Molecular Dynamics Flexible Fitting (MDFF)

Living cells are brimming with the activity of macromolecular complexes carrying out their assigned tasks. Structures of these complexes can be resolved with cryo-electron microscopy (cryo-EM), wherein the complexes are first freeze-shocked into states characterizing their action and subsequently imaged by detection cameras. Recent advances in direct detection camera technology enable today's cryo-EM laboratories to image the macromolecular complexes at high-resolution, giving us a better view of the cell than ever before. Computational techniques like molecular dynamics flexible fitting (MDFF) are a key tool for producing atomic models of the imaged molecules, providing greater insight into their structure and function. The increased resolution of EM maps, which contain sharp valleys capable of trapping structures, presents a challenge to MDFF which was originally developed for maps in a lower resolution range. However, our study unveils two new techniques called cascade (cMDFF) and resolution exchange (ReMDFF) molecular dynamics flexible fitting to overcome the hurdles posed by high-resolution maps. The refinement is achieved by interpreting a range of cryo-EM images, starting with an image of fuzzy resolution and progressively improving the image's contrast until near-atomic resolution is reached. New analysis schemes that look at the flexibility of the obtained structure provide a measure of model uncertainty within the near-atomic EM images, improving their contrast. All the tools are available on cloud computing platforms allowing community-wide usage at low monetary cost; the complex computations can now be performed at the cost of a cup of coffee.



For many, the word 'X-ray' conjures up the images of white bones on black backgrounds hanging on the wall of a doctor's office. However, X-rays have played another important role for the past 100 years through their use in the determination of chemical structures at atomic level detail, starting with the first ever structure of table salt in 1924. Since then, the diffraction properties of X-rays, when shone on a crystal, have been used to solve increasingly large and complex structures including those of biological macromolecules found inside living cells. X-ray crystallography has become the most versatile and dominant technique for determining atomic structures of biomolecules, but despite its strengths, X-ray crystallography struggles in the case of large or flexible structures as well as in the case of membrane proteins, either of which diffract only at low resolutions. Because solving structures from low-resolution data is a difficult, time-consuming process, such data sets are often discarded. To face the challenges posed by low-resolution, new methods, such as xMDFF (Molecular Dynamics Flexible Fitting for X-ray Crystallography) described here, are being developed. xMDFF extends the popular MDFF software originally created for determining atomic-resolution structures from cryo-electron microscopy density maps. xMDFF provides a relatively easy solution to the difficult process of refining structures from low-resolution data. The method has been successfully applied to experimental data as described in a recent article where xMDFF refinement is explained in detail and its use is demonstrated. Together with electrophysiology experiments, xMDFF was also used to validate the first all-atom structure of the voltage sensing protein Ci-VSP, as also  reported. More on our MDFF website.



In recent years, owing to the advances in instrumentation, cryo-EM has emerged as the go-to tool for obtaining high-resolution structures of biomolecular systems. However, building  three-dimensional atomic structures of biomolecules from these high-resolution maps remains a concern for the traditional map-guided structure-determination schemes. Recently, we developed a computational tool, Resolution Exchange Molecular Dynamics Flexible Fitting (ReMDFF) to address this problem by re-refining a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. We have employed the structure determination of carbon monoxide dehydrogenase and Mg2+-channel CorA as case studies. All  scripts are available HERE.

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NAMD tools for large-scale conformational transitions

Millisecond-scale conformational transitions represent a seminal challenge for traditional molecular dynamics simulations, even with the help of high-end supercomputer architectures. Such events are particularly relevant to the study of molecular motors—proteins or abiological constructs that convert chemical energy into mechanical work. Here, we present a hybrid-simulation scheme combining an array of methods including elastic network models, transition path sampling, and advanced free-energy methods, possibly in conjunction with generalized-ensemble schemes to deliver a viable option for capturing the millisecond-scale motor steps of biological motors. The methodology is already implemented in large measure in NAMD, and it can leverage the massively parallel capabilities of petascale computers. 

Motor simulation methodology

First an initial potential-energy minimizing pathway is derived employing Anisotropic Network Models ala Das and Roux ( This initial trajectory is refined to determine the minimum free energy path of the millisecond-scale conformational transition. The path optimization is achieved employing string simulations with swarm of trajectories.  The free energy and rate information are subsequently determined employing Bias exchange umbrella sampling and subsequent maximum-likelihood approaches following Hummer ( and, Szabo and Schulten ( The entire protocol is scripted by Das, Moradi, Chipot and Singharoy, and distributed herewith (find anmpathway.tar and at the buttom of the page). Further theoretical details of the protocol can be found HERE.


NAMD tools for simulations with > 5 million atoms 

Scripts used for setting up a chromatophore simulation are available at the following link

Chromatophore simulation scripts

anmpathway.tar910 KB
simulation-script.zip160 KB