Protein target prediction of a bioactive ligand with Align-it and ePharmaLib

Associated Tutorial

This workflows is part of the tutorial Protein target prediction of a bioactive ligand with Align-it and ePharmaLib, available in the GTN

Thanks to...

Workflow Author(s): Aurélien F. A. Moumbock, Albert-Ludwigs-Universität Freiburg ...

High Throughput Molecular Dynamics and Analysis

Associated Tutorial

This workflows is part of the tutorial High Throughput Molecular Dynamics and Analysis, available in the GTN

Thanks to...

Tutorial Author(s): Simon Bray, [Tharindu ...

Classification in Machine Learning

Associated Tutorial

This workflows is part of the tutorial Classification in Machine Learning, available in the GTN

Features

• Includes Galaxy Workflow Tests
• Includes a [Galaxy Workflow ...

This workflows contains a pipeline in Scipion that performs the following steps:

1.1) Import small molecules: introduces a set of small molecular structures in the pipeline as prospective ligands

1.2) Import atomic structure: introduces a protein atomic structure in the pipeline as receptor.

2.1) Ligand preparation: uses RDKit to prepare the small molecules optimizing their 3D structure.

2.2) Receptor preparation: uses bioPython to prepare the receptor structure, removing waters, adding hydrogens ...

This workflow performs the most basic Virtual Drug Screening Pipeline to import a set of small molecules and dock them to an imported protein structure.

Article abstract

Permeability is an important molecular property in drug discovery, as it co-determines pharmacokinetics whenever a drug crosses the phospholipid bilayer, e.g., into the cell, in the gastrointestinal tract or across the blood-brain barrier. Many methods for the determination of permeability have been developed, including cell line assays, cell-free model systems like PAMPA mimicking, e.g., gastrointestinal epithelia or the skin, as well as the Black lipid membrane (BLM) and ...

Galaxy Workflow Documentation: MS Finder Pipeline

This document outlines a MSFinder Galaxy workflow designed for peak annotation. The workflow consists of several steps aimed at preprocessing MS data, filtering, enhancing, and running MSFinder.

Step 1: Data Collection and Preprocessing

Collect if the inchi and smiles are missing from the dataset, and subsequently filter out the spectra which are missing inchi and smiles.

1.1 MSMetaEnhancer: Collect InChi, Isomeric_smiles, and Nominal_mass

...

Current version of this workflow: https://workflowhub.eu/workflows/1109. Please use only with the new version. KNIME workflow to gather ChEMBL permeability data is availbale: https://workflowhub.eu/workflows/1169.

This repository hosts Metabolome Annotation Workflow (MAW). The workflow takes MS2 .mzML format data files as an input in R. It performs spectral database dereplication using R Package Spectra and compound database dereplication using SIRIUS OR MetFrag . Final candidate selection is done in Python using RDKit and PubChemPy.