In-silico Experiment Research Articles

How does leaf functional diversity affect the light environment in forest canopies? An in-silico biodiversity experiment

The interaction of shortwave radiation with vegetation drives basic processes of the biosphere, such as primary productivity, species interactions through light competition, and energy fluxes between the atmosphere, vegetation, and soil. Here, we aim to understand the effects of leaf functional trait diversity on canopy light absorption. We focus on the diversity of three key functional traits that influence the light-canopy interaction: leaf area index (LAI), leaf angle distribution (LAD) and leaf optical properties (LOP). We used a 3D radiative transfer model to perform an in-silico biodiversity experiment to study the effects of leaf functional diversity on a light proxy for productivity (the fraction of absorbed photosynthetically active radiation (FAPAR)) and net radiation (shortwave albedo). We found that diverse canopies had lower albedo and higher FAPAR than the average of the corresponding monoculture values. In mixtures, FAPAR was unequally re-distributed between trees with distinct traits: some plant functional types absorbed more light and some plant functional types absorbed less than in monocultures. The net biodiversity effect on absorptance was greater when combining plant functional types with more distinct leaf traits. Our results support the mechanistic understanding of overyielding effects in functionally diverse canopies and may partially explain some of the growth-promoting mechanisms in biodiversity-ecosystem functioning experiments. They can further help to account for biodiversity effects in climate models.

COMPUTER SEARCH OF CHEMICAL COMPOUNDS – PROPERTIES ANALOGUES FOR PYRROLIDINOPHENONE DERIVATIVES

The study of forensic toxicology of pyrrolidinophenone derivatives is of great importance now. Obtaining sorbents used for selective solid-phase extraction of pyrrolidinophenone derivatives from biological fluids is a new direction of using this method in the analysis practice. Research on the synthesis of selective sorbents is preceded by a choice of a model chemical compound that is not controlled in the Russian Federation, but maximally reproduces the physicochemical properties of pyrrolidinophenone derivatives, as well as their stereochemical characteristics. Pyrrolidinophenone derivatives are narcotic drugs; it means search for a model chemical compound is possible only by means of an in-silico computer experiment. This study is devoted to the search for model chemical compounds with physicochemical properties and stereochemical characteristics similar to pyrrolidinophenone derivatives using computer modeling methods. We studied the structural formulas of "small" molecules - alpha-pyrrolidinovalerophenone and its metabolite 1-(1-oxo-1-phenylpentan-2-yl) pyrrolidin-2-one, 3,4-methylenedioxypyrovalerone and its metabolite 1-[1-(2H-1,3-benzodioxol-5-yl)-1-oxypentan-2-yl] pyrrolidin-2-one as well as phenylpiracetam, pidotimod, brivaracetam, piracetam and levetiracetam. Structural descriptors of molecules were calculated using the ChemAxonPASS program. Ionization constants (pKb), distribution coefficients in the n-octanol-water system at different pH (logD) and water solubility were calculated. Stereochemical interactions of the investigated "small" molecules with serotonin and dopamine receptors were carried out by the molecular docking method using the SwissDock and GOLD programs with genetic algorithms taking into account the ligand conformational mobility. It has been established that phenylpiracetam, pidotimod, brivaracetam, piracetam and levetiracetam will be in molecular form in a wide range of pH values, which corresponds to the behavior of the alpha-pyrrolidinovalerophenone and 3,4-methylenedioxypyrovalerone metabolites. logD value of phenylpiracetam, which is higher than that for other drugs, has the closest value to the logD value for alpha-pyrrolidinovalerophenone. Taking into account the above regularity and water solubility, it should be assumed that the physicochemical properties of phenylpiracetam, which are significant for sample preparation, are sufficiently close to the properties of pyrrolidinophenone derivatives. Stereochemical identity of phenylpiracetam to pyrrolidinophenone derivatives was determined by molecular docking using the following scoring functions — free binding energy (ΔG); a scoring function based on a force field (GoldScore) and a scoring evaluation function (ChemScore). The intermolecular interaction of the studied compounds with the serotonin and dopamine receptors at the binding sites in this case reproduces the interaction with the structures of synthetic sorbents, which is based on van der Waals forces and hydrogen bonds. The high affinity of phenylpiracetam for receptors indicates a stereochemical analogy to pyrrolidinophenone derivatives. Phenylpiracetam can be recommended as a model chemical compound for laboratory studies to obtain synthetic sorbents for solid-phase extraction of pyrrolidinophenone derivatives.

Hydrochlorothiazide and Indapamide bind the NADPH binding site of bacterial Dihydrofolate Reductase: results of an in-silico study and their implications.

Hypertension is a public health concern. Low dose thiazide diuretics are known to effectively control blood pressure compared to that of other classes of antihypertensive drugs. In this context, we have performed an in-silico study and found that the two Sulphonamide Diuretics Hydrochlorothiazide and Indapamide bound the NADPH binding region of bacterial Dihydrofolate Reductase. Therefore, akin to Sulphonamide Antibiotics, Sulphonamide Diuretics may have antibiotic activity and thereby have the potential to modulate the gut microbiome in a way beneficial to vascular health. The in-silico experiment results were analyzed in the context of the relevant literature. We postulate that Sulphonamide Diuretics exert their antihypertensive role by modulating the gut microbiome, specifically by increasing butyrate-producing taxa in the gut. We recommend extending such work as it is plausible that Indapamide and other Sulphonamide Diuretics may be beneficial for both diabetes and hypertension.

Nephroprotective effect of Combretum micranthum G. Don in nicotinamide-streptozotocin induced diabetic nephropathy in rats: In-vivo and in-silico experiments

Ethnopharmacological relevanceCombretum micranthum G. Don (CM) is extensively used in traditional medicine throughout West Africa and commonly known as “long-life herbal tea” or “plant to heal”. Further, traditional healers frequently use the title plant to mitigate of renal disorders. Aim of the studyTo explore the nephroprotective property of standardised hydroalcoholic extract of Combretum micranthum in nicotinamide-streptozotocin induced diabetic nephropathy in rats. In addition, in-silico computational experiments were performed with bioactive compounds of the title plant against PPARα and PPARγ. Material and methodsMale rats were made diabetic by a single intraperitoneal (ip) injection of STZ (50 mg/kg), 15 min after ip administration of NA (100 mg/kg) dissolved in normal saline. The diabetic rats received CM extract (200 and 400 mg/kg p.o.) daily, for eight weeks. Body weights and blood glucose (non-fasting and fasting) of rats were measured weekly. Daily food and water consumption were also measured. After 8 weeks of treatment, urine biochemical parameters such as N-Acetyl-β-D-Glucosaminidase (NAG), urea (UR), uric acid (UA), creatinine (CRE), and serum markers of diabetes, kidney damage and liver damage such as insulin, lipid parameters), alanine aminotransferase (ALT), aspartate aminotransferase (AST) and gamma-glutamyl transferase (γGT), albumin (Alb), magnesium (Mg2+), calcium (Ca2+), phosphorus (P), were estimated. Blood glycosylated hemoglobin (HbA1C) were also estimated. kidney and liver were used for biochemical estimation of oxidative stress markers such as lipid peroxidation, superoxide dismutase (SOD) activity and glutathione peroxidase (GPx) activity. The kidney and pancreas were used for histopathological study. Further, HPLC chemoprofiling of CM extract and in-silico molecular simulation experiments were performed. ResultsAt the end of eight weeks, renal damage induced by the consequence of prolong diabetic condition was confirmed by altered levels of serum and urine kidney and liver function markers, oxidative stress markers and histopathological variations in kidney. Treatment with CM extract ameliorated the diabetes mellitus-induced renal biochemical parameters and histopathological changes. Further, HPLC-UV & MS experiments revealed that CM extract contains several bioactive compounds including hyperozide (62.35 μg/mg of extract) and quercitrin (19.07 μg/mg of extract). In-silico experiment exhibited cianidanol (−17.133), epicatechin (−15.107) exhibited higher docking score against PPARα and luteoforol (−11.038), epigallocatechin (−10.736) against PPARγ. Based on docking and drug likeness score, four bioactive compounds were selected for molecular dynamic experiments. Cianidanol and epigallocatechin out of the 30 compounds are concluded as a potential candidate for the treatment of DN through activating PPARα and PPARγ target protein. ConclusionsTaken together, the present study provided the scientific footage for the traditional use of Combretum micranthum.

System-based Approach to Prediction of Surfactants’ Influences on Pharmaco-kinetics and Pharmacodynamics

Abstract The paper presents a system-based approach for predicting the changes of the plasma concentration and the therapeutic effect of sodium p-aminosalicylate caused by addition of surfactant Tween 80 to a liquid dosage form. A predictive pharmacokinetic model of the oral administration is synthetized together with the corresponding model of its parametric sensitivity. The sensitivities predicted by the model are then compared to those obtained from the in-vi vo experiment. The close correspondence between them is used to prove the model correctness. Similarly the Emax model of the therapeutic effect predicts influences of the added surfactants on the therapeutic effect. In this context, the problem of determining an optimal absorption rate for the desired time course of the therapeutic effect is solved. As a by-product this study, it is shown that the (in-silico generated) sensitivity of plasma concentration to the drug absorption rate may provide information on how far the in-silico experiment can serve as a substitute for in-vivo bioavailability and bioequivalence studies

Inference and visualization of DNA damage patterns using a grade of membership model.

Quality control plays a major role in the analysis of ancient DNA (aDNA). One key step in this quality control is assessment of DNA damage: aDNA contains unique signatures of DNA damage that distinguish it from modern DNA, and so analyses of damage patterns can help confirm that DNA sequences obtained are from endogenous aDNA rather than from modern contamination. Predominant signatures of DNA damage include a high frequency of cytosine to thymine substitutions (C-to-T) at the ends of fragments, and elevated rates of purines (A & G) before the 5' strand-breaks. Existing QC procedures help assess damage by simply plotting for each sample, the C-to-T mismatch rate along the read and the composition of bases before the 5' strand-breaks. Here we present a more flexible and comprehensive model-based approach to infer and visualize damage patterns in aDNA, implemented in an R package aRchaic. This approach is based on a 'grade of membership' model (also known as 'admixture' or 'topic' model) in which each sample has an estimated grade of membership in each of K damage profiles that are estimated from the data. We illustrate aRchaic on data from several aDNA studies and modern individuals from 1000 Genomes Project Consortium (2012). Here, aRchaic clearly distinguishes modern from ancient samples irrespective of DNA extraction, lab and sequencing protocols. Additionally, through an in-silico contamination experiment, we show that the aRchaic grades of membership reflect relative levels of exogenous modern contamination. Together, the outputs of aRchaic provide a concise visual summary of DNA damage patterns, as well as other processes generating mismatches in the data. aRchaic is available for download from https://www.github.com/kkdey/aRchaic. Supplementary data are available at Bioinformatics online.

A powerful conditional gene-based association approach implicated functionally important genes for schizophrenia

It remains challenging to unravel new susceptibility genes of complex diseases and the mechanisms in genome-wide association studies. There are at least two difficulties, isolation of the genuine susceptibility genes from many indirectly associated genes and functional validation of these genes. We first proposed a novel conditional gene-based association test which can use only summary statistics to isolate independently associated genes of a disease. Applying this method, we detected 185 genes of independent association with schizophrenia. We then designed an in-silico experiment based on expression/co-expression to systematically validate pathogenic potential of these genes. We found that genes of independent association with schizophrenia formed more co-expression pairs in normal post-natal but not pre-natal human brain regions than expected. Interestingly, no co-expression enrichment was found in the brain regions of schizophrenia patients. The genes with independent association also had more significant P-values for differential expression between schizophrenia patients and controls in the brain regions. In contrast, indirectly associated genes or associated genes by other widely-used gene-based tests had no such differential expression and co-expression patterns. In summary, this conditional gene-based association test is effective for isolating directly associated genes from indirectly associated genes, and the results insightfully suggest that common variants might contribute to schizophrenia largely by distorting expression and co-expression in post-natal brains. The conditional gene-based association test has been implemented in a platform 'KGG' in Java and is publicly available at http://grass.cgs.hku.hk/limx/kgg/. Supplementary data are available at Bioinformatics online.

Cell studio: A platform for interactive, 3D graphical simulation of immunological processes.

The field of computer modeling and simulation of biological systems is rapidly advancing, backed by significant progress in the fields of experimentation techniques, computer hardware, and programming software. The result of a simulation may be delivered in several ways, from numerical results, through graphs of the simulated run, to a visualization of the simulation. The vision of an in-silico experiment mimicking an in-vitro or in-vivo experiment as it is viewed under a microscope is appealing but technically demanding and computationally intensive. Here, we report “Cell Studio,” a generic, hybrid platform to simulate an immune microenvironment with biological and biophysical rules. We use game engines—generic programs for game creation which offer ready-made assets and tools—to create a visualized, interactive 3D simulation. We also utilize a scalable architecture that delegates the computational load to a server. The user may view the simulation, move the “camera” around, stop, fast-forward, and rewind it and inject soluble molecules into the extracellular medium at any point in time. During simulation, graphs are created in real time for a broad view of system-wide processes. The model is parametrized using a user-friendly Graphical User Interface (GUI). We show a simple validation simulation and compare its results with those from a “classical” simulation, validated against a “wet” experiment. We believe that interactive, real-time 3D visualization may aid in generating insights from the model and encourage intuition about the immunological scenario.

Introduction to Classical Density Functional Theory by a Computational Experiment

We propose an in-silico experiment to introduce classical density functional theory (cDFT). Den- sity functional theories, whether quantum or classical, rely on abstract concepts that are non- intuitive. However, they are at the heart of powerful tools and active fields of research in both physics and chemistry. They led to the 1998 Nobel Prize in chemistry. DFT is illustrated here in its most simple and yet physically relevant form: the classical density functional theory of an ideal fluid of classical particles. For illustration purpose, it is applied to the prediction of the molecular structure of liquid neon. The numerical experiment proposed therein is built around the writing of a cDFT code by students in Mathematica. Students thus have to deal with (i) the cDFT theory, (ii) some basic concepts of statistical mechanics of simple fluids, (iii) functional minimization, and (iv) a useful functional programming language. This computational experiment is proposed during a molecular simulation class, but may also be of interest in a quantum chemistry class to illustrate electronic DFT, if one highlights the analogies between the quantum and classical DFTs.

Abstract 2223: Screening for oncoviruses using next-generation sequencing

Abstract Introduction: During the last decades numerous viruses have been found to play a causative role in cancer. Besides well established connections like HPV in cancers of the uterine cervix or EBV in nasopharyngeal carcinoma recent advances in next-generation sequencing technologies have led to the discovery of new tumor viruses e.g. a previously unknown Polyoma-virus subtype linked to Merkel-cell carcinoma of the skin. Method: To gain insight into the mechanisms leading to tumor formation we sequenced the transcriptome from an HPV16 positive cell line using short-read Illumina RNA-Seq and established a computational pipeline to screen the short reads for viral sequences based on freely available alignment tools. Results: Due to the large amount of data and in order to narrow down the search space and reduce the chance for false positives the first screening step consists in a subtraction of sequences that align to the human reference genome reducing the amount of reads by ∼70%. To find both known viruses and yet unknown strains/subtypes we apply a two-fold approach: 1. A rapid search for known viruses is done using a short-read alignment tool with a set of stringent parameters to map non-human reads to an index of the viral genbank and subsequent quantification of the hits. 2. Since slight differences between read and index sequence will cause the rapid search to not call a match we implemented a more lenient approach using standalone BLAST. Applying approach 1) to the control cell line we clearly identified HPV16 as being present. To test the possibility of finding a potentially unknown virus we deleted HPV16 from both the rapid approach and the index which caused the first algorithm to no longer identify the virus. Running the BLAST basec approach 2) resulted in multiple hits the most prominent being alignments to HPV subtypes 35 and 58, thus indicating the successful identification of related strains. Conclusion: We demonstrated the feasibility of our dual viral screening approach in an in-silico experiment using an HPV16 positive control. Our approach appears to be able to identify novel related viruses. In the future this will allow screening of patient samples and viral screening was added to our data pipeline. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2223.

Strategies for recovering exact structure of neural circuits with broadly targeted fluorescent connectivity probes

AbstractWe present a framework for reconstructing structure of complete neural circuitsin the brain using collections of independent measurements of connectivityperformed with existing anatomical or functional fluorescent probes, anddesigned to provide complementary information about neural circuit’s structureby targeting slightly different its parts either in deterministic or stochasticsuccession. We discuss specific implementation of this procedure usingsynaptic fluorescent marker GRASP and Cre/Lox system Brainbow to collectensemble of observations of the sets of synapses between stochastically labeledsamples of neurons. By representing such measurements mathematically asweak constraints on circuit’s connectivity matrix and by solving a constrainedoptimization problem, we are able to exactly deduce the wiring diagram in C.Elegans in an in-silico experiment from only ~10,000 measurements. Thisoffers possibility for routinely reconstructing complete connectivity in smallerorganisms, such as C. Elegans, using exclusively light microscopy instrumentsover the span of single weeks.

BioWMS: a web-based Workflow Management System for bioinformatics

BackgroundAn in-silico experiment can be naturally specified as a workflow of activities implementing, in a standardized environment, the process of data and control analysis. A workflow has the advantage to be reproducible, traceable and compositional by reusing other workflows. In order to support the daily work of a bioscientist, several Workflow Management Systems (WMSs) have been proposed in bioinformatics. Generally, these systems centralize the workflow enactment and do not exploit standard process definition languages to describe, in order to be reusable, workflows. While almost all WMSs require heavy stand-alone applications to specify new workflows, only few of them provide a web-based process definition tool.ResultsWe have developed BioWMS, a Workflow Management System that supports, through a web-based interface, the definition, the execution and the results management of an in-silico experiment. BioWMS has been implemented over an agent-based middleware. It dynamically generates, from a user workflow specification, a domain-specific, agent-based workflow engine. Our approach exploits the proactiveness and mobility of the agent-based technology to embed, inside agents behaviour, the application domain features. Agents are workflow executors and the resulting workflow engine is a multiagent system – a distributed, concurrent system – typically open, flexible, and adaptative. A demo is available at .ConclusionBioWMS, supported by Hermes mobile computing middleware, guarantees the flexibility, scalability and fault tolerance required to a workflow enactment over distributed and heterogeneous environment. BioWMS is funded by the FIRB project LITBIO (Laboratory for Interdisciplinary Technologies in Bioinformatics).