Drug-Repurposing-in-KNIME

An Integrative Drug Repurposing Pipeline using KNIME and Programmatic Data Access: A case study on COVID-19 Data

VirtualScreening

The repository contains supplementary files to our study where a consensus screening approach by using different types of machine learning models (proteochemometric models, conformal prediction models, and QSAR models), followed by structure-based virtual screening of preselected hits using the structural models for hepatic OATPs was performed.

EnsembleDocking

This repository contains Supplementary data files to the article "Data-driven Ensemble Docking to Map Molecular Interactions of Steroid Analogs with Hepatic Organic Anion Transporting Polypeptides" by Tuerkova Alzbeta, Ungvari Orsolya, Laczkó-Rigó Réka, Mernyak Erzsebet, Szakacs Gergely, Özvegy-Laczka Csilla, and Zdrazil Barbara, published in Journal of Chemical Information And Modeling (2021).

All-atom-proteoliposome-preparation

This is the repository to our semi-automated strategy that has been developed in Peter Kasson Lab (Uppsala University) to facilitate atomistic proteoliposome preparation. The pipeline consists of bash/python scripts that are consecutively executed to (1) pre-process the input data at coarse-grained resolution (generated via the “Martini Maker” tool in CHARMM-GUI webserver) (2) insert viral fusion protein into a proteoliposome, (3) generate molecular topology, (4) perform energy minimization of a coarse-grained system, (5) perform system equilibration, (6) backmapp a coarse-grained system into atomistic resolution, (7) perform energy minimization of a backmapped system, (8) perform system equilibration. Our pipeline allows for a unified system preparation and is easily reproducible, and therefore can be customized according to individual project needs.