In this new age of computational prowess, many researchers are finding themselves with a growing need for specific, selected computational results. Whether to confirm spectral observations, to correlate experimental observables with structure, or to provide preliminary information on stability or reactivity, the results must first be computed and subsequently analysed. With the construction and implementation of a logical and standardised numbering of atomic nuclei , to define molecular systems, automation of conformational sampling and data extraction could greatly improve the search for structural energy minima on the potential energy hypersurfaces of these systems. A standard affords an objective and reproducible data set, whereby the data generated for one system becomes reusable for other related systems, particularly for peptide, saccharide, DNA and lipid systems, known as the ‘building blocks of life’. Modular and numeric definitions of each incorporated module allows for the removal or truncation of any or all compromising portions at any time, effectively, efficiently and without gross perturbation to the remainder of the model. The practical application to the construction of the topologically possible set of conformers, emerging from Multi-Dimensional Conformational Analysis (MDCA) is highlighted with an elaboration upon the resultant topologically probable (stable) conformer set. Pattern matching and an N-Dimensional Quantitative Structure Activity Relationship (N-D QSAR) ‘trend recognition’ is proposed and supported with exemplary peptide systems.
Global Institute Of COmputational Molecular and Material Sciences (GIOCOMMS), Toronto, Ontario, Canada