Search results for "computer.software_genre"

showing 10 items of 3858 documents

Antiprotozoan lead discovery by aligning dry and wet screening: Prediction, synthesis, and biological assay of novel quinoxalinones

2014

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In …

Quantitative structure–activity relationshipClinical BiochemistryAntiprotozoal AgentsQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear classifierBioinformaticsMachine learningcomputer.software_genreBiochemistryQuinoxalinesMolecular descriptorDrug DiscoveryBioassayMolecular BiologyVirtual screeningMolecular Structurebusiness.industryChemistryOrganic ChemistryBenchmark databaseDrug developmentCyclizationMolecular MedicineIn silico StudyArtificial intelligenceTOMOCOMD-CARDD SoftwarebusinessClassifier (UML)computer
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Molecular topology as a novel approach for drug discovery

2012

Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. One key part of MT is that, in the process of drug design/discovery, there is no need for an explicit knowledge of a drug's mechanism of action unlike other drug discovery methods.In this review, the authors introduce the topic by explaining briefly the most common methodology used today in drug design/discovery and address the most important concepts of MT and the methodology followed (QSAR equations, LDA, etc.). Furthermore, the significant results achieved, from this approach, are outlined and discussed.The results outlined herein can be explained by considering that MT r…

Quantitative structure–activity relationshipDrug IndustryDrug discoveryProcess (engineering)Computer sciencebusiness.industryIn silicoQuantitative Structure-Activity RelationshipModels TheoreticalMachine learningcomputer.software_genreField (computer science)Pharmaceutical PreparationsDrug DesignDrug DiscoveryKey (cryptography)AnimalsComputer-Aided DesignHumansData miningArtificial intelligenceExplicit knowledgeMolecular topologybusinesscomputerExpert Opinion on Drug Discovery
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Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices

2012

In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 fo…

Quantitative structure–activity relationshipEngineeringSpeedupbusiness.industryIn silicoAtom (order theory)Pattern recognitionLinear discriminant analysiscomputer.software_genreSet (abstract data type)Artificial intelligenceData miningbusinesscomputerSelection (genetic algorithm)Applicability domainInternational Journal of Chemoinformatics and Chemical Engineering
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Prediction of acute toxicity of phenol derivatives using multiple linear regression approach for Tetrahymena pyriformis contaminant identification in…

2016

In this article, the modeling of inhibitory grown activity against Tetrahymena pyriformis is described. The 0-2D Dragon descriptors based on structural aspects to gain some knowledge of factors influencing aquatic toxicity are mainly used. Besides, it is done by some enlarged data of phenol derivatives described for the first time and composed of 358 chemicals. It overcomes the previous datasets with about one hundred compounds. Moreover, the results of the model evaluation by the parameters in the training, prediction and validation give adequate results comparable with those of the previous works. The more influential descriptors included in the model are: X3A, MWC02, MWC10 and piPC03 wit…

Quantitative structure–activity relationshipEnvironmental EngineeringDatabases FactualHealth Toxicology and Mutagenesis0211 other engineering and technologiesQuantitative Structure-Activity Relationship02 engineering and technology010501 environmental sciencesBiologycomputer.software_genre01 natural sciencesAquatic toxicologyPhenolsLinear regressionEnvironmental Chemistry0105 earth and related environmental sciences021110 strategic defence & security studiesDatabaseTetrahymena pyriformisPublic Health Environmental and Occupational HealthLinear modelGeneral MedicineGeneral ChemistryModels TheoreticalchEMBLPollutionAcute toxicityTetrahymena pyriformisLinear ModelscomputerChemical databaseChemosphere
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Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity.

2013

The concept of molecular similarity is one of the most central in the fields of predictive toxicology and quantitative structure-activity relationship (QSAR) research. Many toxicological responses result from a multimechanistic process and, consequently, structural diversity among the active compounds is likely. Combining this knowledge, we introduce similarity boosted QSAR modeling, where we calculate molecular descriptors using similarities with respect to representative reference compounds to aid a statistical learning algorithm in distinguishing between different structural classes. We present three approaches for the selection of reference compounds, one by literature search and two by…

Quantitative structure–activity relationshipInformaticsbusiness.industryStatistical learningGeneral Chemical EngineeringStructural diversityQuantitative Structure-Activity RelationshipPattern recognitionGeneral ChemistryPredictive toxicologyLibrary and Information Sciencescomputer.software_genreToxicologyComputer Science ApplicationsSimilarity (network science)Molecular descriptorArtificial intelligenceData miningbusinessCluster analysiscomputerMathematicsJournal of chemical information and modeling
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Combined use of PCA and QSAR/QSPR to predict the drugs mechanism of action. An application to the NCI ACAM Database

2009

During the years the National Cancer Institute (NCI) accumulated an enormous amount of information through the application of a complex protocol of drugs screening involving several tumor cell lines, grouped into panels according to the disease class. The Anti-cancer Agent Mechanism (ACAM) database is a set of 122 compounds with anti-cancer activity and a reasonably well known mechanism of action, for which are available drug screening data that measure their ability to inhibit growth of a panel of 60 human tumor lines, explicitly designed as a training set for neural network and multivariate analysis. The aim of this work is to adapt a methodology (previously developed for the analysis of …

Quantitative structure–activity relationshipMultivariate analysisDatabaseArtificial neural networkMechanism (biology)Computer scienceOrganic Chemistrycomputer.software_genreSettore CHIM/08 - Chimica FarmaceuticaComputer Science ApplicationsSet (abstract data type)Mechanism of actionTest setDrug DiscoveryPrincipal component analysisAnti-cancer Agent Mechanism database PCA QSAR/QSPR Mechanism of actionmedicineData miningmedicine.symptomcomputer
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<strong>Predicting Proteasome Inhibition using Atomic Weighted Vector and Machine Learning</strong>

2018

Ubiquitin/Proteasome System (UPS) is a highly regulated mechanism of intracellular protein degradation and turnover. Through the concerted actions of a series of enzymes, proteins are marked for proteasomal degradation by being linked to the polypeptide co-factor, ubiquitin. The UPS participates in a wide array of biological functions such as antigen presentation, regulation of gene transcription and the cell cycle, and activation of NF-κB. Some researchers have applied QSAR method and machine learning in the study of proteasome inhibition (EC50(µmol/L)), such as: the analysis of proteasome inhibition prediction, in the prediction of multi-target inhibitors of UPP and in the prediction of p…

Quantitative structure–activity relationshipbusiness.industryProtein contact mapPerceptronMachine learningcomputer.software_genreCross-validationRandom forestStatistical classificationMolecular descriptorLinear regressionArtificial intelligencebusinesscomputerMathematicsProceedings of MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition
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QSAR Analysis of Hypoglycemic Agents Using the Topological Indices

2001

The molecular topology model and discriminant analysis have been applied to the prediction of some pharmacological properties of hypoglycemic drugs using multiple regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies performed on the selected prediction models confirmed the goodness of the fits. The method used for hypoglycemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new hypoglycemic agents, and we …

Quantitative structure–activity relationshipbusiness.industryStatistical parameterRegression analysisPattern recognitionGeneral ChemistryMachine learningcomputer.software_genreLinear discriminant analysisStability (probability)Computer Science ApplicationsComputational Theory and MathematicsLinear regressionArtificial intelligencebusinesscomputerPredictive modellingSelection (genetic algorithm)Information SystemsMathematics
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Ab Initio Modeling of Donor–Acceptor Interactions and Charge-Transfer Excitations in Molecular Complexes: The Case of Terthiophene–Tetracyanoquinodim…

2015

This work presents a thorough quantum chemical study of the terthiophene-tetracyanoquinodimethane complex as a model for π-π donor-acceptor systems. Dispersion-corrected hybrid (B3LYP-D) and double hybrid (B2PLYP-D), hybrid meta (M06-2X and M06-HF), and recently proposed long-range corrected (LC-wPBE, CAM-B3LYP, and wB97X-D) functionals have been chosen to deal with π-π intermolecular interactions and charge-transfer excitations in a balanced way. These properties are exhaustively compared to those computed with high-level ab initio SCS-MP2 and CASPT2 methods. The wB97X-D functional exhibits the best performance. It provides reliable intermolecular distances and interaction energies and pre…

Quantum chemicalChemistryAb initioCharge (physics)computer.software_genreTetracyanoquinodimethaneComputer Science Applicationschemistry.chemical_compoundTerthiopheneChemical physicsData miningPhysical and Theoretical ChemistryDonor acceptorcomputerJournal of Chemical Theory and Computation
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Quantum chemical meta-workflows in MoSGrid

2014

Quantum chemical workflows can be built up within the science gateway Molecular Simulation Grid. Complex workflows required by the end users are dissected into smaller workflows that can be combined freely to larger meta-workflows. General quantum chemical workflows are described here as well as the real use case of a spectroscopic analysis resulting in an end-user desired meta-workflow. All workflow features are implemented via Web Services Parallel Grid Runtime and Developer Environment and submitted to UNICORE. The workflows are stored in the Molecular Simulation Grid repository and ported to the SHIWA repository. © 2014 John Wiley & Sons, Ltd.

Quantum chemicalComputer Networks and CommunicationsComputer scienceInformationSystems_INFORMATIONSYSTEMSAPPLICATIONSDistributed computingGridcomputer.software_genrePortingComputer Science ApplicationsTheoretical Computer ScienceWorkflowComputational Theory and MathematicsWeb servicecomputerSoftwareConcurrency and Computation: Practice and Experience
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