) was predicted by homology modeling. The results suggest a flexible structure which is also an important characteristic of active enzymes enabling them to bind various cofactors and substrates for proper functioning. Validation of 3D structure was done using Ramachandran plot ProsA-web and QMEAN score.This predicted information will help in better understanding of mechanisms underlying plipastatin synthase subunit D synthesis. Plipastatin can be used as an inhibitor of various fungal diseases in plants.

Analysis of the disulfide bond arrangement of the HIV-1 envelope protein CON-S gp140 ΔCFI shows variability in the V1 and V2 regions

Disulfide bonding of cysteines is one of the most important protein modifications, and it plays a key role in establishing/maintaining protein structures in biologically active forms. Therefore, the determination of disulfide bond arrangement is one important aspect to understanding the chemical structure of a protein and defining its functional domains. Herein, aiming to understand how the HIV-1 envelope protein's structure influences its immunogenicity, we used an MS-based approach, liquid chromatography electrospray ionization Fourier transform ion cyclotron resonance (LC/ESI-FTICR) mass spectrometry, to determine the disulfide linkages on an oligomeric form of the group M consensus HIV-1 envelope protein (Env), CON-S gp140 ΔCFI. This protein has marked improvement in its immunogenicity compared to monomeric gp120 and wild-type forms of gp140 Envs. Our results demonstrate that the disulfide connectivity in the N-terminal region of CON-S gp140 ΔCFI is different from the disulfide bonding previously reported in the monomeric form of gp120 HIV-1 Env. Additionally, heterogeneity of the disulfide bonding was detected in this region. These data suggest that the V1/V2 region does not have a single, conserved disulfide bonding pattern and that variability could impact immunogenicity of expressed Envs.

Toward understanding the mechanism of action of the yeast multidrug resistance transporter Pdr5p: a molecular modeling study

Pleotropic drug resistant protein 5 (Pdr5p) is a plasma membrane ATP-binding cassette (ABC) transporter and the major drug efflux pump in Saccharomyces cerevisiae. The Pdr5p family of fungal transporters possesses a number of structural features significantly different from other modeled or crystallized ABC transporters, which include a reverse topology, an atypical ATP-binding site, a very low sequence similarity in the transmembrane section and long linkers between domains. These features present a considerable hurdle in molecular modeling studies of these important transporters. Here, we report the creation of an atomic model of Pdr5p based on a combination of homology modeling and ab initio methods, incorporating information from consensus transmembrane segment prediction, residue lipophilicity, and sequence entropy. Reported mutations in the transmembrane substrate-binding pocket that altered drug-resistance were used to validate the model, and one mutation that changed the communication pattern between transmembrane and nucleotide-binding domains was used in model improvement. The predictive power of the model was demonstrated experimentally by the increased sensitivity of yeast mutants to clotrimazole having alanine substitutions for Thr1213 and Gln1253, which are predicted to be in the substrate-binding pocket, without reducing the amount of Pdr5p in the plasma membrane. The quality and reliability of our model are discussed in the context of various approaches used for modeling different parts of the structure.

Cholera- and anthrax-like toxins are among several new ADP-ribosyltransferases

Chelt, a cholera-like toxin from Vibrio cholerae, and Certhrax, an anthrax-like toxin from Bacillus cereus, are among six new bacterial protein toxins we identified and characterized using in silico and cell-based techniques. We also uncovered medically relevant toxins from Mycobacterium avium and Enterococcus faecalis. We found agriculturally relevant toxins in Photorhabdus luminescens and Vibrio splendidus. These toxins belong to the ADP-ribosyltransferase family that has conserved structure despite low sequence identity. Therefore, our search for new toxins combined fold recognition with rules for filtering sequences--including a primary sequence pattern--to reduce reliance on sequence identity and identify toxins using structure. We used computers to build models and analyzed each new toxin to understand features including: structure, secretion, cell entry, activation, NAD+ substrate binding, intracellular target binding and the reaction mechanism. We confirmed activity using a yeast growth test. In this era where an expanding protein structure library complements abundant protein sequence data--and we need high-throughput validation--our approach provides insight into the newest toxin ADP-ribosyltransferases.

Epitope mapping of antibodies using a cell array-based polypeptide library

The authors describe a technique for mapping the epitopes of protein antigens recognized by mono- or polyclonal antibodies. This method is based on a recombinant polypeptide library, expressed in a bacterial expression system, arrayed at high density, and tested on a membrane with automated procedures. The authors analyzed the epitope of a commercially available monoclonal antibody to vitamin D receptor (VDR). About 2300 overlapping VDR peptides were screened on a test array, and a contiguous stretch of 37 amino acids was identified as the epitope. Its authenticity was confirmed by Western blotting and an immunofluorescence competition assay on human skin tissue samples. The authors define the proposed method as a cell-based protein or peptide array that is adaptable to many applications, including epitope mapping of antibodies and autoantibodies, autoantigen detection from patient sera, whole-proteome approaches such as protein-peptide interactions, or selection of monoclonal antibodies from polyclonal sera. The advantages of this method are (a) its ease of protein array production based on well-established bacterial protein/peptide expression procedures; (b) the large number of printable colonies (as many as approximately 25,000) that can be arrayed per membrane; (c) there is no need for protein purification of recombinantly expressed proteins; (d) DNA, rather than protein, is the starting material to generate the arrays; and (e) its high-throughput and automatable format.

Plant cell wall proteomics: mass spectrometry data, a trove for research on protein structure/function relationships

Proteomics allows the large-scale study of protein expression either in whole organisms or in purified organelles. In particular, mass spectrometry (MS) analysis of gel-separated proteins produces data not only for protein identification, but for protein structure, location, and processing as well. An in-depth analysis was performed on MS data from etiolated hypocotyl cell wall proteomics of Arabidopsis thaliana. These analyses show that highly homologous members of multigene families can be differentiated. Two lectins presenting 93% amino acid identity were identified using peptide mass fingerprinting. Although the identification of structural proteins such as extensins or hydroxyproline/proline-rich proteins (H/PRPs) is arduous, different types of MS spectra were exploited to identify and characterize an H/PRP. Maturation events in a couple of cell wall proteins (CWPs) were analyzed using site mapping. N-glycosylation of CWPs as well as the hydroxylation or oxidation of amino acids were also explored, adding information to improve our understanding of CWP structure/function relationships. A bioinformatic tool was developed to locate by means of MS the N-terminus of mature secreted proteins and N-glycosylation.

Structural biology by NMR: structure, dynamics, and interactions

The function of bio-macromolecules is determined by both their 3D structure and conformational dynamics. These molecules are inherently flexible systems displaying a broad range of dynamics on time-scales from picoseconds to seconds. Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as the method of choice for studying both protein structure and dynamics in solution. Typically, NMR experiments are sensitive both to structural features and to dynamics, and hence the measured data contain information on both. Despite major progress in both experimental approaches and computational methods, obtaining a consistent view of structure and dynamics from experimental NMR data remains a challenge. Molecular dynamics simulations have emerged as an indispensable tool in the analysis of NMR data.

C-terminal motif prediction in eukaryotic proteomes using comparative genomics and statistical over-representation across protein families

Background

The carboxy termini of proteins are a frequent site of activity for a variety of biologically important functions, ranging from post-translational modification to protein targeting. Several short peptide motifs involved in protein sorting roles and dependent upon their proximity to the C-terminus for proper function have already been characterized. As a limited number of such motifs have been identified, the potential exists for genome-wide statistical analysis and comparative genomics to reveal novel peptide signatures functioning in a C-terminal dependent manner. We have applied a novel methodology to the prediction of C-terminal-anchored peptide motifs involving a simple z-statistic and several techniques for improving the signal-to-noise ratio.

Results

We examined the statistical over-representation of position-specific C-terminal tripeptides in 7 eukaryotic proteomes. Sequence randomization models and simple-sequence masking were applied to the successful reduction of background noise. Similarly, as C-terminal homology among members of large protein families may artificially inflate tripeptide counts in an irrelevant and obfuscating manner, gene-family clustering was performed prior to the analysis in order to assess tripeptide over-representation across protein families as opposed to across all proteins. Finally, comparative genomics was used to identify tripeptides significantly occurring in multiple species. This approach has been able to predict, to our knowledge, all C-terminally anchored targeting motifs present in the literature. These include the PTS1 peroxisomal targeting signal (SKL*), the ER-retention signal (K/HDEL*), the ER-retrieval signal for membrane bound proteins (KKxx*), the prenylation signal (CC*) and the CaaX box prenylation motif. In addition to a high statistical over-representation of these known motifs, a collection of significant tripeptides with a high propensity for biological function exists between species, among kingdoms and across eukaryotes. Motifs of note include a serine-acidic peptide (DSD*) as well as several lysine enriched motifs found in nearly all eukaryotic genomes examined.

Conclusion

We have successfully generated a high confidence representation of eukaryotic motifs anchored at the C-terminus. A high incidence of true-positives in our results suggests that several previously unidentified tripeptide patterns are strong candidates for representing novel peptide motifs of a widely employed nature in the C-terminal biology of eukaryotes. Our application of comparative genomics, statistical over-representation and the adjustment for protein family homology has generated several hypotheses concerning the C-terminal topology as it pertains to sorting and potential protein interaction signals. This approach to background reduction could be expanded for application to protein motif prediction in the protein interior. A parallel N-terminal analysis is presented as supplementary data.

The use of proteomics to identify novel therapeutic targets for the treatment of disease

The completion of the Human Genome Project has revealed a multitude of potential avenues for the identification of therapeutic targets. Extensive sequence information enables the identification of novel genes but does not facilitate a thorough understanding of how changes in gene expression control the molecular mechanisms underlying the development and regulation of a cell or the progression of disease. Proteomics encompasses the study of proteins expressed by a population of cells, and evaluates changes in protein expression, post-translational modifications, protein interactions, protein structure and splice variants, all of which are imperative for a complete understanding of protein function within the cell. From the outset, proteomics has been used to compare the protein profiles of cells in healthy and diseased states and as such can be used to identify proteins associated with disease development and progression. These candidate proteins might provide novel targets for new therapeutic agents or aid the development of assays for disease biomarkers. This review provides an overview of the current proteomic techniques available and focuses on their application in the search for novel therapeutic targets for the treatment of disease.

Determination of protein-derived epitopes by mass spectrometry

Mass spectrometry has evolved as a technique suitable for the characterization of peptides and proteins beyond their linear sequence. The advantages of mass spectrometric sample analysis are high sensitivity, high mass accuracy, rapid analysis time and low sample consumption. In epitope mapping, the molecular structure of an antigen (the epitope or antigenic determinant) that interacts with the paratope (recognition surface) of the antibody is identified. To obtain information on linear, conformational and/or discontinuous epitopes, various approaches have been developed in conjunction with mass spectrometry. These methods include limited proteolysis and epitope footprinting, epitope excision and epitope extraction for linear epitopes and probing the surface accessibility of residues by differential chemical modifications of specific amino acid side chains or by differential hydrogen/deuterium exchange of the protein backbone amides for conformational and discontinuous epitopes. Epitope mapping by mass spectrometry is applicable in basic biochemical research and, with increasing robustness, should soon find its implementation in routine clinical diagnosis.

Proteomics in human cancer research

Proteomics is now widely employed in the study of cancer. Many laboratories are applying the rapidly emerging technologies to elucidate the underlying mechanisms associated with cancer development, progression, and severity in addition to developing drugs and identifying patients who will benefit most from molecular targeted compounds. Various proteomic approaches are now available for protein separation and identification, and for characterization of the function and structure of candidate proteins. In spite of significant challenges that still exist, proteomics has rapidly expanded to include the discovery of novel biomarkers for early detection, diagnosis and prognostication (clinical application), and for the identification of novel drug targets (pharmaceutical application). To achieve these goals, several innovative technologies including 2-D-difference gel electrophoresis, SELDI, multidimensional protein identification technology, isotope-coded affinity tag, solid-state and suspension protein array technologies, X-ray crystallography, NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulation have evolved, and are being used in different combinations. This review provides an overview of the field of proteomics and discusses the key proteomic technologies available to researchers. It also describes some of the important challenges and highlights the current pharmaceutical and clinical applications of proteomics in human cancer research.

Protein structure by mechanical triangulation

Knowledge of protein structure is essential to understand protein function. High-resolution protein structure has so far been the domain of ensemble methods. Here, we develop a simple single-molecule technique to measure spatial position of selected residues within a folded and functional protein structure in solution. Construction and mechanical unfolding of cysteine-engineered polyproteins with controlled linkage topology allows measuring intramolecular distance with angstrom precision. We demonstrate the potential of this technique by determining the position of three residues in the structure of green fluorescent protein (GFP). Our results perfectly agree with the GFP crystal structure. Mechanical triangulation can find many applications where current bulk structural methods fail.

Effect of pH, urea, peptide length, and neighboring amino acids on alanine α-proton random coil chemical shifts

Accurate random coil alpha-proton chemical shift values are essential for precise protein structure analysis using chemical shift index (CSI) calculations. The current study determines the chemical shift effects of pH, urea, peptide length and neighboring amino acids on the alpha-proton of Ala using model peptides of the general sequence GnXaaAYaaGn, where Xaa and Yaa are Leu, Val, Phe, Tyr, His, Trp or Pro, and n = 1-3. Changes in pH (2-6), urea (0-1M), and peptide length (n = 1-3) had no effect on Ala alpha-proton chemical shifts. Denaturing concentrations of urea (8M) caused significant downfield shifts (0.10 +/- 0.01 ppm) relative to an external DSS reference. Neighboring aliphatic residues (Leu, Val) had no effect, whereas aromatic amino acids (Phe, Tyr, His and Trp) and Pro caused significant shifts in the alanine alpha-proton, with the extent of the shifts dependent on the nature and position of the amino acid. Smaller aromatic residues (Phe, Tyr, His) caused larger shift effects when present in the C-terminal position (approximately 0.10 vs. 0.05 ppm N-terminal), and the larger aromatic tryptophan caused greater effects in the N-terminal position (0.15 ppm vs. 0.10 C-terminal). Proline affected both significant upfield (0.06 ppm, N-terminal) and downfield (0.25 ppm, C-terminal) chemical shifts. These new Ala correction factors detail the magnitude and range of variation in environmental chemical shift effects, in addition to providing insight into the molecular level interactions that govern protein folding.

Combining docking and molecular dynamic simulations in drug design

A rational approach is needed to maximize the chances of finding new drugs, and to exploit the opportunities of potential new drug targets emerging from genomic and proteomic initiatives, and from the large libraries of small compounds now readily available through combinatorial chemistry. Despite a shaky early history, computer-aided drug design techniques can now be effective in reducing costs and speeding up drug discovery. This happy outcome results from development of more accurate and reliable algorithms, use of more thoughtfully planned strategies to apply them, and greatly increased computer power to allow studies with the necessary reliability to be performed. Our review focuses on applications and protocols, with the main emphasis on critical analysis of recent studies where docking calculations and molecular dynamics (MD) simulations were combined to dock small molecules into protein receptors. We highlight successes to demonstrate what is possible now, but also point out drawbacks and future directions. The review is structured to lead the reader from the simpler to more compute-intensive methods. Thus, while inexpensive and fast docking algorithms can be used to scan large compound libraries and reduce their size, more accurate but expensive MD simulations can be applied when a few selected ligand candidates remain. MD simulations can be used: during the preparation of the protein receptor before docking, to optimize its structure and account for protein flexibility; for the refinement of docked complexes, to include solvent effects and account for induced fit; to calculate binding free energies, to provide an accurate ranking of the potential ligands; and in the latest developments, during the docking process itself to find the binding site and correctly dock the ligand a priori.