Background: Techniques for inferring the functions of the protein by comparing their shapeÃ‚Â similarity have been receiving a lot of attention. Proteins are functional units and their shapeÃ‚Â flexibility occupies an essential role in various biological processes. Several shape descriptors haveÃ‚Â demonstrated the capability of protein shape comparison by treating them as rigid bodies. But thisÃ‚Â may give rise to an incorrect comparison of flexible protein shapes.
Results: We introduce an efficient approach for comparing flexible protein shapes by adapting aÃ‚Â local diameter (LD) descriptor. The LD descriptor, developed recently to handle skeleton basedÃ‚Â shape deformations , is adapted in this work to capture the invariant properties of shapeÃ‚Â deformations caused by the motion of the protein backbone. Every sampled point on the proteinÃ‚Â surface is assigned a value measuring the diameter of the 3D shape in the neighborhood of thatÃ‚Â point. The LD descriptor is built in the form of a one dimensional histogram from the distributionÃ‚Â of the diameter values. The histogram based shape representation reduces the shape comparisonÃ‚Â problem of the flexible protein to a simple distance calculation between 1D feature vectors.Ã‚Â Experimental results indicate how the LD descriptor accurately treats the protein shapeÃ‚Â deformation. In addition, we use the LD descriptor for protein shape retrieval and compare it toÃ‚Â the effectiveness of conventional shape descriptors. A sensitivity-specificity plot shows that the LDÃ‚Â descriptor performs much better than the conventional shape descriptors in terms of consistencyÃ‚Â over a family of proteins and discernibility across families of different proteins.
Conclusion: Our study provides an effective technique for comparing the shape of flexibleÃ‚Â proteins. The experimental results demonstrate the insensitivity of the LD descriptor to proteinÃ‚Â shape deformation. The proposed method will be potentially useful for molecule retrieval withÃ‚Â similar shapes and rapid structure retrieval for proteins. The demos and supplemental materials areÃ‚Â available on https://engineering.purdue.edu/PRECISE/LDD.
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