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Acetylcholinesterase inhibitory activity of scopolin and scopoletin discovered by virtual screening of natural products.

For the targeting selection of acetylcholinesterase (AChE) inhibitors from natural sources we generated a structure-based pharmacophore model utilizing an in silico filtering experiment for the discovery of promising candidates out of a 3D multiconformational database consisting of more than 110,000 natural products. In our study, scopoletin (1) and its glucoside scopolin (2) emerged as potential AChE inhibitors by the virtual screening procedure. They were isolated by different chromatographic methods from the medicinal plant Scopolia carniolica Jaqc. and tested in an enzyme assay using Ellman's reagent. They showed moderate, but significant, dose-dependent and long-lasting inhibitory activities. In the in vivo experiments (icv application of 2 micromol) 1 and 2 increased the extracellular acetylcholine (ACh) concentration in rat brain to about 170% and 300% compared to basal release, respectively. At the same concentration, the positive control galanthamine increased the ACh concentration to about the same level as 1. These are the first in vivo results indicating an effect of coumarins on brain ACh.

Acetylcholine↗

Experimental data of a single promoter can be used for in silico detection of genes with related regulation in the absence of sequence similarity.

Gene expression is presently a major focus in genome analysis, and the experimental data on regulatory mechanisms and functional transcription factor binding sites are steadily growing. However, the annotation of transcriptional regulation of sequences cannot keep pace with the exponential growth of sequence databases. Employing detailed experimental data of a single promoter or enhancer to predict genes with similar regulation would provide a powerful method to link the literature about transcriptional regulation and sequence databases. To this end, we used information on individual functional transcription factor binding sites to compose in silico promoter and enhancer models of muscle-specific genes and to analyze the rodents section of EMBL with these models. Exhaustive evaluation of all hits revealed every second to third match to be a muscle-associated gene. Moreover, functionally related regulatory regions were detected by our model-based approach even in the absence of sequence similarity. We believe that this new approach is a substanial extension to database analysis by BLAST or FASTA, which are restricted to sequence similarity.

Animals↗

Ceramide analogue 14S24 ((S)-2-tetracosanoylamino-3-hydroxypropionic acid tetradecyl ester) is effective in skin barrier repair in vitro.

Stratum corneum ceramides are fundamental for maintaining the skin barrier properties. Their content is decreased in some skin diseases, e.g. atopic dermatitis, and ceramide supplementation is one of the therapeutic approaches. In the present study we have designed novel ceramide analogue 14S24 ((S)-2-tetracosanoylamino-3-hydroxypropionic acid tetradecyl ester) as a potential barrier-repairing agent. We report a convenient two-step synthesis of this analogue with high yields. The ability of 14S24 to repair the disturbed skin barrier was evaluated in vitro on the porcine skin. After 2h application of 14S24 on the skin disrupted by lipid extraction, the permeability decreased significantly almost to the values of the native skin. The compound is effective in 0.1% aqueous suspension and its effect is comparable with physiological skin lipids under the same condition. The comparison of 14S24 and skin ceramides was made via computer modelling and the in silico physico-chemical parameters are reported. We suggest that allylic hydroxyl, that is essential for the apoptogenic activity of ceramides, is not a necessary component of the skin barrier-forming ceramides. The main result of this study is to demonstrate that simpler and easier-to-synthesise ceramide analogues could be effective in the skin barrier repair.

Animals↗

A novel missense mutation in tropomyosin 1 gene associated with hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a common genetic heart disorder that can lead to heart failure or sudden death. Family-based identification of rare sarcomeric variants can support molecular diagnosis and cascade screening in inherited HCM. This study aimed to identify and evaluate a novel TPM1 variant found in a Vietnamese family with HCM. The proband, a 3-year-old boy diagnosed with HCM, and eight relatives from three generations underwent clinical and genetic evaluation. A candidate variant initially identified by targeted next-generation sequencing was validated by PCR and Sanger sequencing. Familial segregation analysis was performed, and variant pathogenicity was assessed according to ACMG guidelines with support from in silico prediction and structural modeling. Sanger sequencing confirmed a heterozygous missense variant in exon 6 of TPM1 NM_001018005.2:c.576G > C, p.(Glu192Asp), in the proband, his father, and paternal grandfather, all of whom exhibited clinical signs of HCM. The variant was absent in unaffected relatives and in public population databases. Based on ACMG criteria (PM1, PM2, PM5, and PP3), the variant was classified as likely pathogenic. This novel TPM1 variant segregated with HCM in a Vietnamese family, expands the known mutational spectrum of TPM1 in hypertrophic cardiomyopathy, and warrants further functional investigation and familial genetic evaluation.

American College of Medical Genetics and Genomics ↗

Metabolic flux analysis in complex isotopolog space. Recycling of glucose in tobacco plants.

Tobacco plants grown in vitro were supplied with a mixture of [U-13C6]glucose and unlabelled sucrose via the root system. After 20 days, leaves were harvested and extracted with water. Glucose was isolated from the extract and was analysed by 13C NMR spectroscopy. All 13C signals appeared as complex multiplets due to 13C-13C coupling. The abundance of 21 isotopologous glucose species was determined from the 13C NMR signal integrals by numerical deconvolution using a genetic algorithm. The relative fractions of specific isotopologs in the overall excess of 13C-labelled specimens establish flux contributions via glycolysis/glucogenesis, pentose phosphate pathway, citric acid cycle and Calvin cycle including 13CO2 refixation. The fluxes were modelled and reconstructed in silico by a novel rule-based approach yielding the contributions of circular pathways and the degree of multiple cycling events. The data indicate that the vast majority of the proffered [U-13C6]glucose molecules had been modified by catabolism and subsequent glucogenesis from catabolic fragments, predominantly via passage through the citric acid cycle and the pentose phosphate pathway.

Algorithms↗

The integration profile of EIAV-based vectors.

Lentiviral vectors based on equine infectious anemia virus (EIAV) stably integrate into dividing and nondividing cells such as neurons, conferring long-term expression of their transgene. The integration profile of an EIAV vector was analyzed in dividing HEK293T cells, alongside an HIV-1 vector as a control, and compared to a random dataset generated in silico. A multivariate regression model was generated and the influence of the following parameters on integration site selection determined: (a) within/not within a gene, (b) GC content within 20 kb, (c) within 10 kb of a CpG island, (d) gene density within a 2-Mb window, and (e) chromosome number. The majority of the EIAV integration sites (68%; n = 458) and HIV-1 integration sites (72%; n = 162) were within a gene, and both vectors favored AT-rich regions. Sites within genes were examined using a second model to determine the influence of the gene-specific parameters, gene region, and transcriptional activity. Both EIAV and HIV-1 vectors preferentially integrated within active genes. Unlike the gammaretrovirus MLV, EIAV and HIV-1 vectors do not integrate preferentially into the promoter region or the 5' end of the transcription unit.

Base Composition↗

Bench meets bedside: a 10-year-old girl and amino acid residue glycine 75 of the facilitative glucose transporter GLUT1.

In 2000, amino acid residue G75 of the facilitative glucose transporter GLUT1 was identified by mutagenesis as being essential for transport function [Olsowski, A., et al. (2000) Biochemistry 39, 2469-74]. In 2002, we identified a heterozygous missense mutation substituting glycine at residue 75 for tryptophan in a 10-year-old girl with intractable seizures and low glucose concentrations in the cerebrospinal fluid indicative of GLUT1 deficiency. Glucose uptake into erythrocytes of the patient was 36% of controls, and GLUT1-specific immunoreactivity was normal, indicating a functional GLUT1 defect. In silico three-dimensional modeling of the G75W mutant provided a smaller gyration radius for transmembrane segment 2 as the potential pathogenic mechanism in this patient. This case illustrates a GLUT1 mutation characterized in vitro and later confirmed by disease itself and highlights the potential of basic science and clinical medicine to collaborate for the benefit of patients.

3-O-Methylglucose↗

The Caenorhabditis elegans muscle specific serpin, SRP-3, neutralizes chymotrypsin-like serine peptidases.

Members of the intracellular serpin family may help regulate apoptosis, tumor progression, and metastasis. However, their in vivo functions in the context of a whole organism have not been easily defined. To better understand the biology of these serpins, we initiated a comparative genomics study using Caenorhabditis elegans as a model organism. Previous in silico analysis suggested that the C. elegans genome harbors nine serpin-like sequences bearing significant similarities to the human clade B intracellular serpins. However, only five genes appear to encode full-length serpins with intact reactive site loops. To determine if this was the case, we have cloned and expressed a putative inhibitory-type C. elegans serpin, srp-3. Analysis of SRP-3 inhibitory activity indicated that SRP-3 was a potent inhibitor of the serine peptidases, chymotrypsin and cathepsin G. Spatial and temporal expression studies using GFP and LacZ promoter fusions indicated that SRP-3 was expressed primarily in the anterior body wall muscles, suggesting that it may play a role in muscle cell homeostasis. Combined with previous studies showing that SRP-2 is an inhibitor of the serine peptidase, granzyme B, and lysosomal cysteine peptidases, these data suggested that C. elegans expressed at least two inhibitory-type serpins with nonoverlapping expression and inhibitory profiles. Moreover, the profiles of these clade L serpins in C. elegans share significant similarities with the profiles of clade B intracellular serpin members in higher vertebrates. This degree of conservation suggests that C. elegans should prove to be a valuable resource in the study of metazoan intracellular serpin function.

Amino Acid Sequence↗

Identification of novel parasitic cysteine protease inhibitors by use of virtual screening. 2. The available chemical directory.

The incidence of parasitic infections such as malaria, leishmaniasis, and trypanosomiasis has been steadily increasing. Since the existing chemotherapy of these diseases suffers from lack of safe and effective drugs and/or the presence of widespread drug resistance, there is an urgent need for development of potent, mechanism-based antiparasitic agents against these diseases. Cysteine proteases have been established as valid targets for this purpose. The Available Chemical Directory consisting of nearly 355,000 compounds was screened in silico against the homology models of plasmodial cysteine proteases, falcipain-2, and falcipain-3, to identify structurally diverse non-peptide inhibitors. The study led to identification of 22 inhibitors of parasitic cysteine proteases out of which 18 compounds were active against falcipain-2 and falcipain-3. Eight compounds exhibited dual activity against both enzymes. Additionally, four compounds were found to inhibit L. donovani cysteine protease. While one of the cysteine protease inhibitors also exhibited in vitro antiplasmodial activity with an IC50 value of 9.5 microM, others did not show noticeable antiplasmodial activity up to 20 microM. A model identifying important pharmacophoric features common to the structurally diverse falcipain-2 inhibitors has also been developed. Very few potent non-peptide inhibitors of the parasitic cysteine proteases have been reported so far, and identification of these novel and chemically diverse inhibitors should provide leads to be optimized into candidates to treat protozoal infections.

Animals↗

The visual language of synteny.

The study of polygenic disorders such as cardiovascular and metabolic diseases requires access to vast amounts of experimental and in silico data. Where animal models of disease are being used, visualization of syntenic genome regions is one of the most important tools supporting data analysis. We define what is required to visualize synteny in terms of the data being displayed, the screen layout, and user interaction. We then describe a prototype visualization tool, SyntenyVista, which provides integrated access to quantitative trait loci, microarray, and gene datasets. We believe that SyntenyVista is a significant step towards an improved representation of comparative genomics data.

Algorithms↗

E-CELL: software environment for whole-cell simulation.

MOTIVATION: Genome sequencing projects and further systematic functional analyses of complete gene sets are producing an unprecedented mass of molecular information for a wide range of model organisms. This provides us with a detailed account of the cell with which we may begin to build models for simulating intracellular molecular processes to predict the dynamic behavior of living cells. Previous work in biochemical and genetic simulation has isolated well-characterized pathways for detailed analysis, but methods for building integrative models of the cell that incorporate gene regulation, metabolism and signaling have not been established. We, therefore, were motivated to develop a software environment for building such integrative models based on gene sets, and running simulations to conduct experiments in silico. RESULTS: E-CELL, a modeling and simulation environment for biochemical and genetic processes, has been developed. The E-CELL system allows a user to define functions of proteins, protein-protein interactions, protein-DNA interactions, regulation of gene expression and other features of cellular metabolism, as a set of reaction rules. E-CELL simulates cell behavior by numerically integrating the differential equations described implicitly in these reaction rules. The user can observe, through a computer display, dynamic changes in concentrations of proteins, protein complexes and other chemical compounds in the cell. Using this software, we constructed a model of a hypothetical cell with only 127 genes sufficient for transcription, translation, energy production and phospholipid synthesis. Most of the genes are taken from Mycoplasma genitalium, the organism having the smallest known chromosome, whose complete 580 kb genome sequence was determined at TIGR in 1995. We discuss future applications of the E-CELL system with special respect to genome engineering. AVAILABILITY: The E-CELL software is available upon request. SUPPLEMENTARY INFORMATION: The complete list of rules of the developed cell model with kinetic parameters can be obtained via our web site at: http://e-cell.org/.

Adenosine Triphosphate↗

DeepGeSeq: deep learning library for genomic sequence modeling and analysis.

MOTIVATION: Deep learning methods have demonstrated significant potential in genomics, enabling broad applications such as sequence activity prediction, regulatory rule identification, and variant effect quantification. However, their widespread adoption is often hindered by the steep computational learning curve required for model construction, training, and downstream biological interpretation. Here, we introduce DeepGeSeq, a user-friendly Deep-learning library tailored for Genomic Sequence modeling and analysis. RESULTS: By integrating state-of-the-art architectural modules, DeepGeSeq streamlines the entire deep learning workflow, requiring minimal user input via a simple configuration file and an intuitive agentic skill. We comprehensively validate the efficacy of DeepGeSeq through diverse case studies, encompassing pipeline verification using synthetic datasets, the reproduction and application of established models, and model fine-tuning coupled with biological interpretation on user-defined data. Furthermore, we demonstrate DeepGeSeq's versatility in domain-specific applications, including single-cell ATAC-seq modeling for cell-type clustering, and MPRA data modeling coupled with in silico saturation mutagenesis to dissect cis-regulatory elements. Ultimately, DeepGeSeq bridges the gap between computational complexity and biological discovery, providing an accessible resource that facilitates the development and broad application of deep learning methods in genomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/JiaqiLi1024/DeepGeSeq.

Deep Learning↗

Investigating metabolite essentiality through genome-scale analysis of Escherichia coli production capabilities.

MOTIVATION: A phenotype mechanism is classically derived through the study of a set of mutants and comparison of their biochemical capabilities. One method of comparing mutant capabilities is to characterize producible and knocked out metabolites. However such an effect is difficult to manually assess, especially for a large biochemical network and a complex media. Current algorithmic approaches towards analyzing metabolic networks either do not address this specific property or are computationally infeasible on the genome-scale. RESULTS: We have developed a novel genome-scale computational approach that identifies the full set of biochemical species that are knocked out from the metabolome following a gene deletion. Results from this approach are combined with data from in vivo mutant screens to examine the essentiality of metabolite production for a phenotype. This approach can also be a useful tool for metabolic network annotation validation and refinement in newly sequenced organisms. Combining an in silico genome-scale model of Escherichia coli metabolism with in vivo survival data, we uncover possible essential roles for several cell membranes, cell walls, and quinone species. We also identify specific biomass components whose production appears to be non-essential for survival, contrary to the assumptions of previous models. AVAILABILITY: Programs are available upon request from the authors in the form of Matlab script files. SUPPLEMENTARY INFORMATION: http://www.cis.upenn.edu/biocomp/manuscripts/bioinformatics_bti245/supp-info.html.

Algorithms↗

A triple helix within a pseudoknot is a conserved and essential element of telomerase RNA.

Telomerase copies a short template within its integral telomerase RNA onto eukaryotic chromosome ends, compensating for incomplete replication and degradation. Telomerase action extends the proliferative potential of cells, and thus it is implicated in cancer and aging. Nontemplate regions of telomerase RNA are also crucial for telomerase function. However, they are highly divergent in sequence among species, and their roles are largely unclear. Using in silico three-dimensional modeling, constrained by mutational analysis, we propose a three-dimensional model for a pseudoknot in telomerase RNA of the budding yeast Kluyveromyces lactis. Interestingly, this structure includes a U-A.U major-groove triple helix. We confirmed the triple-helix formation in vitro using oligoribonucleotides and showed that it is essential for telomerase function in vivo. While triplex-disrupting mutations abolished telomerase function, triple compensatory mutations that formed pH-dependent G-C.C(+) triples restored the pseudoknot structure in a pH-dependent manner and partly restored telomerase function in vivo. In addition, we identified a novel type of triple helix that is formed by G-C.U triples, which also partly restored the pseudoknot structure and function. We propose that this unusual structure, so far found only in telomerase RNA, provides an essential and conserved telomerase-specific function.

Base Sequence↗

Mechanism-based inhibition of cytochrome P450 3A4 by therapeutic drugs.

Consistent with its highest abundance in humans, cytochrome P450 (CYP) 3A is responsible for the metabolism of about 60% of currently known drugs. However, this unusual low substrate specificity also makes CYP3A4 susceptible to reversible or irreversible inhibition by a variety of drugs. Mechanism-based inhibition of CYP3A4 is characterised by nicotinamide adenine dinucleotide phosphate hydrogen (NADPH)-, time- and concentration-dependent enzyme inactivation, occurring when some drugs are converted by CYP isoenzymes to reactive metabolites capable of irreversibly binding covalently to CYP3A4. Approaches using in vitro, in silico and in vivo models can be used to study CYP3A4 inactivation by drugs. Human liver microsomes are always used to estimate inactivation kinetic parameters including the concentration required for half-maximal inactivation (K(I)) and the maximal rate of inactivation at saturation (k(inact)). Clinically important mechanism-based CYP3A4 inhibitors include antibacterials (e.g. clarithromycin, erythromycin and isoniazid), anticancer agents (e.g. tamoxifen and irinotecan), anti-HIV agents (e.g. ritonavir and delavirdine), antihypertensives (e.g. dihydralazine, verapamil and diltiazem), sex steroids and their receptor modulators (e.g. gestodene and raloxifene), and several herbal constituents (e.g. bergamottin and glabridin). Drugs inactivating CYP3A4 often possess several common moieties such as a tertiary amine function, furan ring, and acetylene function. It appears that the chemical properties of a drug critical to CYP3A4 inactivation include formation of reactive metabolites by CYP isoenzymes, preponderance of CYP inducers and P-glycoprotein (P-gp) substrate, and occurrence of clinically significant pharmacokinetic interactions with coadministered drugs. Compared with reversible inhibition of CYP3A4, mechanism-based inhibition of CYP3A4 more frequently cause pharmacokinetic-pharmacodynamic drug-drug interactions, as the inactivated CYP3A4 has to be replaced by newly synthesised CYP3A4 protein. The resultant drug interactions may lead to adverse drug effects, including some fatal events. For example, when aforementioned CYP3A4 inhibitors are coadministered with terfenadine, cisapride or astemizole (all CYP3A4 substrates), torsades de pointes (a life-threatening ventricular arrhythmia associated with QT prolongation) may occur.However, predicting drug-drug interactions involving CYP3A4 inactivation is difficult, since the clinical outcomes depend on a number of factors that are associated with drugs and patients. The apparent pharmacokinetic effect of a mechanism-based inhibitor of CYP3A4 would be a function of its K(I), k(inact) and partition ratio and the zero-order synthesis rate of new or replacement enzyme. The inactivators for CYP3A4 can be inducers and P-gp substrates/inhibitors, confounding in vitro-in vivo extrapolation. The clinical significance of CYP3A inhibition for drug safety and efficacy warrants closer understanding of the mechanisms for each inhibitor. Furthermore, such inactivation may be exploited for therapeutic gain in certain circumstances.

Animals↗

The Arabidopsis leaf as a model system for investigating the role of cell cycle regulation in organ growth.

The role of cell cycle regulation and cell division in plant growth and organ development is controversial. Some experimental data are most easily interpreted from the 'cellular perspective' that cell division drives growth, whereas other observations are more consistent with the 'organismal perspective' that cell division is merely a consequence of growth, and to a large extent facultative. Here we develop a model of cell cycle regulation in the context of leaf development based on literature, published kinematic analysis, flow-cytometric and transcriptomic data obtained from growing Arabidopsis leaves. We tested this model by comparing the in silico inhibition of the cell cycle progression with the experimental observations of transgenic plants overexpressing the cell cycle inhibitor Arath;KRP2. The model simulates the behaviour of proliferating cells quite well, but is inadequate in describing the effects on expanding cells. This may point to a difference in the nature of the expansion process during the proliferating and non-dividing phase of leaf development.

Arabidopsis↗

In Silico and Ex silico ADME approaches for drug discovery.

The high attrition rate of drug candidates during clinical trials for poor pharmacokinetic and metabolic properties has created a need to do these studies as early as it is possible during the drug discovery process. In addition the most successful drug is often not the most potent one but the one that has the suitable level of potency, safety, and pharmacokinetics. Science and technology development during the last few years and the generation of last databases and information has created the basis for doing early experimental PK and ADME studies in addition to eADME. Similarly, testing safety features as early as possible is key to affordable drug discovery and development. Throughput and cost are crucial for early application. In silico methods have by far the highest throughput, followed by the in vitro and in vivo approaches. On the other hand, with regard to relevance and reliability of data the ranking is the opposite. The great challenge for in silico methods is generation of models that correlate more closely with in vivo systems. For the in vitro assays increasing the throughput is an absolute must. Ex silico methods that combine in silico predictions with experimental methods are new additions to the scientific repertoire (e.g. Chromatographic Hydrophobicity Index that is deduced from the reverse phase HPLC data can be used for calculation of lipophilicity). The emerging new approaches have clear impact on the design of early stage screening and combinatorial libraries. In addition to the Lipinski's rules descriptors such as number of rotatable bonds, number of aromatic rings, branching behavior and polar surface area (PSA) are commonly used is the drug design process.

Absorption↗

truPK -- human pharmacokinetic models for quantitative ADME prediction.

The use of in silico prediction of absorption, distribution, metabolism and excretion (ADME) properties is gaining acceptance as a useful assessment tool for early identification of likely drug candidate failures. However, it has been difficult to locate reliable models for the prediction of human pharmacokinetics (PK) in silico Currently available methods for estimating ADME and toxicity properties, such as in vitro and animal models, are not very predictive of what is observed in the clinic. Existing in silico ADME prediction tools concentrate on physicochemical properties, such as solubility, log P, rule-of-five compliance, Caco-2 permeability, blood-brain barrier and so on, or only classify drug-like candidates as 'poor', 'medium' or 'good' for a PK parameter, without ascribing values. Although physiology-based pharmacokinetic -models can predict ADME properties, they rely on using various measured properties as input for better accuracy. Strand Genomics has developed a tool, truPK, that predicts the properties of a molecule (bioavailability, protein binding, volume of distribution, elimination half-life and absorption rate) that affect its dose and dose frequency in humans. truPK's five models built using sophisticated machine methods have predicted with > 75% accuracies in external validation sets.

Animals↗