Generating realistic transition paths between protein conformations is valuable for structural analysis, molecular dynamics, and free energy calculations. However, a common, often frustrating hurdle in these workflows is preparing protein structures: missing atoms, extra chains, water molecules, and ligands can…
When working with large and complex molecular systems, modelers often face the challenge of isolating meaningful subsets of data within a structure. Whether it’s identifying loops in protein backbones or analyzing particular conformational changes, precise selection is essential. Thankfully, SAMSON’s…
When studying transitions between molecular states, a common challenge in computational chemistry is building a reliable minimum energy path connecting two conformations. This is essential for exploring reaction mechanisms, ligand unbinding, or protein conformational changes. But what’s the most efficient…
When working with coarse-grained (CG) molecular dynamics simulations, one common scenario is modeling systems that contain multiple copies—or replicas—of the same protein. This is typical in studies involving protein aggregation, crowding effects, or multi-component assemblies using approaches like the MARTINI…
When working with large molecular systems, identifying specific atoms with precision can be time-consuming and frustrating. Whether you’re cleaning up a model, extracting meaningful subsets, or analyzing specific substructures, selecting atoms by hand becomes inefficient and error-prone very quickly. This…
