Shaun M. Kandathil

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We propose a generic method to model polarization in the context of high-rank multipolar electrostatics. This method involves the machine learning technique kriging, here used to capture the response of an atomic multipole moment of a given atom to a change in the positions of the atoms surrounding this atom. The atoms are malleable boxes with sharp(More)
As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions(More)
We discuss the issue of heuristic bias in fragment-assembly methods for protein structure prediction. We explain the importance of this issue, which has been paid insufficient attention by evolutionary computation researchers engaging with the structural biology community. We proceed by describing preliminary data that illustrates the significant (and(More)
Our ongoing work focuses on improvements to the exploration behaviour of heuristic search techniques in fragment-assembly methods for protein structure prediction. Analysing and improving exploration in fragment-assembly can be difficult due to the complexity of measuring diversity between decoys in a meaningful manner. Here, we define a set of local and(More)
A combination of the temperature- and pressure-dependencies of the kinetic isotope effect on the proton coupled electron transfer during ascorbate oxidation by ferricyanide suggests that this reference reaction may exploit vibrationally assisted quantum tunnelling of the transferred proton.
Despite the use of combination antiretroviral drugs for the treatment of HIV-1 infection, the emergence of drug resistance remains a problem. Resistance may be conferred either by a single mutation or a concerted set of mutations. The involvement of multiple mutations can arise due to interactions between sites in the amino acid sequence as a consequence of(More)
Computational approaches to de novo protein tertiary structure prediction, including those based on the preeminent "fragment-assembly" technique, have failed to scale up fully to larger proteins (on the order of 100 residues and above). A number of limiting factors are thought to contribute to the scaling problem over and above the simple combinatorial(More)
Energy functions, fragment libraries, and search methods constitute three key components of fragment-assembly methods for protein structure prediction, which are all crucial for their ability to generate high-accuracy predictions. All of these components are tightly coupled; efficient searching becomes more important as the quality of fragment libraries(More)
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