Ab initio modeling of small proteins by iterative TASSER simulations

Nuclear trafficking of the HIV-1 pre-integration complex depends on the ADAM10 intracellular domain

Previously, we showed that ADAM10 is necessary for HIV-1 replication in primary human macrophages and immortalized cell lines. Silencing ADAM10 expression interrupted the HIV-1 life cycle prior to nuclear translocation of viral cDNA. Furthermore, our data indicated that HIV-1 replication depends on the expression of ADAM15 and γ-secretase, which proteolytically processes ADAM10. Silencing ADAM15 or γ-secretase expression inhibits HIV-1 replication between reverse transcription and nuclear entry. Here, we show that ADAM10 expression also supports replication in CD4(+) T lymphocytes. The intracellular domain (ICD) of ADAM10 associates with the HIV-1 pre-integration complex (PIC) in the cytoplasm and immunoprecipitates and co-localizes with HIV-1 integrase, a key component of PIC. Taken together, our data support a model whereby ADAM15/γ-secretase processing of ADAM10 releases the ICD, which then incorporates into HIV-1 PIC to facilitate nuclear trafficking. Thus, these studies suggest ADAM10 as a novel therapeutic target for inhibiting HIV-1 prior to nuclear entry.

Ranking the quality of protein structure models using sidechain based network properties

Determining the correct structure of a protein given its sequence still remains an arduous task with many researchers working towards this goal. Most structure prediction methodologies result in the generation of a large number of probable candidates with the final challenge being to select the best amongst these. In this work, we have used Protein Structure Networks of native and modeled proteins in combination with Support Vector Machines to estimate the quality of a protein structure model and finally to provide ranks for these models. Model ranking is performed using regression analysis and helps in model selection from a group of many similar and good quality structures. Our results show that structures with a rank greater than 16 exhibit native protein-like properties while those below 10 are non-native like. The tool is also made available as a web-server ( http://vishgraph.mbu.iisc.ernet.in/GraProStr/native_non_native_ranking.html), where, 5 modelled structures can be evaluated at a given time.

In silico prediction of structure and functions for some proteins of male-specific region of the human Y chromosome

Male-specific region of the human Y chromosome (MSY) comprises 95% of its length that is functionally active. This portion inherits in block from father to male offspring. Most of the genes in the MSY region are involved in male-specific function, such as sex determination and spermatogenesis; also contains genes probably involved in other cellular functions. However, a detailed characterization of numerous MSY-encoded proteins still remains to be done. In this study, 12 uncharacterized proteins of MSY were analyzed through bioinformatics tools for structural and functional characterization. Within these 12 proteins, a total of 55 domains were found, with DnaJ domain signature corresponding to be the highest (11%) followed by both FAD-dependent pyridine nucleotide reductase signature and fumarate lyase superfamily signature (9%). The 3D structures of our selected proteins were built up using homology modeling and the protein threading approaches. These predicted structures confirmed in detail the stereochemistry; indicating reasonably good quality model. Furthermore the predicted functions and the proteins with whom they interact established their biological role and their mechanism of action at molecular level. The results of these structure-functional annotations provide a comprehensive view of the proteins encoded by MSY, which sheds light on their biological functions and molecular mechanisms. The data presented in this study may assist in future prognosis of several human diseases such as Turner syndrome, gonadal sex reversal, spermatogenic failure, and gonadoblastoma.

Tertiary structure prediction and identification of druggable pocket in the cancer biomarker - Osteopontin-c

Background

Osteopontin (Eta, secreted sialoprotein 1, opn) is secreted from different cell types including cancer cells. Three splice variant forms namely osteopontin-a, osteopontin-b and osteopontin-c have been identified. The main astonishing feature is that osteopontin-c is found to be elevated in almost all types of cancer cells. This was the vital point to consider it for sequence analysis and structure predictions which provide ample chances for prognostic, therapeutic and preventive cancer research.

Methods

Osteopontin-c gene sequence was determined from Breast Cancer sample and was translated to protein sequence. It was then analyzed using various software and web tools for binding pockets, docking and druggability analysis. Due to the lack of homological templates, tertiary structure was predicted using ab-initio method server – I-TASSER and was evaluated after refinement using web tools. Refined structure was compared with known bone sialoprotein electron microscopic structure and docked with CD44 for binding analysis and binding pockets were identified for drug designing.

Results

Signal sequence of about sixteen amino acid residues was identified using signal sequence prediction servers. Due to the absence of known structures of similar proteins, three dimensional structure of osteopontin-c was predicted using I-TASSER server. The predicted structure was refined with the help of SUMMA server and was validated using SAVES server. Molecular dynamic analysis was carried out using GROMACS software. The final model was built and was used for docking with CD44. Druggable pockets were identified using pocket energies.

Conclusions

The tertiary structure of osteopontin-c was predicted successfully using the ab-initio method and the predictions showed that osteopontin-c is of fibrous nature comparable to firbronectin. Docking studies showed the significant similarities of QSAET motif in the interaction of CD44 and osteopontins between the normal and splice variant forms of osteopontins and binding pockets analyses revealed several pockets which paved the way to the identification of a druggable pocket.

Strategies and molecular tools to fight antimicrobial resistance: resistome, transcriptome, and antimicrobial peptides

The increasing number of antibiotic resistant bacteria motivates prospective research toward discovery of new antimicrobial active substances. There are, however, controversies concerning the cost-effectiveness of such research with regards to the description of new substances with novel cellular interactions, or description of new uses of existing substances to overcome resistance. Although examination of bacteria isolated from remote locations with limited exposure to humans has revealed an absence of antibiotic resistance genes, it is accepted that these genes were both abundant and diverse in ancient living organisms, as detected in DNA recovered from Pleistocene deposits (30,000 years ago). Indeed, even before the first clinical use of antibiotics more than 60 years ago, resistant organisms had been isolated. Bacteria can exhibit different strategies for resistance against antibiotics. New genetic information may lead to the modification of protein structure affecting the antibiotic carriage into the cell, enzymatic inactivation of drugs, or even modification of cellular structure interfering in the drug-bacteria interaction. There are still plenty of new genes out there in the environment that can be appropriated by putative pathogenic bacteria to resist antimicrobial agents. On the other hand, there are several natural compounds with antibiotic activity that may be used to oppose them. Antimicrobial peptides (AMPs) are molecules which are wide-spread in all forms of life, from multi-cellular organisms to bacterial cells used to interfere with microbial growth. Several AMPs have been shown to be effective against multi-drug resistant bacteria and have low propensity to resistance development, probably due to their unique mode of action, different from well-known antimicrobial drugs. These substances may interact in different ways with bacterial cell membrane, protein synthesis, protein modulation, and protein folding. The analysis of bacterial transcriptome may contribute to the understanding of microbial strategies under different environmental stresses and allows the understanding of their interaction with novel AMPs.

ThreaDom: extracting protein domain boundary information from multiple threading alignments

Motivation: Protein domains are subunits that can fold and evolve independently. Identification of domain boundary locations is often the first step in protein folding and function annotations. Most of the current methods deduce domain boundaries by sequence-based analysis, which has low accuracy. There is no efficient method for predicting discontinuous domains that consist of segments from separated sequence regions. As template-based methods are most efficient for protein 3D structure modeling, combining multiple threading alignment information should increase the accuracy and reliability of computational domain predictions.

Result: We developed a new protein domain predictor, ThreaDom, which deduces domain boundary locations based on multiple threading alignments. The core of the method development is the derivation of a domain conservation score that combines information from template domain structures and terminal and internal alignment gaps. Tested on 630 non-redundant sequences, without using homologous templates, ThreaDom generates correct single- and multi-domain classifications in 81% of cases, where 78% have the domain linker assigned within ±20 residues. In a second test on 486 proteins with discontinuous domains, ThreaDom achieves an average precision 84% and recall 65% in domain boundary prediction. Finally, ThreaDom was examined on 56 targets from CASP8 and had a domain overlap rate 73, 87 and 85% with the target for Free Modeling, Hard multiple-domain and discontinuous domain proteins, respectively, which are significantly higher than most domain predictors in the CASP8. Similar results were achieved on the targets from the most recently CASP9 and CASP10 experiments.

Availability:http://zhanglab.ccmb.med.umich.edu/ThreaDom/.

Contact:zhng@umich.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Detecting protein candidate fragments using a structural alphabet profile comparison approach

Predicting accurate fragments from sequence has recently become a critical step for protein structure modeling, as protein fragment assembly techniques are presently among the most efficient approaches for de novo prediction. A key step in these approaches is, given the sequence of a protein to model, the identification of relevant fragments - candidate fragments - from a collection of the available 3D structures. These fragments can then be assembled to produce a model of the complete structure of the protein of interest. The search for candidate fragments is classically achieved by considering local sequence similarity using profile comparison, or threading approaches. In the present study, we introduce a new profile comparison approach that, instead of using amino acid profiles, is based on the use of predicted structural alphabet profiles, where structural alphabet profiles contain information related to the 3D local shapes associated with the sequences. We show that structural alphabet profile-profile comparison can be used efficiently to retrieve accurate structural fragments, and we introduce a fully new protocol for the detection of candidate fragments. It identifies fragments specific of each position of the sequence and of size varying between 6 and 27 amino-acids. We find it outperforms present state of the art approaches in terms (i) of the accuracy of the fragments identified, (ii) the rate of true positives identified, while having a high coverage score. We illustrate the relevance of the approach on complete target sets of the two previous Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 9 and 10. A web server for the approach is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/SAFrag.

The electrostatic profile of consecutive Cβ atoms applied to protein structure quality assessment

The structure of a protein provides insight into its physiological interactions with other components of the cellular soup. Methods that predict putative structures from sequences typically yield multiple, closely-ranked possibilities. A critical component in the process is the model quality assessing program (MQAP), which selects the best candidate from this pool of structures. Here, we present a novel MQAP based on the physical properties of sidechain atoms. We propose a method for assessing the quality of protein structures based on the electrostatic potential difference (EPD) of Cβ atoms in consecutive residues. We demonstrate that the EPDs of Cβ atoms on consecutive residues provide unique signatures of the amino acid types. The EPD of Cβ atoms are learnt from a set of 1000 non-homologous protein structures with a resolution cuto of 1.6 Å obtained from the PISCES database. Based on the Boltzmann hypothesis that lower energy conformations are proportionately sampled more, and on Annsen's thermodynamic hypothesis that the native structure of a protein is the minimum free energy state, we hypothesize that the deviation of observed EPD values from the mean values obtained in the learning phase is minimized in the native structure. We achieved an average specificity of 0.91, 0.94 and 0.93 on hg_structal, 4state_reduced and ig_structal decoy sets, respectively, taken from the Decoys `R' Us database. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.

An evolution-based approach to De Novo protein design and case study on Mycobacterium tuberculosis

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality.

The goal of computational protein design is to create new protein sequences of desirable structure and biological function. Most protein design methods are developed to search for sequences with the lowest free-energy based on physics-based force fields following Anfinsen's thermodynamic hypothesis. A major obstacle of such approaches is the inaccuracy of the force-field design, which cannot accurately describe atomic interactions or correctly recognize protein folds. We propose a novel method which uses evolutionary information, in the form of sequence profiles from structure families, to guide the sequence design. Since sequence profiles are generally more accurate than physics-based potentials in protein fold recognition, a unique advantage lies on that it targets the design procedure to a family of protein sequence profiles to enhance the robustness of designed sequences. The method was tested on 87 proteins and the designed sequences can be folded by I-TASSER to models with an average RMSD 2.1 Å. As a case study of large-scale application, the method is extended to redesign all structurally resolved proteins in the human pathogenic bacteria, Mycobacterium tuberculosis. Five sequences varying in fold and sizes were characterized by circular dichroism and NMR spectroscopy experiments and three were shown to have ordered tertiary structure.

Protein structure quality assessment based on the distance profiles of consecutive backbone Cα atoms

Predicting the three dimensional native state structure of a protein from its primary sequence is an unsolved grand challenge in molecular biology. Two main computational approaches have evolved to obtain the structure from the protein sequence - ab initio/de novo methods and template-based modeling - both of which typically generate multiple possible native state structures. Model quality assessment programs (MQAP) validate these predicted structures in order to identify the correct native state structure. Here, we propose a MQAP for assessing the quality of protein structures based on the distances of consecutive Cα atoms. We hypothesize that the root-mean-square deviation of the distance of consecutive Cα (RDCC) atoms from the ideal value of 3.8 Å, derived from a statistical analysis of high quality protein structures (top100H database), is minimized in native structures. Based on tests with the top100H set, we propose a RDCC cutoff value of 0.012 Å, above which a structure can be filtered out as a non-native structure. We applied the RDCC discriminator on decoy sets from the Decoys 'R' Us database to show that the native structures in all decoy sets tested have RDCC below the 0.012 Å cutoff. While most decoy sets were either indistinguishable using this discriminator or had very few violations, all the decoy structures in the fisa decoy set were discriminated by applying the RDCC criterion. This highlights the physical non-viability of the fisa decoy set, and possible issues in benchmarking other methods using this set. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.

Protein structure quality assessment based on the distance profiles of consecutive backbone Cα atoms

Predicting the three dimensional native state structure of a protein from its primary sequence is an unsolved grand challenge in molecular biology. Two main computational approaches have evolved to obtain the structure from the protein sequence - ab initio/de novo methods and template-based modeling - both of which typically generate multiple possible native state structures. Model quality assessment programs (MQAP) validate these predicted structures in order to identify the correct native state structure. Here, we propose a MQAP for assessing the quality of protein structures based on the distances of consecutive Cα atoms. We hypothesize that the root-mean-square deviation of the distance of consecutive Cα (RDCC) atoms from the ideal value of 3.8 Å, derived from a statistical analysis of high quality protein structures (top100H database), is minimized in native structures. Based on tests with the top100H set, we propose a RDCC cutoff value of 0.012 Å, above which a structure can be filtered out as a non-native structure. We applied the RDCC discriminator on decoy sets from the Decoys 'R' Us database to show that the native structures in all decoy sets tested have RDCC below the 0.012 Å cutoff. While most decoy sets were either indistinguishable using this discriminator or had very few violations, all the decoy structures in the fisa decoy set were discriminated by applying the RDCC criterion. This highlights the physical non-viability of the fisa decoy set, and possible issues in benchmarking other methods using this set. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.

Molecular interactions between fenoterol stereoisomers and derivatives and the β₂-adrenergic receptor binding site studied by docking and molecular dynamics simulations

The β2 adrenergic receptor (β2-AR) has become a model system for studying the ligand recognition process and mechanism of the G protein coupled receptors activation. In the present study stereoisomers of fenoterol and some of its derivatives (N = 94 molecules) were used as molecular probes to identify differences in stereo-recognition interactions between β2-AR and structurally similar agonists. The present study aimed at determining the 3D molecular models of the fenoterol derivative-β2-AR complexes. Molecular models of β2-AR have been developed by using the crystal structure of the human β2-AR T4 lysozyme fusion protein with bound (S)-carazolol (PDB ID: 2RH1) and more recently reported structure of a nanobody-stabilized active state of the β2-AR with the bound full agonist BI-167107 (PDB ID: 3P0G). The docking procedure allowed us to study the similarities and differences in the recognition binding site(s) for tested ligands. The agonist molecules occupied the same binding region, between TM III, TM V, TM VI and TM VII. The residues identified by us during docking procedure (Ser203, Ser207, Asp113, Lys305, Asn312, Tyr308, Asp192) were experimentally indicated in functional and biophysical studies as being very important for the agonist-receptor interactions. Moreover, the additional space, an extension of the orthosteric pocket, was identified and described. Furthermore, the molecular dynamics simulations were used to study the molecular mechanism of interaction between ligands ((R,R')- and (S,S')-fenoterol) and β2-AR. Our research offers new insights into the ligand stereoselective interaction with one of the most important GPCR member. This study may also facilitate the design of improved selective medications, which can be used to treat, prevent and control heart failure symptoms.

Protein structural model selection by combining consensus and single scoring methods

Quality assessment (QA) for predicted protein structural models is an important and challenging research problem in protein structure prediction. Consensus Global Distance Test (CGDT) methods assess each decoy (predicted structural model) based on its structural similarity to all others in a decoy set and has been proved to work well when good decoys are in a majority cluster. Scoring functions evaluate each single decoy based on its structural properties. Both methods have their merits and limitations. In this paper, we present a novel method called PWCom, which consists of two neural networks sequentially to combine CGDT and single model scoring methods such as RW, DDFire and OPUS-Ca. Specifically, for every pair of decoys, the difference of the corresponding feature vectors is input to the first neural network which enables one to predict whether the decoy-pair are significantly different in terms of their GDT scores to the native. If yes, the second neural network is used to decide which one of the two is closer to the native structure. The quality score for each decoy in the pool is based on the number of winning times during the pairwise comparisons. Test results on three benchmark datasets from different model generation methods showed that PWCom significantly improves over consensus GDT and single scoring methods. The QA server (MUFOLD-Server) applying this method in CASP 10 QA category was ranked the second place in terms of Pearson and Spearman correlation performance.

Interplay of I-TASSER and QUARK for template-based and ab initio protein structure prediction in CASP10

We develop and test a new pipeline in CASP10 to predict protein structures based on an interplay of I-TASSER and QUARK for both free-modeling (FM) and template-based modeling (TBM) targets. The most noteworthy observation is that sorting through the threading template pool using the QUARK-based ab initio models as probes allows the detection of distant-homology templates which might be ignored by the traditional sequence profile-based threading alignment algorithms. Further template assembly refinement by I-TASSER resulted in successful folding of two medium-sized FM targets with >150 residues. For TBM, the multiple threading alignments from LOMETS are, for the first time, incorporated into the ab initio QUARK simulations, which were further refined by I-TASSER assembly refinement. Compared with the traditional threading assembly refinement procedures, the inclusion of the threading-constrained ab initio folding models can consistently improve the quality of the full-length models as assessed by the GDT-HA and hydrogen-bonding scores. Despite the success, significant challenges still exist in domain boundary prediction and consistent folding of medium-size proteins (especially beta-proteins) for nonhomologous targets. Further developments of sensitive fold-recognition and ab initio folding methods are critical for solving these problems.

Functional characterization of human myosin-18A and its interaction with F-actin and GOLPH3

Molecular motors of the myosin superfamily share a generic motor domain region. They commonly bind actin in an ATP-sensitive manner, exhibit actin-activated ATPase activity, and generate force and movement in this interaction. Class-18 myosins form heavy chain dimers and contain protein interaction domains located at their unique N-terminal extension. Here, we characterized human myosin-18A molecular function in the interaction with nucleotides, F-actin, and its putative binding partner, the Golgi-associated phosphoprotein GOLPH3. We show that myosin-18A comprises two actin binding sites. One is located in the KE-rich region at the start of the N-terminal extension and appears to mediate ATP-independent binding to F-actin. The second actin-binding site resides in the generic motor domain and is regulated by nucleotide binding in the absence of intrinsic ATP hydrolysis competence. This core motor domain displays its highest actin affinity in the ADP state. Electron micrographs of myosin-18A motor domain-decorated F-actin filaments show a periodic binding pattern independent of the nucleotide state. We show that the PDZ module mediates direct binding of myosin-18A to GOLPH3, and this interaction in turn modulates the actin binding properties of the N-terminal extension. Thus, myosin-18A can act as an actin cross-linker with multiple regulatory modulators that targets interacting proteins or complexes to the actin-based cytoskeleton.

Protein structure validation and identification from unassigned residual dipolar coupling data using 2D-PDPA

More than 90% of protein structures submitted to the PDB each year are homologous to some previously characterized protein structure. The extensive resources that are required for structural characterization of proteins can be justified for the 10% of the novel structures, but not for the remaining 90%. This report presents the 2D-PDPA method, which utilizes unassigned residual dipolar coupling in order to address the economics of structure determination of routine proteins by reducing the data acquisition and processing time. 2D-PDPA has been demonstrated to successfully identify the correct structure of an array of proteins that range from 46 to 445 residues in size from a library of 619 decoy structures by using unassigned simulated RDC data. When using experimental data, 2D-PDPA successfully identified the correct NMR structures from the same library of decoy structures. In addition, the most homologous X-ray structure was also identified as the second best structural candidate. Finally, success of 2D-PDPA in identifying and evaluating the most appropriate structure from a set of computationally predicted structures in the case of a previously uncharacterized protein Pf2048.1 has been demonstrated. This protein exhibits less than 20% sequence identity to any protein with known structure and therefore presents a compelling and practical application of our proposed work.

Mutations in the STAT1‑interacting domain of the hepatitis C virus core protein modulate the response to antiviral therapy

RNA viruses, such as hepatitis C virus (HCV), have markedly error-prone replication, resulting in high rates of mutagenesis. In addition, the standard treatment includes ribavirin, a base analog that is likely to cause mutations in different regions of the HCV genome, resulting in deleterious effects on HCV itself. The N-terminal region of the core protein is reported to block interferon (IFN) signaling by interaction with the STAT1‑SH2 domain, resulting in HCV resistance to IFN therapy. In this study, mutations in the HCV core protein from IFN/ribavirin‑treated patients were analyzed, with particular focus on the N‑terminal domain of the HCV core which is reported to interact with STAT1. HCV PCR positive patients enrolled in this study were either undergoing pegylated IFN/ribavirin bitherapy and had completed 12 weeks of initial treatment or were treatment‑naïve patients. The HCV core protein was cloned and sequenced from these patients and mutations observed in the STAT1‑interacting domain of the core protein from treated patients were characterized using in silico interaction to depict the role of these mutations in disease outcomes. Our results suggest that the amino acids at positions 2, 3, 8, 16 and 23 of the HCV core protein are critical for core-STAT1 interaction and ribavirin-induced mutations at these positions interfere with the interaction, resulting in a better response of the treated patients. In conclusion, this study anticipates that HCV core residues 2, 3, 8, 16 and 23 directly interact with STAT1. We propose that IFN/ribavirin bitherapy‑induced mutations in the STAT1‑interacting domain of the HCV core protein may be responsible for the improved therapeutic response and viral clearance, thus amino acids 1-23 of the N-terminus of the core protein are an ideal antiviral target. However, this treatment may give rise to resistant variants that are able to escape the current therapy. We propose similar studies in responsive and non-responsive genotypes in order to gain a broader picture of this proposed mechanism of viral clearance.

Discovery of a potent small molecule SIRT1/2 inhibitor with anticancer effects

SIRT1 and SIRT2 are deacetylase enzymes that belong to the sirtuin family and are involved in tumorigenesis. In our screen for small molecules inhibiting SIRT1/2 toxoflavin was identified. Toxoflavin potently inhibited SIRT1 activity in in vitro deacetylase assay using purified SIRT1 protein. SIRT2 activity was also inhibited by toxoflavin less potently than SIRT1 in deacetylase assay in vitro. Toxoflavin exhibited growth inhibition of various cancer cell lines including A549 lung cancer cells with a GI(50) of 48 nM. Toxoflavin treatment in A549 cells increased the acetylated form of p53, which is a substrate of SIRT1. The acetylation levels of α-tubulin, a SIRT2 substrate, were also increased by toxoflavin treatment dose-dependently. Several toxoflavin derivatives were synthesized to determine the preliminary structure-activity relationship of toxoflavin. Some of the toxoflavin derivatives showed highly selective inhibition against SIRT1. In conclusion, this study presented toxoflavin as a potent SIRT1/2 inhibitor with anticancer activity.

Transmembrane protein alignment and fold recognition based on predicted topology

BACKGROUND

Although Transmembrane Proteins (TMPs) are highly important in various biological processes and pharmaceutical developments, general prediction of TMP structures is still far from satisfactory. Because TMPs have significantly different physicochemical properties from soluble proteins, current protein structure prediction tools for soluble proteins may not work well for TMPs. With the increasing number of experimental TMP structures available, template-based methods have the potential to become broadly applicable for TMP structure prediction. However, the current fold recognition methods for TMPs are not as well developed as they are for soluble proteins.

METHODOLOGY

We developed a novel TMP Fold Recognition method, TMFR, to recognize TMP folds based on sequence-to-structure pairwise alignment. The method utilizes topology-based features in alignment together with sequence profile and solvent accessibility. It also incorporates a gap penalty that depends on predicted topology structure segments. Given the difference between α-helical transmembrane protein (αTMP) and β-strands transmembrane protein (βTMP), parameters of scoring functions are trained respectively for these two protein categories using 58 αTMPs and 17 βTMPs in a non-redundant training dataset.

RESULTS

We compared our method with HHalign, a leading alignment tool using a non-redundant testing dataset including 72 αTMPs and 30 βTMPs. Our method achieved 10% and 9% better accuracies than HHalign in αTMPs and βTMPs, respectively. The raw score generated by TMFR is negatively correlated with the structure similarity between the target and the template, which indicates its effectiveness for fold recognition. The result demonstrates TMFR provides an effective TMP-specific fold recognition and alignment method.

A novel hepacivirus with an unusually long and intrinsically disordered NS5A protein in a wild Old World primate

GB virus B (GBV-B; family Flaviviridae, genus Hepacivirus) has been studied in New World primates as a model for human hepatitis C virus infection, but the distribution of GBV-B and its relatives in nature has remained obscure. Here, we report the discovery of a novel and highly divergent GBV-B-like virus in an Old World monkey, the black-and-white colobus (Colobus guereza), in Uganda. The new virus, guereza hepacivirus (GHV), clusters phylogenetically with GBV-B and recently described hepaciviruses infecting African bats and North American rodents, and it shows evidence of ancient recombination with these other hepaciviruses. Direct sequencing of reverse-transcribed RNA from blood plasma from three of nine colobus monkeys yielded near-complete GHV genomes, comprising two distinct viral variants. The viruses contain an exceptionally long nonstructural 5A (NS5A) gene, approximately half of which codes for a protein with no discernible homology to known proteins. Computational structure-based analyses indicate that the amino terminus of the GHV NS5A protein may serve a zinc-binding function, similar to the NS5A of other viruses within the family Flaviviridae. However, the 521-amino-acid carboxy terminus is intrinsically disordered, reflecting an unusual degree of structural plasticity and polyfunctionality. These findings shed new light on the natural history and evolution of the hepaciviruses and on the extent of structural variation within the Flaviviridae.

Recurrent structural motifs in non-homologous protein structures

We have extracted an extensive collection of recurrent structural motifs (RSMs), which consist of sequentially non-contiguous structural motifs (4–6 residues), each of which appears with very similar conformation in three or more mutually unrelated protein structures. We find that the proteins in our set are covered to a substantial extent by the recurrent non-contiguous structural motifs, especially the helix and strand regions. Computational alanine scanning calculations indicate that the average folding free energy changes upon alanine mutation for most types of non-alanine residues are higher for amino acids that are present in recurrent structural motifs than for amino acids that are not. The non-alanine amino acids that are most common in the recurrent structural motifs, i.e., phenylalanine, isoleucine, leucine, valine and tyrosine and the less abundant methionine and tryptophan, have the largest folding free energy changes. This indicates that the recurrent structural motifs, as we define them, describe recurrent structural patterns that are important for protein stability. In view of their properties, such structural motifs are potentially useful for inter-residue contact prediction and protein structure refinement.

Effective identification of bacterial type III secretion signals using joint element features

Type III secretion system (T3SS) plays important roles in bacteria and host cell interactions by specifically translocating type III effectors into the cytoplasm of the host cells. The N-terminal amino acid sequences of the bacterial type III effectors determine their specific secretion via type III secretion conduits. It is still unclear as to how the N-terminal sequences guide this specificity. In this work, the amino acid composition, secondary structure, and solvent accessibility in the N-termini of type III and non-type III secreted proteins were compared and contrasted. A high-efficacy mathematical model based on these joint features was developed to distinguish the type III proteins from the non-type III ones. The results indicate that secondary structure and solvent accessibility may make important contribution to the specific recognition of type III secretion signals. Analysis also showed that the joint feature of the N-terminal 6^th–10^th amino acids are especially important for guiding specific type III secretion. Furthermore, a genome-wide screening was performed to predict Salmonella type III secreted proteins, and 8 new candidates were experimentally validated. Interestingly, type III secretion signals were also predicted in gram-positive bacteria and yeasts. Experimental validation showed that two candidates from yeast can indeed be secreted through Salmonella type III secretion conduit. This research provides the first line of direct evidence that secondary structure and solvent accessibility contain important features for guiding specific type III secretion. The new software based on these joint features ensures a high accuracy (general cross-validation sensitivity of ∼96% at a specificity of ∼98%) in silico identification of new type III secreted proteins, which may facilitate our understanding about the specificity of type III secretion and the evolution of type III secreted proteins.

High-throughput genotyping of single-nucleotide polymorphisms in ace-1 gene of mosquitoes using MALDI-TOF mass spectrometry

Acetylcholinesterase (AChE) plays a vital role in the nervous system of insects and other animal species and serves as the target for many chemical agents such as organophosphate and carbamate insecticides. The mosquito, Culex pipiens complex, a vector of human disease, has evolved to be resistant to insecticides by a limited number of amino acid substitutions in AChE1, which is encoded by the ace-1 gene. The aims of this study are to identify single nucleotide polymorphism (SNP) sites in the ace-1 gene of the C. pipiens complex and explore an economical high-throughput method to differentiate the genotypes of these sites in mosquitoes collected in the field. We identified 22 SNP sites in exon regions of the ace-1 gene. Four of them led to non-synonymous mutations, that is, Y163C, G247S, C677S and T682A. We used matrix-assisted laser desorption ionization - time-of-flight mass spectrometry for genotyping at these four sites and another site F416V, which was relevant to insecticide resistance, in 150 mosquitoes collected from 15 field populations. We were able to synchronize analysis of the five SNP sites in each well of a 384-well plate for each individual mosquito, thus decreasing the cost to one-fifth of the routine analysis. Heterozygous genotypes at Y163C and G247S sites were observed in one mosquito. The possible influence of the five SNP sites on the activity or function of the enzyme is discussed based on the predicted tertiary structure of the enzyme.

Inhibition of ovine in vitro fertilization by anti-Prt antibody: hypothetical model for Prt/ZP interaction

BACKGROUND

The impact of prion proteins in the rules that dictate biological reproduction is still poorly understood. Likewise, the role of prnt gene, encoding the prion-like protein testis specific (Prt), in ram reproductive physiology remains largely unknown. In this study, we assessed the effect of Prt in ovine fertilization by using an anti-Prt antibody (APPA) in fertilization medium incubated with spermatozoa and oocytes. Moreover, a computational model was constructed to infer how the results obtained could be related to a hypothetical role for Prt in sperm-zona pellucida (ZP) binding.

METHODS

Mature ovine oocytes were transferred to fertilization medium alone (control) or supplemented with APPA, or pre-immune serum (CSerum). Oocytes were inseminated with ovine spermatozoa and after 18 h, presumptive zygotes (n=142) were fixed to evaluate fertilization rates or transferred (n=374) for embryo culture until D6-7. Predicted ovine Prt tertiary structure was compared with data obtained by circular dichroism spectroscopy (CD) and a protein-protein computational docking model was estimated for a hypothetical Prt/ZP interaction.

RESULTS

The fertilizing rate was lower (P=0.006) in APPA group (46.0+/-6.79%) when compared to control (78.5+/-7.47%) and CSerum (64.5+/-6.65%) groups. In addition, the cleavage rate was higher (P<0.0001) in control (44.1+/-4.15%) than in APPA group (19.7+/-4.22%). Prt CD spectroscopy showed a 22% alpha-helical structure in 30% (m/v) aqueous trifluoroethanol (TFE) and 17% alpha in 0.6% (m/v) TFE. The predominant alpha-helical secondary structure detected correlates with the predicted three dimensional structure for ovine Prt, which was subsequently used to test Prt/ZP docking. Computational analyses predicted a favorable Prt-binding activity towards ZP domains.

CONCLUSIONS

Our data indicates that the presence of APPA reduces the number of fertilized oocytes and of cleaved embryos. Moreover, the CD analysis data reinforces the predicted ovine Prt trend towards an alpha-helical structure. Predicted protein-protein docking suggests a possible interaction between Prt and ZP, thus supporting an important role for Prt in ovine fertilization.

ClusCo: clustering and comparison of protein models

BACKGROUND

The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline.

RESULTS

Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering.

CONCLUSIONS

The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs.

Classifying the metal dependence of uncharacterized nitrogenases

Nitrogenase enzymes have evolved complex iron–sulfur (Fe–S) containing cofactors that most commonly contain molybdenum (MoFe, Nif) as a heterometal but also exist as vanadium (VFe, Vnf) and heterometal-independent (Fe-only, Anf) forms. All three varieties are capable of the reduction of dinitrogen (N₂) to ammonia (NH₃) but exhibit differences in catalytic rates and substrate specificity unique to metal type. Recently, N₂ reduction activity was observed in archaeal methanotrophs and methanogens that encode for nitrogenase homologs which do not cluster phylogenetically with previously characterized nitrogenases. To gain insight into the metal cofactors of these uncharacterized nitrogenase homologs, predicted three-dimensional structures of the nitrogenase active site metal-cofactor binding subunits NifD, VnfD, and AnfD were generated and compared. Dendrograms based on structural similarity indicate nitrogenase homologs cluster based on heterometal content and that uncharacterized nitrogenase D homologs cluster with NifD, providing evidence that the structure of the enzyme has evolved in response to metal utilization. Characterization of the structural environment of the nitrogenase active site revealed amino acid variations that are unique to each class of nitrogenase as defined by heterometal cofactor content; uncharacterized nitrogenases contain amino acids near the active site most similar to NifD. Together, these results suggest that uncharacterized nitrogenase homologs present in numerous anaerobic methanogens, archaeal methanotrophs, and firmicutes bind FeMo-co in their active site, and add to growing evidence that diversification of metal utilization likely occurred in an anoxic habitat.

Computational design of glutamate dehydrogenase in Bacillus subtilis natto

Bacillus subtilis natto is widely used in industry to produce natto, a traditional and popular Japanese soybean food. However, during its secondary fermentation, high amounts of ammonia are released to give a negative influence on the flavor of natto. Glutamate dehydrogenase (GDH) is a key enzyme for the ammonia produced and released, because it catalyzes the oxidative deamination of glutamate to alpha-ketoglutarate using NAD(+) or NADP(+) as co-factor during carbon and nitrogen metabolism processes. To solve this problem, we employed multiple computational methods model and re-design GDH from Bacillus subtilis natto. Firstly, a structure model of GDH with cofactor NADP(+) was constructed by threading and ab initio modeling. Then the substrate glutamate were flexibly docked into the structure model to form the substrate-binding mode. According to the structural analysis of the substrate-binding mode, Lys80, Lys116, Arg196, Thr200, and Ser351 in the active site were found could form a significant hydrogen bonding network with the substrate, which was thought to play a crucial role in the substrate recognition and position. Thus, these residues were then mutated into other amino acids, and the substrate binding affinities for each mutant were calculated. Finally, three single mutants (K80A, K116Q, and S351A) were found to have significant decrease in the substrate binding affinities, which was further supported by our biochemical experiments.

An improved method to detect correct protein folds using partial clustering

Background

Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient “partial“ clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods.

Results

We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either C_α RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite.

Conclusions

The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance.

Antiviral potential of 4-hydroxypanduratin A, secondary metabolite of Fingerroot, Boesenbergia pandurata (Schult.), towards Japanese Encephalitis virus NS2B/NS3 protease

4-hydroxypanduratin A is a secondary metabolite of Boesenbergia pandurata Schult. (Fingerroot) plant with various pharmacological activities such as neuroprotective, potent antioxidant, antibacterial and antifungal. Flaviviral NS2B/NS3 protease activity is essential for polyprotein processing and viral replication for Japanese Encephalitis Virus (JEV), a major cause of Acute Encephaltis in Asia. Inhibition of formation of this complex by arresting the binding of NS2B with NS3 would reduce the enzyme's activity to meager proportions and hence would prevent further viral proliferation. The automated 3D structure of NS2B protein of the JEV GP78 was predicted based on the sequence-to-structure-to-function paradigm using I-TASSER and the function of NS2B protein was inferred by matching to other known proteins. The stereochemical quality of predicted structure was checked by PROCHECK. The antiviral activity of 4-hydroxypanduratin A against NS2B protein as a potential drug has been elucidated in this paper. Docking simulation analysis showed 4-hydroxypanduratin A as potential inhibitor of NS2B protein/cofactor which is necessary for NS3 protease activity. 220 derivatives of 4-hydroxypanduratin A were virtually screened with rigid criteria of Lipinski's rule of 5 using Autodock4.2. 4-hydroxypanduratin A was found interacting with target hydrophilic domain in NS2B protein by two Hbonds (Gly80 and Asp81) with active residues, several hydrophobic interactions, Log P value of 5.6, inhibition constant (Ki) of 51.07nM and lowest binding energy of -9.95Kcal/Mol. Hence, 4-hydroxypanduratin A targeted to Site 2 will have sufficient profound effect to inhibit protease activity to abrogate viral replication. It could be a promising potential drug candidate for JEV infections using NS2B Site 2 as a Drug target.

Fast algorithm for population-based protein structural model analysis

De novo protein structure prediction often generates a large population of candidates (models), and then selects near-native models through clustering. Existing structural model clustering methods are time consuming due to pairwise distance calculation between models. In this paper, we present a novel method for fast model clustering without losing the clustering accuracy. Instead of the commonly used pairwise root mean square deviation and TM-score values, we propose two new distance measures, Dscore1 and Dscore2, based on the comparison of the protein distance matrices for describing the difference and the similarity among models, respectively. The analysis indicates that both the correlation between Dscore1 and root mean square deviation and the correlation between Dscore2 and TM-score are high. Compared to the existing methods with calculation time quadratic to the number of models, our Dscore1-based clustering achieves a linearly time complexity while obtaining almost the same accuracy for near-native model selection. By using Dscore2 to select representatives of clusters, we can further improve the quality of the representatives with little increase in computing time. In addition, for large size (~500 k) models, we can give a fast data visualization based on the Dscore distribution in seconds to minutes. Our method has been implemented in a package named MUFOLD-CL, available at http://mufold.org/clustering.php.

The electrostatic profile of consecutive Cβ atoms applied to protein structure quality assessment

The structure of a protein provides insight into its physiological interactions with other components of the cellular soup. Methods that predict putative structures from sequences typically yield multiple, closely-ranked possibilities. A critical component in the process is the model quality assessing program (MQAP), which selects the best candidate from this pool of structures. Here, we present a novel MQAP based on the physical properties of sidechain atoms. We propose a method for assessing the quality of protein structures based on the electrostatic potential difference (EPD) of Cβ atoms in consecutive residues. We demonstrate that the EPDs of Cβ atoms on consecutive residues provide unique signatures of the amino acid types. The EPD of Cβ atoms are learnt from a set of 1000 non-homologous protein structures with a resolution cuto of 1.6 Å obtained from the PISCES database. Based on the Boltzmann hypothesis that lower energy conformations are proportionately sampled more, and on Annsen's thermodynamic hypothesis that the native structure of a protein is the minimum free energy state, we hypothesize that the deviation of observed EPD values from the mean values obtained in the learning phase is minimized in the native structure. We achieved an average specificity of 0.91, 0.94 and 0.93 on hg_structal, 4state_reduced and ig_structal decoy sets, respectively, taken from the Decoys `R' Us database. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.

In silico studies of C 3 metabolic pathway proteins of wheat (Triticum aestivum)

Photosynthesis is essential for plant productivity and critical for plant growth. More than 90% of plants have a C₃ metabolic pathway primarily for carbon assimilation. Improving crop yields for food and fuel is a major challenge for plant biology. To enhance the production of wheat there is need to adopt the strategies that can create the change in plants at the molecular level. During the study we have employed computational bioinformatics and interactomics analysis of C₃ metabolic pathway proteins in wheat. The three-dimensional protein modeling provided insight into molecular mechanism and enhanced understanding of physiological processes and biological systems. Therefore in our study, initially we constructed models for nine proteins involving C₃ metabolic pathway, as these are not determined through wet lab experiment (NMR, X-ray Crystallography) and not available in RCSB Protein Data Bank and UniProt KB. On the basis of docking interaction analysis, we proposed the schematic diagram of C₃ metabolic pathway. Accordingly, there also exist vice versa interactions between 3PGK and Rbcl. Future site and directed mutagenesis experiments in C₃ plants could be designed on the basis of our findings to confirm the predicted protein interactions.

LabCaS: labeling calpain substrate cleavage sites from amino acid sequence using conditional random fields

The calpain family of Ca(2+) -dependent cysteine proteases plays a vital role in many important biological processes which is closely related with a variety of pathological states. Activated calpains selectively cleave relevant substrates at specific cleavage sites, yielding multiple fragments that can have different functions from the intact substrate protein. Until now, our knowledge about the calpain functions and their substrate cleavage mechanisms are limited because the experimental determination and validation on calpain binding are usually laborious and expensive. In this work, we aim to develop a new computational approach (LabCaS) for accurate prediction of the calpain substrate cleavage sites from amino acid sequences. To overcome the imbalance of negative and positive samples in the machine-learning training which have been suffered by most of the former approaches when splitting sequences into short peptides, we designed a conditional random field algorithm that can label the potential cleavage sites directly from the entire sequences. By integrating the multiple amino acid features and those derived from sequences, LabCaS achieves an accurate recognition of the cleave sites for most calpain proteins. In a jackknife test on a set of 129 benchmark proteins, LabCaS generates an AUC score 0.862. The LabCaS program is freely available at: http://www.csbio.sjtu.edu.cn/bioinf/LabCaS. Proteins 2013. © 2012 Wiley Periodicals, Inc.

Toward optimal fragment generations for ab initio protein structure assembly

Fragment assembly using structural motifs excised from other solved proteins has shown to be an efficient method for ab initio protein-structure prediction. However, how to construct accurate fragments, how to derive optimal restraints from fragments, and what the best fragment length is are the basic issues yet to be systematically examined. In this work, we developed a gapless-threading method to generate position-specific structure fragments. Distance profiles and torsion angle pairs are then derived from the fragments by statistical consistency analysis, which achieved comparable accuracy with the machine-learning-based methods although the fragments were taken from unrelated proteins. When measured by both accuracies of the derived distance profiles and torsion angle pairs, we come to a consistent conclusion that the optimal fragment length for structural assembly is around 10, and at least 100 fragments at each location are needed to achieve optimal structure assembly. The distant profiles and torsion angle pairs as derived by the fragments have been successfully used in QUARK for ab initio protein structure assembly and are provided by the QUARK online server at http://zhanglab.ccmb. med.umich.edu/QUARK/.

PSP toxin release from the cyanobacterium Raphidiopsis brookii D9 (Nostocales) can be induced by sodium and potassium ions

Paralytic shellfish poisoning (PSP) toxins are a group of naturally occurring neurotoxic alkaloids produced among several genera of primarily freshwater cyanobacteria and marine dinoflagellates. Although saxitoxin (STX) and analogs are all potent Na(+) channel blockers in vertebrate cells, the functional role of these compounds for the toxigenic microorganisms is unknown. Based upon the known importance of monovalent cations (such as sodium) in the maintenance of cellular homeostasis and ion channel function, we examined the effect of high extracellular concentrations of these ions on growth, cellular integrity, toxin production and release to the external medium in the filamentous freshwater cyanobacterium, Raphidiopsis brookii D9; a gonyautoxins (GTX2/3) and STX producing toxigenic strain. We observed a toxin export in response to high (17 mM) NaCl and KCl concentrations in the growth medium that was not primarily related to osmotic stress effects, compared to the osmolyte mannitol. Addition of exogenous PSP toxins with the same compositional profile as the one produced by R. brookii D9 was able to partially mitigate this effect of high Na⁺ (17 mM). The PSP toxin biosynthetic gene cluster (sxt) in D9 has two genes (sxtF and sxtM) that encode for a MATE (multidrug and toxic compound extrusion) transporter. This protein family, represented by NorM in the bacterium Vibrio parahaemolyticus, confers resistance to multiple cationic toxic agents through Na⁺/drug antiporters. Conserved domains for Na⁺ and drug recognition have been described in NorM. For the D9 sxt cluster, the Na⁺ recognition domain is conserved in both SxtF and SxtM, but the drug recognition domain differs between them. These results suggest that PSP toxins are exported directly in response to the presence of monovalent cations (Na⁺, K⁺) at least at elevated concentrations. Thus, the presence of both genes in the sxt cluster from strain D9 can be explained as a selective recognition mechanism by the SxtF/M transporters for GTX2/3 and STX. We propose that these toxins in cyanobacteria could act extracellularly as a protective mechanism to ensure homeostasis against extreme salt variation in the environment.

Structure and location of the regulatory β subunits in the (αβγδ)4 phosphorylase kinase complex

Phosphorylase kinase (PhK) is a hexadecameric (αβγδ)(4) complex that regulates glycogenolysis in skeletal muscle. Activity of the catalytic γ subunit is regulated by allosteric activators targeting the regulatory α, β, and δ subunits. Three-dimensional EM reconstructions of PhK show it to be two large (αβγδ)(2) lobes joined with D(2) symmetry through interconnecting bridges. The subunit composition of these bridges was unknown, although indirect evidence suggested the β subunits may be involved in their formation. We have used biochemical, biophysical, and computational approaches to not only address the quaternary structure of the β subunits within the PhK complex, i.e. whether they compose the bridges, but also their secondary and tertiary structures. The secondary structure of β was determined to be predominantly helical by comparing the CD spectrum of an αγδ subcomplex with that of the native (αβγδ)(4) complex. An atomic model displaying tertiary structure for the entire β subunit was constructed using chemical cross-linking, MS, threading, and ab initio approaches. Nearly all this model is covered by two templates corresponding to glycosyl hydrolase 15 family members and the A subunit of protein phosphatase 2A. Regarding the quaternary structure of the β subunits, they were directly determined to compose the four interconnecting bridges in the (αβγδ)(4) kinase core, because a β(4) subcomplex was observed through both chemical cross-linking and top-down MS of PhK. The predicted model of the β subunit was docked within the bridges of a cryoelectron microscopic density envelope of PhK utilizing known surface features of the subunit.

New insights regarding protein folding as learned from beta-sheets

The folding of denatured proteins into their native conformations is called Anfinsen's dogma, and is the rationale for predicting protein structures based on primary sequences. Through the last 40 years of study, all available algorithms which either predict 3D or 2D protein structures, or predict the rate of protein folding based on the amino acid sequence alone, are limited in accuracy (80 %). This fact has led some researchers to look for the lost information, from mRNA to protein sequences, and it encourages us to rethink the rationale of Anfinsen's dogma. In this study, we focus on the relationship between the strand and its partners. We find two rules based on a non-redundant dataset taken from the PDB database. We refer to these two rules as the "first coming first pairing" rule and the "loveless" rule. The first coming first pairing rule indicates that a given strand prefers to pair with the next strand, if the connected region is flexible enough. The loveless rule means that the affinities between a given strand and another strand are comparable to the affinity between the given strand and its partner. Of course, the affinities between the given strand and a helix/coil peptide are significantly less than the affinity between the given strand and its partner. These two rules suggest that in protein folding, we have folding taking place during translation, and suggest also that a denatured protein is not the same as its primary sequence. Rechecking the original Anfinsen experiments, we find that the method used to denature protein in the experiment simply breaks the disulfide bonds, while the helices and sheets remain intact. In other words, denatured proteins still retain all helices and beta sheets, while the primary sequence does not. Although further verification via biological experiments is needed, our results as shown in this study may reveal a new insight for studying protein folding.

S-Glutathionylation underscores the modulation of the heteromeric Kir4.1-Kir5.1 channel in oxidative stress

The Kir4.1 channel is expressed in the brainstem, retina and kidney where it acts on K(+) transportation and pH-dependent membrane potential regulation. Its heteromerization with Kir5.1 leads to K(+) currents with distinct properties such as single-channel conductance, rectification, pH sensitivity and phosphorylation modulation. Here we show that Kir5.1 also enables S-glutathionylation to the heteromeric channel. Expressed in HEK cells, an exposure to the oxidant H(2)O(2) or diamide produced concentration-dependent inhibitions of the whole-cell Kir4.1-Kir5.1 currents. In inside-out patches, currents were inhibited strongly by a combination of diamide/GSH or H(2)O(2)/GSH but not by either alone. The currents were also suppressed by GSSG and the thiol oxidants pyridine disulfides (PDSs), suggesting S-glutathionylation. In contrast, none of the exposures had significant effects on the homomeric Kir4.1 channel. Cys158 in the TM2 helix of Kir5.1 was critical for the S-glutathionylation, which was accessible to intracellular but not extracellular oxidants. Site-directed mutagenesis of this residue (C158A or C158T) abolished the Kir4.1-Kir5.1 current modulation by oxidants, and eliminated almost completely the biochemical interaction of Kir5.1 with GSH. In tandem Kir4.1-Kir5.1 constructs, the channel with a single Cys158 was inhibited to the same degree as the wild-type channel, suggesting that one glutathione moiety is sufficient to block the channel. Consistent with the location of Cys158, GSSG inhibited the channel only when the channel was open, indicating that the channel inhibition was state dependent. The finding that the heteromeric Kir4.1-Kir5.1 channel but not the homomeric Kir4.1 is subject to the S-glutathionylation thus suggests a novel Kir4.1-Kir5.1 channel modulation mechanism that is likely to occur in oxidative stress.

Pharmacological Evaluation and Docking Studies of 3-Thiadiazolyl- and Thioxo-1,2,4-triazolylcoumarin Derivatives as Cholinesterase Inhibitors

Inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) is considered a promising strategy for the treatment of Alzheimer's disease (AD). This research project aims to provide a comprehensive knowledge of newly synthesized coumarin analogues with anti-AD potential. In the present work a series of 3-thiadiazolyl- and thioxo-1,2,4-triazolylcoumarins derivatives were designed, synthesized, and tested as potent inhibitors of cholinesterases. These compounds were assayed against AChE from electrophorus electricus and rabbit; and BChE from horse serum and rabbit by Ellman's method using neostigmine methylsulphate and donepezil as reference drugs. Some of the assayed compounds proved to be potent inhibitors of AChE and BChE with K_i values in the micromolar range. 4b was found to be the most active compound with K_i value 0.028 ± 0.002 μM and higher selectivity for AChE/BChE. The ability of 4b to interact with AChE was further confirmed through computational studies, in which a primary binding was proved to occur at the active gorge site, and a secondary binding was revealed at the peripheral anionic site. Structure activity relationships of prepared compounds were also discussed.