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Welcome to AD-ENM!

News and updates

A new SAXS-based modeling tool has been developed that flexibly fits a given initial protein structure with a given solution X-ray scattering profile based on a modified elastic network model. For details, check out our paper. This tool is now available as a linux-based pre-compiled executable. Please contact Wenjun Zheng (wjzheng@buffalo.edu) for further information. We are also happy to run the program for you if you are interested in collaboration.

A new tool (EMFF) is now available that flexibly fits a given initial protein structure into a given cryo-EM density map based on a modified elastic network model. Please click here to submit your job. You can find an example here.

A new tool (iENM) is now available that generates a transition path between two given macromolecular structures. Please click here to submit your job. You can find an example here.

A new tool (PATH-ENM) is now available that generates transition paths between two given macromolecular structures. Please click here to submit your job. You can find an example here.

A new modeling tool (DC-ENM) is now available that uses low-frequency normal modes and a few pairs of distance constraints to build protein structural models. Please feel free to submit your job. You can find an example here.

AD-ENM server now supports Jmol-based visualization and animation of the generated protein structural models and their motions as described by normal modes. Alternatively, you can still download the PDB files to view the motions with VMD.

Note on visualization with Jmol

If you have trouble running Jmol, please add "http://enm.lobos.nih.gov" to the Exception Site List on your Java Control Panel and set your Java security level to MEDIUM or HIGH (for details, see this help document). This change will give you the option of allowing the Jmol Java applet to run. If you have problems running Jmol using Chrome, please try Internet Explorer (Windows) or Safari (Mac OS X) instead.


The AD-ENM (Analysis of Dynamics of Elastic Network Model) server performs analysis of macromolecular dynamics based on a highly simplified physical model --- Elastic Network Model (ENM): it is built from a given protein structure by connecting its neighboring residues (or CA atoms within certain distance cutoff) by springs with a uniform force constant. For DNA/RNA structures P atoms are used instead to build the ENM. Then a normal modes analysis is executed to yield a spectrum of normal modes for the ENM. The low-frequency end of the spectrum is particularly interesting because those lowest modes are able to capture collective conformational changes that are hard to access by all-atom molecular dynamics simulations.

molecule image

The AD-ENM server provides a set of useful analysis of ENM dynamics in addition to the standard ones. To build the ENM, you must supply a macromolecular structure (in PDB format) and set several parameters (or use their default settings). Then you can choose from 3 options currently offered by AD-ENM:

1. If a second structure for the same macromolecule is known, the ENM can determine the contribution of each normal mode to the conformational changes between the two structures. This is a standard procedure to validate ENM and is thus kept here to honor the tradition, however, it is not very useful for predicting new information as compared with the latter two options.

2. If a new conformation of a subset of residues (so called pocket residues) is known, and you want to predict how the whole macromolecular structure changes in response to the given pocket deformation, you can do it by checking this option. This is a new analysis uniquely offered by AD-ENM (for reference, see Zheng & Doniach 2003 and Zheng & Brooks 2005). It allows you to predict possible global conformational changes triggered by a local structural deformation (for example, caused by ligand binding).

3. If you only know the identities of a subset of interesting residues (so called pocket residues) but you don't know their new conformation, you can check this option. This analysis examines the mean square fluctuation (MSF) of the pocket residues at a functional site, and it identifies those dynamically important hot-spot residues whose perturbation may affect the pocket MSF significantly, and those relevant normal modes that contribute significantly to the pocket MSF (for reference, see Zheng & Brooks 2005 and Zheng et al. 2007). Those hot-spot residues may be involved in allosteric couplings in enzymes and thus make good targets for mutational studies.

Start your job

If you feel like you know enough about AD-ENM and wish to give it a try, just go ahead and submit your job. You are also welcome to try the two newly added tools DC-ENM and PATH-ENM. After you submit a job (and leave your email address), you will be assigned a job ID number and when the job is finished you will be notified by email with a URL for you to check the results.


To help you get familiar with AD-ENM, an example is shown here.


If you are not satisfied with the brief introduction presented here and wish to find out more details, please check out our papers (all with links to PubMed).


If you have questions regarding the results of AD-ENM, please contact Wenjun Zheng.

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