Mol Biosyst [JOURNAL]
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200 papers
Imbalance in amino acid and purine metabolisms at the hypothalamus in inflammation-associated depression by GC-MS.
Wu Y, Li Y, Jia Y … +7 more , Wei C, Xu H, Guo R, Li Y, Jia J, Qi X, Gao X
Mol Biosyst · 2017 Nov · PMID 29160327 · Publisher ↗
Hypothalamic dysfunction is a key factor in depression; increasing evidence highlights neuroinflammation abnormalities as well as imbalances in neurotransmitters and the purinergic system in the pathophysiology of depres...
Hypothalamic dysfunction is a key factor in depression; increasing evidence highlights neuroinflammation abnormalities as well as imbalances in neurotransmitters and the purinergic system in the pathophysiology of depression. However, little is known about the metabolomic changes in the hypothalamus of depressed patients with neuroinflammation. Herein, taking advantage of the well-established lipopolysaccharide (LPS)-induced depression mouse model, we measured metabolic changes in the hypothalamus using gas chromatography-mass spectrometry (GC-MS). Sucrose preference test (SPT), open field test (OFT), forced swimming test (FST), and tail suspension test (TST) were conducted to assess our depressive model. To better understand the metabolic disturbances occurring in the hypothalamus of depressed mice, multivariate statistics were applied to analyse the clinical significance of differentially expressed metabolites in the hypothalamus of mice with LPS-induced depression. Bioinformatic analysis was conducted to detect potential relationships among the changed metabolites. The data confirmed that mice with LPS-induced depression were good mimics of depression patients in some characteristic symptoms such as decreased sucrose intake and increased immobility. In our study, 27 differentially expressed metabolites were identified in the hypothalamus of mice with LPS-induced depression. Herein, seventeen of these metabolites decreased, whereas 10 metabolites increased. These molecular changes were closely related to perturbations in the amino acid and purine metabolisms. Our data indicate that dysfunction of amino acid and purine metabolisms is one of main characteristics of inflammation-mediated depression. These results provide new insights into the mechanisms underlying depression, which may shed some light on the role of the hypothalamus in the pathogenesis of inflammation-mediated depression.
Correction: Dynamic properties of dipeptidyl peptidase III from Bacteroides thetaiotaomicron and the structural basis for its substrate specificity - a computational study.
Tomin M, Tomić S
Mol Biosyst · 2017 Nov · PMID 29130463 · Publisher ↗
Correction for 'Dynamic properties of dipeptidyl peptidase III from Bacteroides thetaiotaomicron and the structural basis for its substrate specificity - a computational study' by M. Tomin et al., Mol. BioSyst., 2017, 13...
Correction for 'Dynamic properties of dipeptidyl peptidase III from Bacteroides thetaiotaomicron and the structural basis for its substrate specificity - a computational study' by M. Tomin et al., Mol. BioSyst., 2017, 13, 2407-2417.
Conformational heterogeneity in tails of DNA-binding proteins is augmented by proline containing repeats.
Khare H, Dey D, Madhu C … +4 more , Senapati D, Raghothama S, Govindaraju T, Ramakumar S
Mol Biosyst · 2017 Nov · PMID 29104984 · Publisher ↗
A cationic terminal extension or tail is a common feature of many DNA-binding proteins. We show that a particular type of tail rich in proline, alanine and lysine belongs to the class of 'flexible disorder' and consists...
A cationic terminal extension or tail is a common feature of many DNA-binding proteins. We show that a particular type of tail rich in proline, alanine and lysine belongs to the class of 'flexible disorder' and consists of characteristic pentapeptide repeats. Our designed peptides, (AAKKA) and (PAKKA), represent the tails of several bacterial DNA-binding proteins. Enhanced conformational sampling of these representative peptides using accelerated molecular dynamic simulations supported by circular dichroism spectroscopy and nuclear magnetic resonance studies demonstrates the role of frequent and interspersed prolines in augmenting conformational heterogeneity of the peptide backbone. Analysis of circular variance of backbone dihedral angles indicates alternating regions of relative rigidity and flexibility along the peptide sequence due to prolines. Preferred placement of lysines in the regions of higher backbone flexibility might improve DNA-binding by conformational selection. Our results could be relevant for rational de novo design of disordered peptides.
Mechanism of the formation of the RecA-ssDNA nucleoprotein filament structure: a coarse-grained approach.
Mukherjee G, Pal A, Levy Y
Mol Biosyst · 2017 Nov · PMID 29104981 · Publisher ↗
In prokaryotes, the RecA protein catalyzes the repair and strand exchange of double-stranded DNA. RecA binds to single-stranded DNA (ssDNA) and forms a presynaptic complex in which the protein polymerizes around the ssDN...
In prokaryotes, the RecA protein catalyzes the repair and strand exchange of double-stranded DNA. RecA binds to single-stranded DNA (ssDNA) and forms a presynaptic complex in which the protein polymerizes around the ssDNA to form a right-handed helical nucleoprotein filament structure. In the present work, the mechanism for the formation of the RecA-ssDNA filament structure is modeled using coarse-grained molecular dynamics simulations. Information from the X-ray structure was used to model the protein itself but not its interactions; the interactions between the protein and the ssDNA were modeled solely by electrostatic, aromatic, and repulsive energies. For the present study, the monomeric, dimeric, and trimeric units of RecA and 4, 8, and 11 NT-long ssDNA, respectively, were studied. Our results indicate that monomeric RecA is not sufficient for nucleoprotein filament formation; rather, dimeric RecA is the elementary binding unit, with higher multimeric units of RecA facilitating filament formation. Our results reveal that loop region flexibility at the primary binding site of RecA is essential for it to bind the incoming ssDNA, that the aromatic residues present in the loop region play an important role in ssDNA binding, and that ATP may play a role in guiding the ssDNA by changing the electrostatic potential of the RecA protein.
Staphylococcus aureus extracellular vesicles (EVs): surface-binding antagonists of biofilm formation.
Im H, Lee S, Soper SA … +1 more , Mitchell RJ
Mol Biosyst · 2017 Nov · PMID 29104975 · Full text
The prevalence of Staphylococcus aureus worldwide as a nosocomial infectious agent is recognized but the reason behind the spread of this bacterium has remained elusive. Here, we hypothesized that the communication of S....
The prevalence of Staphylococcus aureus worldwide as a nosocomial infectious agent is recognized but the reason behind the spread of this bacterium has remained elusive. Here, we hypothesized that the communication of S. aureus might benefit from it blocking other bacteria from establishing themselves on the surface. This was found to be the case for several pathogens as the S. aureus supernatant curtailed their ability to form biofilms. Subsequent analyses using Acinetobacter baumannii as a model found this effect is primarily mediated by S. aureus' extracellular vesicles (EVs), which bound to the polystyrene surface. We found the EV-treated surfaces were significantly more hydrophilic after EV treatment, a condition that made it difficult for A. baumannii to initially adhere to the polystyrene surface and reduced its resulting biofilm by up to 93%. Subsequent tests found this also extended to several other bacterial pathogens, with a 40-70% decrease in their biofilm mass. The S. aureus EVs and their activity still remained after the surface was washed with 10% bleach, while the use of ethylenediaminetetraacetic acid (EDTA) removed both the EVs from the surface and their activity.
Development of an AlphaLISA high throughput technique to screen for small molecule inhibitors targeting protein arginine methyltransferases.
Prabhu L, Chen L, Wei H … +7 more , Demir Ö, Safa A, Zeng L, Amaro RE, O'Neil BH, Zhang ZY, Lu T
Mol Biosyst · 2017 Nov · PMID 29099132 · Full text
The protein arginine methyltransferase (PRMT) family of enzymes comprises nine family members in mammals. They catalyze arginine methylation, either monomethylation or symmetric/asymmetric dimethylation of histone and no...
The protein arginine methyltransferase (PRMT) family of enzymes comprises nine family members in mammals. They catalyze arginine methylation, either monomethylation or symmetric/asymmetric dimethylation of histone and non-histone proteins. PRMT methylation of its substrate proteins modulates cellular processes such as signal transduction, transcription, and mRNA splicing. Recent studies have linked overexpression of PRMT5, a member of the PRMT superfamily, to oncogenesis, making it a potential target for cancer therapy. In this study, we developed a highly sensitive (Z' score = 0.7) robotic high throughput screening (HTS) platform to discover small molecule inhibitors of PRMT5 by adapting the AlphaLISA™ technology. Using biotinylated histone H4 as a substrate, and S-adenosyl-l-methionine as a methyl donor, PRMT5 symmetrically dimethylated H4 at arginine (R) 3. Highly specific acceptor beads for symmetrically dimethylated H4R3 and streptavidin-coated donor beads bound the substrate, emitting a signal that is proportional to the methyltransferase activity. Using this powerful approach, we identified specific PRMT5 inhibitors P1608K04 and P1618J22, and further validated their efficacy and specificity for inhibiting PRMT5. Importantly, these two compounds exhibited much more potent efficacy than the commercial PRMT5 inhibitor EPZ015666 in both pancreatic and colorectal cancer cells. Overall, our work highlights a novel, powerful, and sensitive approach to identify specific PRMT5 inhibitors. The general principle of this HTS screening method can not only be applied to PRMT5 and the PRMT superfamily, but may also be extended to other epigenetic targets. This approach allows us to identify compounds that inhibit the activity of their respective targets, and screening hits like P1608K04 and P1618J22 may serve as the basis for novel drug development to treat cancer and/or other diseases.
Host immune evasion strategies of malaria blood stage parasite.
Yam XY, Preiser PR
Mol Biosyst · 2017 Nov · PMID 29091093 · Publisher ↗
Host immune evasion is a key strategy for the continual survival of many microbial pathogens including Apicomplexan protozoan: Plasmodium spp., the causative agent of Malaria. The malaria parasite has evolved a variety o...
Host immune evasion is a key strategy for the continual survival of many microbial pathogens including Apicomplexan protozoan: Plasmodium spp., the causative agent of Malaria. The malaria parasite has evolved a variety of mechanisms to evade the host immune responses within its two hosts: the female Anopheles mosquito vector and vertebrate host. In this review, we will focus on the molecular mechanisms of the immune evasion strategies used by the Plasmodium parasite at the blood stage which is responsible for the clinical manifestations of human malaria. We also aim to provide some insights on the potential targets for malaria interventions through the recent advancement in understanding the molecular biology of the parasite.
Pharmacology of predatory and defensive venom peptides in cone snails.
Prashanth JR, Dutertre S, Lewis RJ
Mol Biosyst · 2017 Nov · PMID 29090697 · Publisher ↗
Cone snails are predatory gastropods whose neurotoxic venom peptides (conotoxins) have been extensively studied for pharmacological probes, venom evolution mechanisms and potential therapeutics. Conotoxins have a wide ra...
Cone snails are predatory gastropods whose neurotoxic venom peptides (conotoxins) have been extensively studied for pharmacological probes, venom evolution mechanisms and potential therapeutics. Conotoxins have a wide range of structural and functional classes that continue to undergo accelerated evolution that underlies the rapid expansion of the genus over their short evolutionary history. A number of pharmacological classes, driven by separately evolved defensive and predatory venoms, have been hypothesised to facilitate shifts in prey that exemplify the adaptability of cone snails. Here we provide an overview of these pharmacological families and discuss their ecological roles and evolutionary impact.
Model system based proteomics to understand the host response during bacterial infections.
Kamaladevi A, Marudhupandiyan S, Balamurugan K
Mol Biosyst · 2017 Nov · PMID 29082410 · Publisher ↗
Infectious diseases caused by bacterial pathogens pose a major concern to public health and, thus, greater attention must be given to providing insightful knowledge on host-pathogen interactions. There are several theori...
Infectious diseases caused by bacterial pathogens pose a major concern to public health and, thus, greater attention must be given to providing insightful knowledge on host-pathogen interactions. There are several theories addressing the dynamics of complex mechanisms of host-pathogen interactions. The availability of an ample number of universally accepted model systems, including vertebrates, invertebrates, and mammalian cells, provides in-depth transcriptomics data to evaluate these complex mechanisms during host-pathogen interactions. Recent model system based proteomic studies have addressed the issues related to human diseases by establishing the protein profile of model animals that closely resemble the environment. As a result, model system based proteomics has been widely accepted as a powerful and effective approach to understand the highly complex host-pathogen interfaces at their protein levels. This review offers a snapshot of the contributions of selective model systems on host-bacterial pathogen interactions through proteomic approaches.
An interaction network approach to study the correlation between endocrine disrupting chemicals and breast cancer.
Polo A, Nittoli C, Crispo A … +8 more , Langastro T, Cocco S, Severino L, De Laurentiis M, Ciliberto G, Montella M, Budillon A, Costantini S
Mol Biosyst · 2017 Nov · PMID 29072741 · Publisher ↗
Endocrine disrupting chemicals (EDCs) are natural or synthetic exogenous substances affecting human health. Although present at low concentrations in the environment, they can cause a broad range of negative effects on t...
Endocrine disrupting chemicals (EDCs) are natural or synthetic exogenous substances affecting human health. Although present at low concentrations in the environment, they can cause a broad range of negative effects on the endocrine functions by mimicking the action of steroid hormones due to their structural similarity. Hormonal unbalance can play an important role in carcinogenesis at any stage of disease. In the case of the breast cancer, EDCs directly affect the transformation of normal breast cells into cancer cells by interfering with hormonal regulation and by inducing the alteration of factors that regulate gene expression. The principal aims of this work were to study the interaction networks of proteins modulated in breast cancer by either environmental EDCs or mycotoxins, and to identify the proteins with the strongest coordination role defined as hub nodes. Our studies evidenced the presence of seven and six hub proteins in two EDCs and mycotoxins networks, respectively. Then, by merging the two networks, we identified that three hub nodes (BCL2, ESR2 and CTNNB1) in the environmental EDCs network show direct interactions with three hub nodes (CASP8, RELA and MKI67) in the mycotoxins network. These data highlighted that two networks are linked through proteins involved in the apoptosis regulation and in processes related to cell proliferation and survival, and, thus, in breast cancer progression.
Hybrid deterministic/stochastic simulation of complex biochemical systems.
Lecca P, Bagagiolo F, Scarpa M
Mol Biosyst · 2017 Nov · PMID 29058744 · Publisher ↗
In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by complex networks of chemical reactions involving genes, proteins, and enzymes. Accurate computational models...
In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by complex networks of chemical reactions involving genes, proteins, and enzymes. Accurate computational models are indispensable means for understanding the mechanisms behind the evolution of a complex system, not always explored with wet lab experiments. To serve their purpose, computational models, however, should be able to describe and simulate the complexity of a biological system in many of its aspects. Moreover, it should be implemented by efficient algorithms requiring the shortest possible execution time, to avoid enlarging excessively the time elapsing between data analysis and any subsequent experiment. Besides the features of their topological structure, the complexity of biological networks also refers to their dynamics, that is often non-linear and stiff. The stiffness is due to the presence of molecular species whose abundance fluctuates by many orders of magnitude. A fully stochastic simulation of a stiff system is computationally time-expensive. On the other hand, continuous models are less costly, but they fail to capture the stochastic behaviour of small populations of molecular species. We introduce a new efficient hybrid stochastic-deterministic computational model and the software tool MoBioS (MOlecular Biology Simulator) implementing it. The mathematical model of MoBioS uses continuous differential equations to describe the deterministic reactions and a Gillespie-like algorithm to describe the stochastic ones. Unlike the majority of current hybrid methods, the MoBioS algorithm divides the reactions' set into fast reactions, moderate reactions, and slow reactions and implements a hysteresis switching between the stochastic model and the deterministic model. Fast reactions are approximated as continuous-deterministic processes and modelled by deterministic rate equations. Moderate reactions are those whose reaction waiting time is greater than the fast reaction waiting time but smaller than the slow reaction waiting time. A moderate reaction is approximated as a stochastic (deterministic) process if it was classified as a stochastic (deterministic) process at the time at which it crosses the threshold of low (high) waiting time. A Gillespie First Reaction Method is implemented to select and execute the slow reactions. The performances of MoBios were tested on a typical example of hybrid dynamics: that is the DNA transcription regulation. The simulated dynamic profile of the reagents' abundance and the estimate of the error introduced by the fully deterministic approach were used to evaluate the consistency of the computational model and that of the software tool.
The nucleosomal surface is the main target of histone ADP-ribosylation in response to DNA damage.
Karch KR, Langelier MF, Pascal JM … +1 more , Garcia BA
Mol Biosyst · 2017 Nov · PMID 29058739 · Full text
ADP-ribosylation is a protein post-translational modification catalyzed by ADP-ribose transferases (ARTs). ART activity is critical in mediating many cellular processes, and is required for DNA damage repair. All five hi...
ADP-ribosylation is a protein post-translational modification catalyzed by ADP-ribose transferases (ARTs). ART activity is critical in mediating many cellular processes, and is required for DNA damage repair. All five histone proteins are extensively ADP-ribosylated by ARTs upon induction of DNA damage. However, how these modifications aid in repair processes is largely unknown, primarily due to lack of knowledge about where they site-specifically occur on histones. Here, we conduct a comprehensive analysis of histone Asp/Glu ADP-ribosylation sites upon DNA damage induced by dimethyl sulfate (DMS). We also demonstrate that incubation of cell nuclei with NAD, as has been done previously in the literature, leads to spurious ADP-ribosylation levels of histone proteins. Altogether, we were able to identify 30 modification sites, 20 of which are novel. We also quantify the abundance of these modification sites during the course of DNA damage insult to identify which sites are critical for mediating repair. We found that every quantifiable site increases in abundance over time and that each identified ADP-ribosylation site is located on the surface of the nucleosome. Together, the data suggest specific Asp/Glu residues are unlikely to be critical for DNA damage repair and rather that this process is likely dependent on ADP-ribosylation of the nucleosomal surface in general.
NARRMDA: negative-aware and rating-based recommendation algorithm for miRNA-disease association prediction.
Peng L, Chen Y, Ma N … +1 more , Chen X
Mol Biosyst · 2017 Nov · PMID 29053164 · Publisher ↗
An increasing amount of evidence indicates that microRNAs (miRNAs) are closely related to many important biological processes and play a significant role in various human diseases. More and more researchers have begun to...
An increasing amount of evidence indicates that microRNAs (miRNAs) are closely related to many important biological processes and play a significant role in various human diseases. More and more researchers have begun to seek effective methods to predict potential miRNA-disease associations. However, reliable computational methods to predict potential disease-related miRNAs are lacking. In this study, we developed a new miRNA-disease association prediction model called Negative-Aware and rating-based Recommendation algorithm for miRNA-Disease Association prediction (NARRMDA) based on the known miRNA-disease associations in the HMDD database, miRNA functional similarity, disease semantic similarity and Gaussian interaction profile kernel similarity. NARRMDA combined a rating-based recommendation algorithm and a negative-aware algorithm to score and rank miRNAs without known associations with investigated diseases. Furthermore, we used leave-one-out cross validation to evaluate the accuracy of NARRMDA and compared NARRMDA with four previous classical prediction models (RLSMDA, HDMP, RWRMDA and MCMDA). As it turned out, NARRMDA and the other four prediction models achieved AUCs of 0.8053, 0.6953, 0.7702, 0.7891 and 0.7718, respectively, which proved that NARRMDA has superior performance of prediction accuracy. Furthermore, we verified the prediction results associated with colon neoplasms, esophageal neoplasms, lymphoma and breast neoplasms by two different validation schemas. In these case studies, 92%, 84%, 92%, and 100% of the top 50 potential miRNAs for these four diseases were confirmed by experimental discoveries, respectively. These results further show that NARRMDA has reliable performance of prediction ability.
Insights into human intrinsically disordered proteins from their gene expression profile.
Panda A, Acharya D, Chandra Ghosh T
Mol Biosyst · 2017 Nov · PMID 29051952 · Publisher ↗
Expression level provides important clues about gene function. Previously, various efforts have been undertaken to profile human genes according to their expression level. Intrinsically disordered proteins (IDPs) do not...
Expression level provides important clues about gene function. Previously, various efforts have been undertaken to profile human genes according to their expression level. Intrinsically disordered proteins (IDPs) do not adopt any rigid conformation under physiological conditions, however, are considered as an important functional class in all domains of life. Based on a human tissue-averaged gene expression level, previous studies showed that IDPs are expressed at a lower level than ordered globular proteins. Here, we examined the gene expression pattern of human ordered and disordered proteins in 32 normal tissues. We noticed that in most of the tissues, ordered and disordered proteins are expressed at a similar level. Moreover, in a number of tissues IDPs were found to be expressed at a higher level than ordered proteins. Rigorous statistical analyses suggested that the lower tissue-averaged gene expression level of IDPs (reported earlier) may be the consequence of their biased gene expression in some specific tissues and higher protein length. When we considered the gene repertory of each tissue we noticed that a number of human tissues (brain, testes, etc.) selectively express a higher fraction of disordered proteins, which help them to maintain higher protein connectivity by forming disordered binding motifs and to sustain their functional specificities. Our results demonstrated that the disordered proteins are indispensable in these tissues for their functional advantages.
Pre-steady-state kinetic analysis of damage recognition by human single-strand selective monofunctional uracil-DNA glycosylase SMUG1.
Kuznetsova AA, Iakovlev DA, Misovets IV … +4 more , Ishchenko AA, Saparbaev MK, Kuznetsov NA, Fedorova OS
Mol Biosyst · 2017 Nov · PMID 29051947 · Publisher ↗
In all organisms, DNA glycosylases initiate base excision repair pathways resulting in removal of aberrant bases from DNA. Human SMUG1 belongs to the superfamily of uracil-DNA glycosylases catalyzing the hydrolysis of th...
In all organisms, DNA glycosylases initiate base excision repair pathways resulting in removal of aberrant bases from DNA. Human SMUG1 belongs to the superfamily of uracil-DNA glycosylases catalyzing the hydrolysis of the N-glycosidic bond of uridine and uridine lesions bearing oxidized groups at C5: 5-hydroxymethyluridine (5hmU), 5-formyluridine (5fU), and 5-hydroxyuridine (5hoU). An apurinic/apyrimidinic (AP) site formed as the product of an N-glycosylase reaction is tightly bound to hSMUG1, thus inhibiting the downstream action of AP-endonuclease APE1. The steady-state kinetic parameters (k and K; obtained from the literature) correspond to the enzyme turnover process limited by the release of hSMUG1 from the complex with the AP-site. In the present study, our objective was to carry out a stopped-flow fluorescence analysis of the interaction of hSMUG1 with a DNA substrate containing a dU:dG base pair to follow the pre-steady-state kinetics of conformational changes in both molecules. A comparison of kinetic data obtained by means of Trp and 2-aminopurine fluorescence and Förster resonance energy transfer (FRET) detection allowed us to elucidate the stages of specific and nonspecific DNA binding, to propose the mechanism of damaged base recognition by hSMUG1, and to determine the true rate of the catalytic step. Our results shed light on the kinetic mechanism underlying the initiation of base excision repair by hSMUG1 using the "wedge" strategy for DNA lesion search.
Methods for monitoring and measurement of protein translation in time and space.
Dermit M, Dodel M, Mardakheh FK
Mol Biosyst · 2017 Nov · PMID 29051942 · Full text
Regulation of protein translation constitutes a crucial step in control of gene expression. In comparison to transcriptional regulation, however, translational control has remained a significantly under-studied layer of...
Regulation of protein translation constitutes a crucial step in control of gene expression. In comparison to transcriptional regulation, however, translational control has remained a significantly under-studied layer of gene expression. This trend is now beginning to shift thanks to recent advances in next-generation sequencing, proteomics, and microscopy based methodologies which allow accurate monitoring of protein translation rates, from single target messenger RNA molecules to genome-wide scale studies. In this review, we summarize these recent advances, and discuss how they are enabling researchers to study translational regulation in a wide variety of in vitro and in vivo biological systems, with unprecedented depth and spatiotemporal resolution.
Molecular dynamics simulations of β2-microglobulin interaction with hydrophobic surfaces.
Dongmo Foumthuim CJ, Corazza A, Esposito G … +1 more , Fogolari F
Mol Biosyst · 2017 Nov · PMID 29051937 · Publisher ↗
Hydrophobic surfaces are known to adsorb and unfold proteins, a process that has been studied only for a few proteins. Here we address the interaction of β2-microglobulin, a paradigmatic protein for the study of amyloido...
Hydrophobic surfaces are known to adsorb and unfold proteins, a process that has been studied only for a few proteins. Here we address the interaction of β2-microglobulin, a paradigmatic protein for the study of amyloidogenesis, with hydrophobic surfaces. A system with 27 copies of the protein surrounded by a model cubic hydrophobic box is studied by implicit solvent molecular dynamics simulations. Most proteins adsorb on the walls of the box without major distortions in local geometry, whereas free molecules maintain proper structures and fluctuations as observed in explicit solvent molecular dynamics simulations. The major conclusions from the simulations are as follows: (i) the adopted implicit solvent model is adequate to describe protein dynamics and thermodynamics; (ii) adsorption occurs readily and is irreversible on the simulated timescale; (iii) the regions most involved in molecular encounters and stable interactions with the walls are the same as those that are important in protein-protein and protein-nanoparticle interactions; (iv) unfolding following adsorption occurs at regions found to be flexible by both experiments and simulations; (v) thermodynamic analysis suggests a very large contribution from van der Waals interactions, whereas unfavorable electrostatic interactions are not found to contribute much to adsorption energy. Surfaces with different degrees of hydrophobicity may occur in vivo. Our simulations show that adsorption is a fast and irreversible process which is accompanied by partial unfolding. The results and the thermodynamic analysis presented here are consistent with and rationalize previous experimental work.
Hedgehog-mesenchyme gene signature identifies bi-modal prognosis in luminal and basal breast cancer sub-types.
Torres-García W, Domenech M
Mol Biosyst · 2017 Nov · PMID 29034935 · Full text
Hedgehog signaling (Hh) has been shown to be hyper-activated in several cancers. However, active Hh signaling can promote or inhibit tumor growth; thus identification of markers beyond main canonical Hh target genes is n...
Hedgehog signaling (Hh) has been shown to be hyper-activated in several cancers. However, active Hh signaling can promote or inhibit tumor growth; thus identification of markers beyond main canonical Hh target genes is needed to improve patient selection and clinical outcome in response to Hh inhibitors. Cancer-associated fibroblasts (CAFs) have been linked with tumor progression and beneficial response to Hh inhibitors. Thus, we hypothesized that genes associated with Hh-activated CAFs can be used for stratification of tumors that will benefit from Hh inhibitors. In this work, we evaluated a 15-gene fingerprint that combines Hh and mesenchymal genes associated with CAF phenotype to profile breast cancer sub-types based on gene expression patterns among clustered groups. About 3800 cancer samples were evaluated using random forest models and linear discriminant analysis to sort breast cancer by subtypes and therapeutic approach. The results showed that the Hh-mesenchyme gene fingerprint has a highly sensitive and differential expression pattern among basal and luminal A sub-groups. Basal samples with high levels of Hh target genes had better prognosis than luminal A samples. Luminal A samples with a tendency towards Hh signaling suppression had higher overall and disease-free survival rates particularly if deprived of hormone therapy. Hh transcriptional repressor GLI3 and signaling activator SMO were the top 2 genes for discriminating among samples with active Hh signaling in human breast cancer subtypes and Hh-inhibitor resistant tumors. Caveolin-1 (CAV1), a gene with low expression in CAFs, shows strong correlation with active Hh signaling and discrimination among survival curves in luminal A patients with active or inactive Hh signaling. Our data suggest that CAV1 is an important gene for monitoring Hh inhibition in tumors and support further stratification by hormone therapy status prior to use of Hh inhibitors.
Exploring the role of GS-GOGAT cycle in microcystin synthesis and regulation - a model based analysis.
Banerjee S, Subramanian A, Chattopadhyay J … +1 more , Sarkar RR
Mol Biosyst · 2017 Nov · PMID 29034927 · Publisher ↗
Toxic cyanobacteria blooms populate water bodies by consuming external nutrients and releasing cyanotoxins that are detrimental for other aquatic species, producing a significant impact on the plankton ecosystem and food...
Toxic cyanobacteria blooms populate water bodies by consuming external nutrients and releasing cyanotoxins that are detrimental for other aquatic species, producing a significant impact on the plankton ecosystem and food web. To exercise population-level control of toxin production, understanding the biochemical mechanisms that explain cyanotoxin regulation within a bacterial cell is of utmost importance. In this study, we explore the mechanistic events to investigate the dependence of toxin microcystin on external nitrogen, a known regulator of the toxin, and for the first time, propose a kinetic model that analyzes the intracellular conditions required to ensure nitrogen dependence on microcystin. We hypothesize that the GS-GOGAT cycle is manipulated by variable influx of different intracellular metabolites that can either disturb or promote the balance between the enzyme microcystin synthetase and substrate glutamate to produce variable microcystin levels. As opposed to the popular notion that nitrogen starvation increases microcystin synthesis, our analyses suggest that under certain intracellular metabolite regimes, this relationship can either be completely lost or reversed. External nitrogen can only complement the conditions fixed by intracellular glutamate, glutamine and 2-oxoglutarate. This mechanistic understanding can provide an experimentally testable hypothesis for exploring the less-known biology of microcystin synthesis and designing specific interventions.
A Bayesian approach for estimating protein-protein interactions by integrating structural and non-structural biological data.
Ur Rehman H, Bari I, Ali A … +1 more , Mahmood H
Mol Biosyst · 2017 Nov · PMID 29028065 · Publisher ↗
Accurate elucidation of genome wide protein-protein interactions is crucial for understanding the regulatory processes of the cell. High-throughput techniques, such as the yeast-2-hybrid (Y2H) assay, co-immunoprecipitati...
Accurate elucidation of genome wide protein-protein interactions is crucial for understanding the regulatory processes of the cell. High-throughput techniques, such as the yeast-2-hybrid (Y2H) assay, co-immunoprecipitation (co-IP), mass spectrometric (MS) protein complex identification, affinity purification (AP) etc., are generally relied upon to determine protein interactions. Unfortunately, each type of method is inherently subject to different types of noise and results in false positive interactions. On the other hand, precise understanding of proteins, especially knowledge of their functional associations is necessary for understanding how complex molecular machines function. To solve this problem, computational techniques are generally relied upon to precisely predict protein interactions. In this work, we present a novel method that combines structural and non-structural biological data to precisely predict protein interactions. The conceptual novelty of our approach lies in identifying and precisely associating biological information that provides substantial interaction clues. Our model combines structural and non-structural information using Bayesian statistics to calculate the likelihood of each interaction. The proposed model is tested on Saccharomyces cerevisiae's interactions extracted from the DIP and IntAct databases and provides substantial improvements in terms of accuracy, precision, recall and F1 score, as compared with the most widely used related state-of-the-art techniques.
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