Multifunctional behavior by a Bis-(phosphinimino)methanide ligand: eta 2- vs eta 3-coordination vs Bronsted basicity

The reaction of [(Cymene)RuCl2]2 with the chelate LiHC(PPh2NPh)2 occurs to remove both chloride ligands, to furnish a cationic Ru(II) complex with the monoanionic ligand bound eta3, through two N and an sp3 carbon. This cation is also produced from the conjugate acid of the ligand H2C(PPh2NPh)2 because this molecule can serve as a Br?nsted base, to deprotonate the acidic carbon of another molecule of H2C(PPh2NPh)2. DFT calculations show an energy surface where (Cymene)RuHC(PPh2NPh)2L is more stable with a Ru-CH(PPh2NPh)2 bond and with L = Cl- or MeCN not coordinated to Ru, than to an eta2-HC(PPh2NPh)2 structure with coordinated L; this is tested experimentally. The greater tendency for this ligand to be coordinated eta3 vs analogous diketiminates is discussed. The nucleophilicity of Cgamma in structure 1, vs that of donors L = Cl- or MeCN, is evaluated to understand the preference of the bis(phosphinimino)methanide to be bidentate or tridentate.     

Empirical and DFT GIAO quantum‐mechanical methods of 13C chemical shifts prediction: competitors or collaborators?

The accuracy of ¹³C chemical shift prediction by both DFT GIAO quantum‐mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM‐calculated chemical shifts were published in the literature. For these structures, ¹³C chemical shifts were calculated using HOSE code and neural network (NN) algorithms developed within our laboratory. In total, 2531 chemical shifts were analyzed and statistically processed. It has been shown that, in general, QM methods are capable of providing similar but inferior accuracy to the empirical approaches, but quite frequently they give larger mean average error values. For the structural set examined in this work, the following mean absolute errors (MAEs) were found: MAE(HOSE) = 1.58 ppm, MAE(NN) = 1.91 ppm and MAE(QM) = 3.29 ppm. A strategy of combined application of both the empirical and DFT GIAO approaches is suggested. The strategy could provide a synergistic effect if the advantages intrinsic to each method are exploited. Copyright © 2010 John Wiley & Sons, Ltd.     

Computer-aided determination of relative stereochemistry and 3D models of complex organic molecules from 2D NMR spectra

A method for elucidation of the relative stereoconfiguration of natural product molecular structures and their 3D models based on NOE data and the application of a genetic algorithm is described. The method is applicable mainly for rigid polycyclic structures commonly encountered in natural products. It is demonstrated that the technique of simulated annealing cannot be easily used when dealing with low-weight fused ring molecules but the application of a genetic algorithm is proven successful. Examples of a typical genetic algorithm workflow and the optimization of the algorithmic parameters are discussed. The efficiency of the approach developed here is demonstrated on the complex natural products of both Taxol^® (C₄₇H₅₁NO₁₄) and brevetoxin B (C₅₀H₇₀O₁₄).     

Performance validation of neural network based (13)c NMR prediction using a publicly available data source

The validation of the performance of a neural network based 13C NMR prediction algorithm using a test set available from an open source publicly available database, NMRShiftDB, is described. The validation was performed using a version of the database containing ca. 214,000 chemical shifts as well as for two subsets of the database to compare performance when overlap with the training set is taken into account. The first subset contained ca. 93,000 chemical shifts that were absent from the ACD\CNMR DB, the "excluded shift set" used for training of the neural network and the ACD\CNMR prediction algorithm, while the second contained ca. 121,000 shifts that were present in the ACD\CNMR DB training set, the "included shift set". This work has shown that the mean error between experimental and predicted shifts for the entire database is 1.59 ppm, while the mean deviation for the subset with included shifts is 1.47 and 1.74 ppm for excluded shifts. Since similar work has been reported online for another algorithm we compared the results with the errors determined using Robien's CNMR Neural Network Predictor using the entire NMRShiftDB for program validation.     

Calculating protein structures directly from anisotropic spin interaction constraints

Protein structure determination by solid-state NMR of aligned samples relies on the fundamental characteristics of the anisotropic nuclear spin interactions present in isotopically labeled proteins. Progress in the implementation of algorithms that calculate protein structures from the orientational constraints in the chemical shift and heteronuclear dipolar coupling interactions is described using both simulated and experimental data.     

Exceptionally facile CO addition to a saturated ruthenium complex

Synthesis and characterization of Cp*Ru[eta3-HC(PPh2NPh)2], 1, reveals it to have a "piano stool" structure with the ligand bound to Ru(II) via two N and the unique, sp3 hybridized carbon. While the analogous (cymene) Ru[eta3-HC(PPh2NPh)2]+ does not react with CO, under the same conditions, 1 adds one CO rapidly (25 degrees C, 1 atm CO). Characterization, including an X-ray structure determination, shows that CO has displaced one chelate ligand nitrogen, which then hangs off the molecule, free of Ru. DFT calculations reveal a possible mechanism via a remarkably low energy (+9.3 kcal/mol) intermediate, pendant N, but with one phenyl on phosphorus stabilizing Ru via donation from a C(ipso)=C(ortho) bond. DFT calculations show that the electronic energy change for binding CO is over 20 kcal/mol less favorable for cymene than for C5Me5- as ligand; the reactivity difference is thus thermodynamic in origin.