MINDPROT: Markov Inside for Drugs and Proteins
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Updated
Mar 18, 2023 - Python
MINDPROT: Markov Inside for Drugs and Proteins
Comprehensive resource for molecular studies, featuring SQL scripts for ChEMBL database analysis and detailed molecular dynamics simulation protocols. Ideal for computational chemistry and drug discovery research.
AI-based Quantitative structure Activity relationship study for Alzheimer's disease
A Drug Discovery method using CHEMBL database, Lipinski Parameters, molecular fingerprint (padel) for SARS coronavirus 3C-like proteinase.
A Python package to process & model ChEMBL data.
Drug Discovery for Multiple Sclerosis Disease
This scripts tries to predict the bioactivity of 131 compounds related to Aspartate Racemase enzyme with the aid of decision trees and SVM
An SGC Chemical Networks Project devoted to the DENV Rdrp, focusing specifically on exploring the ChEMBL database
HWs - "Computational Drug Design" - Sharif University of Technology (SUT) - Prof. Ali Mohammadian - Fall 2022 (1401-1).
A Python script predicting pIC50 values of compounds obtained from the ChEMBL database against the target protein, aromatase. The molecular descriptor used in this script is PubChem fingerprint.
Drug Discovery model targeting the SARS coronavirus
This ebook has information about life science databases, their SPARQL endpoints, what information they hold, what data models they use, and how to query those.
Code to retrieve drugs against a desired target using the ChEMBL database API
Automatic extraction of interacting compound-target pairs from ChEMBL.
Supervised classification algorithm to predict if potential drug candidate will inhibit a protein involved in cancer metastasis, achieving 84% accuracy.
Working with ChEMBL Data Web Services to retrieve data.
Machine learning project to evaluate machine learning approaches in drug discovery.
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