Sensitivity Analysis of DP4+ with the Probability Distribution Terms: Development of a Universal and Customizable Method.

DP4+ is a popular tool for structural elucidation using GIAO NMR calculations. The method was built with 16 statistical parameters [µ,σ,ν], which depend on the level of theory. Herein, we deeply analyzed the sensitivity of DP4+ when using improper [µ,σ,ν] sets, a common situation found in the literature. The results led us to develop a customizable DP4+ methodology that allows preliminary calculations at any desired level of theory using a small set of training molecules.

Therapeutic potential of LINS01 histamine H3 receptor antagonists as antineoplastic agents for triple negative breast cancer.

The aims of this work were to evaluate the expression of histamine H3 receptor (H3R) in triple negative breast cancer (TNBC) samples and to investigate the antitumoral efficacy and safety of the LINS01 series of H3R antagonists, through in silico, in vitro, and in vivo approaches. Antitumor activity of LINS01009, LINS01010, LINS01022, LINS01023 was assayed in vitro in 4T1 and MDA-MB-231 TNBC cells (0.01-100 µM), and in vivo in 4T1 tumors orthotopically established in BALB/c mice (1 or 20 mg/kg). Additionally, H3R expression was assessed in 50 human TNBC samples. We have described a higher H3R mRNA expression in basal-like/TNBC tumors vs. matched normal tissue using TCGA Pan-Cancer Atlas data, and a higher H3R expression in human tumor samples vs. peritumoral tissue evidenced by immunohistochemistry associated with poorer survival. Furthermore, while all the essayed compounds showed antitumoral properties, LINS01022 and LINS01023 exhibited the most potent antiproliferative effects by: i) inducing cell apoptosis and suppressing cell migration in 4T1 and MDA-MB-231 TNBC cells, and ii) inhibiting cell growth in paclitaxel-resistant 4T1 cells (potentiating the paclitaxel antiproliferative effect). Moreover, 20 mg/kg LINS01022 reduced tumor size in 4T1 tumor-bearing mice, exhibiting a safe toxicological profile and potential for druggability estimated by ADME calculations. We conclude that the H3R is involved in the regulation of TNBC progression, offering promising therapeutic potential for the novel LINS01 series of H3R antagonists.

ML-J-DP4: An Integrated Quantum Mechanics-Machine Learning Approach for Ultrafast NMR Structural Elucidation.

A new tool, ML-J-DP4, provides an efficient and accurate method for determining the most likely structure of complex molecules within minutes using standard computational resources. The workflow involves combining fast Karplus-type J calculations with NMR chemical shifts predictions at the cheapest HF/STO-3G level enhanced using machine learning (ML), all embedded in the J-DP4 formalism. Our ML provides accurate predictions, which compare favorably alongside with other ML methods.

On the effect of intramolecular H-bonding in the configurational assessment of polyhydroxylated compounds with computational methods. The hyacinthacines case.

Hyacinthacines are important members of the pyrrolizidine family, with several compounds having ambiguous, revised or unverified structures. Herein we thoroughly explored the performance DP4 and DP4+ for the in silico stereoassignment of hyacinthacines A1, A2 and five synthetic isomers. The results suggested that the quality of the predictions strongly depended on the conformational landscape provided by DFT energies, with five compounds correctly assigned. In the two cases incorrectly classified we found that the source of the problem was conformational in nature, with spurious conformations being considerably over-stabilized by intramolecular H-bondings. We showed that neglecting such shapes resulted in a noteworthy improvement, with all compounds correctly assigned in high confidence (>99.9%).