• Title, Summary, Keyword: in silico

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Isomer Differentiation Using in silico MS2 Spectra. A Case Study for the CFM-ID Mass Spectrum Predictor

  • Milman, Boris L.;Ostrovidova, Ekaterina V.;Zhurkovich, Inna K.
    • Mass Spectrometry Letters
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    • v.10 no.3
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    • pp.93-101
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    • 2019
  • Algorithms and software for predicting tandem mass spectra have been developed in recent years. In this work, we explore how distinct in silico $MS^2$ spectra are predicted for isomers, i.e. compounds having the same formula and similar molecular structures, to differentiate between them. We used the CFM-ID 2.0/3.0 predictor with regard to (a) test compounds, whose experimental mass spectra had been randomly sampled from the MassBank of North America (MoNA) collection, and to (b) the most widespread isomers of test compounds searched in the PubChem database. In the first validation test, in silico mass spectra constitute a reference library, and library searches are performed for test experimental spectra of "unknowns". The searches led to the true positive rate (TPR) of ($46-48{\pm}10$)%. In the second test, in silico and experimental spectra were interchanged and this resulted in a TPR of ($58{\pm}10$)%. There were no significant differences between results obtained with different metrics of spectral similarity and predictor versions. In a comparison of test compounds vs. their isomers, a statistically significant correlation between mass spectral data and structural features was observed. The TPR values obtained should be regarded as reasonable results for predicting tandem mass spectra of related chemical structures.

In-silico and In-vitro based studies of Streptomyces peucetius CYP107N3 for oleic acid epoxidation

  • Bhattarai, Saurabh;Niraula, Narayan Prasad;Sohng, Jae Kyung;Oh, Tae-Jin
    • BMB Reports
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    • v.45 no.12
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    • pp.736-741
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    • 2012
  • Certain members of the cytochromes P450 superfamily metabolize polyunsaturated long-chain fatty acids to several classes of oxygenated metabolites. An approach based on in silico analysis predicted that Streptomyces peucetius CYP107N3 might be a fatty acid-metabolizing enzyme, showing high homology with epoxidase enzymes. Homology modeling and docking studies of CYP107N3 showed that oleic acid can fit directly into the active site pocket of the double bond of oleic acid within optimum distance of $4.6{\AA}$ from the Fe. In order to confirm the epoxidation activity proposed by in silico analysis, a gene coding CYP107N3 was expressed in Escherichia coli. The purified CYP107N3 was shown to catalyze $C_9-C_{10}$ epoxidation of oleic acid in vitro to 9,10-epoxy stearic acid confirmed by ESI-MS, HPLC-MS and GC-MS spectral analysis.

Receptor-oriented Pharmacophore-based in silico Screening of Human Catechol O-Methyltransferase for the Design of Antiparkinsonian Drug

  • Lee, Jee-Young;Baek, Sun-Hee;Kim, Yang-Mee
    • Bulletin of the Korean Chemical Society
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    • v.28 no.3
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    • pp.379-385
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    • 2007
  • Receptor-oriented pharmacophore-based in silico screening is a powerful tool for rapidly screening large number of compounds for interactions with a given protein. Inhibition of the enzyme catechol-Omethyltransferase (COMT) offers a novel possibility for treating Parkinson's disease. Bisubstrate inhibitors of COMT containing the adenine of S-adenosylmethionine (SAM) and a catechol moiety are a new class of potent and selective inhibitor. In the present study, we used receptor-oriented pharmacophore-based in silico screening to examine the interactions between the active site of human COMT and bisubstrate inhibitors. We generated 20 pharmacophore maps, of which 4 maps reproduced the docking model of hCOMT and a bisubstrate inhibitor. Only one of these four, pharmacophore map I, effectively described the common features of a series of bisubstrate inhibitors. Pharmacophore map I consisted of one hydrogen bond acceptor (to Mg2+), three hydrogen bond donors (to Glu199, Glu90, and Gln120), and one hydrophobic feature (an active site region surrounded by several aromatic and hydrophobic residues). This map represented the most essential pharmacophore for explaining interactions between hCOMT and a bisubstrate inhibitor. These results revealed a pharmacophore that should help in the development of new drugs for treating Parkinson's disease.

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

  • Cronin, Mark T.D.;Enoch, Steven J.;Mellor, Claire L.;Przybylak, Katarzyna R.;Richarz, Andrea-Nicole;Madden, Judith C.
    • Toxicological Research
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    • v.33 no.3
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    • pp.173-182
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    • 2017
  • In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

Virtual Screening Approaches in Identification of Bioactive Compounds Akin to Delphinidin as Potential HER2 Inhibitors for the Treatment of Breast Cancer

  • Patidar, Kavisha;Deshmukh, Aruna;Bandaru, Srinivas;Lakkaraju, Chandana;Girdhar, Amandeep;Gutlapalli, VR;Banerjee, Tushar;Nayarisseri, Anuraj;Singh, Sanjeev Kumar
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.4
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    • pp.2291-2295
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    • 2016
  • Small molecule tyrosine kinase inhibitors targeting HER 2 receptors have emerged as an important therapeutic approach in inhibition of downstream proliferation and survival signals for the treatment of breast cancers. Recent drug discovery efforts have demonstrated that naturally occurring polyphenolic compounds like delphinidin have potential to inhibit proliferation and promote apoptosis of breast cancer cells by targeting HER2 receptors. While delphinidin may thus reduce tumour size, it is associated with serious side effects like dysphonia. Owing to the narrow therapeutic window of delphinidin, the present study aimed to identify high affinity compounds targeting HER2 with safer pharmacological profiles than delphinidin through virtual screening approaches. Delphinidin served as the query parent for identification of structurally similar compounds by Tanimoto-based similarity searching with a threshold of 95% against the PubChem database. The compounds retrieved were further subjected to Lipinski and Verber's filters to obtain drug like agents, then further filtered by diversity based screens with a cut off of 0.6. The compound with Pubchem ID: 91596862 was identified to have higher affinity than its parent. In addition it also proved to be non-toxic with a better ADMET profile and higher kinase activity. The compound identified in the study can be put to further in vitro drug testing to complement the present study.

In Silico Interaction and Docking Studies Indicate a New Mechanism for PML Dysfunction in Gastric Cancer and Suggest Imatinib as a Drug to Restore Function

  • Imani-Saber, Zeinab;Ghafouri-Fard, Soudeh
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.12
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    • pp.5005-5006
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    • 2015
  • Gastric cancer as one of the most common cancers worldwide has various genetic and environmental risk factors including Helicobacter pylori (H.pylori) infection. Recently, loss of a tumor suppressor gene named promyelocytic leukemia (PML) has been identified in gastric cancer. However, no mutation has been found in this gene in gastric cancer samples. Cag A H.pylori protein has been shown to exert post transcriptional regulation of some tumor suppressor genes. In order to assess such a mechanism for PML degradation, we performed in silico analyses to establish any interaction between PML and Cag A proteins. In silico interaction and docking studies showed that these two proteins may have stable interactions. In addition, we showed that imatinib kinase inhibitor can restore PML function by inhibition of casein kinase 2.

Study of in Silico Simulation Method for Dynamic Network Model in Lactic Acid Bacteria (Lactic Acid Bacteria의 동역학 네트워크 모델을 이용한 in Silico 모사방법 연구)

  • Jung, Ui-Sub;Lee, Hye-Won;Lee, Jin-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.10
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    • pp.823-829
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    • 2005
  • We have newly constructed an in silico model of fermentative metabolism for Lactococcus lactis in order to analyze the characteristics of metabolite flux for dynamic network. A rigorous mathematical model for metabolic flux has been developed and simulation researches have been performed by using GEPASI program. In this simulation task, we were able to predict the whole flux distribution trend for lactate metabolism and analyze the flux ratio on the pyruvate branch point by using metabolic flux analysis(MFA). And we have studied flux control coefficients of key reaction steps in the model by using metabolic control analysis(MCA). The role of pyruvate branch seems to be essential for the secretion of lactate and other organic byproducts. Then we have made an effort to elucidate its metabolic regulation characteristics and key reaction steps, and find an optimal condition for the production of lactate.

An in silico Appraisal to Identify High Affinity Anti-Apoptotic Synthetic Tetrapeptide Inhibitors Targeting the Mammalian Caspase 3 Enzyme

  • Kelotra, Seema;Jain, Meeta;Kelotra, Ankit;Jain, Ish;Bandaru, Srinivas;Nayarisseri, Anuraj;Bidwai, Anil
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.23
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    • pp.10137-10142
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    • 2015
  • Apoptosis is a general phenomenon of all multicellular organisms and caspases form a group of important proteins central to suicide of cells. Pathologies like cancer, Myocardial infarction, Stroke, Sepsis, Alzheimer's, Psoriasis, Parkinson and Huntington diseases are often associated with change in caspase 3 mediated apoptosis and therefore, caspases may serve as potential inhibitory targets for drug development. In the present study, two series of synthetic acetylated tetrapeptides containing aldehyde and fluromethyl keto groups respectively at the C terminus were proposed. All these compounds were evaluated for binding affinity against caspase 3 structure. In series 1 compound Ac-DEHD-CHO demonstrated appreciable and high binding affinity (Rerank Score: -138.899) against caspase 3. While in series 2 it was Ac-WEVD-FMK which showed higher binding affinity (Rerank Score: -139.317). Further these two compounds met ADMET properties and demonstrated to be non-toxic.

In-silico inferences for expression data using IGAM: Applied to Fuzzy-Clustering & Regulatory Network Modeling (연판 지식을 이용한 유전자 발현 데이터 분석: 퍼지 플러스링과 조절 네트웍 모델링에의 응용)

  • Lee, Philhyone;Hojeong Nam;Lee, Doheon;Lee, Kwang H.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.273-276
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    • 2004
  • Genome-scale expression data provides us with valuable insights about organisms, but the biological validation of in-silico analysis is difficult and often controversial. Here we present a new approach for integrating previously established knowledge with computational analysis. Based on the known biological evidences, IGAM (Integrated Gene Association Matrix) automatically estimates the relatedness between a pair of genes. We combined this association knowledge to the regulatory network modeling and fuzzy clustering in yeast 5. Cerevisiae. The result was found to be more effective for extracting biological meanings from in-silico inferences for gene expression data.

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In silico target identification of biologically active compounds using an inverse docking simulation

  • Choi, Youngjin
    • CELLMED
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    • v.3 no.2
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    • pp.12.1-12.4
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    • 2013
  • Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.