BMC Structural Biology最新文献

Malyl-CoA lyase (MCL) is a promiscuous carbon-carbon bond lyase that catalyzes the reversible cleavage of structurally related Coenzyme A (CoA) thioesters. This enzyme plays a crucial, multifunctional role in the 3-hydroxypropionate bi-cycle for autotrophic CO₂ fixation in Chloroflexus aurantiacus. A second, phylogenetically distinct MCL from Rhodobacter sphaeroides is involved in the ethylmalonyl-CoA pathway for acetate assimilation. Both MCLs belong to the large superfamily of CitE-like enzymes, which includes the name-giving β-subunit of citrate lyase (CitE), malyl-CoA thioesterases and other enzymes of unknown physiological function. The CitE-like enzyme superfamily also bears sequence and structural resemblance to the malate synthases. All of these different enzymes share highly conserved catalytic residues, although they catalyze distinctly different reactions: C-C bond formation and cleavage, thioester hydrolysis, or both (the malate synthases).

Here we report the first crystal structures of MCLs from two different phylogenetic subgroups in apo- and substrate-bound forms. Both the C. aurantiacus and the R. sphaeroides MCL contain elaborations on the canonical β₈/α₈ TIM barrel fold and form hexameric assemblies. Upon ligand binding, changes in the C-terminal domains of the MCLs result in closing of the active site, with the C-terminal domain of one monomer forming a lid over and contributing side chains to the active site of the adjacent monomer. The distinctive features of the two MCL subgroups were compared to known structures of other CitE-like superfamily enzymes and to malate synthases, providing insight into the structural subtleties that underlie the functional versatility of these enzymes.

Although the C. aurantiacus and the R. sphaeroides MCLs have divergent primary structures (~37% identical), their tertiary and quaternary structures are very similar. It can be assumed that the C-C bond formation catalyzed by the MCLs occurs as proposed for malate synthases. However, a comparison of the two MCL structures with known malate synthases raised the question why the MCLs are not also able to hydrolyze CoA thioester bonds. Our results suggest the previously proposed reaction mechanism for malate synthases may be incomplete or not entirely correct. Further studies involving site-directed mutagenesis based on these structures may be required to solve this puzzling question.

To understand the effect of the long intracellular loop 3 (ICL3) on the intrinsic dynamics of human β₂-adrenergic receptor, molecular dynamics (MD) simulations were performed on two different models, both of which were based on the inactive crystal structure in complex with carazolol (after removal of carazolol and T4-lysozyme). In the so-called loop model, the ICL3 region that is missing in available crystal structures was modeled as an unstructured loop of 32-residues length, whereas in the clipped model, the two open ends were covalently bonded to each other. The latter model without ICL3 was taken as a reference, which has also been commonly used in recent computational studies. Each model was embedded into POPC bilayer membrane with explicit water and subjected to a 1 μs molecular dynamics (MD) simulation at 310?K.

After around 600?ns, the loop model started a transition to a “very inactive” conformation, which is characterized by a further movement of the intracellular half of transmembrane helix 6 (TM6) towards the receptor core, and a close packing of ICL3 underneath the membrane completely blocking the G-protein’s binding site. Concurrently, the binding site at the extracellular part of the receptor expanded slightly with the Ser207-Asp113 distance increasing to 18?? from 11??, which was further elaborated by docking studies.

The essential dynamics analysis indicated a strong coupling between the extracellular and intracellular parts of the intact receptor, implicating a functional relevance for allosteric regulation. In contrast, no such transition to the “very inactive” state, nor any structural correlation, was observed in the clipped model without ICL3. Furthermore, elastic network analysis using different conformers for the loop model indicated a consistent picture on the specific ICL3 conformational change being driven by global modes.

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units.

Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures.

Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

Certain amino acids in proteins play a critical role in determining their structural stability and function. Examples include flexible regions such as hinges which allow domain motion, and highly conserved residues on functional interfaces which allow interactions with other proteins. Detecting these regions can aid in the analysis and simulation of protein rigidity and conformational changes, and helps characterizing protein binding and docking. We present an analysis of critical residues in proteins using a combination of two complementary techniques. One method performs in-silico mutations and analyzes the protein's rigidity to infer the role of a point substitution to Glycine or Alanine. The other method uses evolutionary conservation to find functional interfaces in proteins.

We applied the two methods to a dataset of proteins, including biomolecules with experimentally known critical residues as determined by the free energy of unfolding. Our results show that the combination of the two methods can detect the vast majority of critical residues in tested proteins.

Our results show that the combination of the two methods has the potential to detect more information than each method separately. Future work will provide a confidence level for the criticalness of a residue to improve the accuracy of our method and eliminate false positives. Once the combined methods are integrated into one scoring function, it can be applied to other domains such as estimating functional interfaces.

Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured.

We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima.

Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions.

Conformational flexibility creates errors in the comparison of protein structures. Even small changes in backbone or sidechain conformation can radically alter the shape of ligand binding cavities. These changes can cause structure comparison programs to overlook functionally related proteins with remote evolutionary similarities, and cause others to incorrectly conclude that closely related proteins have different binding preferences, when their specificities are actually similar. Towards the latter effort, this paper applies protein structure prediction algorithms to enhance the classification of homologous proteins according to their binding preferences, despite radical conformational differences.

Specifically, structure prediction algorithms can be used to "remodel" existing structures against the same template. This process can return proteins in very different conformations to similar, objectively comparable states. Operating on close homologs exploits the accuracy of structure predictions on closely related proteins, but structure prediction is often a nondeterministic process. Identical inputs can generate subtly different models with very different binding cavities that make structure comparison difficult. We present a first method to mitigate such errors, called "medial remodeling", that examines a large number of predicted structures to eliminate extreme models of the same binding cavity.

Our results, on the enolase and tyrosine kinase superfamilies, demonstrate that remodeling can enable proteins in very different conformations to be returned to states that can be objectively compared. Structures that would have been erroneously classified as having different binding preferences were often correctly classified after remodeling, while structures that would have been correctly classified as having different binding preferences almost always remained distinct. The enolase superfamily, which exhibited less sequential diversity than the tyrosine kinase superfamily, was classified more accurately after remodeling than the tyrosine kinases. Medial remodeling reduced errors from models with unusual perturbations that distort the shape of the binding site, enhancing classification accuracy.

This paper demonstrates that protein structure prediction can compensate for conformational variety in the comparison of protein-ligand binding sites. While protein structure prediction introduces new uncertainties into the structure comparison problem, our results indicate that unusual models can be ignored through an analysis of many models, using techniques like medial remodeling. These results point to applications of protein structure comparison that extend beyond existing crystal structures.

Resveratrol, a naturally occurring stilbene, has been categorized as a phytoestrogen due to its ability to compete with natural estrogens for binding to estrogen receptor alpha (ERα) and modulate the biological responses exerted by the receptor. Biological effects of resveratrol (RES) on estrogen receptor alpha (ERα) remain highly controversial, since both estrogenic and anti-estrogenic properties were observed.

Here, we provide insight into the structural basis of the agonist/antagonist effects of RES on ERα ligand binding domain (LBD). Using atomistic simulation, we found that RES bound ERα monomer in antagonist conformation, where Helix 12 moves away from the ligand pocket and orients into the co-activator binding groove of LBD, is more stable than RES bound ERα in agonist conformation, where Helix 12 lays over the ligand binding pocket. Upon dimerization, the agonistic conformation of RES-ERα dimer becomes more stable compared to the corresponding monomer but still remains less stable compared to the corresponding dimer in antagonist conformation. Interestingly, while the binding pocket and the binding contacts of RES to ERα are similar to those of pure agonist diethylstilbestrol (DES), the binding energy is much less and the hydrogen bonding contacts also differ providing clues for the partial agonistic character of RES on ERα.

Our Molecular Dynamics simulation of RES-ERα structures with agonist and antagonist orientations of Helix 12 suggests RES action is more similar to Selective Estrogen Receptor Modulator (SERM) opening up the importance of cellular environment and active roles of co-regulator proteins in a given system. Our study reveals that potential co-activators must compete with the Helix 12 and displace it away from the activator binding groove to enhance the agonistic activity.

Pyridoxal 5′-phosphate (PLP)-dependent enzymes of fold type I, the most studied structural class of the PLP-dependent enzyme superfamily, are known to exist as stand-alone homodimers or homotetramers. These enzymes have been found also embedded in multimodular and multidomain assembly lines involved in the biosynthesis of polyketides (PKS) and nonribosomal peptides (NRPS). The aim of this work is to provide a proteome-wide view of the distribution and characteristics of type I domains covalently integrated in these assemblies in prokaryotes.

An ad-hoc Hidden Markov profile was calculated using a sequence alignment derived from a multiple structural superposition of distantly related PLP-enzymes of fold type I. The profile was utilized to scan the sequence databank and to collect the proteins containing at least one type I domain linked to a component of an assembly line in bacterial genomes. The domains adjacent to a carrier protein were further investigated. Phylogenetic analysis suggested the presence of four PLP-dependent families: Aminotran_3, Beta_elim_lyase and Pyridoxal_deC, occurring mainly within mixed NRPS/PKS clusters, and Aminotran_1_2 found mainly in PKS clusters. Sequence similarity to the reference PLP enzymes with solved structures ranged from 24 to 42% identity. Homology models were built for each representative type I domain and molecular docking simulations with putative substrates were carried out. Prediction of the protein-protein interaction sites evidenced that the surface regions of the type I domains embedded within multienzyme assemblies were different from those of the self-standing enzymes; these structural features appear to be required for productive interactions with the adjacent domains in a multidomain context.

This work provides a systematic view of the occurrence of type I domain within NRPS and PKS assembly lines and it predicts their structural characteristics using computational methods. Comparison with the corresponding stand-alone enzymes highlighted the common and different traits related to various aspects of their structure-function relationship. Therefore, the results of this work, on one hand contribute to the understanding of the functional and structural diversity of the PLP-dependent type I enzymes and, on the other, pave the way to further studies aimed at their applications in combinatorial biosynthesis.

Methionine adenosyltransferases catalyse the synthesis of S-adenosylmethionine, a cofactor abundant in all domains of life. In contrast to the enzymes from bacteria and eukarya that show high sequence similarity, methionine adenosyltransferases from archaea diverge on the amino acid sequence level and only few conserved residues are retained.

We describe the initial characterisation and the crystal structure of the methionine adenosyltransferase from the hyperthermophilic archaeon Thermococcus kodakarensis. As described for other archaeal methionine adenosyltransferases the enzyme is a dimer in solution and shows high temperature stability. The overall structure is very similar to that of the bacterial and eukaryotic enzymes described, with some additional features that might add to the stability of the enzyme. Compared to bacterial and eukaryotic structures, the active site architecture is largely conserved, with some variation in the substrate/product-binding residues. A flexible loop that was not fully ordered in previous structures without ligands in the active side is clearly visible and forms a helix that leaves an entrance to the active site open.

The similar three-dimensional structures of archaeal and bacterial or eukaryotic methionine adenosyltransferases support that these enzymes share an early common ancestor from which they evolved independently, explaining the low similarity in their amino acid sequences. Furthermore, methionine adenosyltransferase from T. kodakarensis is the first structure without any ligands bound in the active site where the flexible loop covering the entrance to the active site is fully ordered, supporting a mechanism postulated earlier for the methionine adenosyltransferase from E. coli. The structure will serve as a starting point for further mechanistic studies and permit the generation of enzyme variants with different characteristics by rational design.