CLICK--topology-independent comparison of biomolecular 3D structures

Computational Design of Potent and Selective d-Peptide Agonists of the Glucagon-like Peptide-2 Receptor

Here, we designed three d-GLP-2 agonists that activated the glucagon-like peptide-2 receptor (GLP-2R) cyclic adenosine monophosphate (cAMP) accumulation without stimulating the glucagon-like peptide-1 receptor (GLP-1R). All the d-GLP-2 agonists increased the protein kinase B phosphorylated (p-AKT) expression levels in a time- and concentration-dependent manner in vitro. The most effective d-GLP-2 analogue boosted the AKT phosphorylation 2.28 times more effectively compared to the native l-GLP-2. The enhancement in the p-AKT levels induced by the d-GLP-2 analogues could be explained by GLP-2R's more prolonged activation, given that the d-GLP-2 analogues induce a lower β-arrestin recruitment. The higher stability to protease degradation of our d-GLP-2 agonists helps us envision their potential applications in enhancing intestinal absorption and treating inflammatory bowel illness while lowering the high dosage required by the current treatments.

Unravelling structural, functional, evolutionary and genetic basis of SWEET transporters regulating abiotic stress tolerance in maize

Sugars Will Eventually be Exported Transporters (SWEETs) are the novel sugar transporters widely distributed among living systems. SWEETs play a crucial role in various bio-physiological processes, viz., plant developmental, nectar secretion, pollen development, and regulation of biotic and abiotic stresses, in addition to their prime sugar-transporting activity. Thus, in-depth structural, evolutionary, and functional characterization of maize SWEET transporters was performed for their utility in maize improvement. The mining of SWEET genes in the latest maize genome release (v.5) showed an uneven distribution of 20 ZmSWEETs. The comprehensive structural analyses and docking of ZmSWEETs with four sugars, viz., fructose, galactose, glucose, and sucrose, revealed frequent amino acid residues forming hydrogen (asparagine, valine, serine) and hydrophobic (tryptophan, glycine, and phenylalanine) interactions. Evolutionary analyses of SWEETs showed a mixed lineage with 50-100 % commonality of ortho-groups and -sequences evolved under strong purifying selection (Ka/Ks < 0.5). The duplication analysis showed non-functionalization (ZmSWEET18 in B73) and neo- and sub-functionalization (ZmSWEET3, ZmSWEET6, ZmSWEET9, ZmSWEET19, and ZmSWEET20) events in maize. Functional analyses of ZmSWEET genes through co-expression, in silico expression and qRT-PCR assays showed the relevance of ZmSWEETs expression in regulating drought, heat, and waterlogging stress tolerances in maize. The first ever ZmSWEET-regulatory network revealed 286 direct (ZmSWEET-TF: 140 ZmSWEET-miRNA: 146) and 1226 indirect (TF-TF: 597; TF-miRNA: 629) edges. The present investigation has given new insights into the complex transcriptional and post-transcriptional regulation and the regulatory and functional relevance of ZmSWEETs in assigning stress tolerance in maize.

Genome-Wide Identification, Characterization and Expression Profiling of Potato (Solanum tuberosum) Frataxin (FH) Gene

Frataxin (FH) plays a crucial role in the biogenesis of mitochondria and the regulation of iron in the cells of various organisms. However, there has been very little research on FH in plants. In this study, the potato FH gene (StFH) was identified and characterized using a genome-wide approach, and its sequence was compared to those of FH genes from Arabidopsis, rice, and maize. The FH genes were found to have a lineage-specific distribution and were more conserved in monocots than in dicots. While multiple copies of FH genes have been reported in some species, including plants, only one isoform of FH was found in potato. The expression of StFH in leaves and roots was analyzed under two different abiotic stress conditions, and the results showed that StFH was upregulated more in leaves and that its expression levels increased with the severity of the stress. This is the first study to examine the expression of an FH gene under abiotic stress conditions.

The structure of the human LACTB filament reveals the mechanisms of assembly and membrane binding

Mitochondria are complex organelles that play a central role in metabolism. Dynamic membrane-associated processes regulate mitochondrial morphology and bioenergetics in response to cellular demand. In tumor cells, metabolic reprogramming requires active mitochondrial metabolism for providing key metabolites and building blocks for tumor growth and rapid proliferation. To counter this, the mitochondrial serine beta-lactamase-like protein (LACTB) alters mitochondrial lipid metabolism and potently inhibits the proliferation of a variety of tumor cells. Mammalian LACTB is localized in the mitochondrial intermembrane space (IMS), where it assembles into filaments to regulate the efficiency of essential metabolic processes. However, the structural basis of LACTB polymerization and regulation remains incompletely understood. Here, we describe how human LACTB self-assembles into micron-scale filaments that increase their catalytic activity. The electron cryo-microscopy (cryoEM) structure defines the mechanism of assembly and reveals how highly ordered filament bundles stabilize the active state of the enzyme. We identify and characterize residues that are located at the filament-forming interface and further show that mutations that disrupt filamentation reduce enzyme activity. Furthermore, our results provide evidence that LACTB filaments can bind lipid membranes. These data reveal the detailed molecular organization and polymerization-based regulation of human LACTB and provide new insights into the mechanism of mitochondrial membrane organization that modulates lipid metabolism.

Insights into the capsid structure of banana bunchy top virus

Banana is the major staple food crop for approximately 400 million people. Bunchy top disease of banana is one of the most devastating diseases caused by banana bunchy top virus (BBTV), which results in stunting of plants, bunchy appearance of leaves and a significant loss of yield. While many isolates of BBTV from various regions of India have been characterized by different groups, no structural study exists for this important virus. To bridge this gap, the pET28a clone of the coat protein (CP) gene from BBTV isolate of Hill banana grown in lower Pulney Hills (Virupakshi) of Tamilnadu was expressed in BL21 (DE3) pLysS. Purification of the CP was achieved by Ni-NTA affinity chromatography. In vitro capsid assembly studied using sucrose density gradient centrifugation suggested that the CP did not assemble as a virus-like particle (VLP), but remained as smaller oligomers. Studies using dynamic light scattering (DLS) indicate that the purified protein is poly-dispersed, represented majorly as pentamers. Homology modeling studies provided useful insights into the probable fold of the CP suggesting that it is a β-sandwich, similar to that seen in the majority of plant viruses. In silico capsid reconstruction aided the understanding of the quaternary organization of subunits in the capsid and their molecular interactions. The location of the aphid-binding EAG motif was identified on the surface loops close to the pentameric axis indicating its role in vector-mediated transmission. Comparison with the CP and capsid structure of geminiviruses provided useful insights into the mode of nucleic acid binding and the role of genome during capsid assembly.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03204-4.

Mitochondrial iron transporter (MIT) gene in potato (Solanum tuberosum): comparative bioinformatics, physiological and expression analyses in response to drought and salinity

Mitochondrial iron transporter (MIT) genes are essential for mitochondrial acquisition/import of iron and vital to proper functioning of mitochondria. Unlike other organisms, research on the MITs in plants is limited. The present study provides comparative bioinformatics assays for the potato MIT gene (StMIT) as well as gene expression analyses. The phylogenetic analyses revealed monocots-dicot divergence in MIT proteins and it was also found clade specific motif diversity. In addition, docking analyses indicated that Asp172 and Gly100 residues to be identified as the closest residues binding to ferrous iron. The percentage of structure overlap of the StMIT 3D protein model with Arabidopsis, maize and rice MIT proteins was found between 80.18% and 85.71%. The transcript analyses exhibited that the expression of StMIT was triggered under drought and salinity stresses. The findings of the present study would provide valuable leads for further studies targeting specifically the MIT gene and generally the plant iron metabolism.

AllerCatPro 2.0: a web server for predicting protein allergenicity potential

Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict protein allergenicity potential with better accuracy than other computational methods and new features that help assessors making informed decisions. AllerCatPro 2.0 predicts the similarity between input proteins using both their amino acid sequences and predicted 3D structures towards the most comprehensive datasets of reliable proteins associated with allergenicity. These datasets currently include 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens with manual expert curation from the databases of WHO/International Union of Immunological Societies (IUIS), Comprehensive Protein Allergen Resource (COMPARE), Food Allergy Research and Resource Program (FARRP), UniProtKB and Allergome. Various examples of profilins, autoimmune allergens, low allergenic proteins, very large proteins, and nucleotide input sequences showcase the utility of AllerCatPro 2.0 for predicting protein allergenicity potential. The AllerCatPro 2.0 web server is freely accessible at https://allercatpro.bii.a-star.edu.sg.

Analysis of NIA and GSNOR family genes and nitric oxide homeostasis in response to wheat-leaf rust interaction

Nitric oxide (NO) modulates plant response to biotic and abiotic stresses by S-nitrosylation-mediated protein post-translational modification. Nitrate reductase (NR) and S-nitrosoglutathione reductase (GSNOR) enzymes are essential for NO synthesis and the maintenance of Nitric oxide/S-nitroso glutathione (NO/GSNO) homeostasis, respectively. S-nitrosoglutathione, formed by the S-nitrosylation reaction of NO with glutathione, plays a significant physiological role as the mobile reservoir of NO. The genome-wide analysis identified nine NR (NIA) and three GSNOR genes in the wheat genome. Phylogenic analysis revealed that the nine NIA genes +were clustered into four groups and the 3 GSNORs into two groups. qRT-PCR expression profiling of NIAs and GSNORs was done in Chinese spring (CS), a leaf rust susceptible wheat line showing compatible interaction, and Transfer (TR), leaf rust-resistant wheat line showing incompatible interaction, post-inoculation with leaf rust pathotype 77-5 (121-R-63). All the NIA genes showed upregulation during incompatible interaction in comparison with the compatible reaction. The GSNOR genes showed a variable pattern of expression: the TaGSNOR1 showed little change, whereas TaGSNOR2 showed higher expression during the incompatible response. TaGSNOR3 showed a rise of expression both in compatible and incompatible reactions. Before inoculation and after 72 h of pathogen inoculation, NO localization was studied in both compatible and incompatible reactions. The S-nitrosothiol accumulation, NR, and glutathione reductase activity showed a consistent increase in the incompatible interactions. The results demonstrate that both NR and GSNOR plays significant role in defence against the leaf rust pathogen in wheat by modulating NO homeostasis or signalling.

Computational Design of Potent D-Peptide Inhibitors of SARS-CoV-2

Blocking the association between the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor-binding domain (RBD) and the human angiotensin-converting enzyme 2 (ACE2) is an attractive therapeutic approach to prevent the virus from entering human cells. While antibodies and other modalities have been developed to this end, d-amino acid peptides offer unique advantages, including serum stability, low immunogenicity, and low cost of production. Here, we designed potent novel D-peptide inhibitors that mimic the ACE2 α1-binding helix by searching a mirror-image version of the PDB. The two best designs bound the RBD with affinities of 29 and 31 nM and blocked the infection of Vero cells by SARS-CoV-2 with IC50 values of 5.76 and 6.56 μM, respectively. Notably, both D-peptides neutralized with a similar potency the infection of two variants of concern: B.1.1.7 and B.1.351 in vitro. These potent D-peptide inhibitors are promising lead candidates for developing SARS-CoV-2 prophylactic or therapeutic treatments.

ATG8 is conserved between Saccharomyces cerevisiae and psychrophilic, polar-collected fungi

Autophagy is a conserved catabolic process by which eukaryotic cells respond to stress by targeting damaged or unneeded molecules or organelles for sequestration into specialized vesicles known as autophagosomes. Autophagosomes ultimately facilitate the digestion and recycling of their contents by fusing with the degradative organelle of the cell. Studies of the budding yeast Saccharomyces cerevisiae have revealed various types of stress that can regulate autophagy, including starvation and extreme temperatures. While autophagy has not yet been directly shown to confer the ability to survive extreme cold or freeze-thaw stress in yeast, upregulation of autophagy has been directly implicated in the ability of arctic insects to survive cold temperatures. We are interested in investigating the potential role of autophagy in polar habitat survival by cold-loving (psychrophilic) yeast like Mrakia blollopsis. To begin to examine the conservation of Atg machinery in polar-collected yeast, we focused on Atg8, a small, ubiquitin-like protein that plays an important role in autophagy. We report that Atg8 is conserved between S. cerevisiae and polar-collected yeast, using Atg8 from Mrakia blollopsis (strain TGK1-2) as an example. This study represents the first direct examination of autophagy machinery conservation across mesophilic and psychrophilic species of yeast.

Temperature-Dependent Low-Frequency Modes in the Active Site of Bovine Carbonic Anhydrase II Probed by 2D-IR Spectroscopy

Enzyme catalysis achieves tremendous rate accelerations. Enzyme reaction centers provide a constraint geometry that preferentially binds an activated form of the substrate and thus lowers the energy barrier. However, this transition state picture neglects the flexibility of proteins and its role in enzymatic catalysis. Especially for proton transfer reactions, it has been suggested that motions of the protein modulate the donor-acceptor distance and prepare a tunneling-ready state. We report the detection of frequency fluctuations of an azide anion (N₃^-) bound in the active site of the protein carbonic anhydrase II, where a low-frequency mode of the protein has been proposed to facilitate proton transfer over two water molecules during the catalyzed reaction. 2D-IR spectroscopy resolves an underdamped low-frequency mode at about 1 THz (30 cm^-1). We find its frequency to be viscosity- and temperature-dependent and to decrease by 6 cm^-1 between 230 and 320 K, reporting the softening of the mode's potential.

Genome-wide identification of serine acetyltransferase (SAT) gene family in rice (Oryza sativa) and their expressions under salt stress

BACKGROUND

Assimilation of sulfur to cysteine (Cys) occurs in presence of serine acetyltransferase (SAT). Drought and salt stresses are known to be regulated by abscisic acid, whose biosynthesis is limited by Cys. Cys is formed by cysteine synthase complex depending on SAT and OASTL enzymes. Functions of some SAT genes were identified in Arabidopsis; however, it is not known how SAT genes are regulated in rice (Oryza sativa) under salt stress.

METHODS AND RESULTS

Sequence, protein domain, gene structure, nucleotide, phylogenetic, selection, gene duplication, motif, synteny, digital expression and co-expression, secondary and tertiary protein structures, and binding site analyses were conducted. The wet-lab expressions of OsSAT genes were also tested under salt stress. OsSATs have underwent purifying selection. Segmental and tandem duplications may be driving force of structural and functional divergences of OsSATs. The digital expression analyses of OsSATs showed that jasmonic acid (JA) was the only hormone inducing the expressions of OsSAT1;1, OsSAT2;1, and OsSAT2;2 whereas auxin and ABA only triggered OsSAT1;1 expression. Leaf blade is the only plant organ where all OsSATs but OsSAT1;1 were expressed. Wet-lab expressions of OsSATs indicated that OsSAT1;1, OsSAT1;2 and OsSAT1;3 genes were upregulated at different exposure times of salt stress.

CONCLUSIONS

OsSAT1;1, expressed highly in rice roots, may be a hub gene regulated by cross-talk of JA, ABA and auxin hormones. The cross-talk of the mentioned hormones and the structural variations of OsSAT proteins may also explain the different responses of OsSATs to salt stress.

Cloning, characterization and expression of a gene encoding endo-1, 4- β-xylanase from the fungus Termitomyces clypeatus

Enzymatic degradation of hemi-cellulosic substrates has gained plenty of industrial attentions recently. Complete enzymatic degradation of complex and recalcitrant hemicellulose requires an enzymatic cocktail consisting primarily of endo-1,4-β-xylanase (xyl), β-xylosidase, arabinofuranosidase etc. This article reports, for the first time, the identification, cloning, expression and partial characterization of a potent endo-1,4- β-xylanase gene (pxyl) from the mushroom Termitomyces clypeatus (TC) in E. coli and S. cerevisiae. The cDNA for pxyl was found to be 678 bp that in turn gives rise to a precursor protein (Pxyl) of 225 amino acids long when cloned in prokaryotic expression vector. To characterize additionally, the cDNA was also expressed in S. cerevisiae. Bioinformatics study predicted that the Pxyl contains a 19 amino acid long leader peptide that enables post translational modifications including glycosylation as well as its efficient secretion in the medium. The recombinant protein has been found to be a member of GH11 family containing two distant glutamic acids as catalytic residues. This report describes yet another new and potent source of xylanase for commercial exploitation by industry in future.

Computational generation of proteins with predetermined three-dimensional shapes using ProteinSolver

Computational generation of new proteins with a predetermined three-dimensional shape and computational optimization of existing proteins while maintaining their shape are challenging problems in structural biology. Here, we present a protocol that uses ProteinSolver, a pre-trained graph convolutional neural network, to quickly generate thousands of sequences matching a specific protein topology. We describe computational approaches that can be used to evaluate the generated sequences, and we show how select sequences can be validated experimentally. For complete details on the use and execution of this protocol, please refer to Strokach et al. (2020).

Full-length de novo protein structure determination from cryo-EM maps using deep learning

MOTIVATION

Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-EM maps. However, building accurate models for the EM maps at 3-5 Å resolution remains a challenging and time-consuming process. With the rapid growth of deposited EM maps, there is an increasing gap between the maps and reconstructed/modeled 3-dimensional (3D) structures. Therefore, automatic reconstruction of atomic-accuracy full-atomstructures fromEMmaps is pressingly needed.

RESULTS

We present a semi-automatic de novo structure determination method using a deep learningbased framework, named as DeepMM, which builds atomic-accuracy all-atom models from cryo-EM maps at near-atomic resolution. In our method, the main-chain and Cα positions as well as their amino acid and secondary structure types are predicted in the EM map using Densely Connected Convolutional Networks. DeepMM was extensively validated on 40 simulated maps at 5 Å resolution and 30 experimental maps at 2.6-4.8 Å resolution as well as an EMDB-wide data set of 2931 experimental maps at 2.6-4.9 Å resolution, and compared with state-of-the-art algorithms including RosettaES, MAINMAST, and Phenix. Overall, our DeepMM algorithm obtained a significant improvement over existing methods in terms of both accuracy and coverage in building full-length protein structures on all test sets, demonstrating the efficacy and general applicability of DeepMM.

AVAILABILITY

http://huanglab.phys.hust.edu.cn/DeepMM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The miRISC component AGO2 has multiple binding sites for Nup358 SUMO-interacting motif

Micro-RNA mediated suppression of mRNA translation represents a major regulatory mode of post-transcriptional gene expression. Recently, the nucleoporin Nup358 was shown to interact with AGO protein, a key component of miRNA-induced silencing complex (miRISC), and facilitate the coupling of miRISC with target mRNA. Previous results suggested that SUMO-interacting motifs (SIMs) present on Nup358 mediate interaction with AGO protein. Here we show that Nup358-SIM has multiple interacting regions on AGO2, specifically within the N, PAZ and MID domains, with an affinity comparable to SIM-SUMO1 interaction. The study also unraveled specific residues involved in the interaction of AGO2 with miRNA-loading components such as Dicer and HSP90. Collectively, the results support the conclusion that multiple SIMs contribute to the association of Nup358 with AGO2.

An Insight into Oligopeptide Transporter 3 (OPT3) Family Proteins

BACKGROUND

OPT3s are involved in the transport of Fe from xylem to phloem, in loading Fe into phloem, and in the transmission of shoot-to-root iron signaling. Yet, apart from Arabidopsis, little is known about these transporters'functions in other plant species.

OBJECTIVE

OPT3 proteins of several plant species were characterized using bioinformatical tools. Also, a probable Fe chelating protein, GSH, was used in docking analyses to shed light on the interactions of ligand binding sites of OPT3s.

METHODS

The multiple sequence alignment (MSA) analysis, protein secondary and tertiary structure analyses, molecular phylogeny analysis, transcription factor binding site analyses, co-expression and docking analyses were performed using up-to-date bioinformatical tools.

RESULTS

All OPT3s in this study appear to be transmembrane proteins. They appear to have broad roles and substrate specificities in different metabolic processes. OPT3 gene structures were highly conserved. Promoter analysis showed that bZIP, WRKY, Dof and AT-Hook Transcription factors (TFs) may regulate the expression of OPT3 genes. Consequently, they seemed to be taking part in both biotic and abiotic stress responses as well as growth and developmental processes.

CONCLUSION

The results showed that OPT3 proteins are involved in ROS regulation, plant stress responses, and basal pathogen resistance. They have species-specific roles in biological processes. Lastly, the transport of iron through OPT3s may occur with GSH according to the binding affinity results of the docking analyses.

Unveiling the binding mode of perfluorooctanoic acid to human serum albumin

Perfluorooctanoic acid (PFOA) is a toxic compound that is absorbed and distributed throughout the body by noncovalent binding to serum proteins such as human serum albumin (hSA). Though the interaction between PFOA and hSA has been already assessed using various analytical techniques, a high resolution and detailed analysis of the binding mode is still lacking. We report here the crystal structure of hSA in complex with PFOA and a medium-chain saturated fatty acid (FA). A total of eight distinct binding sites, four occupied by PFOAs and four by FAs, have been identified. In solution binding studies confirmed the 4:1 PFOA-hSA stoichiometry and revealed the presence of one high and three low affinity binding sites. Competition experiments with known hSA-binding drugs allowed locating the high affinity binding site in sub-domain IIIA. The elucidation of the molecular basis of the interaction between PFOA and hSA might provide not only a better assessment of the absorption and elimination mechanisms of these compounds in vivo but also have implications for the development of novel molecular receptors for diagnostic and biotechnological applications.

Methods for Molecular Modelling of Protein Complexes

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular complexes.

GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins

Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable.

Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment.

Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues.

Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.

Structural basis of self-assembly in the lipid-binding domain of mycobacterial polar growth factor Wag31

Wag31, or DivIVA, is an essential protein and a drug target in the human pathogen Mycobacterium tuberculosis that self-assembles at the negatively curved membrane surface to form a higher-order structural scaffold, maintains rod-shaped cellular morphology and localizes key cell-wall synthesizing enzymes at the pole for exclusive polar growth. The crystal structure of the N-terminal lipid-binding domain of mycobacterial Wag31 was determined at 2.3 Å resolution. The structure revealed a highly polar surface lined with several conserved charged residues that suggest probable sites for interactions with membrane lipids. Crystal-packing analysis revealed a previously unseen 'dimer-of-dimers' assembly state of N-terminal Wag31, which is formed by antiparallel stacking of two coiled-coil dimers. Size-exclusion column-chromatography-coupled small-angle solution X-ray scattering data revealed a tetrameric form as a major assembly state of N-terminal Wag31 in solution, further supporting the crystal structure. The results suggest that, in addition to lipid binding, the N-terminal Wag31 can participate in self-assembly to form filamentous structures. Plausible models of linear self-assembly and branching of Wag31 filaments consistent with available data are suggested.

Human Single-chain Variable Fragments Neutralize Pseudomonas aeruginosa Quorum Sensing Molecule, 3O-C12-HSL, and Prevent Cells From the HSL-mediated Apoptosis

The quorum sensing (QS) signaling molecule, N-(3-oxododecanoyl)-L-homoserine lactone (3O-C12-HSL), contributes to the pathogenesis of Pseudomonas aeruginosa by regulating expression of the bacterial virulence factors that cause intense inflammation and toxicity in the infected host. As such, the QS molecule is an attractive therapeutic target for direct-acting inhibitors. Several substances, both synthetic and naturally derived products, have shown effectiveness against detrimental 3O-C12-HSL activity. Unfortunately, these compounds are relatively toxic to mammalian cells, which limits their clinical application. In this study, fully human single-chain variable fragments (HuscFvs) that bind to P. aeruginosa haptenic 3O-C12-HSL were generated based on the principle of antibody polyspecificity and molecular mimicry of antigenic molecules. The HuscFvs neutralized 3O-C12-HSL activity and prevented mammalian cells from the HSL-mediated apoptosis, as observed by Annexin V/PI staining assay, sub-G1 arrest population investigation, transmission electron microscopy for ultrastructural morphology of mitochondria, and confocal microscopy for nuclear condensation and DNA fragmentation. Computerized homology modeling and intermolecular docking predicted that the effective HuscFvs interacted with several regions of the bacterially derived ligand that possibly conferred neutralizing activity. The effective HuscFvs should be tested further in vitro on P. aeruginosa phenotypes as well as in vivo as a sole or adjunctive therapeutic agent against P. aeruginosa infections, especially in antibiotic-resistant cases.

AllerCatPro-prediction of protein allergenicity potential from the protein sequence

Motivation

Due to the risk of inducing an immediate Type I (IgE-mediated) allergic response, proteins intended for use in consumer products must be investigated for their allergenic potential before introduction into the marketplace. The FAO/WHO guidelines for computational assessment of allergenic potential of proteins based on short peptide hits and linear sequence window identity thresholds misclassify many proteins as allergens.

Results

We developed AllerCatPro which predicts the allergenic potential of proteins based on similarity of their 3D protein structure as well as their amino acid sequence compared with a data set of known protein allergens comprising of 4180 unique allergenic protein sequences derived from the union of the major databases Food Allergy Research and Resource Program, Comprehensive Protein Allergen Resource, WHO/International Union of Immunological Societies, UniProtKB and Allergome. We extended the hexamer hit rule by removing peptides with high probability of random occurrence measured by sequence entropy as well as requiring 3 or more hexamer hits consistent with natural linear epitope patterns in known allergens. This is complemented with a Gluten-like repeat pattern detection. We also switched from a linear sequence window similarity to a B-cell epitope-like 3D surface similarity window which became possible through extensive 3D structure modeling covering the majority (74%) of allergens. In case no structure similarity is found, the decision workflow reverts to the old linear sequence window rule. The overall accuracy of AllerCatPro is 84% compared with other current methods which range from 51 to 73%. Both the FAO/WHO rules and AllerCatPro achieve highest sensitivity but AllerCatPro provides a 37-fold increase in specificity.

Availability and implementation

https://allercatpro.bii.a-star.edu.sg/

Supplementary information

Supplementary data are available at Bioinformatics online.

Ammonium transporter 1 (AMT1) gene family in tomato (Solanum lycopersicum L.): Bioinformatics, physiological and expression analyses under drought and salt stresses

Nitrogen (N) is an essential macronutrient for plants, and mainly taken from the soil as ammonium (NH⁺⁴). It is particularly transported into the plants by AMmonium Transporters (AMTs), which are plasma membrane proteins. In the present study, genome-wide identification, physiological and expression analyses of tomato (Solanum lycopersicum L.) ammonium transporters 1 (SlAMT1) genes under drought and salt stresses were performed. Sequence analyses revealed the presence of variations in SlAMT1s at nucleotide and protein levels. While all the SlAMT1s comprise an ammonium transporter domain (PF00909), the numbers of their transmembrane helices were found to be diverse. Digital expression analyses proved that SlAMT1-3 gene had different expression patterns compared to the others, suggesting its functional diversities. The expression analyses revealed that SlAMT1 genes were 0.16 and 5.94 -fold down-regulated under drought and salt stresses, respectively. The results suggested that expression of SlAMT1 genes were adversely affected by abiotic stress conditions.

Unraveling virus relationships by structure-based phylogenetic classification

Delineation of the intricacies of protein function from macromolecular structure constitutes a continual obstacle in the study of cell and pathogen biology. Structure-based phylogenetic analysis has emerged as a powerful tool for addressing this challenge, allowing the detection and quantification of conserved architectural properties between proteins, including those with low or no detectable sequence homology. With a focus on viral protein structure, we highlight how a number of investigations have utilized this powerful method to infer common functionality and ancestry.

Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design

Rab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.

Extreme divergence between one-to-one orthologs: the structure of N15 Cro bound to operator DNA and its relationship to the λ Cro complex

The gene cro promotes lytic growth of phages through binding of Cro protein dimers to regulatory DNA sites. Most Cro proteins are one-to-one orthologs, yet their sequence, structure and binding site sequences are quite divergent across lambdoid phages. We report the cocrystal structure of bacteriophage N15 Cro with a symmetric consensus site. We contrast this complex with an orthologous structure from phage λ, which has a dissimilar binding site sequence and a Cro protein that is highly divergent in sequence, dimerization interface and protein fold. The N15 Cro complex has less DNA bending and smaller DNA-induced changes in protein structure. N15 Cro makes fewer direct contacts and hydrogen bonds to bases, relying mostly on water-mediated and Van der Waals contacts to recognize the sequence. The recognition helices of N15 Cro and λ Cro make mostly nonhomologous and nonanalogous contacts. Interface alignment scores show that half-site binding geometries of N15 Cro and λ Cro are less similar to each other than to distantly related CI repressors. Despite this divergence, the Cro family shows several code-like protein–DNA sequence covariations. In some cases, orthologous genes can achieve a similar biological function using very different specific molecular interactions.

Structural and ligand binding analyses of the periplasmic sensor domain of RsbU in Chlamydia trachomatis support a role in TCA cycle regulation

Chlamydia trachomatis is an obligate intracellular bacteria that undergo dynamic morphologic and physiologic conversions upon gaining an access to a eukaryotic cell. These conversions likely require the detection of key environmental conditions and regulation of metabolic activity. Chlamydia encodes homologs to proteins in the Rsb phosphoregulatory partner-switching pathway, best described in Bacillus subtilis. ORF CT588 has a strong sequence similarity to RsbU cytoplasmic phosphatase domain but also contains a unique periplasmic sensor domain that is expected to control the phosphatase activity. A 1.7 Å crystal structure of the periplasmic domain of the RsbU protein from C. trachomatis (PDB 6MAB) displays close structural similarity to DctB from Vibrio and Sinorhizobium. DctB has been shown, both structurally and functionally, to specifically bind to the tricarboxylic acid (TCA) cycle intermediate succinate. Surface plasmon resonance and differential scanning fluorimetry of TCA intermediates and potential metabolites from a virtual screen of RsbU revealed that alpha-ketoglutarate, malate and oxaloacetate bound to the RsbU periplasmic domain. Substitutions in the putative binding site resulted in reduced binding capabilities. An RsbU null mutant showed severe growth defects which could be restored through genetic complementation. Chemical inhibition of ATP synthesis by oxidative phosphorylation phenocopied the growth defect observed in the RsbU null strain. Altogether, these data support a model with the Rsb system responding differentially to TCA cycle intermediates to regulate metabolism and key differentiation processes.

Simulations of mutant p53 DNA binding domains reveal a novel druggable pocket

The DNA binding domain (DBD) of the tumor suppressor p53 is the site of several oncogenic mutations. A subset of these mutations lowers the unfolding temperature of the DBD. Unfolding leads to the exposure of a hydrophobic β-strand and nucleates aggregation which results in pathologies through loss of function and dominant negative/gain of function effects. Inspired by the hypothesis that structural changes that are associated with events initiating unfolding in DBD are likely to present opportunities for inhibition, we investigate the dynamics of the wild type (WT) and some aggregating mutants through extensive all atom explicit solvent MD simulations. Simulations reveal differential conformational sampling between the WT and the mutants of a turn region (S6-S7) that is contiguous to a known aggregation-prone region (APR). The conformational properties of the S6-S7 turn appear to be modulated by a network of interacting residues. We speculate that changes that take place in this network as a result of the mutational stress result in the events that destabilize the DBD and initiate unfolding. These perturbations also result in the emergence of a novel pocket that appears to have druggable characteristics. FDA approved drugs are computationally screened against this pocket.

AppA: a web server for analysis, comparison, and visualization of contact residues and interfacial waters of antibody-antigen structures and models

The study of contact residues and interfacial waters of antibody–antigen (Ab-Ag) structures could help in understanding the principles of antibody–antigen interactions as well as provide guidance for designing antibodies with improved affinities. Given the rapid pace with which new antibody–antigen structures are deposited in the protein databank (PDB), it is crucial to have computational tools to analyze contact residues and interfacial waters, and investigate them at different levels. In this study, we have developed AppA, a web server that can be used to analyze and compare 3D structures of contact residues and interfacial waters of antibody–antigen complexes. To the best of our knowledge, this is the first web server for antibody–antigen structures equipped with the capability for dissecting the contributions of interfacial water molecules, hydrogen bonds, hydrophobic interactions, van der Waals interactions and ionic interactions at the antibody–antigen interface, and for comparing the structures and conformations of contact residues. Various examples showcase the utility of AppA for such analyses and comparisons that could help in the understanding of antibody–antigen interactions and suggest mutations of contact residues to improve affinities of antibodies. The AppA web server is freely accessible at http://mspc.bii.a-star.edu.sg/minhn/appa.html.

Structural insights of a cellobiose dehydrogenase enzyme from the basidiomycetes fungus Termitomyces clypeatus

Filamentous fungi secrete various oxidative enzymes to degrade the glycosidic bonds of polysaccharides. Cellobiose dehydrogenase (CDH) (E.C.1.1.99.18) is one of the important lignocellulose degrading enzymes produced by various filamentous fungi. It contains two stereo specific ligand binding domains, cytochrome and dehydrogenase - one for heme and the other for flavin adenine dinucleotide (FAD) respectively. The enzyme is of commercial importance for its use in amperometric biosensor, biofuel production, lactose determination in food, bioremediation etc. Termitomyces clypeatus, an edible fungus belonging to the basidiomycetes group, is a good producer of CDH. In this paper we have analyzed the structural properties of this enzyme from T. clypeatus and identified a distinct carbohydrate binding module (CBM) which is not present in most fungi belonging to the basidiomycetes group. In addition, the dehydrogenase domain of T. clypeatus CDH exhibited the absence of cellulose binding residues which is in contrast to the dehydrogenase domains of CDH of other basidiomycetes. Sequence analysis of cytochrome domain showed that the important residues of this domain were conserved like in other fungal CDHs. Phylogenetic tree, constructed using basidiomycetes and ascomycetes CDH sequences, has shown that very surprisingly the CDH from T. clypeatus, which is classified as a basidiomycetes fungus, is clustered with the ascomycetes group. A homology model of this protein has been constructed using the CDH enzyme of ascomycetes fungus Myricoccum thermophilum as a template since it has been found to be the best match sequence with T. clypeatus CDH. We also have modelled the protein with its substrate, cellobiose, which has helped us to identify the substrate interacting residues (L354, P606, T629, R631, Y649, N732, H733 and N781) localized within its dehydrogenase domain. Our computational investigation revealed for the first time the presence of all three domains - cytochrome, dehydrogenase and CBM - in the CDH of T. clypeatus, a basidiomycetes fungus. In addition to discovering the unique structural attributes of this enzyme from T. clypeatus, our study also discusses the possible phylogenetic status of this fungus.

Computational prediction and in vitro validation of VEGFR1 as a novel protein target for 2,3,7,8-tetrachlorodibenzo-p-dioxin

The toxic manifestations of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an environmental contaminant, primarily depend on its ability to activate aryl hydrocarbon receptor (AhR), which is a ligand-dependent transcription factor belonging to the superfamily of basic-helix-loop-helix DNA-binding proteins. In the present study, we aimed to identify novel protein receptor targets for TCDD using computational and in vitro validation experiments. Interestingly, results from computational methods predicted that Vascular Endothelial Growth Factor Receptor 1 (VEGFR1) could be one of the potential targets for TCDD in both mouse and humans. Results from molecular docking studies showed that human VEGFR1 (hVEGFR1) has less affinity towards TCDD compared to the mouse VEGFR1 (mVEGFR1). In vitro validation results showed that TCDD can bind and phosphorylate hVEGFR1. Further, results from molecular dynamic simulation studies showed that hVEGFR1 interaction with TCDD is stable throughout the simulation time. Overall, the present study has identified VEGFR1 as a novel target for TCDD, which provides the basis for further elucidating the role of TCDD in angiogenesis.

The three-dimensional structure of an H-superfamily conotoxin reveals a granulin fold arising from a common ICK cysteine framework

Venomous marine cone snails produce peptide toxins (conotoxins) that bind ion channels and receptors with high specificity and therefore are important pharmacological tools. Conotoxins contain conserved cysteine residues that form disulfide bonds that stabilize their structures. To gain structural insight into the large, yet poorly characterized conotoxin H-superfamily, we used NMR and CD spectroscopy along with MS-based analyses to investigate H-Vc7.2 from Conus victoriae, a peptide with a VI/VII cysteine framework. This framework has Cys^I-Cys^IV/Cys^II-Cys^V/Cys^III-Cys^VI connectivities, which have invariably been associated with the inhibitor cystine knot (ICK) fold. However, the solution structure of recombinantly expressed and purified H-Vc7.2 revealed that although it displays the expected cysteine connectivities, H-Vc7.2 adopts a different fold consisting of two stacked β-hairpins with opposing β-strands connected by two parallel disulfide bonds, a structure homologous to the N-terminal region of the human granulin protein. Using structural comparisons, we subsequently identified several toxins and nontoxin proteins with this "mini-granulin" fold. These findings raise fundamental questions concerning sequence-structure relationships within peptides and proteins and the key determinants that specify a given fold.

RMalign: an RNA structural alignment tool based on a novel scoring function RMscore

Background

RNA-protein 3D complex structure prediction is still challenging. Recently, a template-based approach PRIME is proposed in our team to build RNA-protein 3D complex structure models with a higher success rate than computational docking software. However, scoring function of RNA alignment algorithm SARA in PRIME is size-dependent, which limits its ability to detect templates in some cases.

Results

Herein, we developed a novel RNA 3D structural alignment approach RMalign, which is based on a size-independent scoring function RMscore. The parameter in RMscore is then optimized in randomly selected RNA pairs and phase transition points (from dissimilar to similar) are determined in another randomly selected RNA pairs. In tRNA benchmarking, the precision of RMscore is higher than that of SARAscore (0.88 and 0.78, respectively) with phase transition points. In balance-FSCOR benchmarking, RMalign performed as good as ESA-RNA with a non-normalized score measuring RNA structural similarity. In balance-x-FSCOR benchmarking, RMalign achieves much better than a state-of-the-art RNA 3D structural alignment approach SARA due to a size-independent scoring function. Take the advantage of RMalign, we update our RNA-protein modeling approach PRIME to version 2.0. The PRIME2.0 significantly improves about 10% success rate than PRIME.

Conclusion

Based on a size-independent scoring function RMscore, a novel RNA 3D structural alignment approach RMalign is developed and integrated into PRIME2.0, which could be useful for the biological community in modeling protein-RNA interaction.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5631-3) contains supplementary material, which is available to authorized users.

Inhibition of Nuclear PTEN Tyrosine Phosphorylation Enhances Glioma Radiation Sensitivity through Attenuated DNA Repair

Ionizing radiation (IR) and chemotherapy are standard-of-care treatments for glioblastoma (GBM) patients and both result in DNA damage, however, the clinical efficacy is limited due to therapeutic resistance. We identified a mechanism of such resistance mediated by phosphorylation of PTEN on tyrosine 240 (pY240-PTEN) by FGFR2. pY240-PTEN is rapidly elevated and bound to chromatin through interaction with Ki-67 in response to IR treatment and facilitates the recruitment of RAD51 to promote DNA repair. Blocking Y240 phosphorylation confers radiation sensitivity to tumors and extends survival in GBM preclinical models. Y240F-Pten knockin mice showed radiation sensitivity. These results suggest that FGFR-mediated pY240-PTEN is a key mechanism of radiation resistance and is an actionable target for improving radiotherapy efficacy.

Non-sequential protein structure alignment by conformational space annealing and local refinement

Protein structure alignment is an important tool for studying evolutionary biology and protein modeling. A tool which intensively searches for the globally optimal non-sequential alignments is rarely found. We propose ALIGN-CSA which shows improvement in scores, such as DALI-score, SP-score, SO-score and TM-score over the benchmark set including 286 cases. We performed benchmarking of existing popular alignment scoring functions, where the dependence of the search algorithm was effectively eliminated by using ALIGN-CSA. For the benchmarking, we set the minimum block size to 4 to prevent much fragmented alignments where the biological relevance of small alignment blocks is hard to interpret. With this condition, globally optimal alignments were searched by ALIGN-CSA using the four scoring functions listed above, and TM-score is found to be the most effective in generating alignments with longer match lengths and smaller RMSD values. However, DALI-score is the most effective in generating alignments similar to the manually curated reference alignments, which implies that DALI-score is more biologically relevant score. Due to the high demand on computational resources of ALIGN-CSA, we also propose a relatively fast local refinement method, which can control the minimum block size and whether to allow the reverse alignment. ALIGN-CSA can be used to obtain much improved alignment at the cost of relatively more extensive computation. For faster alignment, we propose a refinement protocol that improves the score of a given alignment obtained by various external tools. All programs are available from http://lee.kias.re.kr.

Comparative analysis of interactions between aryl hydrocarbon receptor ligand binding domain with its ligands: a computational study

BACKGROUND

Aryl hydrocarbon receptor (AhR) ligands may act as potential carcinogens or anti-tumor agents. Understanding how some of the residues in AhR ligand binding domain (AhRLBD) modulate their interactions with ligands would be useful in assessing their divergent roles including toxic and beneficial effects. To this end, we have analysed the nature of AhRLBD interactions with 2,3,7,8-tetrachlorodibenzo-ρ-dioxin (TCDD), 6-formylindolo[3,2-b]carbazole (FICZ), indole-3-carbinol (I3C) and its degradation product, 3,3'-diindolylmethane (DIM), Resveratrol (RES) and its analogue, Piceatannol (PTL) using molecular modeling approach followed by molecular dynamic simulations.

RESULTS

Results showed that each of the AhR ligands, TCDD, FICZ, I3C, DIM, RES and PTL affect the local and global conformations of AhRLBD.

CONCLUSION

The data presented in this study provide a structural understanding of AhR with its ligands and set the basis for its functions in several pathways and their related diseases.

HIF-2α-pVHL complex reveals broad genotype-phenotype correlations in HIF-2α-driven disease

It is definitively established that mutations in transcription factor HIF-2α are causative of both neuroendocrine tumors (class 1 disease) and polycythemia (class 2 disease). However, the molecular mechanism that underlies this emergent genotype–phenotype relationship has remained unclear. Here, we report the structure of HIF-2α peptide bound to pVHL-elongin B-elongin C (VBC) heterotrimeric complex, which shows topographical demarcation of class 1 and 2 mutations affecting residues predicted, and demonstrated via biophysical analyses, to differentially impact HIF-2α-pVHL interaction interface stability. Concordantly, biochemical experiments showed that class 1 mutations disrupt pVHL affinity to HIF-2α more adversely than class 2 mutations directly or indirectly via impeding PHD2-mediated hydroxylation. These findings suggest that neuroendocrine tumor pathogenesis requires a higher HIF-2α dose than polycythemia, which requires only a mild increase in HIF-2α activity. These biophysical data reveal a structural basis that underlies, and can be used to predict de novo, broad genotype-phenotype correlations in HIF-2α-driven disease.

Hypoxia inducible factor (HIF)-2α transcription factor is mutated in polycythemia and various neuroendocrine tumors. Here the authors present the crystal structure of a HIF-2α peptide bound to the pVHL-elongin B-elongin C (VBC) heterotrimeric complex and propose a classification scheme for HIF-2α mutations that helps to predict disease phenotype outcome.

Genome-wide and comparative analysis of bHLH38, bHLH39, bHLH100 and bHLH101 genes in Arabidopsis, tomato, rice, soybean and maize: insights into iron (Fe) homeostasis

Iron (Fe) is an essential element for plant life. Its deficiency impedes growth and development and excessive iron can cause the toxic effect via the Fenton reaction. Thus, plants have developed various mechanisms to acquire, distribute and utilize Fe for the maintenance of their iron homeostasis at cellular and systemic levels. A basic helix-loop-helix (bHLH) transcription factor family plays essential roles in many regulatory and development processes in plants. In this study, we aimed to understand the roles of bHLH38, bHLH39, bHLH100 and bHLH101 genes for Fe homeostasis in Arabidopsis, tomato, rice, soybean and maize species by using bioinformatics approaches. The gene/protein sequence analyses of these genes demonstrated that all bHLH proteins comprised helix-loop-helix DNA binding domain (PF00010) with varied exon numbers between 2 and 13. The phylogenetic analysis did not reveal a clear distinction between monocot and dicot plants. A total of 61 cis-elements were found in promotor sequences, including biotic and abiotic stress responsiveness, hormone responsiveness, and tissue specific expressions. The some structural divergences were identified in predicted 3D structures of bHLH proteins with different channels numbers. The co-expression network analysis demonstrated that bHLH39 and bHLH101 played more important roles in Fe regulation in Arabidopsis. The digital expression analysis showed various expression profiles of bHLH genes which were identified in developmental stages, anatomical parts, and perturbations. Particularly, bHLH39 and bHLH101 genes were found to be more active genes in Fe homeostasis. As a result, our findings can contribute to understanding of bHLH38, bHLH39, bHLH100 and bHLH101 genes in Fe homeostasis in plants.

Substrate-induced domain movement in a bifunctional protein, DcpA, regulates cyclic di-GMP turnover: Functional implications of a highly conserved motif

In eubacteria, cyclic di-GMP (c-di-GMP) signaling is involved in virulence, persistence, motility and generally orchestrates multicellular behavior in bacterial biofilms. Intracellular c-di-GMP levels are maintained by the opposing activities of diguanylate cyclases (DGCs) and cognate phosphodiesterases (PDEs). The c-di-GMP homeostasis in Mycobacterium smegmatis is supported by DcpA, a conserved, bifunctional protein with both DGC and PDE activities. DcpA is a multidomain protein whose GAF-GGDEF-EAL domains are arranged in tandem and are required for these two activities. To gain insight into how interactions among these three domains affect DcpA activity, here we studied its domain dynamics using real-time FRET. We demonstrate that substrate binding in DcpA results in domain movement that prompts a switch from an "open" to a "closed" conformation and alters its catalytic activity. We found that a single point mutation in the conserved EAL motif (E384A) results in complete loss of the PDE activity of the EAL domain and in a significant decrease in the DGC activity of the GGDEF domain. Structural analyses revealed multiple hydrophobic and aromatic residues around Cys⁵⁷⁹ that are necessary for proper DcpA folding and maintenance of the active conformation. On the basis of these observations and taking into account additional bioinformatics analysis of EAL domain-containing proteins, we identified a critical putatively conserved motif, GCXXXQGF, that plays an important role in c-di-GMP turnover. We conclude that a substrate-induced conformational switch involving movement of a loop containing a conserved motif in the bifunctional diguanylate cyclase-phosphodiesterase DcpA controls c-di-GMP turnover in M. smegmatis.

Method to generate highly stable D-amino acid analogs of bioactive helical peptides using a mirror image of the entire PDB

Biologics are a rapidly growing class of therapeutics with many advantages over traditional small molecule drugs. A major obstacle to their development is that proteins and peptides are easily destroyed by proteases and, thus, typically have prohibitively short half-lives in human gut, plasma, and cells. One of the most effective ways to prevent degradation is to engineer analogs from dextrorotary (D)-amino acids, with up to 105-fold improvements in potency reported. We here propose a general peptide-engineering platform that overcomes limitations of previous methods. By creating a mirror image of every structure in the Protein Data Bank (PDB), we generate a database of ∼2.8 million D-peptides. To obtain a D-analog of a given peptide, we search the (D)-PDB for similar configurations of its critical-"hotspot"-residues. As a proof of concept, we apply our method to two peptides that are Food and Drug Administration approved as therapeutics for diabetes and osteoporosis, respectively. We obtain D-analogs that activate the GLP1 and PTH1 receptors with the same efficacy as their natural counterparts and show greatly increased half-life.

Terzyme: a tool for identification and analysis of the plant terpenome

BACKGROUND

Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data.

RESULTS

We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants.

CONCLUSIONS

Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes.

SupeRNAlign: a new tool for flexible superposition of homologous RNA structures and inference of accurate structure-based sequence alignments

RNA has been found to play an ever-increasing role in a variety of biological processes. The function of most non-coding RNA molecules depends on their structure. Comparing and classifying macromolecular 3D structures is of crucial importance for structure-based function inference and it is used in the characterization of functional motifs and in structure prediction by comparative modeling. However, compared to the numerous methods for protein structure superposition, there are few tools dedicated to the superimposing of RNA 3D structures. Here, we present SupeRNAlign (v1.3.1), a new method for flexible superposition of RNA 3D structures, and SupeRNAlign-Coffee—a workflow that combines SupeRNAlign with T-Coffee for inferring structure-based sequence alignments. The methods have been benchmarked with eight other methods for RNA structural superposition and alignment. The benchmark included 151 structures from 32 RNA families (with a total of 1734 pairwise superpositions). The accuracy of superpositions was assessed by comparing structure-based sequence alignments to the reference alignments from the Rfam database. SupeRNAlign and SupeRNAlign-Coffee achieved significantly higher scores than most of the benchmarked methods: SupeRNAlign generated the most accurate sequence alignments among the structure superposition methods, and SupeRNAlign-Coffee performed best among the sequence alignment methods.