Chemistry of Biomacromolecules: Current Research Articles
Current Articles about the Chemistry of Biomacromolecules published in scientific online journals.
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On this page considered biochemistry journals:
BMC Structural Biology - published by
BioMed Central -
... is an open access journal publishing original peer-reviewed research articles in investigations into the structure and function of biological macromolecules.
Biomacromolecules - published by
The American Chemical Society -
... explores the interactions of macromolecules with biological systems and their environments as well as biological approaches to the design of polymeric materials. Cutting-edge research at the interface of polymer science and biological sciences.
Current research articles of the mentioned
journals:
Background:
One of the major challenges in understanding enzyme catalysis is to identify the different conformations and their populations at detailed molecular level in response to ligand binding/environment. A detail description of the ligand induced conformational changes provides meaningful insights into the mechanism of action of enzymes and thus its function.
Results:
In this study, we have explored the ligand induced conformational changes in H.pylori LuxS and the associated mechanistic features. LuxS, a dimeric protein, produces the precursor (4,5-dihydroxy-2,3-pentanedione) for autoinducer-2 production which is a signalling molecule for bacterial quorum sensing. We have performed molecular dynamics simulations on H.pylori LuxS in its various ligand bound forms and analyzed the simulation trajectories using various techniques including the structure network analysis, free energy evaluation and water dynamics at the active site. The results bring out the mechanistic details such as co-operativity and asymmetry between the two subunits, subtle changes in the conformation as a response to the binding of active and inactive forms of ligands and the population distribution of different conformations in equilibrium. These investigations have enabled us to probe the free energy landscape and identify the corresponding conformations in terms of network parameters. In addition, we have also elucidated the variations in the dynamics of water co-ordination to the Zn2+ ion in LuxS and its relation to the rigidity at the active sites.
Conclusions:
In this article, we provide details of a novel method for the identification of conformational changes in the different ligand bound states of the protein, evaluation of ligand-induced free energy changes and the biological relevance of our results in the context of LuxS structure-function. The methodology outlined here is highly generalized to illuminate the linkage between structure and function in any protein of known structure.
Background:
The transient, or permanent, association of proteins to form organized complexes is one of the most common mechanisms of regulation of biological processes. Systematic physico-chemical studies of the binding interfaces have previously shown that a key mechanism for the formation/stabilization of dimers is the steric and chemical complementarity of the two semi-interfaces. The role of the fluctuation dynamics at the interface of the interacting subunits, although expectedly important, proved more elusive to characterize. The aim of the present computational study is to gain insight into salient dynamics-based aspects of protein-protein interfaces.
Results:
The interface dynamics was characterized by means of an elastic network model for 22 representative dimers covering three main interface types. The three groups gather dimers sharing the same interface but with good (type I) or poor (type II) similarity of the overall fold, or dimers sharing only one of the semi-interfaces (type III). The set comprises obligate dimers, which are complexes for which no structural representative of the free form(s) is available. Considerations were accordingly limited to bound and unbound forms of the monomeric subunits of the dimers. We proceeded by first computing the mobility of amino acids at the interface of the bound forms and compare it with the mobility of (i) other surface amino acids (ii) interface amino acids in the unbound forms. In both cases different dynamic patterns were observed across interface types and depending on whether the interface belongs to an obligate or non-obligate complex.
Conclusions:
The comparative investigation indicated that the mobility of amino acids at the dimeric interface is generally lower than for other amino acids at the protein surface. The change in interfacial mobility upon removing "in silico" the partner monomer (unbound form) was next found to be correlated with the interface type, size and obligate nature of the complex. In particular, going from the unbound to the bound forms, the interfacial mobility is noticeably reduced for dimers with type I interfaces, while it is largely unchanged for type II ones. The results suggest that these structurally- and biologically-different types of interfaces are stabilized by different balancing mechanisms between enthalpy and conformational entropy.
Background:
ALG-2 (a gene product of PDCD6) belongs to the penta-EF-hand (PEF) protein family and Ca2+-dependently interacts with various intracellular proteins including mammalian Alix, an adaptor protein in the ESCRT system. Our previous X-ray crystal structural analyses revealed that binding of Ca2+ to EF3 enables the side chain of R125 to move enough to make a primary hydrophobic pocket (Pocket 1) accessible to a short fragment of Alix. The side chain of F122, facing a secondary hydrophobic pocket (Pocket 2), interacts with the Alix peptide. An alternatively spliced shorter isoform, designated ALG-2ΔGF122, lacks Gly121Phe122 and does not bind Alix, but the structural basis of the incompetence has remained to be elucidated.
Results:
We solved the X-ray crystal structure of the PEF domain of ALG-2ΔGF122 in the Ca2+-bound form and compared it with that of ALG-2. Deletion of the two residues shortened α-helix 5 (α5) and changed the configuration of the R125 side chain so that it partially blocked Pocket 1. A wall created by the main chain of 121-GFG-123 and facing the two pockets was destroyed. Surprisingly, however, substitution of F122 with Ala or Gly, but not with Trp, increased the Alix-binding capacity in binding assays. The F122 substitutions exhibited different effects on binding of ALG-2 to other known interacting proteins, including TSG101 (Tumor susceptibility gene 101) and annexin A11. The X-ray crystal structure of the F122A mutant revealed that removal of the bulky F122 side chain not only created an additional open space in Pocket 2 but also abolished inter-helix interactions with W95 and V98 (present in α4) and that α5 inclined away from α4 to expand Pocket 2, suggesting acquirement of more appropriate positioning of the interacting residues to accept Alix.
Conclusions:
We found that the inability of the two-residue shorter ALG-2 isoform to bind Alix is not due to the absence of bulky side chain of F122 but due to deformation of a main-chain wall facing pockets 1 and 2. Moreover, a residue at the position of F122 contributes to target specificity and a smaller side chain is preferable for Alix binding but not favored to bind annexin A11.
Background:
Protein sequence insertions/deletions (indels) can be introduced during evolution or through alternative splicing (AS). Alternative splicing is an important biological phenomenon and is considered as the major means of expanding structural and functional diversity in eukaryotes. Knowledge of the structural changes due to indels is critical to our understanding of the evolution of protein structure and function. In addition, it can help us probe the evolution of alternative splicing and the diversity of functional isoforms. However, little is known about the effects of indels, in particular the ones involving core secondary structures, on the folding of protein structures. The long term goal of our study is to accurately predict the protein AS isoform structures. As a first step towards this goal, we performed a systematic analysis on the structural changes caused by short internal indels through mining highly homologous proteins in Protein Data Bank (PDB).
Results:
We compiled a non-redundant dataset of short internal indels (2-40 amino acids) from highly homologous protein pairs and analyzed the sequence and structural features of the indels. We found that about one third of indel residues are in disordered state and majority of the residues are exposed to solvent, suggesting that these indels are generally located on the surface of proteins. Though naturally occurring indels are fewer than engineered ones in the dataset, there are no statistically significant differences in terms of amino acid frequencies and secondary structure types between the "Natural" indels and "All" indels in the dataset. Structural comparisons show that all the protein pairs with short internal indels in the dataset preserve the structural folds and about 85% of protein pairs have global RMSDs (root mean square deviations) of 2Å or less, suggesting that protein structures tend to be conserved and can tolerate short insertions and deletions. A few pairs with high RMSDs are results of relative domain positions of the proteins, probably due to the intrinsically dynamic nature of the proteins.
Conclusions:
The analysis demonstrated that protein structures have the "plasticity" to tolerate short indels. This study can provide valuable guides in modeling protein AS isoform structures and homologous proteins with indels through placing the indels at the right locations since the accuracy of sequence alignments dictate model qualities in homology modeling.
Background:
Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB) for coplanar aromatic motifs similar to those found in known glycan-binding proteins.
Results:
The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO) enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192) in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry.
Conclusions:
Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.
Background:
Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction.
Results:
We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of ~20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD < 0.5A from the native) as top-ranked, and selecting at least one near-native model in the top-5-ranked models, respectively. Similar effectiveness of the POC method is also found in the decoy sets from membrane protein loops. Furthermore, the POC method outperforms the other popularly-used consensus strategies in model ranking, such as rank-by-number, rank-by-rank, rank-by-vote, and regression-based methods.
Conclusions:
By integrating multiple knowledge- and physics-based scoring functions based on Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set.
Background:
Type III secretion systems are a common virulence mechanism in many Gram-negative bacterial pathogens. These systems use a nanomachine resembling a molecular needle and syringe to provide an energized conduit for the translocation of effector proteins from the bacterial cytoplasm to the host cell cytoplasm for the benefit of the pathogen. Prior to translocation specialized chaperones maintain proper effector protein conformation. The class II chaperone, Invasion plasmid gene (Ipg) C, stabilizes two pore forming translocator proteins. IpgC exists as a functional dimer to facilitate the mutually exclusive binding of both translocators.
Results:
In this study, we present the 3.3 Å crystal structure of an amino-terminally truncated form (residues 10-155, denoted IpgC10-155) of the class II chaperone IpgC from Shigella flexneri. Our structure demonstrates an alternative quaternary arrangement to that previously described for a carboxy-terminally truncated variant of IpgC (IpgC1-151). Specifically, we observe a rotationally-symmetric "head-to- head" dimerization interface that is far more similar to that previously described for SycD from Yersinia enterocolitica than to IpgC1-151. The IpgC structure presented here displays major differences in the amino terminal region, where extended coil-like structures are seen, as opposed to the short, ordered alpha helices and asymmetric dimerization interface seen within IpgC1-151. Despite these differences, however, both modes of dimerization support chaperone activity, as judged by a copurification assay with a recombinant form of the translocator protein, IpaB.
Conclusions:
From primary to quaternary structure, these results presented here suggest that a symmetric dimerization interface is conserved across bacterial class II chaperones. In light of previous data which have described the structure and function of asymmetric dimerization, our results raise the possibility that class II chaperones may transition between asymmetric and symmetric dimers in response to changes in either biochemical modifications (e.g. proteolytic cleavage) or other biological cues. Such transitions may contribute to the broad range of protein-protein interactions and functions attributed to class II chaperones.
Background:
Structural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA) can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information.
Results:
In this work, we present a novel method for predicting two kinds of protein motions in ordered structures. The prediction uses only information from the amino acid sequence. We prepared a dataset of the internal and external motions of segments in many proteins by application of NMA. Subsequently, we analyzed the relation between thermal motion assessed from X-ray crystallographic B-factor and internal/external motions calculated by NMA. Results show that attributes of amino acids related to the internal motion have different features from those related to the B-factors, although those related to the external motion are correlated strongly with the B-factors. Next, we developed a method to predict internal and external motions from amino acid sequences based on the Random Forest algorithm. The proposed method uses information associated with adjacent amino acid residues and secondary structures predicted from the amino acid sequence. The proposed method exhibited moderate correlation between predicted internal and external motions with those calculated by NMA. It has the highest prediction accuracy compared to a naïve model and three published predictors.
Conclusions:
Finally, we applied the proposed method predicting the internal motion to a set of 20 proteins that undergo large conformational change upon protein-protein interaction. Results show significant overlaps between the predicted high internal motion regions and the observed conformational change regions.
Background:
Kinesin motors hydrolyze ATP to produce force and move along microtubules, converting chemical energy into work by a mechanism that is only poorly understood. Key transitions and intermediate states in the process are still structurally uncharacterized, and remain outstanding questions in the field. Perturbing the motor by introducing point mutations could stabilize transitional or unstable states, providing critical information about these rarer states.
Results:
Here we show that mutation of a single residue in the kinesin-14 Ncd causes the motor to release ADP and hydrolyze ATP faster than wild type, but move more slowly along microtubules in gliding assays, uncoupling nucleotide hydrolysis from force generation. A crystal structure of the motor shows a large rotation of the stalk, a conformation representing a force-producing stroke of Ncd. Three C-terminal residues of Ncd, visible for the first time, interact with the central β-sheet and dock onto the motor core, forming a structure resembling the kinesin-1 neck linker, which has been proposed to be the primary force-generating mechanical element of kinesin-1.
Conclusions:
Force generation by minus-end Ncd involves docking of the C-terminus, which forms a structure resembling the kinesin-1 neck linker. The mechanism by which the plus- and minus-end motors produce force to move to opposite ends of the microtubule appears to involve the same conformational changes, but distinct structural linkers. Unstable ADP binding may destabilize the motor-ADP state, triggering Ncd stalk rotation and C-terminus docking, producing a working stroke of the motor.
Background:
Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information.
Results:
In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem.
Conclusions:
Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.
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