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3dgcn

Three-Dimensionally Embedded Graph Convolutional Network (3DGCN) for Molecule Interpretation

antibody-sars-cov-2-molecular-dynamics-setup-and-energy-estimation

automated-ligand-net-workflow

This automated workflow allows the user to generate a model to predict protein-ligand features through a regression approach. It also offers the user whether he wants to predict a ligand for a specific protein as active or decoy (classification ML approach).

cadd-workflows

code-dti

CoDe-DTI: Collaborative Deep Learning-based Drug-Target Interaction Predictior

deep-learning

Multi-layer perceptron, cnn,opencv

deep-rules

Ten Quick Tips for Deep Learning in Biology

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

deepchem-workshop

DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials

deepconv-dti

deepdta

deeplytough

dlscore

DLSCORE: A deep learning based scoring function for predicting protein-ligand binding affinity

docking-of-metallo-proteins-with-autodock4

An step-by-step tutorial to dock proteins in presence of metall ion and ligands (feedback is acepted).

dta_pred

Protein Ligand Binding Affinity Prediction with Deep Learning models

e3fp

3D molecular fingerprints

emp_free_energy_ff_ad4

Empirical Free Energy Force Field for AutoDock 4 Overview AutoDock 4 estimates free energy of binding for a receptor-ligand complex using a semi-empirical free energy force field. This force field has been calibrated against a dataset composed of crystallographic structures for which ligand-binding affinity data is known (Morris et al., 2009). The present Python code calculates the van der Waals, intermolecular hydrogen bond, electrostatic interaction, and desolvation potentials based on the atomic coordinates of the ligand and the receptor. This program reads atomic coordinates in the PDBQT format and prints the potential energy terms. It is not calibrated for a specific dataset, so it might be used to develop targeted-scoring functions, which may be used to explore the scoring function space (Heck et al. 2017). The zipped folder has the atomic coordinates for both, receptor (receptor.pdbqt) and ligand (lig.pdbqt) structures. I intend to use this code to develop a new tool in the SAnDReS program (Xavier et al., 2016)( https://github.com/azevedolab/sandres) to generate targeted-scoring functions. References Heck GS, Pintro VO, Pereira RR, de Ávila MB, Levin NMB, de Azevedo WF. Supervised Machine Learning Methods Applied to Predict Ligand-Binding Affinity. Curr Med Chem. 2017; 24(23): 2459–2470. Morris GM, Huey R, Lindstrom W, Sanner, MF, Belew RK, Goodsell DS, Olson AJ. Autodock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 2009 30: 2785–2791. Xavier MM, Heck GS, de Avila MB, Levin NM, Pintro VO, Carvalho NL, Azevedo WF Jr. SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions. Comb Chem High Throughput Screen. 2016; 19(10): 801–812.

fastbook

Draft of the fastai book

gnn_dti

htmd

HTMD: Programming Environment for Molecular Discovery

icmr

ICMR Sponsored Seminar On Deep Learning Techniques and Tools for Medical Applications

icmr-seminar

ICMR Sponsored Seminar On Deep Learning Techniques and Tools for Medical Applications

ligand-net-workflow

Workflow that works as a shell where the user inputs protein-ligand data to determine whether a ligand is an active or a decoy for that specific protein

ligandnet

LigandNet, a tool which combines different machine learning models into one platform for the prediction of the state of the ligands either actives or inactives for a particular proteins.

machine-learning

prediction using different machine learning algorithm

molecuar-docking-with-autodock4

A basic step-by-step tutorial to run molecular docking.

molecular-dyamics-protein-in-water

A tutorial to run molecular dynamics (protein in water) with Gromacs

molecular-dynamics-proteina-ligando

An step by step procedure to perform molecualr dynamics (protein-ligand complex) with gromcas (MPI GPU)

moleculekit

MoleculeKit: Your favorite molecule manipulation kit

morld