Mol Biosyst [JOURNAL]
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200 papers
A multiscale agent-based framework integrated with a constraint-based metabolic network model of cancer for simulating avascular tumor growth.
Ghadiri M, Heidari M, Marashi SA … +1 more , Mousavi SH
Mol Biosyst · 2017 Aug · PMID 28737788 · Publisher ↗
In recent years, many efforts have been made in the field of computational modeling of cancerous tumors, in order to obtain a better understanding and predictions of their growth patterns. Furthermore, constraint-based m...
In recent years, many efforts have been made in the field of computational modeling of cancerous tumors, in order to obtain a better understanding and predictions of their growth patterns. Furthermore, constraint-based modeling of metabolic networks has become increasingly popular, which is appropriate for the systems-level reconstruction of cell physiology. The goal of the current study is to integrate a multiscale agent-based modeling framework with a constraint-based metabolic network model of cancer cells in order to simulate the three dimensional early growth of avascular tumors. In order to develop the integrated model, a previously published generic metabolic network model of cancer cells was introduced into a multiscale agent-based framework. This model is initiated with a single tumor cell. Nutrients can diffuse through the simulation space and the cells uptake or excrete metabolites, grow, proliferate or become necrotic based on certain defined criteria and flux values of particular reactions. The simulation was run for a period of 20 days and the plots corresponding to various features such as the growth profile and necrotic core evolution were obtained. These features were compared with the ones observed in other (experimental) studies. One interesting characteristic of our modeling is that it provides us with the ability to predict gene expression patterns through different layers of a tumor, which can have important implications, especially in drug target selection in the field of cancer therapy.
DBA-induced caspase-3-dependent apoptosis occurs through mitochondrial translocation of cyt-c in the rat hippocampus.
Jiang W, Chen Y, Li B … +1 more , Gao S
Mol Biosyst · 2017 Aug · PMID 28731097 · Publisher ↗
Dibromoacetic acid (DBA), a by-product of disinfection, develops in drinking water during chlorination or ozonation processes. Water intake is the main source of DBA exposure in humans, which is potentially neurotoxic. T...
Dibromoacetic acid (DBA), a by-product of disinfection, develops in drinking water during chlorination or ozonation processes. Water intake is the main source of DBA exposure in humans, which is potentially neurotoxic. The present study investigated the neurotoxic effects of DBA by assessing the behavioral and biochemical characteristics of Sprague Dawley rats intragastrically treated with DBA at concentrations of 20, 50 and 125 mg kg body weight for 28 consecutive days. The results indicated that animal weight gain and food consumption were not significantly affected by DBA. However, shuttle box tests showed increases in mistake frequency and reaction latency between the control and high-dose group. We found significant changes in hippocampal neurons by histomorphological observation. Additionally, biochemical analysis indicated enhanced production of reactive oxygen species (ROS) resulting in disruption of cellular antioxidant defense systems including decreased mitochondrial superoxide dismutase (SOD) activity and release of cytochrome c (cyt-c) from mitochondria into the cytosol, which can induce neuronal apoptosis. Furthermore, the increase of cyt-c in the cytosol enhanced caspase-3 and caspase-9 activity, which was confirmed by poly ADP-ribose polymerase-1 (PARP-1) cleavage to its signature fragment of 85 kDa and decreased levels of protein kinase C-δ (PKC-δ) in the hippocampus. Meanwhile, DBA treatment caused differential modulation of apoptosis-associated proteins and mRNAs for phosphorylated apoptosis signal regulating kinase 1 (p-ASK-1), phosphorylated c-jun N-terminal kinase (p-JNK), cyt-c, Bax, Bcl-2, caspase-9 and cleaved caspase-3 accompanied by DNA damage. Taken together, these data indicate that DBA may induce neurotoxicity via caspase-3-dependent apoptosis involving mitochondrial translocation of cyt-c in the rat hippocampus.
Association of cultured myotubes and fasting plasma metabolite profiles with mitochondrial dysfunction in type 2 diabetes subjects.
Abu Bakar MH, Sarmidi MR
Mol Biosyst · 2017 Aug · PMID 28726959 · Publisher ↗
Accumulating evidence implicates mitochondrial dysfunction-induced insulin resistance in skeletal muscle as the root cause for the greatest hallmarks of type 2 diabetes (T2D). However, the identification of specific meta...
Accumulating evidence implicates mitochondrial dysfunction-induced insulin resistance in skeletal muscle as the root cause for the greatest hallmarks of type 2 diabetes (T2D). However, the identification of specific metabolite-based markers linked to mitochondrial dysfunction in T2D has not been adequately addressed. Therefore, we sought to identify the markers-based metabolomics for mitochondrial dysfunction associated with T2D. First, a cellular disease model was established using human myotubes treated with antimycin A, an oxidative phosphorylation inhibitor. Non-targeted metabolomic profiling of intracellular-defined metabolites on the cultured myotubes with mitochondrial dysfunction was then determined. Further, a targeted MS-based metabolic profiling of fasting blood plasma from normal (n = 32) and T2D (n = 37) subjects in a cross-sectional study was verified. Multinomial logical regression analyses for defining the top 5% of the metabolites within a 95% group were employed to determine the differentiating metabolites. The myotubes with mitochondrial dysfunction exhibited insulin resistance, oxidative stress and inflammation with impaired insulin signalling activities. Four metabolic pathways were found to be strongly associated with mitochondrial dysfunction in the cultured myotubes. Metabolites derived from these pathways were validated in an independent pilot investigation of the fasting blood plasma of healthy and diseased subjects. Targeted metabolic analysis of the fasting blood plasma with specific baseline adjustment revealed 245 significant features based on orthogonal partial least square discriminant analysis (PLS-DA) with a p-value < 0.05. Among these features, 20 significant metabolites comprised primarily of branched chain and aromatic amino acids, glutamine, aminobutyric acid, hydroxyisobutyric acid, pyroglutamic acid, acylcarnitine species (acetylcarnitine, propionylcarnitine, dodecenoylcarnitine, tetradecenoylcarnitine hexadecadienoylcarnitine and oleylcarnitine), free fatty acids (palmitate, arachidonate, stearate and linoleate) and sphingomyelin (d18:2/16:0) were identified as predictive markers for mitochondrial dysfunction in T2D subjects. The current study illustrates how cellular metabolites provide potential signatures associated with the biochemical changes in the dysregulated body metabolism of diseased subjects. Our finding yields additional insights into the identification of robust biomarkers for T2D associated with mitochondrial dysfunction in cultured myotubes.
Peculiarities of thermal denaturation of OmpF porin from Yersinia ruckeri.
Novikova OD, Chistyulin DK, Khomenko VA … +7 more , Sidorin EV, Kim NY, Sanina NM, Portnyagina OY, Solov'eva TF, Uversky VN, Shnyrov VL
Mol Biosyst · 2017 Aug · PMID 28726924 · Publisher ↗
Irreversible denaturation of membrane proteins in detergent solutions is similar to unfolding of water-soluble multidomain proteins and represents a complex, multistage process. Pore-forming proteins of Gram-negative bac...
Irreversible denaturation of membrane proteins in detergent solutions is similar to unfolding of water-soluble multidomain proteins and represents a complex, multistage process. Pore-forming proteins of Gram-negative bacteria are heat-modifiable proteins, i.e., proteins altering their molecular forms (trimers or monomers), and accordingly, their electrophoretic mobilities depending upon denaturation conditions. There are still some contradictory data on the peculiarities of the conformational changes in the porin structure with temperature. Some authors demonstrated the loss of the porin trimeric structure only after unfolding of monomer subunits. Other researchers initially observed the dissociation of porin oligomers into the folded monomers. Using SDS-PAGE, spectroscopic methods and differential scanning calorimetry, a detailed study of thermally induced changes in the spatial structure of OmpF porin from the fish pathogen Yersinia ruckeri (Yr-OmpF) was carried out. The data obtained allowed us to conclude unambiguously that changes in the spatial structure of the monomers of Yr-OmpF precede the dissociation of the porin trimer.
Molecular dynamics simulations and in vitro analysis of the CRMP2 thiol switch.
Möller D, Gellert M, Langel W … +1 more , Lillig CH
Mol Biosyst · 2017 Aug · PMID 28726921 · Publisher ↗
The collapsin response mediator protein CRMP2 (gene: DPYSL2) is crucial for neuronal development. The homotetrameric CRMP2 complex is regulated via two mechanisms: first by phosphorylation and second by the reduction and...
The collapsin response mediator protein CRMP2 (gene: DPYSL2) is crucial for neuronal development. The homotetrameric CRMP2 complex is regulated via two mechanisms: first by phosphorylation and second by the reduction and oxidation of the Cys504 residues of two adjacent subunits. Here, we have analysed the effects of this redox switch on the protein in vitro combined with force field molecular dynamics (MD). Earlier X-ray data reveal the structure of the rigid body of the molecule but lack the flexible C-terminus with the important sites for phosphorylation and redox regulation. An in silico model for this part was established by replica exchange simulations and homology modelling, which is consistent with the CD spectroscopy results of the recombinant protein. Thermofluor data indicated that the protein aggregates at bivalent ion concentrations below 200 mM. In simulations the protein surface was covered under these conditions by a large number of ions, which most likely prevent aggregation. A tryptophan residue (Trp295) in close proximity to the forming disulphide allowed the measurement of the structural relaxation of the rigid body upon reduction by fluorescence quenching. We were also able to determine the second-order rate constant of CRMP2 oxidation by HO. The simulated solvent accessible surface of the hydroxyl group of Ser518 significantly increased upon reduction of the disulphide bond. Our results give the first detailed insight into the profound structural changes of the tetrameric CRMP2 due to oxidation and indicate a tightly connected regulation by phosphorylation and redox modification.
An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency.
Guo WL, Huang DS
Mol Biosyst · 2017 Aug · PMID 28718849 · Publisher ↗
Transcription factors (TFs) are DNA-binding proteins that have a central role in regulating gene expression. Identification of DNA-binding sites of TFs is a key task in understanding transcriptional regulation, cellular...
Transcription factors (TFs) are DNA-binding proteins that have a central role in regulating gene expression. Identification of DNA-binding sites of TFs is a key task in understanding transcriptional regulation, cellular processes and disease. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) enables genome-wide identification of in vivo TF binding sites. However, it is still difficult to map every TF in every cell line owing to cost and biological material availability, which poses an enormous obstacle for integrated analysis of gene regulation. To address this problem, we propose a novel computational approach, TFBSImpute, for predicting additional TF binding profiles by leveraging information from available ChIP-seq TF binding data. TFBSImpute fuses the dataset to a 3-mode tensor and imputes missing TF binding signals via simultaneous completion of multiple TF binding matrices with positional consistency. We show that signals predicted by our method achieve overall similarity with experimental data and that TFBSImpute significantly outperforms baseline approaches, by assessing the performance of imputation methods against observed ChIP-seq TF binding profiles. Besides, motif analysis shows that TFBSImpute preforms better in capturing binding motifs enriched in observed data compared with baselines, indicating that the higher performance of TFBSImpute is not simply due to averaging related samples. We anticipate that our approach will constitute a useful complement to experimental mapping of TF binding, which is beneficial for further study of regulation mechanisms and disease.
A comparative review of computational methods for pathway perturbation analysis: dynamical and topological perspectives.
Vanhaelen Q, Aliper AM, Zhavoronkov A
Mol Biosyst · 2017 Aug · PMID 28714509 · Publisher ↗
Stem cells offer great promise within the field of regenerative medicine but despite encouraging results, the large scale use of stem cells for therapeutic applications still faces challenges when it comes to controlling...
Stem cells offer great promise within the field of regenerative medicine but despite encouraging results, the large scale use of stem cells for therapeutic applications still faces challenges when it comes to controlling signaling pathway responses with respect to environmental perturbations. This step is critical for the elaboration of stable and reproducible differentiation protocols, and computational modeling can be helpful to overcome these difficulties. This article is a comparative review of the mechanism-based methods used for hypothesis-driven approaches and data-driven methods which are two types of computational approaches commonly used for analysing the dynamics of pathways involved in stem cell regulation. We firstly review works based on kinetic modelling. We emphasize the relationships between the dynamics of these pathways and their topological features, and illustrative examples are described to show how the analysis of these relationships can contribute to a more detailed and formal understanding of the signaling dynamics. This discussion is followed by a review of the recent data-driven pathway analysis methods. Based on a simplified description of the pathways, these methods are able to handle high dimensionality data, and topological features of the pathways taken into account in the latest methods improve both accuracy and predictive power. Nevertheless, progress is still needed to clarify the biological meaning of the topological decompositions used by these methods.
The antiproliferative activity of di-2-pyridylketone dithiocarbamate is partly attributed to catalase inhibition: detailing the interaction by spectroscopic methods.
Li C, Liu Y, Fu Y … +3 more , Huang T, Kang L, Li C
Mol Biosyst · 2017 Aug · PMID 28714505 · Publisher ↗
The bioactivity of drugs is attributed to their interaction with biological molecules, embodied in either their direct or indirect influence on enzyme activity and conformation. Di-2-pyridylketone hydrazine dithiocarbama...
The bioactivity of drugs is attributed to their interaction with biological molecules, embodied in either their direct or indirect influence on enzyme activity and conformation. Di-2-pyridylketone hydrazine dithiocarbamate (DpdtC) exhibits significant antitumor activity in our preliminary study. We speculated that its activity may partly stem from enzyme inhibition due to strong metal chelating ability. To this end, we assessed its effect on catalase from erythrocytes and found evidence of inhibition, which was further confirmed by ROS determination in vivo. Thus, detailing the interaction between the agent and catalase via spectroscopic methods and molecular docking was required to obtain information on both the dynamics and thermodynamic parameters. The Lineweaver-Burk plot implied an uncompetitive pattern between DpdtC and catalase from beef liver, and IC = ∼7 μM. The thermodynamic parameters from fluorescence quenching measurements indicated that DpdtC could bind to catalase with moderate affinity (K = approximately 10 M). CD spectra revealed that DpdtC could significantly disrupt the secondary structure of catalase. Docking studies indicated that DpdtC bound to a flexible region of catalase, involving hydrogen bonds and salt bond; this was consistent with thermodynamic results from spectral investigations. Our data clearly showed that catalase inhibition of DpdtC was not due to direct chelation of iron from heme (killing), but through an allosteric effect. Thus, it can be concluded that the antiproliferative activity of DpdtC is partially attributed to its catalase inhibition.
Insights into the RNA binding mechanism of human L1-ORF1p: a molecular dynamics study.
Rajagopalan M, Balasubramanian S, Ramaswamy A
Mol Biosyst · 2017 Aug · PMID 28714502 · Publisher ↗
The recognition and binding of nucleic acids by ORF1p, an L1 retrotransposon protein, have not yet been clearly understood due to the lack of structural knowledge. The present study attempts to identify the probable sing...
The recognition and binding of nucleic acids by ORF1p, an L1 retrotransposon protein, have not yet been clearly understood due to the lack of structural knowledge. The present study attempts to identify the probable single-stranded RNA binding pathway of trimeric ORF1p using computational methods like ligand mapping methodology combined with molecular dynamics simulations. Using the ligand mapping methodology, the possible RNA interacting sites on the surface of the trimeric ORF1p were identified. The crystal structure of the ORF1p timer and an RNA molecule of 29 nucleotide bases in length were used to generate the structure of the ORF1p complex based on information on predicted binding sites as well as the functional states of the CTD. The various complexes of ORF1p-RNA were generated using polyU, polyA and L1RNA sequences and were simulated for a period of 75 ns. The observed stable interaction pattern was used to propose the possible binding pathway. Based on the binding free energy for complex formation, both polyU and L1RNA complexes were identified as stable complexes, while the complex formed with polyA was the least stable one. Furthermore, the importance of the residues in the CC domain (Lys137 and Arg141), the RRM loop (Arg206, Arg210 and Arg211) and the CTD (Arg 261 and Arg262) of all three chains in stabilizing the wrapped RNA has been highlighted in this study. The presence of several electrostatic interactions including H-bond interactions increases the affinity towards RNA and hence plays a vital role in retaining the wrapped position of RNA around ORF1p. Altogether, this study presents one of the possible RNA binding pathways of ORF1p and clearly highlights the functional state of ORF1p visited during RNA binding.
Understanding the role of tyrosine in glycogenin.
Camiruaga A, Usabiaga I, Insausti A … +3 more , Cocinero EJ, León I, Fernández JA
Mol Biosyst · 2017 Aug · PMID 28714501 · Publisher ↗
We explored the molecular basis of tyrosine as the docking amino acid for the first glucose molecule during the synthesis of glycogen. The IR spectra show that the aromatic ring acts as bait to keep the position where th...
We explored the molecular basis of tyrosine as the docking amino acid for the first glucose molecule during the synthesis of glycogen. The IR spectra show that the aromatic ring acts as bait to keep the position where the next glucose unit has to bind clear, by luring non-desirable molecules towards the aromatic ring. Only, α-/β-glucose shows particular affinity for the O3H and O4H moieties.
Structural switch from a multistranded G-quadruplex to single strands as a consequence of point mutation in the promoter of the human GRIN1 gene.
Chaudhary S, Kaushik M, Kukreti R … +1 more , Kukreti S
Mol Biosyst · 2017 Aug · PMID 28702665 · Publisher ↗
A huge number of G-rich sequences forming quadruplexes are found in the human genome, especially in telomeric regions, UTRs, and the promoter regions of a number of genes. One such gene is GRIN1 encoding the NR1 subunit...
A huge number of G-rich sequences forming quadruplexes are found in the human genome, especially in telomeric regions, UTRs, and the promoter regions of a number of genes. One such gene is GRIN1 encoding the NR1 subunit of the N-methyl-d-aspartate receptor (NMDA). Several lines of reports have implicated that attenuated function of NMDA results in schizophrenia, a genetic disorder characterized by hallucinations, delusions, and psychosis. Involvement of the GRIN1 gene in the pathogenesis of schizophrenia has been extensively analysed. Recent reports have demonstrated that polymorphism in the promoter region of GRIN1 at position -855 (G/C) has a possible association with schizophrenia. The binding site for the NF-κB transcription factor gets altered due to this mutation, resulting in reduced gene expression as well as NMDA activity. By combining gel electrophoresis (PAGE), circular dichroism (CD) and CD melting techniques, the G → C single nucleotide polymorphism (SNP) at the G-rich sequence (d-CTTAGCCCGAGGAG[combining low line]GGGGGTCCCAAGT; GRIN1) was investigated. We report that the GRIN1 sequence can form an octameric/multistranded quadruplex structure with parallel conformation in the presence of K as well as Na. CD and gel studies are in good correlation in order to detect molecularity and strand conformation. The parallel G-quadruplex species was hypothesized to be octameric in K/Na salts. The mutated sequence (d-CTTAGCCCGAGGAC[combining low line]GGGGGTCCCAAGT; GRIN1M) remained single stranded under physiological conditions. CD melting studies support the formation of an interstranded G-quadruplex structure by the GRIN1 sequence. Two structural models are propounded for a multistranded parallel G-quadruplex conformation which might be responsible for regulating the gene expression normally underlying memory and learning.
An enhanced hTERT promoter-driven CRISPR/Cas9 system selectively inhibits the progression of bladder cancer cells.
Huang X, Zhuang C, Zhuang C … +3 more , Xiong T, Li Y, Gui Y
Mol Biosyst · 2017 Aug · PMID 28702647 · Publisher ↗
The current therapies for treating tumors are lacking in efficacy and specificity. Synthetic biology principles may bring some new possible methods for curing cancer. Here we present a synthetic logic circuit based on th...
The current therapies for treating tumors are lacking in efficacy and specificity. Synthetic biology principles may bring some new possible methods for curing cancer. Here we present a synthetic logic circuit based on the CRISPR/Cas9 system. The CRISPR/Cas9 technology has been applied in many biological fields, including cancer research. In this study, the expression of Cas9 nuclease was controlled indirectly by an enhanced hTERT promoter using the GAL4/upstream activating sequence (UAS) binding system. Cas9 was driven by 5XUAS, single guide RNA (sgRNA) was used to target mutant or wild-type HRAS, and the fusion gene GAL4-P65 was driven by the enhanced hTERT promoter. The system was tested in bladder cancer cells (T24 and 5637) and the results showed that the enhanced hTERT promoter could drive the expression of GAL4-P65 in these bladder cancer cell lines. Then all these devices were packed into lentivirus and the results of quantitative real-time PCR showed that the mRNA expression level of HRAS was selectively inhibited in the T24 and 5637 cells. The results of functional experiments suggested that the proliferation, cell migration and invasion were selectively suppressed, and that the apoptosis rate was increased in bladder cancer cells but not in human foreskin fibroblasts (HFF). In conclusion, we successfully constructed an enhanced hTERT promoter-driven CRISPR/Cas9 system and data showed that it could selectively suppress the progression of bladder cancer cells.
Identification of perturbed signaling pathways from gene expression data using information divergence.
Hu X, Wei H, Zheng H
Mol Biosyst · 2017 Aug · PMID 28702621 · Publisher ↗
Abnormal regulation of signaling pathways is the key causative factor in several diseases. Although many methods have been proposed to identify significantly differential pathways between two conditions via microarray ge...
Abnormal regulation of signaling pathways is the key causative factor in several diseases. Although many methods have been proposed to identify significantly differential pathways between two conditions via microarray gene expression datasets, most of them concentrate on differences in the pathway components-either the differential expression or the correlation of genes in a given pathway. However, as biological functional units, signaling pathways may have diverse activity patterns across different biological contexts. In order to detect overall changes in pathways, we propose an analysis model called SPAID (Signaling Pathway Analysis based on Information Divergence). SPAID is based on the concept of information divergence, which can be used to compare two conditions by computing the differential probability distribution of the regulation capacity. We compared SPAID with several classical algorithms using different datasets, and the results indicate that SPAID produces higher repeatability, has better performance and universality, and extracts more comprehensive information regarding the underlying biological processes. In conclusion, by introducing the idea of information divergence, our study measures differences in pathways from an overall perspective and will provide a complementary analysis framework for pathway analysis.
LPI-ETSLP: lncRNA-protein interaction prediction using eigenvalue transformation-based semi-supervised link prediction.
Hu H, Zhu C, Ai H … +4 more , Zhang L, Zhao J, Zhao Q, Liu H
Mol Biosyst · 2017 Aug · PMID 28702594 · Publisher ↗
RNA-protein interactions are essential for understanding many important cellular processes. In particular, lncRNA-protein interactions play important roles in post-transcriptional gene regulation, such as splicing, trans...
RNA-protein interactions are essential for understanding many important cellular processes. In particular, lncRNA-protein interactions play important roles in post-transcriptional gene regulation, such as splicing, translation, signaling and even the progression of complex diseases. However, the experimental validation of lncRNA-protein interactions remains time-consuming and expensive, and only a few theoretical approaches are available for predicting potential lncRNA-protein associations. Here, we presented eigenvalue transformation-based semi-supervised link prediction (LPI-ETSLP) to uncover the relationship between lncRNAs and proteins. Moreover, it is semi-supervised and does not need negative samples. Based on 5-fold cross validation, an AUC of 0.8876 and an AUPR of 0.6438 have demonstrated its reliable performance compared with three other computational models. Furthermore, the case study demonstrated that many lncRNA-protein interactions predicted by our method can be successfully confirmed by experiments. It is indicated that LPI-ETSLP would be a useful bioinformatics resource for biomedical research studies.
pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC.
Cheng X, Xiao X, Chou KC
Mol Biosyst · 2017 Aug · PMID 28702580 · Publisher ↗
One of the fundamental goals in cellular biochemistry is to identify the functions of proteins in the context of compartments that organize them in the cellular environment. To realize this, it is indispensable to develo...
One of the fundamental goals in cellular biochemistry is to identify the functions of proteins in the context of compartments that organize them in the cellular environment. To realize this, it is indispensable to develop an automated method for fast and accurate identification of the subcellular locations of uncharacterized proteins. The current study is focused on plant protein subcellular location prediction based on the sequence information alone. Although considerable efforts have been made in this regard, the problem is far from being solved yet. Most of the existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions. This kind of multiplex protein is particularly important for both basic research and drug design. Using the multi-label theory, we present a new predictor called "pLoc-mPlant" by extracting the optimal GO (Gene Ontology) information into the Chou's general PseAAC (Pseudo Amino Acid Composition). Rigorous cross-validation on the same stringent benchmark dataset indicated that the proposed pLoc-mPlant predictor is remarkably superior to iLoc-Plant, the state-of-the-art method for predicting plant protein subcellular localization. To maximize the convenience of most experimental scientists, a user-friendly web-server for the new predictor has been established at , by which users can easily get their desired results without the need to go through the complicated mathematics involved.
Identifying the common genetic networks of ADR (adverse drug reaction) clusters and developing an ADR classification model.
Hwang Y, Oh M, Jang G … +4 more , Lee T, Park C, Ahn J, Yoon Y
Mol Biosyst · 2017 Aug · PMID 28702565 · Publisher ↗
Adverse drug reactions (ADRs) are one of the major concerns threatening public health and have resulted in failures in drug development. Thus, predicting ADRs and discovering the mechanisms underlying ADRs have become im...
Adverse drug reactions (ADRs) are one of the major concerns threatening public health and have resulted in failures in drug development. Thus, predicting ADRs and discovering the mechanisms underlying ADRs have become important tasks in pharmacovigilance. Identification of potential ADRs by computational approaches in the early stages would be advantageous in drug development. Here we propose a computational method that elucidates the action mechanisms of ADRs and predicts potential ADRs by utilizing ADR genes, drug features, and protein-protein interaction (PPI) networks. If some ADRs share similar features, there is a high possibility that they may appear together in a drug and share analogous mechanisms. Proceeding from this assumption, we clustered ADRs according to interactions of ADR genes in the PPI networks and the frequency of co-occurrence of ADRs in drugs. ADR clusters were verified based on a side effect database and literature data regarding whether ADRs have relevance to other ADRs in the same cluster. Gene networks shared by ADRs in each cluster were constructed by cumulating the shortest paths between drug target genes and ADR genes in the PPI network. We developed a classification model to predict potential ADRs using these gene networks shared by ADRs and calculated cross-validation AUC (area under the curve) values for each ADR cluster. In addition, in order to demonstrate correlations between gene networks shared by ADRs and ADRs in a cluster, we applied the Wilcoxon rank sum statistical test to the literature data and results of a Google query search. We attained statistically meaningful p-values (<0.05) for every ADR cluster. The results suggest that our approach provides insights into discovering the action mechanisms of ADRs and is a novel attempt to predict ADRs in a biological aspect.
Functional roles of intrinsic disorder in CRISPR-associated protein Cas9.
Du Z, Uversky VN
Mol Biosyst · 2017 Aug · PMID 28692085 · Publisher ↗
Protein intrinsic disorder is an important characteristic commonly detected in multifunctional or RNA- and DNA-binding proteins. Due to their high conformational flexibility and solvent accessibility, intrinsically disor...
Protein intrinsic disorder is an important characteristic commonly detected in multifunctional or RNA- and DNA-binding proteins. Due to their high conformational flexibility and solvent accessibility, intrinsically disordered proteins (IDPs) and IDP regions (IDPRs) execute diverse functions including interaction with multiple partners, and are frequently subjected to various post-translational modifications. Recent studies on the components comprising the CRISPR (clustered regularly interspaced short palindromic repeats) system have elucidated the crystal structure of Cas9 proteins and the mechanism by which the Cas9-sgRNA complex recognizes and cleaves its target DNA. Yet the extent and functional implications of intrinsic disorder in the Cas9 protein have never been fully assessed. Here, we present a comprehensive computational analysis based on both sequence and structural data in an attempt to investigate the roles of IDPRs in the functioning of Cas9 proteins of different origin. We conclude that among the functional roles of IDPRs in Cas9 proteins are recognition of the target DNA and mediation of nucleic acid and protein binding.
Modeling of alcohol oxidase enzyme of Candida boidinii and in silico analysis of competitive binding of proton ionophores and FAD with enzyme.
Khan MW, Murali A
Mol Biosyst · 2017 Aug · PMID 28692078 · Publisher ↗
Alcohol oxidase (AOX) is an important flavin adenine dinucleotide (FAD) dependent oxidoreductase, which is responsible for converting methanol into formaldehyde and hydrogen peroxide for the growth of methylotrophic yeas...
Alcohol oxidase (AOX) is an important flavin adenine dinucleotide (FAD) dependent oxidoreductase, which is responsible for converting methanol into formaldehyde and hydrogen peroxide for the growth of methylotrophic yeast Candida boidinii. Although AOX plays a crucial role in methanol catabolism, the experimental structure of AOX from Candida boidinii has not been elucidated. This study reports the first complete in silico model of AOX from C. boidinii. This paper also reports the AOX structure modeled using the threading approach, followed by structure analysis and molecular dynamics simulation. The modeled structure was compared with the aryl alcohol oxidase structure (a glucose-methanol-choline family member, pdbID: 3fim). A docking study was performed to analyze the interaction between AOX and its cofactor FAD. The AOX modeled structure also exhibited high similarity with respect to the FAD binding sites, which are the substrate binding sites as seen with 3fim. It was observed that the adenosine part of FAD was deeply buried inside AOX while the isoalloxazine ring stuck to the surface. This paper reports the interaction of selective proton ionophores (CCCP and DNP) with AOX and also reports their binding sites. These proton ionophores showed competitive binding with FAD. The occupancy of the FAD binding sites by the proton ionophore may lead to blocking of the entry of FAD and thereby disruption of AOX import into peroxisomes.
Identification of microRNA precursors using reduced and hybrid features.
Khan A, Shah S, Wahid F … +2 more , Khan FG, Jabeen S
Mol Biosyst · 2017 Jul · PMID 28686281 · Publisher ↗
MicroRNAs (also called miRNAs) are a group of short non-coding RNA molecules. They play a vital role in the gene expression of transcriptional and post-transcriptional processes. However, abnormality of their expression...
MicroRNAs (also called miRNAs) are a group of short non-coding RNA molecules. They play a vital role in the gene expression of transcriptional and post-transcriptional processes. However, abnormality of their expression has been observed in cancer, heart diseases and nervous system disorders. Therefore for basic research and microRNA based therapy, it is imperative to separate real pre-miRNAs from false ones (hairpin sequences similar to pre-miRNA stem loops). Different conservation and machine learning methods have been applied for the identification of miRNAs. However, machine learning algorithms have gained more popularity than conservative based algorithms in terms of sensitivity and overall performance. Due to the avalanche of RNA sequences discovered in a post-genomic age, it is necessary to construct a predictor for the identification of pre-microRNAs in humans. We have developed a predictor called MicroR-Pred in which the RNA sequences are formulated by a hybrid feature vector. The novelty of the new predictor is in the use of the partial least squares technique followed by the Random Forest and SVM (Support Vector Machine) algorithms for dimension reduction and classification. The performance of the MicroR-Pred model is quite promising compared to other state-of-the-art miRNA predictors. It has achieved 88.40% and 93.90% accuracies for RF and SVM.
C-Peptide replacement therapy in type 1 diabetes: are we in the trough of disillusionment?
Pinger CW, Entwistle KE, Bell TM … +2 more , Liu Y, Spence DM
Mol Biosyst · 2017 Jul · PMID 28685788 · Full text
Type 1 diabetes is associated with such complications as blindness, kidney failure, and nerve damage. Replacing C-peptide, a hormone normally co-secreted with insulin, has been shown to reduce diabetes-related complicati...
Type 1 diabetes is associated with such complications as blindness, kidney failure, and nerve damage. Replacing C-peptide, a hormone normally co-secreted with insulin, has been shown to reduce diabetes-related complications. Interestingly, after nearly 30 years of positive research results, C-peptide is still not being co-administered with insulin to diabetic patients. The following review discusses the potential of C-peptide as an auxilliary replacement therapy and why it's not currently being used as a therapeutic.
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