Abstract:
:We propose a new geometric buildup algorithm for the solution of the distance geometry problem in protein modeling, which can prevent the accumulation of the rounding errors in the buildup calculations successfully and also tolerate small errors in given distances. In this algorithm, we use all instead of a subset of available distances for the determination of each unknown atom and obtain the position of the atom by using a least-squares approximation instead of an exact solution to the system of distance equations. We show that the least-squares approximation can be obtained by using a special singular value decomposition method, which not only tolerates and minimizes small distance errors, but also prevents the rounding errors from propagation effectively, especially when the distance data is sparse. We describe the least-squares formulations and their solution methods, and present the test results from applying the new algorithm for the determination of a set of protein structures with varying degrees of availability and accuracy of the distances. We show that the new development of the algorithm increases the modeling ability, and improves stability and robustness of the geometric buildup approach significantly from both theoretical and practical points of view.
journal_name
Bull Math Bioljournal_title
Bulletin of mathematical biologyauthors
Sit A,Wu Z,Yuan Ydoi
10.1007/s11538-009-9431-9subject
Has Abstractpub_date
2009-11-01 00:00:00pages
1914-33issue
8eissn
0092-8240issn
1522-9602journal_volume
71pub_type
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