molsimplify-legacy-tutorials

Visualizing molecules built from SMILES strings in Jupyter Notebooks using molSimplify
molSimplify can be used to visualize molecules built from SMILES strings. In this tutorial, we will use molSimplify to generate several variants of a molecule and display them in a grid.
Nov 3, 2021 molsimplify-legacy-tutorials, tutorials
Visualizing molecules built from SMILES strings in Jupyter Notebooks using molSimplify
Installing molSimplify
This tutorial describes installation options for molSimplify, including from Conda and building from source.
Last updated on Jan 29, 2026 molsimplify-legacy-tutorials, tutorials
Installing molSimplify
molSimplify Tutorial 13: molscontrol -- an intelligent job control system to manage your DFT geometry optimizations for inorganic discovery.
In this tutorial, we demonstrate job control system that can offer an effective two-fold acceleration for your calculations by killing simulations with a low expected success rate based on a dynamic classifier machine learning model.
Apr 1, 2019 molsimplify-legacy-tutorials, tutorials
molSimplify Tutorial 13: molscontrol -- an intelligent job control system to manage your DFT geometry optimizations for inorganic discovery.
molSimplify Tutorial 12: Using the static classifier to predict your simulation outcomes before they waste your time
In this tutorial, we demonstrate the use of a machine learning classification model that predicts whether a geometry optimization will be successful.
Last updated on Jan 29, 2026 molsimplify-legacy-tutorials, tutorials
molSimplify Tutorial 12: Using the static classifier to predict your simulation outcomes before they waste your time
molSimplify Tutorial 11: Using molSimplify in Python scripts
In this tutorial, we show how you can use the classes and methods of molSimplify to build your own custom analysis or molecule generation scripts.
Feb 5, 2019 molsimplify-legacy-tutorials, tutorials
molSimplify Tutorial 11: Using molSimplify in Python scripts
molSimplify Tutorial 10: Adding ligands to molSimplify
In this tutorial, we demonstrate how you can use your own ligands in molSimplify by providing either SMILES strings or using 3D molecule formats.
Last updated on Jan 29, 2026 molsimplify-legacy-tutorials, tutorials
molSimplify Tutorial 10: Adding ligands to molSimplify
QM9 kernel models using molSimplify, RACs and R: Part 1
In this two-part tutorial, we’ll show you how to use molSimplify to collect autocorrelation-based descriptors from molecular structures and use those to make predictions using a simple kernel ridge regression (KRR) model, as shown in our recent paper.
Feb 20, 2018 molsimplify-legacy-tutorials, tutorials
QM9 kernel models using molSimplify, RACs and R: Part 1
QM9 kernel models using molSimplify, RACs and R: Part 2
In the second part of our tutorial, we will demonstrate how to use R to conduct kernel based prediction of atomization energies based on RACs. You’ll need QM9_descriptor_file.csv, which we prepared using molSimplify in the previous tutorial and also provide here.
Feb 20, 2018 molsimplify-legacy-tutorials, tutorials
QM9 kernel models using molSimplify, RACs and R: Part 2
molSimplify Tutorial 9: Bidentate Ligand Replacement
In this tutorial, we will show how to replace multidentate ligands in a prebuilt complex. This feature, which facilitates screening of diverse catalyst scaffolds, was recently added to molSimplify.
Last updated on Jan 29, 2026 molsimplify-legacy-tutorials, tutorials
molSimplify Tutorial 9: Bidentate Ligand Replacement
molSimplify Tutorial 8: Higher Period Transition Metal Complexes
In this tutorial, we will show how to use molSimplify for generating structures of second and third row transition metal complexes.
Last updated on Jan 29, 2026 molsimplify-legacy-tutorials, tutorials
molSimplify Tutorial 8: Higher Period Transition Metal Complexes