Abstract
This paper introduces ISOLDE, a new software package designed to provide an intuitive environment for high-fidelity interactive remodelling/refinement of macromolecular models into electron-density maps. ISOLDE combines interactive molecular-dynamics flexible fitting with modern molecular-graphics visualization and established structural biology libraries to provide an immersive interface wherein the model constantly acts to maintain physically realistic conformations as the user interacts with it by directly tugging atoms with a mouse or haptic interface or applying/removing restraints. In addition, common validation tasks are accelerated and visualized in real time. Using the recently described 3.8 Å resolution cryo-EM structure of the eukaryotic minichromosome maintenance (MCM) helicase complex as a case study, it is demonstrated how ISOLDE can be used alongside other modern refinement tools to avoid common pitfalls of low-resolution modelling and improve the quality of the final model. A detailed analysis of changes between the initial and final model provides a somewhat sobering insight into the dangers of relying on a small number of validation metrics to judge the quality of a low-resolution model.
Highlights
As the resolution of a crystallographic or cryo-EM data set degrades, the challenge faced by the model builder increases rapidly as first individual atoms, small bonded groups and eventually entire residues become effectively unidentifiable from the density alone
While standards have improved over time, it remains common for novel lowresolution structures to be published with statistics indicating high levels of residual error
The quality of visualization becomes important at low resolution: whereas at high resolution the source of a problem and its solution are usually contained within the space of 1–3 residues, identifying the root cause of an error in a low-resolution structure may require a careful inspection of many dozens of residues at once
Summary
As the resolution of a crystallographic or cryo-EM data set degrades, the challenge faced by the model builder increases rapidly as first individual atoms, small bonded groups and eventually entire residues become effectively unidentifiable from the density alone. The difficulty is further compounded by the fact that low-resolution structures often tend to be large structures (Supplementary Fig. S1), with thousands or even tens of thousands of residues to contend with. It is unsurprising, that the rate of residual errors in published structures grows steeply with decreasing resolution. That the rate of residual errors in published structures grows steeply with decreasing resolution This fact has long been recognized (Kleywegt & Jones, 1995), and over the past two decades it has been common to see 3–4 Aresolution structures published with outlier rates 1–2 orders of magnitude higher than would be expected from atomic resolution structures (Croll & Andersen, 2016). While standards have improved over time (aided in no small part by an ever-increasing supply of high-resolution structures to mine for reference models), it remains common for novel lowresolution structures (with no useful high-resolution homology templates) to be published with statistics indicating high levels of residual error
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