Biochemical Functions Of Proteins Research Articles

Perspective: How Fast Dynamics Affect Slow Function in Protein Machines.

Internal motions in proteins take place on a broad range of time- and space-scales. The potential roles of these dynamics in the biochemical functions of proteins have intrigued biophysicists for many years, and multiple mechanisms to couple motions to function have been proposed. Some of these mechanisms have relied on equilibrium concepts. For example, the modulation of dynamics was proposed to change the entropy of a protein, hence affecting processes such as binding. This so-called dynamic allostery scenario has been demonstrated in several recent experiments. Perhaps even more intriguing may be models that involve out-of-equilibrium operation, which by necessity require the input of energy. We discuss several recent experimental studies that expose such potential mechanisms for coupling dynamics and function. In Brownian ratchets, for example, directional motion is promoted by switching a protein between two free energy surfaces. An additional example involves the effect of microsecond domain-closure dynamics of an enzyme on its much slower chemical cycle. These observations lead us to propose a novel two-time-scale paradigm for the activity of protein machines: fast equilibrium fluctuations take place on the microsecond-millisecond time scale, while on a slower time scale, free energy is invested in order to push the system out of equilibrium and drive functional transitions. Motions on the two time scales affect each other and are essential for the overall function of these machines.

Probing Adaptation of Hydration and Protein Dynamics to Temperature.

Protein dynamics is strongly influenced by the surrounding environment and physiological conditions. Here we employ broadband megahertz-to-terahertz spectroscopy to explore the dynamics of water and myoglobin protein on an extended time scale from femto- to nanosecond. The dielectric spectra reveal several relaxations corresponding to the orientational polarization mechanism, including the dynamics of loosely bound, tightly bound, and bulk water, as well as collective vibrational modes of protein in an aqueous environment. The dynamics of loosely bound and bulk water follow non-Arrhenius behavior; however, the dynamics of water molecules in the tightly bound layer obeys the Arrhenius-type relation. Combining molecular simulations and effective-medium approximation, we have determined the number of water molecules in the tightly bound hydration layer and studied the dynamics of protein as a function of temperature. The results provide the important impact of water on the biochemical functions of proteins.

Development in Detection Methods for the Expression of Surface-Displayed Proteins.

Directed evolution is a widely-used engineering strategy for improving the stabilities or biochemical functions of proteins by repeated rounds of mutation and selection. A protein of interest is selected as the template and expressed on a molecular display platform such as a bacteriophage for engineering. Initially, the surface-displayed protein template needs to be checked against the desired target via ELISA to examine whether the functions of the displayed template remain intact. The ELISA signal is subject to the protein-target binding affinity. A low-affinity results in a weak ELISA signal which makes it difficult to determine whether the weak signal is because of low affinity or because of poor expression of the protein. Using a methyllysine-binding chromodomain protein Cbx1 that weakly binds to the histone H3K9me3 peptide, we developed and compared three different approaches to increase the signal-to-background ratio of ELISA measurements. We observed that the specific peptide-binding signal was enhanced by increasing the Cbx1 phage concentration on the ELISA plate. The introduction of previously known gain-of-function mutations to the Cbx1 protein significantly increased the ELISA signals. Moreover, we demonstrated that the H3K9me3-specific binding signal was enhanced by fusing Cbx1 with a high-affinity phosphotyrosine-binding protein and by coating the ELISA plate with a mixture of H3K9me3 and phosphotyrosine peptides. This approach also worked with binding to a lower affinity momomethyllysine peptide H3K9me1. These approaches may help improve ELISA experiments when dealing with low-affinity ligand-protein interactions.

How Ligand Binding Affects the Dynamical Transition Temperature in Proteins.

The biochemical functions of proteins are activated at the protein glass transition temperature, which has been proposed to be dependent upon protein-water interactions. However, at the molecular level it is unclear how ligand binding to well-defined binding sites can influence this transition temperature. We thus report molecular dynamics (MD) simulations of the ϵ subunit from thermophilic Bacillus PS3 in the ATP-free and ligand-bound states over a range of temperatures from 20 to 300 K, to study the influence of ligand association upon the transition temperature. We also measure the protein mean square displacement (MSD) in each state, which is well established as a means to quantify this dynamical temperature dependence. We find that the transition temperature is largely unaffected by ligand association, but the MSD beyond the transition temperature increases more rapidly in the ATP-free state. Our data suggests that ligands can effectively "shield" a binding site from solvent, and hence stabilize protein domains with increasing temperature.

Homolog comparisons further reconcile in vitro and in vivo correlations of protein activities by revealing over‐looked physiological factors

To bridge biological and biochemical disciplines, the relationship between in vitro protein biochemical function and in vivo activity must be established. Such studies can (a) help determine whether properties measured in simple, dilute solutions extrapolate to the complex in vivo conditions and (b) illuminate cryptic biological factors that are new avenues for study. We have explored the in vivo-in vitro relationship for chimeras built from LacI/GalR transcription regulators. In prior studies of individual chimeras, amino acid changes that altered in vitro DNA binding affinity exhibited correlated changes in in vivo transcription repression. However, discrepancies arose when the two datasets were compared to each other: Although their DNA binding domains were identical and their in vitro binding affinities spanned the same range, their in vivo repression ranges differed by >50-fold. Here, we determined that the presence of endogenous ligand for one chimera further exacerbated the offset, but that different abilities to simultaneously bind and "loop" two DNA operators resolves the discrepancy. Indeed, results suggest that the lac operon can be looped by even weakly interacting repressor dimers. For looping-competent repressors, we measured in vitro binding to the secondary operator. Surprisingly, this was largely insensitive to amino acid changes in the repressor protein, which reflects altered specificity; this supports the emerging view that the locations of specificity determining positions can be unique to each protein homolog. In aggregate, this work illustrates how a comparative approach can enrich understanding of the in vivo-in vitro relationship and suggest unexpected avenues for future study.

CosR is an oxidative stress sensing a MarR-type transcriptional repressor in Corynebacterium glutamicum

The MarR family is unique to both bacteria and archaea. The members of this family, one of the most prevalent families of transcriptional regulators in bacteria, enable bacteria to adapt to changing environmental conditions, such as the presence of antibiotics, toxic chemicals, or reactive oxygen species (ROS), mainly by thiol-disulfide switches. Although the genome of Corynebacterium glutamicum encodes a large number of the putative MarR-type transcriptional regulators, their physiological and biochemical functions have so far been limited to only two proteins, regulator of oxidative stress response RosR and quinone oxidoreductase regulator QosR. Here, we report that the ncgl2617 gene (cosR) of C. glutamicum encoding an MarR-type transcriptional regulator plays an important role in oxidative stress resistance. The cosR null mutant is found to be more resistant to various oxidants and antibiotics, accompanied by a decrease in ROS production and protein carbonylation levels under various stresses. Protein biochemical function analysis shows that two Cys residues presenting at 49 and 62 sites in CosR are redox-active. They form intermolecular disulfide bonds in CosR under oxidative stress. This CosR oxidation leads to its dissociation from promoter DNA, depression of the target DNA, and increased oxidative stress resistance of C. glutamicum. Together, the results reveal that CosR is a redox-sensitive regulator that senses peroxide stress to mediate oxidative stress resistance in C. glutamicum.

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Interplay of physics and evolution in the likely origin of protein biochemical function

The intrinsic ability of protein structures to exhibit the geometric and sequence properties required for ligand binding without evolutionary selection is shown by the coincidence of the properties of pockets in native, single domain proteins with those in computationally generated, compact homopolypeptide, artificial (ART) structures. The library of native pockets is covered by a remarkably small number of representative pockets (∼400), with virtually every native pocket having a statistically significant match in the ART library, suggesting that the library is complete. When sequences are selected for ART structures based on fold stability, pocket sequence conservation is coincident to native. The fact that structurally and sequentially similar pockets occur across fold classes combined with the small number of representative pockets in native proteins implies that promiscuous interactions are inherent to proteins. Based on comparison of PDB (real, single domain protein structures found in the Protein Data Bank) and ART structures and pockets, the widespread assumption that the co-occurrence of global structure, pocket similarity, and amino acid conservation demands an evolutionary relationship between proteins is shown to significantly underestimate the random background probability. Indeed, many features of biochemical function arise from the physical properties of proteins that evolution likely fine-tunes to achieve specificity. Finally, our study suggests that a repertoire of thermodynamically (marginally) stable proteins could engage in many of the biochemical reactions needed for living systems without selection for function, a conclusion with significant implications for the origin of life.

Energetics-Based Discovery of Protein–Ligand Interactions on a Proteomic Scale

Biochemical functions of proteins in cells frequently involve interactions with various ligands. Proteomic methods for the identification of proteins that interact with specific ligands such as metabolites, signaling molecules, and drugs are valuable in investigating the regulatory mechanisms of cellular metabolism, annotating proteins with unknown functions, and elucidating pharmacological mechanisms. Here we report an energetics-based target identification method in which target proteins in a cell lysate are identified by exploiting the effect of ligand binding on their stabilities. Urea-induced unfolding of proteins in cell lysates is probed by a short pulse of proteolysis, and the effect of a ligand on the amount of folded protein remaining is monitored on a proteomic scale. As proof of principle, we identified proteins that interact with ATP in the Escherichia coli proteome. Literature and database mining confirmed that a majority of the identified proteins are indeed ATP-binding proteins. Four identified proteins that were previously not known to interact with ATP were cloned and expressed to validate the result. Except for one protein, the effects of ATP on urea-induced unfolding were confirmed. Analyses of the protein sequences and structure models were also employed to predict potential ATP binding sites in the identified proteins. Our results demonstrate that this energetics-based target identification approach is a facile method to identify proteins that interact with specific ligands on a proteomic scale.

In the light of directed evolution: Pathways of adaptive protein evolution

Directed evolution is a widely-used engineering strategy for improving the stabilities or biochemical functions of proteins by repeated rounds of mutation and selection. These experiments offer empirical lessons about how proteins evolve in the face of clearly-defined laboratory selection pressures. Directed evolution has revealed that single amino acid mutations can enhance properties such as catalytic activity or stability and that adaptation can often occur through pathways consisting of sequential beneficial mutations. When there are no single mutations that improve a particular protein property experiments always find a wealth of mutations that are neutral with respect to the laboratory-defined measure of fitness. These neutral mutations can open new adaptive pathways by at least 2 different mechanisms. Functionally-neutral mutations can enhance a protein's stability, thereby increasing its tolerance for subsequent functionally beneficial but destabilizing mutations. They can also lead to changes in "promiscuous" functions that are not currently under selective pressure, but can subsequently become the starting points for the adaptive evolution of new functions. These lessons about the coupling between adaptive and neutral protein evolution in the laboratory offer insight into the evolution of proteins in nature.

The p53 codon 72 polymorphism, sunburns, and risk of skin cancer in US caucasian women

The p53 gene is involved in the control of cell-cycle arrest and apoptosis. The germline Arg72Pro polymorphism alters the protein's biochemical functions, and may confer individual susceptibility to skin cancer. We evaluated the association of the Arg72Pro polymorphism with skin cancer risk among Caucasians in a nested case-control study within the Nurses' Health Study (NHS) (219 melanoma, 286 squamous cell carcinoma (SCC), and 300 basal cell carcinoma (BCC) and 874 controls). Compared to the Arg/Arg genotype, the Pro/Pro genotype had an OR of 1.57 (95%CI, 0.81-3.06) for melanoma risk, and an OR of 1.79 (95%CI, 1.01-3.17) for BCC risk. The positive association of the Pro allele with BCC risk was only limited to women with two or fewer lifetime sunburns (P, trend, 0.002; P, interaction, 0.02). No association was observed between the polymorphism and SCC risk. We also observed that the Pro allele was inversely associated with the risk of childhood sunburn among Caucasian participants pooled from four nested case-control studies within the NHS. This study suggests that the Arg72Pro polymorphism may play a role in skin carcinogenesis.

Identification of the ligand binding sites on the molecular surface of proteins

Identification of protein biochemical functions based on their three-dimensional structures is now required in the post-genome-sequencing era. Ligand binding is one of the major biochemical functions of proteins, and thus the identification of ligands and their binding sites is the starting point for the function identification. Previously we reported our first trial on structure-based function prediction, based on the similarity searches of molecular surfaces against the functional site database. Here we describe the extension of our first trial by expanding the search database to whole heteroatom binding sites appearing within the Protein Data Bank (PDB) with the new analysis protocol. In addition, we have determined the similarity threshold line, by using 10 structure pairs with solved free and complex structures. Finally, we extensively applied our method to newly determined hypothetical proteins, including some without annotations, and evaluated the performance of our methods.

Prediction of Functional Sites in Proteins Using Conserved Functional Group Analysis

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in ∼96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.

Identification of Protein Biochemical Function by Searching the Similar Shape and Electrostatic Potential on the Molecular Surface of Proteins

In the theoretical viewpoints, three-dimensional structure of proteins determines their functions, therefore we should be able to identify the function of proteins when the structures of proteins are provided, but it has not been realized. Here we describe our trials of the structure-based function identification of proteins. We focus our attention on the shape and electrostatic potential of molecular surface where the function of proteins is exhibited. Our approach is based on the similarity search of those properties against the functional site database of known proteins. As an application to hypothetical proteins, one successful result for the case of MJ0226 is described.

Identification of protein biochemical functions by similarity search using the molecular surface database eF‐site

The identification of protein biochemical functions based on their three-dimensional structures is strongly required in the post-genome-sequencing era. We have developed a new method to identify and predict protein biochemical functions using the similarity information of molecular surface geometries and electrostatic potentials on the surfaces. Our prediction system consists of a similarity search method based on a clique search algorithm and the molecular surface database eF-site (electrostatic surface of functional-site in proteins). Using this system, functional sites similar to those of phosphoenoylpyruvate carboxy kinase were detected in several mononucleotide-binding proteins, which have different folds. We also applied our method to a hypothetical protein, MJ0226 from Methanococcus jannaschii, and detected the mononucleotide binding site from the similarity to other proteins having different folds.

分子表面の形状と静電ポテンシャルの類似性検索による蛋白質の機能推定

分子表面の形状と静電ポテンシャルの類似性検索による蛋白質の機能推定

Infective proteins: the prion puzzle.

According to the Koch postulates an infectious organism is the one that can be isolated from an host suffering from a disorder, can be propagated in laboratory, can cause the same disease when introduced in another host, and finally, can be re-isolated from the host itself. If we change the word "organism" with the word "protein" we have a quite exact description of prions. Prion related disorders are a very unique category of infectious diseases. The ethiology of the so-called prionoses is related to the conversion of a normal protein (PrP(C), the cellular isoform of the prion protein) into a pathological form (the scrapie isoform of the prion protein, PrP(Sc)) which is able to propagate. The striking difference between the two forms seems to consist in a conformational modification of a mainly alpha-helix structured PrP(C) into a mainly beta-sheet PrP(Sc). The latter forms amyloid-like fibrils which precipitate into insoluble aggregates leading to the neurodegenerative changes specific of Spongiform Encephalopathies. This review will focus on the structure of the prion proteins and on PrP(C) cellular cycle, and it will discuss some hypothesis about the protein biochemical function. Finally, the various molecular mechanisms proposed for the development of conformational modifications will be reviewed, i.e. how a protein can become infectious by simply changing its structure.

Protein functions and biological contexts

The availability of a rough draft of the predicted human proteome allows an evaluation of the extent to which the predicted and biochemical functions of proteins are in alignment, and the roles of different technologies and approaches to understanding human diseases and instantiating therapeutics. Microarray technologies at the transcriptomic and proteomic levels can be high throughput and excellent for diagnostic purposes, but their informational outputs are inferior in quality to those emerging from the co- and post-translational levels and from antibody-based molecular anatomy. It is now abundantly clear that data transfer between the transcriptome and proteome is not straightforward, and that increasing emphasis needs to be placed on pure proteomic approaches at the structural, quantitative, cell biological and phenomic levels, with special focus on embryogenic and foetal processes. Finally, the precision genetic engineering that is required to evaluate the functional significance of context--dependent protein interactions underpinned by post-translational modifications and proteolytic cleavage events, is still too time consuming and rudimentary to be implemented on a large scale in the mouse, and basic principles and first order networks will need to be sorted out in even simpler model systems such as Drosophila.

Protein functions and biological contexts

The availability of a rough draft of the predicted human proteome allows an evaluation of the extent to which the predicted and biochemical functions of proteins are in alignment, and the roles of different technologies and approaches to understanding human diseases and instantiating therapeutics. Microarray technologies at the transcriptomic and proteomic levels can be high throughput and excellent for diagnostic purposes, but their informational outputs are inferior in quality to those emerging from the co- and post-translational levels and from antibody-based molecular anatomy. It is now abundantly clear that data transfer between the transcriptome and proteome is not straightforward, and that increasing emphasis needs to be placed on pure proteomic approaches at the structural, quantitative, cell biological and phenomic levels, with special focus on embryogenic and foetal processes. Finally, the precision genetic engineering that is required to evaluate the functional significance of context-dependent protein interactions underpinned by post-translational modifications and proteolytic cleavage events, is still too time consuming and rudimentary to be implemented on a large scale in the mouse, and basic principles and first order networks will need to be sorted out in even simpler model systems such as Drosophila.

Clustering amino acid contents of protein domains: biochemical functions of proteins and implications for origin of biological macromolecules.

Structural classes of protein domains correlate with their amino acid compositions. Several successful algorithms (that use only amino acid composition) have been elaborated for the prediction of structural class or potential biochemical significance. This work deals with dynamic classification (clustering) of the domains on the basis of their amino acid composition. Amino acid contents of domains from a non-redundant PDB set were clustered in 20-dimensional space of amino acid contents. Despite the variations of an empirical parameter and non-redundancy of the set, only one large cluster (tens-hundreds of proteins) surrounded by hundreds of small clusters (1-5 proteins), was identified. The core of the largest cluster contains at least 64% DNA (nucleotide)-interacting protein domains from various sources. About 90% of the proteins of the core are intracellular proteins. 83% of the DNA/nucleotide interacting domains in the core belong to the mixed alpha-beta folds (a+b, a/b), 14% are all-alpha (mostly helices) and all-beta (mostly beta-strands) proteins. At the same time, when core domains that belong to one organism (E.coli) are considered, over 80% of them prove to be DNA/nucleotide interacting proteins. The core is compact: amino acid contents of domains from the core lie in relatively narrow and specific ranges. The core also contains several Fe-S cluster-binding domains, amino acid contents of the core overlap with ferredoxin and CO-dehydrogenase clusters, the oldest known proteins. As Fe-S clusters are thought to be the first biocatalysts, the results are discussed in relation to contemporary experiments and models dealing with the origin of biological macromolecules. The origin of most primordial proteins is considered here to be a result of co-adsorption of nucleotides and amino acids on specific clays, followed by en-block polymerization of the adsorbed mixtures of amino acids.