By Forbes J. Burkowski
ISBN-10: 1420011790
ISBN-13: 9781420011791
... the publication offers a couple of themes in structural bioinformatics, aiming to stress the wonderful thing about the world in addition to a number of the major difficulties. It pursuits complex undergraduate scholars and therefore the outline of extra advanced algorithms is kept away from. It however offers a fascinating advent to the area.
-Lucian Ilie, Mathematical Reviews, Issue
summary:
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Additional info for Structural Bioinformatics : An Algorithmic Approach
Sample text
254], we can derive the value of the conversion factor as Kc = 332 (kcal/mol)(Å/esu2). Partial charge values for various atoms in both amino acids and nucleotides are reported in [Cc95] based on [Ccb95]. For now, we will assume that ε = 1 . Other values of ε will be discussed in the next section. 14) where Kc is 332 (kcal/mol)(Å/esu2), qi, q j are the partial charges for atom(i) and atom(j), respectively, r is the distance between atom(i) and atom(j), ij ε is the dielectric constant for the atom(i) and atom(j) “environ ij ment” (assumed to be 1 for now), F is the full set of all indices for the atoms, and [ i < j ] means that index i is less than index j, and also that atom(i) and atom(j) are either in separate molecules or, if in the same molecule, they are separated by at least three bonds.
Consequently, even though the potential of each interacting atom decreases as one gets farther from A, the number of these charges goes up. As noted in Schreiber and Steinhauser [Ss92], the cumulative sum over the shells does not converge to a final value in a monotonic fashion. Instead, as the radius of the shells grows, the electrostatic contributions oscillate in sign. It should be stressed that, even though the number of atoms in a shell increases, their net resultant is usually reduced, on average, due to cancellation effects.
When applied to mathematical modeling, the typical utilization of Ockham’s razor leads us to remove as many components (or variables) as possible from the model while still maintaining the power of the model to represent the observables seen in the natural process. Unfortunately, as noted in [Br01a], the accuracy of a model and its simplicity are often in conflict. This is especially true when simplification goes too far and the accuracy of the model is weakened because it lacks necessary information.
Structural Bioinformatics : An Algorithmic Approach by Forbes J. Burkowski
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