Clifford algebra and discretizable distance geometry
Protein structure calculations using nuclear magnetic resonance (NMR) experiments are one of the most important applications of distance geometry. The chemistry of proteins and the NMR data allow us to define an atomic order, such that the distances related to the pairs of atoms {i−3,i},{i−2,i},{i−1...
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| Veröffentlicht in: | Mathematical methods in the applied sciences Jg. 41; H. 11; S. 4063 - 4073 |
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| Abstract | Protein structure calculations using nuclear magnetic resonance (NMR) experiments are one of the most important applications of distance geometry. The chemistry of proteins and the NMR data allow us to define an atomic order, such that the distances related to the pairs of atoms {i−3,i},{i−2,i},{i−1,i} are available, and solve the problem iteratively using a combinatorial method, called branch‐and‐prune. The main step of BP algorithm is to intersect three spheres centered at the positions for atoms i−3,i−2,i, with radius given by the atomic distances di−3,i,di−2,i,di−1,i, respectively, to obtain the position for atom i. Because of uncertainty in NMR data, some of the distances di−3,i may not be precise or even not be available. Using conformal Clifford algebra, in addition to take care of NMR uncertainties, which implies that we have to calculate sphere intersections considering that their centers and radius may not be fixed anymore, we consider a more flexible atomic order, where distances di−3,i are replaced by dj,i, where j⩽i−3. Copyright © 2017 John Wiley & Sons, Ltd. |
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| AbstractList | Protein structure calculations using nuclear magnetic resonance (NMR) experiments are one of the most important applications of distance geometry. The chemistry of proteins and the NMR data allow us to define an atomic order, such that the distances related to the pairs of atoms {i−3,i},{i−2,i},{i−1,i} are available, and solve the problem iteratively using a combinatorial method, called branch‐and‐prune. The main step of BP algorithm is to intersect three spheres centered at the positions for atoms i−3,i−2,i, with radius given by the atomic distances di−3,i,di−2,i,di−1,i, respectively, to obtain the position for atom i. Because of uncertainty in NMR data, some of the distances di−3,i may not be precise or even not be available. Using conformal Clifford algebra, in addition to take care of NMR uncertainties, which implies that we have to calculate sphere intersections considering that their centers and radius may not be fixed anymore, we consider a more flexible atomic order, where distances di−3,i are replaced by dj,i, where j⩽i−3. Copyright © 2017 John Wiley & Sons, Ltd. Protein structure calculations using nuclear magnetic resonance (NMR) experiments are one of the most important applications of distance geometry. The chemistry of proteins and the NMR data allow us to define an atomic order, such that the distances related to the pairs of atoms { i −3, i },{ i −2, i },{ i −1, i } are available, and solve the problem iteratively using a combinatorial method, called branch‐and‐prune. The main step of BP algorithm is to intersect three spheres centered at the positions for atoms i −3, i −2, i , with radius given by the atomic distances d i −3, i , d i −2, i , d i −1, i , respectively, to obtain the position for atom i . Because of uncertainty in NMR data, some of the distances d i −3, i may not be precise or even not be available. Using conformal Clifford algebra, in addition to take care of NMR uncertainties, which implies that we have to calculate sphere intersections considering that their centers and radius may not be fixed anymore, we consider a more flexible atomic order, where distances d i −3, i are replaced by d j , i , where j ⩽ i −3. Copyright © 2017 John Wiley & Sons, Ltd. |
| Author | Alves, R. Souza, C. Souza, M. Lavor, C. |
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| Cites_doi | 10.29007/6fc5 10.1007/0-387-30927-6_9 10.1016/j.dam.2014.08.035 10.1007/978-1-4614-5128-0 10.1007/BF01448840 10.1007/s00006-016-0653-2 10.1007/s11590-011-0358-3 10.1016/j.ejor.2011.11.007 10.1016/j.orl.2011.07.007 10.1142/S0219720012420097 10.1007/s10288-016-0314-2 10.1007/s11590-014-0724-z 10.1186/s12859-015-0451-1 10.15439/2014F92 10.1111/j.1475-3995.2009.00757.x 10.1111/itor.12170 10.1103/PhysRevLett.79.325 10.1201/b18273 10.1063/1.4756054 10.1007/978-3-662-04621-0_2 10.1111/j.1475-3995.2007.00622.x 10.1007/s10898-011-9799-6 10.1109/MSP.2015.2398954 10.1007/s00006-010-0206-z 10.1016/j.dam.2013.01.020 10.1007/978-1-4612-0159-5_1 10.1007/s00006-015-0532-2 10.1186/1471-2105-14-S9-S7 10.1145/2949035.2949057 10.1137/120875909 10.1007/s10589-011-9402-6 10.1126/science.2911719 |
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| SubjectTerms | 3D protein structure Atomic radius Atomic structure branch‐and‐prune algorithm Combinatorial analysis conformal Clifford algebra distance geometry Intersections Mathematical analysis NMR Nuclear magnetic resonance Organic chemistry Proteins Uncertainty |
| Title | Clifford algebra and discretizable distance geometry |
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