A robust and efficient algorithm for determining molecular connectivities.

Molecular dynamics (MD) simulations are a powerful tool for describing the structure, dynamics, and function of biomolecules in microscopic detail. The role of numerical simulations in biochemistry has been steadily growing in recent decades. The continuing growth in computer power has made it possible to analyse, compare and characterise large and complex datasets obtained from computational experiments, like protein folding. Proteins are particularly important biomolecules, because they perform important biological functions that are critical for sustaining complex life, such as biocatalysis, energy production, storage and processing, and electrochemical signal transduction. Therefore, they have been the focus of most molecular dynamics studies. However, other biopolymers - DNA, RNA, polysaccharides - and biomolecules - sugars, lipids, neurotransmitters, nucleobases - are also important but have received far less attention from the molecular simulation community. This is largely due to the additional complexity associated with describing the structures and energies of these molecules and in particular interactions between them