molsimplify

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-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.

Oct 27, 2021 molsimplify-tutorials, tutorials

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-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.

Mar 25, 2019 molsimplify-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-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.

May 9, 2018 molsimplify-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-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-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.

Dec 21, 2017 molsimplify-tutorials, tutorials

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.

Dec 6, 2017 molsimplify-tutorials, tutorials

molSimplify Tutorial 8: Higher Period Transition Metal Complexes