Abstract
Model building into experimental maps is a key element of structural biology, but can be both time consuming and error prone for low-resolution maps. Here we present Namdinator, an easy-to-use tool that enables the user to run a molecular dynamics flexible fitting simulation followed by real-space refinement in an automated manner through a pipeline system. Namdinator will modify an atomic model to fit within cryo-EM or crystallography density maps, and can be used advantageously for both the initial fitting of models, and for a geometrical optimization step to correct outliers, clashes and other model problems. We have benchmarked Namdinator against 39 deposited cryo-EM models and maps, and observe model improvements in 34 of these cases (87%). Clashes between atoms were reduced, and the model-to-map fit and overall model geometry were improved, in several cases substantially. We show that Namdinator is able to model large-scale conformational changes compared to the starting model. Namdinator is a fast and easy tool for structural model builders at all skill levels. Namdinator is available as a web service (https://namdinator.au.dk), or it can be run locally as a command-line tool.
Highlights
In recent years, major technical advances in the cryo-EM field have resulted in an increasing number of cryo-EM density maps being deposited (Kuhlbrandt, 2014; Subramaniam, 2019)
molecular dynamics flexible fitting (MDFF) can fit a model in a flexible manner into a cryo-EM density map using molecular dynamic simulations (Trabuco et al, 2008)
Through testing and benchmarking we demonstrate that we can obtain excellent MDFF fits of models to cryo-EM maps with no manual intervention by using Namdinator
Summary
Major technical advances in the cryo-EM field have resulted in an increasing number of cryo-EM density maps being deposited (Kuhlbrandt, 2014; Subramaniam, 2019). In 2008, the powerful molecular dynamics flexible fitting (MDFF) method was presented. MDFF can fit a model in a flexible manner into a cryo-EM density map using molecular dynamic simulations (Trabuco et al, 2008). Implementing MDFF as a standard tool for model building involves a steep learning curve, including preparing and restraining an input model for molecular dynamics simulations, converting EM or crystallographic maps to a potential field, and setting up and running the simulations. Through testing and benchmarking we demonstrate that we can obtain excellent MDFF fits of models to cryo-EM maps with no manual intervention by using Namdinator. Namdinator assists and speeds up all types of model building and improves the quality of the final model while ensuring a good fit to the observed density
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