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NCIPLOT: A Program for Plotting Noncovalent Interaction Regions

Journal of Chemical Theory and Computation · 2011 · Vol. 7(3) · pp. 625–632
Julia Contreras‐GarcíaErin R. JohnsonShahar KeinanRobin ChaudretJean‐Philip PiquemalDavid N. BeratanWeitao Yang

Abstract

Non-covalent interactions hold the key to understanding many chemical, biological, and technological problems. Describing these non-covalent interactions accurately, including their positions in real space, constitutes a first step in the process of decoupling the complex balance of forces that define non-covalent interactions. Because of the size of macromolecules, the most common approach has been to assign van der Waals interactions (vdW), steric clashes (SC), and hydrogen bonds (HBs) based on pairwise distances between atoms according to their van der Waals radii. We recently developed an alternative perspective, derived from the electronic density: the Non-Covalent Interactions (NCI) index [J. Am. Chem. Soc. 2010, 132, 6498]. This index has the dual advantages of being generally transferable to diverse chemical applications and being very fast to compute, since it can be calculated from promolecular densities. Thus, NCI analysis is applicable to large systems, including proteins and DNA, where analysis of non-covalent interactions is of great potential value. Here, we describe the NCI computational algorithms and their implementation for the analysis and visualization of weak interactions, using both self-consistent fully quantum-mechanical, as well as promolecular, densities. A wide range of options for tuning the range of interactions to be plotted is also presented. To demonstrate the capabilities of our approach, several examples are given from organic, inorganic, solid state, and macromolecular chemistry, including cases where NCI analysis gives insight into unconventional chemical bonding. The NCI code and its manual are available for download at http://www.chem.duke.edu/~yang/software.htm.

Protein Structure and DynamicsChemical Synthesis and AnalysisMachine Learning in Materials ScienceComputer scienceNon-covalent interactionsComputer graphics (images)Human–computer interactionChemistryHydrogen bond
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