Computational Identification of Inhibitors Using QSAR Approach Against Nipah Virus

Frontiers in Pharmacology - Switzerland
doi 10.3389/fphar.2019.00071
Full Text
Abstract

Available in full text

Categories
Pharmacology
Date
Authors
Publisher

Frontiers Media SA

Related search

Virtual Screening for Identification of Small Lead Compound Inhibitors of Nipah Virus Attachment Glycoprotein

Journal of Pharmacogenomics & Pharmacoproteomics
2018English

Predicting and Designing Therapeutics Against the Nipah Virus

PLoS Neglected Tropical Diseases
PharmacologyPublic HealthEnvironmentalToxicologyInfectious DiseasesPharmaceuticsOccupational Health
2019English

Nipah Virus

Scire Science Newsletter
2018English

Nipah Virus Infection

Journal of Clinical Microbiology
Microbiology
2018English

Computational QSAR Model Combined Molecular Descriptors and Fingerprints to Predict HDAC1 Inhibitors

Medecine/Sciences
BiochemistryMedicineGeneticsMolecular Biology
2018English

Nipah Virus Disease

2020English

Nipah Virus – An Overview

International Journal of Current Microbiology and Applied Sciences
2018English

QSAR Based Model for Discriminating EGFR Inhibitors and Non-Inhibitors Using Random Forest

Biology Direct
EvolutionEcologyGeneticsMolecular BiologyBiochemistryApplied MathematicsSystematicsSimulationImmunologyBehaviorBiological SciencesAgriculturalModeling
2015English

Searching for Chymase Inhibitors Among Chamomile Compounds Using a Computational-Based Approach

Biomolecules
BiochemistryMolecular Biology
2018English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy