Bio3D-web is a new online application for the user friendly investigation of protein structure ensembles.
Major functionality allows you to map and explore the structural, conformational and internal dynamic properties of proteins for which there are high resolution structures available. Read More>>
Bio3D-web is a new online web server for the user friendly exploratory analysis of protein sequence-structure-dynamics relationship. Bio3D-web is powered by the well established Bio3D R package for structural bioinformatics (Grant et al. (2006)).
Bio3D-web does not require any installation or programming skills – you explore through an easy to use online interface. This is in contrast to the conventional Bio3D package, which typically requires installation on your own hardware, knowledge of the R-Bio3D language, and use of the unix like command line.
No. There are lots of excellent normal mode analysis servers already out there such as WebNM@, elNémo, AD-ENM, ANM and iMODS. These offer NMA calculation capabilities for individual biomolecular structures.
Bio3D-web is unique in providing more expansive and integrated functionality for the identification, comparison and detailed analysis of large homologous structure sets online. We designed Bio3D-web to increase the accessibility and decrease the entry barrier to performing advanced comparative sequence, structure and dynamics analysis across user defined structure sets not just single structures.
Both Bio3D and ProDy (a related python library developed by others) offer much more functionality than is provided in this online application. If you can use these packages productively then we encourage you to do so. One of our main motivations for developing Bio3D-web was to allow new users to be productive with methods like PCA and eNMA without having to first learn Bio3D usage. We hope you will find Bio3D-web useful and then feel motivated to use the conventional Bio3D R-package on your own computers and for your own custom analysis.
Principal component analysis (PCA) is a well established statistical method that is most commonly used as a dimensionally reduction technique for multivariate data analysis - that is input data that has many dimensions, e.g. many different atomic coordinates that have been measured for multiple experimental structures.
Essentially, the PCA performed here aims to succinctly ‘map out’ the conformational relationships in large sets of protein structures and provide quantitate insight into the structural regions that contribute to any distinct conformations identified.
More explicitly, Bio3D-web utilizes PCA to provide a new condensed view of large structural datasets. This condensed view is basically a re-framing that retains the essential essence of the entire coordinate data. The new view is given in terms of what are known as principal components. These principal components are new directions in the data along which there is maximal variance - or more simply put, the directions where our set of structures differ most (i.e. are most spread out). The whole idea of PCA is to find these new directions of maximal variation in the coordinate data and use them to better understand major conformational features of the dataset.
The output of PCA includes a lower dimensional ‘reframing’ of your complete structure set that can simplify visualization and make it easier to uncover and further analyze interesting underlying structure relationships. These relationships can be hard to see in the original coordinate data (e.g. from just looking at superposed structures) because you might have many original dimensions to examine. PCA is also particularly useful as it allows you to qualitatively assess which regions of your structures are contributing most to the revealed structure relationships.
We encourage users that are not familiar with PCA to look into many of the great resources available online (e.g. the Bio3D website).
Normal modes analysis (NMA) is a computational technique to characterize all possible deformations a protein can undergo. These motions are conveniently sorted with respect to the energy needed to deform the protein along the particular normal mode vector. This computational technique is particularly suited to probe large-scale collective motions typically associated with protein function.
NMA application most often involves the analysis of only a single protein structure. As the normal modes are sensitive to the specific protein conformation for which they are calculated, the exclusion of alternative protein conformations provides only a limited picture of the overall flexibility of the protein under different conditions.
A more complete picture of protein flexibility can be obtained by performing NMA across all structure in an ensemble in a way that facilities the interoperation of structural similarity and dissimilarity trends. This allows a user to explore dynamic trends of all crystalized states in relation to each other without the conventional caveat of potentially over-interpreting the differences between extreme cases or a single artifactual structure. Furthermore, by carefully contrasting the fluctuation profiles one can provide new information on state specific global and local dynamics of potential functional relevance.
A major current limitation is our restriction to analyzing only single chains from multi-chain PDB structures. Future versions of Bio3D-web will include the ability to perform single-chain, multi-chain and reconstructed biounit analysis. For now, if you would like to perform this type of analysis you should use the full Bio3D R package and the new biounit() function.
Another limitation is the comparatively slow performance of the ensemble normal mode analysis tab. Note that due to available hardware limitations we currently perform eNMA in series and thus restrict the total number of structures analyzed (even though our underlying code and approach is now paralyzed). Bio3D-web currently runs entirely on a small virtual machine. We plan to improve performance of the eNMA tab to seconds even for many hundreds of structures by linking to suitable cluster computing resources. Please contact us if this is something you would like to do now.
Our 3D structure viewer has limited interactivity and does not render trajectories as movies etc. For example, you can not click on a region of structure and find out what residues are involved in a large-scale motion. We are currently using the inbuilt Bio3D view.pdbs() function via WebGL but are exploring using PV for future versions. In this regard please note that we provide links/buttons to view your superposed structure ensembles, PCA and eNMA results in PyMOL on your own computer. We also provide PDB file download options that should allow you to more comprehensively view your results in other powerful molecular viewers including VMD and Chimera .
The bitscore is a score that describes the overall quality of the alignment between the query sequence and the search result. High bitscore corresponds to high sequence similarity. We report the bit scores from the HMMER search.
The algorithm iteratively refines an initial structural superposition determined from a multiple alignment. This involves iterated rounds of superposition, where at each round the position(s) displaying the largest differences is(are) excluded from the dataset (Grant et al. (2006)).
The principal components is calcualted from the superimposed coordinates excluding the gap containing columns (Skjaerven et al. (2014)).
The normal modes for each structure in the representative ensemble are calculated according to Fuglebakk et al. (2012) (see also Skjaerven et al. (2014)). The C-alpha force field developed by Konrad Hinsen (Hinsen et al. (2000)) is used for normal mode calculation. For a discussion and comparison of other force-fields and NMA methods see Yao et al. (2016)
If you have used Bio3D-web, please consider citing the following reference that describes this work:
Your questions and comments are important to us. If you like or do not like what we are doing, then please get in touch. Also, if there are new features that you would like to have added to the server, then drop us a line and we will see what we can do!
For the moment please use our BitBucket based issues tracker for any questions regarding the use of Bio3D-web or the larger Bio3D software package.
To expedite our response to your questions, please provide us with as much information as possible so that we can recreate the problem. Useful things to include are:
Many questions are also covered in the Bio3D documentation, so it may be worth browsing them before posting an issue.
This site provides an online interface to several Bio3D tools for comparative protein structure analysis.
Methods include (1) Searching for related structures, (2) Alignment of selected structures, (3) Fitting based on rigid core positions, (4) PCA (principal component analysis) for inter-conformer characterization and (5) eNMA (ensemble normal mode analysis) for additional structure dynamic characterization.
Each of these analysis steps is implemented as consecutive tabs accessible from the top navigation bar.
Start your analysis by entering a PDB code of interest and then proceed by navigating through the above tabs or following the NEXT buttons.
For a detailed usage guide please download and consult the Bio3D-web tutorial [ PDF ].
The results from your analyses will be saved on the server for 30 days.
You can revisit your data by pasting the session ID in the box below.