Cloud Job Management in Molecular Modeling: A Practical Guide

For molecular modelers working with computationally intensive tasks like protein structure prediction or molecular dynamics, accessing sufficient computing power is often a challenge. Long simulations, resource-heavy algorithms, and multi-step workflows can overwhelm local computers or delay projects. This is where…

A Faster Way to Build Carbon Nanotube Models for Simulations

Designing nanotube-based nanodevices or studying their properties often means building precise atomic models, which can be a time-consuming task. If you’ve worked in nanotechnology, molecular transport modeling, or material science, you’re probably familiar with the repetitive steps needed to create…

Updating Molecular Topology in Real Time with IM-UFF

One common challenge in molecular modeling is adapting molecular structures when atoms move during a simulation. Often, manually updating topologies like covalent bonds and atom types can slow down workflows and increase the chance of errors. If you’ve ever tried…

Processing Multiple Protein Structures Without the Headaches

Working with dozens (or hundreds) of PDB files can be a common challenge in computational biology and drug discovery. Whether you’re screening compounds, running molecular dynamics, or preparing datasets for machine learning, there’s one recurring issue: curating and prepping all…

What Happens When Atoms Go Missing in Crystals?

Crystal structures are often taught as perfect, repetitive lattices. But in actual materials, atoms are not always perfectly placed. Defects—such as missing atoms or substitutions—can significantly change the properties of a material, from conductivity to hardness. For molecular modelers trying…