The Fourier‐transform infrared spectra of CHCl3 solutions containing a non‐conjugated imine, R1HC=NR2 and an acid of the series HCl, HBr, HI, trichloro‐, dichloro‐, monochloro‐, monobromo acetic acids and propionic acid have been recorded. Both the N+H and double bond stretching regions are examined. The results show that HCl, HBr and HI protonate the imine completely, trichloroacetic acid to about 90‐95%, the other haloacetic acids to 55‐80% and propionic acid to <10%. Considered as model studies for the problem of protonation in rhodopsins our results lead to the conclusion that with the relatively weak acids available in the pigments full protonation requires a stabilization mechanism which should be further investigated.

Here we describe a 5-step sequence to prepare the AB enone 1, the key precursor to fully synthetic tetracyclines, that begins with a diastereoselective Michael–Claisen coupling of two simple starting materials, a cyclohexenone (compound 2 or, in a refinement, a substituted variant, vide infra) and the isoxazole ester 3. This advance defines an 8-step linear sequence to 6-deoxytetracycline antibiotics from three components of similar complexity (cyclohexenone 2, isoxazole ester 3, and structurally diverse D-ring precursors) in which sequential diastereoselective Michael–Claisen cyclization reactions form the A- and C-rings, respectively, of the linearly fused ABCD tetracycline skeleton. In addition to providing a readily scalable, practical route to fully synthetic tetracyclines of broad structural diversity, the sequence reported comprises a series of non-obvious stereoselective transformations, including a novel means for C12a hydroxylation.

A deaminative reductive coupling of amino acid pyridinium salts with aryl bromides has been developed to enable efficient synthesis of noncanonical amino acids and diversification of peptides. This method transforms natural, commercially available lysine, ornithine, diaminobutanoic acid, and diaminopropanoic acid to aryl alanines and homologated derivatives with varying chain lengths. Attractive features include ability to transverse scales, tolerance of pharma-relevant (hetero)aryls and biorthogonal functional groups, and the applicability beyond monomeric amino acids to short and macrocyclic peptide substrates. The success of this work relied on high-throughput experimentation to identify complementary reaction conditions that proved critical for achieving the coupling of a broad scope of aryl bromides with a range of amino acid and peptide substrates including macrocyclic peptides.

[chemical reaction: see text]. An advanced intermediate to the highly oxygenated triterpene quassinoids was prepared in 14 steps from tetrahydrofuran. The key steps are three diene-transmissive Diels-Alder cycloadditions. Several features of this synthesis are noteworthy, including a successful Mitsunobu reaction on an allenylic alcohol, a rare [4 + 2] cycloaddition involving an enethiol ether dienophile, and complete control over all 10 chiral centers created.

Mathematical modeling of chemical reaction kinetics has been proven to aid the development of new reactions and processes. Chemical kinetic modeling is a well-established principle in chemical engineering that uses fundamental knowledge of the reaction mechanism to predict conversion data. In pharmaceutical drug development, elementary-type kinetics are hardly common, because of the nature of the complex organic reaction mixtures and low-level impurities. Thus, data-driven modeling plays an important role in understanding the relationship between reaction parameters and reaction profiles. Advances in reaction automation technologies, such as high-throughput platforms and autosamplers, enable greater data collection to enrich our understanding of chemical reactions. As a result, statistical analysis has shifted from conventional end-point analysis to modeling the entire reaction profile using more advanced statistical models. Data-driven approaches are especially useful in early stage of development where not enough time or material is available for a proper kinetic model development. For the same modeling task, regardless of the underlying approach, we strongly feel that a systematic process of model development needs to be applied. We developed a rigorous and general modeling workflow describing how to apply kinetic models and statistical models to a set of dynamic reaction data. In particular, a semiparametric model was applied. An industrial case study is presented with a methyl ester chemoselective hydrolysis reaction, to showcase the performance and robustness of the two modeling approaches and their impacts, side by side, on parameter effect estimation, reaction robustness range finding, and reaction optimization and operation window prediction. New and innovative visualization techniques are shared in this article for efficient data and model result interpretation.