Abstract
We propose a modified version of the mountain clustering method (MCM) to find a library of structural building blocks for the construction of three-dimensional (3-D) structures of proteins. The algorithm decides on building blocks based on a measure of local density of structural patterns. We tested our algorithm on a well-known data set and found it to successfully reconstruct a set of 71 test proteins (up to first 60 residues as done by others) with lower global-fit root mean square (RMS) errors compared to an existing method that inspired our algorithm. The constructed library of building blocks is also evaluated using some other benchmark data set for comparison. Our algorithm achieved good local-fit RMS errors, indicating that these building blocks can model the nearby fragments quite accurately. In this context, we have proposed two alternative ways to compare the quality of such quantization and reconstruction results, which can be used in other applications too.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
