Investigation of the influence of hydroxy groups on the radical scavenging ability of polyphenols

Recently, O-H bond dissociation enthalpies (BDEs) have been successfully used to express the free radical scavenging ability of polyphenolic antioxidants. In this work, the BDEs of phenol, catechol, resorcinol, hydroquinone, pyrogallol, phloroglucinol, 1,2,4-benzenetriol, and 5-hydroxypyrogallol have been calculated at B3LYP/6-311G++(3df, 3pd) and used to elucidate the effect of OH groups. Increasing the number of OH groups in the adjacent (vicinal) position decreases the BDE of phenols. Increasing the number of O-H groups in the alternative position C(1,3) as in resorcinol and C(1,3,5) as in phloroglucinol does not show any notable change in the BDEs when compared to that of OH in C(1) as in phenol. 5-Hydroxypyrogallol has the smallest BDE (250.3 kJ mol(-1)) followed by pyrogallol (289.4 kJ mol(-1)), then 1,2,4-benzenetriol (294.8 kJ mol(-1)), and then catechol (312.8 kJ mol(-1)). Overall, our results indicated that the presence of ortho and para hydroxy groups reduces the BDEs. An intramolecular hydrogen bond (IHB) develops due to the ortho arrangement of OH's and plays a dominant role in decreasing the BDEs. This key study on phenols showed that the reactive order of OH position in the benzene ring is the following: 5-hydroxypyrogallol > pyrogallol > 1,2,4-benzenetriol > catechol > hydroquinone > phenol approximately resorcinol approximately phloroglucinol.     

A restarting approach for the symmetric rank one update for unconstrained optimization

Two basic disadvantages of the symmetric rank one (SR1) update are that the SR1 update may not preserve positive definiteness when starting with a positive definite approximation and the SR1 update can be undefined. A simple remedy to these problems is to restart the update with the initial approximation, mostly the identity matrix, whenever these difficulties arise. However, numerical experience shows that restart with the identity matrix is not a good choice. Instead of using the identity matrix we used a positive multiple of the identity matrix. The used positive scaling factor is the optimal solution of the measure defined by the problem—maximize the determinant of the update subject to a bound of one on the largest eigenvalue. This measure is motivated by considering the volume of the symmetric difference of the two ellipsoids, which arise from the current and updated quadratic models in quasi-Newton methods. A replacement in the form of a positive multiple of the identity matrix is provided for the SR1 update when it is not positive definite or undefined. Our experiments indicate that with such simple initial scaling the possibility of an undefined update or the loss of positive definiteness for the SR1 method is avoided on all iterations.     

The Involvement of l-Arginine-Nitric Oxide-cGMP-ATP-Sensitive K+ Channel Pathway in Antinociception of BBHC,a Novel Diarylpentanoid Analogue,in Mice Model

The present study focuses on the possible involvement of l-arginine-nitric oxide-cGMP-ATP-sensitive K⁺ channel pathway in the antinociceptive activity of a novel diarylpentanoid analogue, 2-benzoyl-6-(3-bromo-4-hydroxybenzylidene)cyclohexen-1-ol (BBHC) via a chemical nociceptive model in mice. The antinociceptive action of BBHC (1 mg/kg, i.p.) was attenuated by the intraperitoneal pre-treatment of l-arginine (a nitric oxide synthase precursor) and glibenclamide (an ATP-sensitive K⁺ channel blocker) in acetic acid-induced abdominal constriction tests. Interestingly, BBHC’s antinociception was significantly enhanced by the i.p. pre-treatment of 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one (ODQ), a selective inhibitor of soluble guanylyl cyclase (p < 0.05). Altogether, these findings suggest that the systemic administration of BBHC is able to establish a significant antinociceptive effect in a mice model of chemically induced pain. BBHC’s antinociception is shown to be mediated by the involvement of l-arginine-nitric oxide-cGMP-ATP-sensitive K⁺ channel pathway, without any potential sedative or muscle relaxant concerns.     

Photoregulated Sol‐Gel Transition of Novel Azobenzene‐Functionalized Hydroxypropyl Methylcellulose and Its α‐Cyclodextrin Complexes

Summary: Novel azobenzene‐functionalized hydroxypropyl methylcellulose (AZO‐HPMC) polymers and their α‐cyclodextrin (α‐CD) complexes have been prepared. These polymers show interesting sol‐gel transition behavior in aqueous solutions. In the absence of α‐CD, the gelation temperature increases after UV irradiation, while in the presence of α‐CD, the gelation temperature decreases after UV irradiation. The difference in the gelation temperatures between the trans and cis samples of AZO‐HPMC opens a wide operating window for reversible regulation of the sol‐gel transition behavior by photoirradiation.

The UV‐induced cis/trans isomerism of azobenzene‐functionalized hydroxypropyl methylcellulose and its α‐cyclodextrin complexes.     

DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction

Protein N-linked glycosylation is a post-translational modification that plays an important role in a myriad of biological processes. Computational prediction approaches serve as complementary methods for the characterization of glycosylation sites. Most of the existing predictors for N-linked glycosylation utilize the information that the glycosylation site occurs at the N-X-[S/T] sequon, where X is any amino acid except proline. Not all N-X-[S/T] sequons are glycosylated, thus the N-X-[S/T] sequon is a necessary but not sufficient determinant for protein glycosylation. In that regard, computational prediction of N-linked glycosylation sites confined to N-X-[S/T] sequons is an important problem. Here, we report DeepNGlyPred a deep learning-based approach that encodes the positive and negative sequences in the human proteome dataset (extracted from N-GlycositeAtlas) using sequence-based features (gapped-dipeptide), predicted structural features, and evolutionary information. DeepNGlyPred produces SN, SP, MCC, and ACC of 88.62%, 73.92%, 0.60, and 79.41%, respectively on N-GlyDE independent test set, which is better than the compared approaches. These results demonstrate that DeepNGlyPred is a robust computational technique to predict N-Linked glycosylation sites confined to N-X-[S/T] sequon. DeepNGlyPred will be a useful resource for the glycobiology community.