Abstract
In this paper, we propose a constraint-based approach to determining protein structures compatible with distance constraints obtained from Nuclear Magnetic Resonance (NMR) data. We compare the performance of our proposed algorithm with DYANA (“Dynamics algorithm for NMR applications” [1]) an existing commercial application based on simulated annealing. For our test case, computation time for DYANA was more than six hours, whereas the method we propose produced similar results in 8 minutes, so we show that the application of Constraint Programming (CP) technology can greatly reduce computation time. This is a major advantage because this NMR technique generally demands multiple runs of structural computation.
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Krippahl, L., Barahona, P. (1999). Applying Constraint Programming to Protein Structure Determination. In: Jaffar, J. (eds) Principles and Practice of Constraint Programming – CP’99. CP 1999. Lecture Notes in Computer Science, vol 1713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48085-3_21
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DOI: https://doi.org/10.1007/978-3-540-48085-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66626-4
Online ISBN: 978-3-540-48085-3
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