Catalyst-Enabled In Situ Linkage Reduction in Imine Covalent Organic Frameworks.

New linkages for covalent organic frameworks (COFs) have been continuously pursued by chemists as they serve as the structure and property foundation for the materials. Developing new reaction types or modifying known linkages have been the only two methods to create new COF linkages. Herein, we report a novel strategy that uses H3PO3 as a bifunctional catalyst to achieve amine-linked COFs from readily available amine and aldehyde linkers. The acidic proton of H3PO3 catalyzes the imine framework formation, which is then in situ reduced to the amine COF by the reductive P-H moiety. The amine-linked COF outperforms its imine analogue in promoting Knoevenagel condensation because of the more basic sites and higher stability.

(Thio)urea-Based Covalent Organic Framework as a Hydrogen-Bond-Donating Catalyst.

Two-dimensional urea- and thiourea-containing covalent organic frameworks (COFs) were synthesized at ambient conditions at large scale within 1 h in the absence of an acid catalyst. The site-isolated urea and thiourea in the COF showed enhanced catalytic efficiency as a hydrogen-bond-donating organocatalyst compared to the molecular counterparts in epoxide ring-opening reaction, aldehyde acetalization, and Friedel-Crafts reaction. The COF catalysts also had excellent recyclability.

Prediction of pKa Using Machine Learning Methods with Rooted Topological Torsion Fingerprints: Application to Aliphatic Amines.

The acid-base dissociation constant, pKa, is a key parameter to define the ionization state of a compound and directly affects its biopharmaceutical profile. In this study, we developed a novel approach for pKa prediction using rooted topological torsion fingerprints in combination with five machine learning (ML) methods: random forest, partial least squares, extreme gradient boosting, lasso regression, and support vector regression. With a large and diverse set of 14 499 experimental pKa values, pKa models were developed for aliphatic amines. The models demonstrated consistently good prediction statistics and were able to generate accurate prospective predictions as validated with an external test set of 726 pKa values (RMSE 0.45, MAE 0.33, and R2 0.84 by the top model). The factors that may affect prediction accuracy and model applicability were carefully assessed. The results demonstrated that rooted topological torsion fingerprints coupled with ML methods provide a promising approach for developing accurate pKa prediction models.

The use of ligand-based de novo design for scaffold hopping and sidechain optimization: two case studies.

This paper describes the application of de novo design utilizing exclusively ligand information. In the current approach, ligand design criteria, including pharmacophores, similarity and desired properties are applied as part of a fitness function driving the design process, instead of using them as filters after the process. This allows relevant parts of chemical space to be explored more efficiently. Two case studies of successful ligand design are also presented, one aimed at scaffold hopping, the other for exploring substitution patterns around a novel scaffold.

NMR structural characterization of a minimal peptide antagonist bound to the extracellular domain of the corticotropin-releasing factor1 receptor.

Natural peptide agonists of corticotrophin-releasing factor (CRF) receptors bind to the receptor by a two-site mechanism as follows: the carboxyl end of the ligand binds the N-terminal extracellular domain (ECD) of the receptor and the amino portion of the ligand binds the extracellular face of the seven transmembrane region. Recently, peptide antagonists homologous to the 12 C-terminal residues of CRF have been derived, which bind the CRF(1) receptor through an interaction with the ECD. Here we characterized the binding of a minimal 12-residue peptide antagonist while bound to the isolated ECD of the CRF(1) receptor. We have expressed and purified soluble and properly folded ECD independent from the seven-transmembrane region as a thioredoxin fusion protein in Escherichia coli. A model of the peptide antagonist, cyclic corticotrophin-releasing factor residues 30-41 (cCRF(30-41)), was calculated while bound to the recombinant ECD using transferred nuclear Overhauser effect spectroscopy. Although the peptide is unstructured in solution, it adopts an alpha-helical conformation when bound to the ECD. Residues of cCRF(30-41) comprising the binding interface with the ECD were mapped using saturation transfer difference NMR. Two hydrophobic residues (Met(38) and Ile(41)) as well as two amide groups (Asn(34) and the C-terminal amide) on one face of the helix defined the binding epitope of the antagonist. This epitope may be used as a starting point for development of non-peptide antagonists targeting the ECD of this receptor.

The use of consensus scoring in ligand-based virtual screening.

A new consensus approach has been developed for ligand-based virtual screening. It involves combining highly disparate properties in order to improve performance in virtual screening. The properties include structural, 2D pharmacophore and property-based fingerprints, scores derived using BCUT descriptors, and 3D pharmacophore approaches. Different approaches for the combination of all or some of these methods have been tested. Logistic regression and sum ranks were found to be the most advantageous in different pharmaceutical applications. The three major reasons consensus scoring appears to enrich data sets better than single scoring functions are (1) using multiple scoring functions is similar to repeated samplings, in which case the mean is closer to the true value than any single value, (2) due to the better clustering of actives, multiple sampling will recover more actives than inactives, and (3) different methods seem to agree more on the ranking of the actives than on the inactives. Furthermore, consensus results are not only better but are also more consistent across receptor systems.

(Arene)tricarbonylchromium complexes synthesized on NaX zeolite: solid-state NMR and DRIFTS studies.

Various (arene)tricarbonylchromium complexes were synthesized within the confines of NaX zeolite and studied with diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and carbon-13 magic-angle-spinning nuclear magnetic resonance (MAS NMR) spectroscopy. In each case, the surface complex Cr(CO)3(Oz)3 (Oz represents a framework oxygen of the NaX zeolite) was prepared before a particular arene was added. The arenes benzene, toluene, mesitylene, anisole, and aniline all produce hexahapto pi-complexes physisorbed within the zeolite supercage. DRIFTS spectra show three bands in the carbonyl region indicating less than C3v symmetry. The NMR spectra have narrow carbonyl bands near 240 ppm which indicate rapidly reorienting complexes within the zeolite. The (eta 6-benzene)tricarbonylchromium complex is physisorbed at two sites as indicated both by the DRIFTS spectra and by two carbonyl resonances at 242.5 and 239.1 ppm at 300 K. Variable-temperature MAS NMR shows these two resonances coalescing near 360 K with an activation energy of 48 +/- 6 kJ/mol. When the temperature is decreased to 205 K, the high-frequency carbonyl resonance disappears. The 239 ppm resonance is still narrow at 134 K while MAS sidebands show that the resonance from physisorbed benzene is ca. 200 ppm wide. The complex prepared with pyridine gave a broad resonance as indicated by the spinning sidebands in the MAS NMR spectra. The pyridine complex was identified as Cr(CO)3(C5H5N)3.