2017
DOI: 10.1016/j.jmgm.2017.03.018
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Hybrid Voronoi diagrams, their computation and reduction for applications in computational biochemistry

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Cited by 6 publications
(5 citation statements)
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“…For example, although eukaryotic ribosomes are generally larger in size than bacterial ones, their exit tunnel is narrower with heterogeneous variations along it [ 14 , 98 ]. Various algorithms and computational methods adapted to molecular structures, based on tesselation [ 99 , 100 , 101 ] (illustrated in Figure 4 a), or spectral geometry [ 102 ], can be used to encode the structure into geometric objects [ 103 ], and in particular compare ribosome geometric features. For example, by estimating the relative position of residues to the surface, one can separate proteins according to their degree of exposition to the solvent (see Figure 4 b), which has been hypothesized as a key factor for differentiating proteins prone to ribosome repair [ 64 ] or with distinct electrostatic properties [ 104 ].…”
Section: Computational Challenges For Quantifying Heterogeneity Frmentioning
confidence: 99%
“…For example, although eukaryotic ribosomes are generally larger in size than bacterial ones, their exit tunnel is narrower with heterogeneous variations along it [ 14 , 98 ]. Various algorithms and computational methods adapted to molecular structures, based on tesselation [ 99 , 100 , 101 ] (illustrated in Figure 4 a), or spectral geometry [ 102 ], can be used to encode the structure into geometric objects [ 103 ], and in particular compare ribosome geometric features. For example, by estimating the relative position of residues to the surface, one can separate proteins according to their degree of exposition to the solvent (see Figure 4 b), which has been hypothesized as a key factor for differentiating proteins prone to ribosome repair [ 64 ] or with distinct electrostatic properties [ 104 ].…”
Section: Computational Challenges For Quantifying Heterogeneity Frmentioning
confidence: 99%
“…In particular, we selected two set of parameters. The first set aimed to monitor the evolution of solvent-accessible tunnels from the protein surface towards the catalytic site, where we used a probe radius of 1.5 Å, comparable to the size of a water molecule [73], a shell radius of 5 Å, shell depth of 4 Å, and a clustering threshold of 7 Å. In the second set of parameters, we used the same parameters as the first set but with a probe radius of 2.0 Å to resemble the size of the natural substrate 3-methylaspartate.…”
Section: Methodsmentioning
confidence: 99%
“…The first set aimed to monitor the evolution of solvent-accessible tunnels from the protein surface towards the catalytic site, where we used a probe radius of 1.5 Å, comparable to the size of a water molecule [73], a shell radius of 5 Å, shell depth of 4 Å, and a clustering threshold of 7 Å. In the second set of parameters, we used the same parameters as the first set but with a probe radius of 2.0 Å to resemble the size of the natural substrate 3-methylaspartate.…”
Section: Tunnel Analysesmentioning
confidence: 99%