Validation of protein models by a neural network approach

Molecular docking and MD simulations reveal protease inhibitors block the catalytic residues in Prp8 intein of Aspergillus fumigatus: a potential target for antimycotics

Resistance to azoles and amphotericin B especially in Aspergillus fumigatus is a growing concern towards the treatment of invasive fungal infection. At this critical juncture, intein splicing would be a productive, and innovative target to establish therapies against resistant strains. Intein splicing is the central event for the activation of host protein, essential for the growth and survival of various microorganisms including A. fumigatus. The splicing process is a four-step protease-like nucleophilic cascade. Thus, we hypothesise that protease inhibitors would successfully halt intein splicing and potentially restrict the growth of the aforementioned pathogen. Using Rosetta Fold and molecular dynamics simulations, we modelled Prp8 intein structure; resembling classic intein fold with horse shoe shaped splicing domain. To fully comprehend the active site of Afu Prp8 intein, C1, T62, H65, H818, N819 from intein sequences and S820, the first C-extein residue are selected. Molecular docking shows that two FDA-approved drugs, i.e. Lufotrelvir and Remdesivir triphosphate efficiently interact with Prp8 intein from the assortment of 212 protease inhibitors. MD simulation portrayed that Prp8 undergoes conformational change upon ligand binding, and inferred the molecular recognition and stability of the docked complexes. Per-residue decomposition analysis confirms the importance of F: block R802, V803, and Q807 binding pocket in intein splicing domain towards recognition of inhibitors, along with active site residues through strong hydrogen bonds and hydrophobic contacts. However, in vitro and in vivo assays are required to confirm the inhibitory action on Prp8 intein splicing; which may pave the way for the development of new antifungals for A. fumigatus.Communicated by Ramaswamy H. Sarma.

E2 superfamily of ubiquitin-conjugating enzymes: constitutively active or activated through phosphorylation in the catalytic cleft

Protein phosphorylation is a modification that offers a dynamic and reversible mechanism to regulate the majority of cellular processes. Numerous diseases are associated with aberrant regulation of phosphorylation-induced switches. Phosphorylation is emerging as a mechanism to modulate ubiquitination by regulating key enzymes in this pathway. The molecular mechanisms underpinning how phosphorylation regulates ubiquitinating enzymes, however, are elusive. Here, we show the high conservation of a functional site in E2 ubiquitin-conjugating enzymes. In catalytically active E2s, this site contains aspartate or a phosphorylatable serine and we refer to it as the conserved E2 serine/aspartate (CES/D) site. Molecular simulations of substrate-bound and -unbound forms of wild type, mutant and phosphorylated E2s, provide atomistic insight into the role of the CES/D residue for optimal E2 activity. Both the size and charge of the side group at the site play a central role in aligning the substrate lysine toward E2 catalytic cysteine to control ubiquitination efficiency. The CES/D site contributes to the fingerprint of the E2 superfamily. We propose that E2 enzymes can be divided into constitutively active or regulated families. E2s characterized by an aspartate at the CES/D site signify constitutively active E2s, whereas those containing a serine can be regulated by phosphorylation.

Studies on synthetic LuxR solo hybrids

A sub-group of LuxR family of proteins that plays important roles in quorum sensing, a process of cell-cell communication, is widespread in proteobacteria. These proteins have a typical modular structure consisting of N-ter autoinducer binding and C-ter helix-turn-helix (HTH) DNA binding domains. The autoinducer binding domain recognizes signaling molecules which are most often N-acyl homoserine lactones (AHLs) but could also be other novel and yet unidentified molecules. In this study we carried out a series of specific domain swapping and promoter activation experiments as a first step to engineer synthetic signaling modules, taking advantage of the modularity and the versatile/diverse signal specificities of LuxR proteins. In our experiments the N-ter domains from different LuxR homologs were either interchanged or placed in tandem followed by a C-ter domain. The rational design of the hybrid proteins was supported by a structure-based homology modeling studies of three members of the LuxR family (i.e., LasR, RhlR, and OryR being chosen for their unique ligand binding specificities) and of selected chimeras. Our results reveal that these LuxR homologs were able to activate promoter elements that were not their usual targets; we also show that hybrid LuxR proteins retained the ability to recognize the signal specific for their N- ter autoinducer binding domain. However, the activity of hybrid LuxR proteins containing two AHL binding domains in tandem appears to depend on the organization and nature of the introduced domains. This study represents advances in the understanding of the modularity of LuxR proteins and provides additional possibilities to use hybrid proteins in both basic and applied synthetic biology based research.

SInCRe-structural interactome computational resource for Mycobacterium tuberculosis

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding.

Database URL:http://proline.biochem.iisc.ernet.in/sincre

Mutations of C19orf12, coding for a transmembrane glycine zipper containing mitochondrial protein, cause mis-localization of the protein, inability to respond to oxidative stress and increased mitochondrial Ca²⁺

Mutations in C19orf12 have been identified in patients affected by Neurodegeneration with Brain Iron Accumulation (NBIA), a clinical entity characterized by iron accumulation in the basal ganglia. By using western blot analysis with specific antibody and confocal studies, we showed that wild-type C19orf12 protein was not exclusively present in mitochondria, but also in the Endoplasmic Reticulum (ER) and MAM (Mitochondria Associated Membrane), while mutant C19orf12 variants presented a different localization. Moreover, after induction of oxidative stress, a GFP-tagged C19orf12 wild-type protein was able to relocate to the cytosol. On the contrary, mutant isoforms were not able to respond to oxidative stress. High mitochondrial calcium concentration and increased H₂O₂ induced apoptosis were found in fibroblasts derived from one patient as compared to controls. C19orf12 protein is a 17 kDa mitochondrial membrane-associated protein whose function is still unknown. Our in silico investigation suggests that, the glycine zipper motifs of C19orf12 form helical regions spanning the membrane. The N- and C-terminal regions with respect to the transmembrane portion, on the contrary, are predicted to rearrange in a structural domain, which is homologs to the N-terminal regulatory domain of the magnesium transporter MgtE, suggesting that C19orf12 may act as a regulatory protein for human MgtE transporters. The mutations here described affect respectively one glycine residue of the glycine zipper motifs, which are involved in dimerization of transmembrane helices and predicted to impair the correct localization of the protein into the membranes, and one residue present in the regulatory domain, which is important for protein-protein interaction.

Characterizing the pocketome of Mycobacterium tuberculosis and application in rationalizing polypharmacological target selection

Polypharmacology is beginning to emerge as an important concept in the field of drug discovery. However, there are no established approaches to either select appropriate target sets or design polypharmacological drugs. Here, we propose a structural-proteomics approach that utilizes the structural information of the binding sites at a genome-scale obtained through in-house algorithms to characterize the pocketome, yielding a list of ligands that can participate in various biochemical events in the mycobacterial cell. The pocket-type space is seen to be much larger than the sequence or fold-space, suggesting that variations at the site-level contribute significantly to functional repertoire of the organism. All-pair comparisons of binding sites within Mycobacterium tuberculosis (Mtb), pocket-similarity network construction and clustering result in identification of binding-site sets, each containing a group of similar binding sites, theoretically having a potential to interact with a common set of compounds. A polypharmacology index is formulated to rank targets by incorporating a measure of druggability and similarity to other pockets within the proteome. This study presents a rational approach to identify targets with polypharmacological potential along with possible drugs for repurposing, while simultaneously, obtaining clues on lead compounds for use in new drug-discovery pipelines.

Structural Annotation of the Mycobacterium tuberculosis Proteome

Efforts from the TB Structural Genomics Consortium together with those of tuberculosis structural biologists worldwide have led to the determination of about 350 structures, making up nearly a tenth of the pathogen's proteome. Given that knowledge of protein structures is essential to obtaining a high-resolution understanding of the underlying biology, it is desirable to have a structural view of the entire proteome. Indeed, structure prediction methods have advanced sufficiently to allow structural models of many more proteins to be built based on homology modeling and fold recognition strategies. By means of these approaches, structural models for about 2,877 proteins, making up nearly 70% of the Mycobacterium tuberculosis proteome, are available. Knowledge from bioinformatics has made significant inroads into an improved annotation of the M. tuberculosis genome and in the prediction of key protein players that interact in vital pathways, some of which are unique to the organism. Functional inferences have been made for a large number of proteins based on fold-function associations. More importantly, ligand-binding pockets of the proteins are identified and scanned against a large database, leading to binding site-based ligand associations and hence structure-based function annotation. Near proteome-wide structural models provide a global perspective of the fold distribution in the genome. New insights about the folds that predominate in the genome, as well as the fold combinations that make up multidomain proteins, are also obtained. This chapter describes the structural proteome, functional inferences drawn from it, and its applications in drug discovery.

The kiwifruit emerging pathogen Pseudomonas syringae pv. actinidiae does not produce AHLs but possesses three luxR solos

Pseudomonas syringae pv. actinidiae (Psa) is an emerging phytopathogen causing bacterial canker disease in kiwifruit plants worldwide. Quorum sensing (QS) gene regulation plays important roles in many different bacterial plant pathogens. In this study we analyzed the presence and possible role of N-acyl homoserine lactone (AHL) quorum sensing in Psa. It was established that Psa does not produce AHLs and that a typical complete LuxI/R QS system is absent in Psa strains. Psa however possesses three putative luxR solos designated here as PsaR1, PsaR2 and PsaR3. PsaR2 belongs to the sub-family of LuxR solos present in many plant associated bacteria (PAB) that binds and responds to yet unknown plant signal molecules. PsaR1 and PsaR3 are highly similar to LuxRs which bind AHLs and are part of the canonical LuxI/R AHL QS systems. Mutation in all the three luxR solos of Psa showed reduction of in planta survival and also showed additive effect if more than one solo was inactivated in double mutants. Gene promoter analysis revealed that the three solos are not auto-regulated and investigated their possible role in several bacterial phenotypes.

Structural insights into a novel interkingdom signaling circuit by cartography of the ligand-binding sites of the homologous quorum sensing LuxR-family

Recent studies have identified a novel interkingdom signaling circuit, via plant signaling molecules, and a bacterial sub-family of LuxR proteins, bridging eukaryotes and prokaryotes. Indeed pivotal plant-bacteria interactions are regulated by the so called Plant Associated Bacteria (PAB) LuxR solo regulators that, although closely related to the quorum sensing (QS) LuxR family, do not bind or respond to canonical quorum sensing N-acyl homoserine lactones (AHLs), but only to specific host plant signal molecules. The large body of structural data available for several members of the QS LuxR family complexed with different classes of ligands (AHLs and other compounds), has been exploited to dissect the cartography of their regulatory domains through structure-based multiple sequence alignments, structural superimposition and a comparative analysis of the contact residues involved in ligand binding. In the absence of experimentally determined structures of members of the PAB LuxR solos subfamily, an homology model of its prototype OryR is presented, aiming to elucidate the architecture of its ligand-binding site. The obtained model, in combination with the cartography of the regulatory domains of the homologous QS LuxRs, provides novel insights into the 3D structure of its ligand-binding site and unveils the probable molecular determinants responsible for differences in selectivity towards specific host plant signal molecules, rather than to canonical QS compounds.

Functional and structural study of the dimeric inner membrane protein SbmA

SbmA protein has been proposed as a dimeric secondary transporter. The protein is involved in the transport of microcins B17 and J25, bleomycin, proline-rich antimicrobial peptides, antisense peptide phosphorodiamidate morpholino oligomers, and peptide nucleic acids into the Escherichia coli cytoplasm. The sbmA homologue is found in a variety of bacteria, though the physiological role of the protein is hitherto unknown. In this work, we carried out a functional and structural analysis to determine which amino acids are critical for the transport properties of SbmA. We created a set of 15 site-directed sbmA mutants in which single conserved amino acids were replaced by glycine residues. Our work demonstrated that strains carrying the site-directed mutants V102G, F219G, and E276G had a null phenotype for SbmA transport functions. In contrast, strains carrying the single point mutants W19G, W53G, F60G, S69G, N155G, R190, L233G, A344G, T255G, N308G, and R385G showed transport capacities indistinguishable from those of strains harboring a wild-type sbmA. The strain carrying the Y116G mutant exhibited mixed phenotypic characteristics. We also demonstrated that those sbmA mutants with severely impaired transport capacity showed a dominant negative phenotype. Electron microscopy data and in silico three-dimensional (3D) homology modeling support the idea that SbmA forms a homodimeric complex, closely resembling the membrane-spanning region of the ATP-binding cassette transporter family. Direct mapping of the sbmA single point mutants on the protein surface allowed us to explain the observed phenotypic differences in transport ability.

The shape of protein crowders is a major determinant of protein diffusion

As a model for understanding how molecular crowding influences diffusion and transport of proteins in cellular environments, we combined experimental and theoretical approaches to study the diffusion of proteins in highly concentrated protein solutions. Bovine serum albumin and γ-Globulin were chosen as molecular crowders and as tracers. These two proteins are representatives of the main types of plasma protein and have different shapes and sizes. Solutions consisting of one or both proteins were studied. The self-diffusion coefficients of the fluorescently labeled tracer proteins were measured by means of fluorescence correlation spectroscopy at a total protein concentration of up to 400 g/L. γ-Globulin is found to have a stronger influence as a crowder on the tracer self-diffusion coefficient than Bovine serum albumin. Brownian dynamics simulations show that the excluded volume and the shape of the crowding protein have a significantly stronger influence on translational and rotational diffusion coefficients, as well as transient oligomerization, than hydrodynamic or direct interactions. Anomalous subdiffusion, which is not observed at the experimental fluorescence correlation spectroscopy timescales (>100 μs), appears only at very short timescales (<1 μs) in the simulations due to steric effects of the proteins. We envision that the combined experimental and computational approach employed here can be developed to unravel the different biophysical contributions to protein motion and interaction in cellular environments by systematically varying protein properties such as molecular weight, size, shape, and electrostatic interactions.

Structural annotation of Mycobacterium tuberculosis proteome

Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well.

Sub-AQUA: real-value quality assessment of protein structure models

Computational protein tertiary structure prediction has made significant progress over the past years. However, most of the existing structure prediction methods are not equipped with functionality to predict accuracy of constructed models. Knowing the accuracy of a structure model is crucial for its practical use since the accuracy determines potential applications of the model. Here we have developed quality assessment methods, which predict real value of the global and local quality of protein structure models. The global quality of a model is defined as the root mean square deviation (RMSD) and the LGA score to its native structure. The local quality is defined as the distance between the corresponding Calpha positions of a model and its native structure when they are superimposed. Three regression methods are employed to combine different types of quality assessment measures of models, including alignment-level scores, residue-position level scores, atomic-detailed structure level scores and composite scores. The regression models were tested on a large benchmark data set of template-based protein structure models of various qualities. In predicting RMSD and the LGA score, a combination of two terms, length-normalized SPAD, a score that assesses alignment stability by considering suboptimal alignments, and Verify3D normalized by the square of the model length shows a significant performance, achieving 97.1 and 83.6% accuracy in identifying models with an RMSD of <2 and 6 A, respectively. For predicting the local quality of models, we find that a two-step approach, in which the global RMSD predicted in the first step is further combined with the other terms, can dramatically increase the accuracy. Finally, the developed regression equations are applied to assess the quality of structure models of whole E. coli proteome.

A tripeptide deletion in the R2 loop of the class C beta-lactamase enzyme FOX-4 impairs cefoxitin hydrolysis and slightly increases susceptibility to beta-lactamase inhibitors

OBJECTIVES

A natural variant of the AmpC enzyme from Escherichia coli HKY28 with a tripeptide deletion (Gly-286/Ser-287/Asp-288) was recently described. The isolate produced an inhibitor-sensitive AmpC beta-lactamase variant that also conferred higher than usual levels of resistance to ceftazidime in the E. coli host. To demonstrate whether this is true in other class C beta-lactamase enzymes, we deleted the equivalent tripeptide in the FOX-4 plasmid-mediated class C beta-lactamase.

METHODS

By site-directed mutagenesis, we deleted the tripeptide Gly-306/Asn-307/Ser-308 of FOX-4, thus generating FOX-4(DeltaGNS). The enzymes (FOX-4 wild-type and DeltaGNS) were purified and kinetic parameters (kcat, Km, kcat/Km) as well as IC50 values of several beta-lactams were assessed. Modelling studies were also performed.

RESULTS

FOX-4(DeltaGNS) did not increase the catalytic efficiency towards ceftazidime, although it conferred a slight increase in the susceptibility to beta-lactamase inhibitors. There was also a noteworthy decrease in the cefoxitin MIC with the FOX-4(DeltaGNS) mutant (from 512 to 16 mg/L) as well as a 10-fold decrease in kcat/Km towards imipenem, which revealed specific structural features.

CONCLUSIONS

Although deletions in the R2-loop are able to extend the substrate spectrum of class C enzymes, the present results do not confirm this hypothesis in FOX-4. The FOX-4 R2 site would already be wide enough to accommodate antibiotic molecules, and thus any amino acid replacement or deletion at this location would not affect the hydrolytic efficiency towards beta-lactams and would have a less drastic effect on the susceptibility to beta-lactamase inhibitors.

A database for human Y chromosome protein data

The human Y chromosome is the sex determining chromosome. The number of proteins associated with this chromosome is 196 and 107 of the 196 proteins have yet not been characterised. Here, we describe the analysis of these 107 proteins by computing various physicochemical properties using sequence and predicted structural data to elucidate molecular function. We present the derived data in the form a form a database made freely available for download, review, refinement and update.

AVAILABILITY

http://puratham.googlepages.com/ or http://puratham.googlepages.com/ftpconnection.

Protein structure prediction and model quality assessment

Protein structures have proven to be a crucial piece of information for biomedical research. Of the millions of currently sequenced proteins only a small fraction is experimentally solved for structure and the only feasible way to bridge the gap between sequence and structure data is computational modeling. Half a century has passed since it was shown that the amino acid sequence of a protein determines its shape, but a method to translate the sequence code reliably into the 3D structure still remains to be developed. This review summarizes modern protein structure prediction techniques with the emphasis on comparative modeling, and describes the recent advances in methods for theoretical model quality assessment.