Expanding DP4: application to drug compounds and automation.

The DP4 parameter, which provides a confidence level for NMR assignment, has been widely used to help assign the structures of many stereochemically-rich molecules. We present an improved version of the procedure, which can be downloaded as Python script instead of running within a web-browser, and which analyses output from open-source molecular modelling programs (TINKER and NWChem) in addition to being able to use output from commercial packages (Schrodinger's Macromodel and Jaguar; Gaussian). The new open-source workflow incorporates a method for the automatic generation of diastereomers using InChI strings and has been tested on a range of new structures. This improved workflow permits the rapid and convenient computational elucidation of structure and relative stereochemistry.The authors wish to thank Medivir for the generous financial support.This is the final version of the article. It first appeared from the Royal Society of Chemistry via https://doi.org/10.1039/C6OB00015

The optimal DFT approach in DP4 NMR structure analysis - pushing the limits of relative configuration elucidation.

What computational methods should be used to achieve the most reliable result in computational structure elucidation? A study on the effect of quality and quantity of geometries on computational NMR structure elucidation performance is reported. Semi-empirical, HF and DFT methods were explored, and B3LYP optimized geometries in combination with mPW1PW91 shifts and M06-2X conformer energies was found to be best. The required number of conformers considered has also been investigated, as well as several methods for the reduction of this number. Clear guidelines for the best computational NMR structure elucidation methods for different levels of available computing power are provided.Medivir, Leverhulme Trust and Isaac Newton Trus

Conformational search and DFT calculation data investigating effect of geometry quantity, quality and energy calculation method on structure elucidation performance

This dataset contains macromodel conformational search input and output files, Gaussian DFT and GIAO calculation input and output files, as well as NMR description files for DP4 analysis.Medivir Leverhulme Trust Isaac Newton Trus

Quantitative measurement of protease ligand conformation

The tendency for protease ligands to bind in an extended conformation has been suggested as an important factor for the identification of compounds of medicinal importance. Here we present a novel graph-theoretical method giving a quantitative measure of ligand conformation, and through application of this method to a representative set of protease ligands in bound and unbound conformations, derive the result that protease ligands are more extended in conformation when in their bound state. © Springer Science+Business Media B.V. 2008

Connectivity and binding-site recognition: Applications relevant to drug design

Here, we describe a family of methods based on residue-residue connectivity for characterizing binding sites and apply variants of the method to various types of protein-ligand complexes including proteases, allosteric-binding sites, correctly and incorrectly docked poses, and inhibitors of protein-protein interactions. Residues within ligand-binding sites have about 25% more contact neighbors than surface residues in general; high-connectivity residues are found in contact with the ligand in 84% of all complexes studied. In addition, a k-means algorithm was developed that may be useful for identifying potential binding sites with no obvious geometric or connectivity features. The analysis was primarily carried out on 61 protein-ligand structures from the MEROPS protease database, 250 protein-ligand structures from the PDBSelect (25%), and 30 protein-protein complexes. Analysis of four proteases with crystal structures for multiple bound ligands has shown that residues with high connectivity tend to have less variable side-chain conformation. The relevance to drug design is discussed in terms of identifying allosteric-binding sites, distinguishing between alternative docked poses and designing protein interface inhibitors. Taken together, this data indicate that residue-residue connectivity is highly relevant to medicinal chemistry. © 2010 Wiley Periodicals, Inc