Tetrahydrocurcumin Has Similar Anti-Amyloid Properties as Curcumin: In Vitro Comparative Structure-Activity Studies

Despite its potent anti-amyloid properties, the utility of curcumin (Cur) for the treatment of Alzheimer’s disease (AD) is limited due to its low bioavailability. Tetrahydrocurcumin (THC), a more stable metabolite has been found in Cur-treated tissues. We compared the anti-amyloid and neuroprotective properties of curcumin, bisdemethoxycurcumin (BDMC), demethoxycurcumin (DMC) and THC using molecular docking/dynamics, in-silico and in vitro studies. We measured the binding affinity, H-bonding capabilities of these compounds with amyloid beta protein (Aβ). Dot blot assays, photo-induced cross linking of unmodified protein (PICUP) and transmission electron microscopy (TEM) were performed to monitor the Aβ aggregation inhibition using these compounds. Neuroprotective effects of these derivatives were evaluated in N2a, CHO and SH-SY5Y cells using Aβ42 (10 µM) as a toxin. Finally, Aβ-binding capabilities were compared in the brain tissue derived from the 5× FAD mouse model of AD. We observed that THC had similar binding capability and Aβ aggregation inhibition such as keto/enol Cur and it was greater than BDMC and DMC. All these derivatives showed a similar degree of neuroprotection in vitro and labeled Aβ-plaques ex vivo. Overall, ECur and THC showed greater anti-amyloid properties than other derivatives. Therefore, THC, a more stable and bioavailable metabolite may provide greater therapeutic efficacy in AD than other turmeric derivatives.

Modeling to support physicochemical enhancement techniques

The article discusses ways to increase the oil recovery factor in already developed fields, special attention is paid to the methods of enhanced oil recovery. The comparative structure of oil production in Russia in the medium term is given. The experience of oil and gas companies in the application of enhanced oil recovery in the fields is analyzed and the dynamics of the growth in the use of various enhanced oil recovery in Russia is estimated. With an increase in the number of operations in the fields, the requirements for the selection of candidates inevitably increase, therefore, the work focuses on hydrodynamic modeling of physical and chemical modeling, highlights the features and disadvantages of existing simulators. The main dependences for adequate modeling during polymer flooding are given. The calculation with different concentration of polymer solution is presented, which significantly affects the water cut and further reduction of operating costs for the preparation of the produced fluid. The possibility of creating a specialized hydrodynamic simulator for low-volume chemical enhanced oil recovery is considered, since mainly simulators are applicable for chemical waterflooding and the impact is on the formation as a whole.

PDBrenum: A webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences

The Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In mid 2021, the database has almost 180,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions, including binding partners such as ligands, nucleic acids, or other proteins; mutations, and post-translational modifications, thus enabling extensive comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. For instance, some authors may include N-terminal signal peptides or the N-terminal methionine in the sequence numbering and others may not. In addition to the coordinates, there are many fields that contain structural and functional information regarding specific residues numbered according to the author. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries or a list of UniProt identifiers (e.g., “P04637” or “P53_HUMAN”) and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe.

Structural variability and dynamics in the ectodomain of an ancestral-type classical cadherin revealed by AFM imaging

Type III cadherin represents the ancestral form of classical cadherin in bilaterian metazoans. Drosophila possesses type III and type IVa cadherins, known as DN- and DE-cadherins, respectively. Mature DN- and DE-cadherins have 15 and 7 extracellular cadherin domain (EC) repeats, respectively, with DN-cadherin EC6–11 homologous to DE-cadherin EC1–6. These EC repeats contain predicted complete or partial Ca2+-free inter-EC linkers that potentially contribute to adhesion. Comparative structure-function studies of DN- and DE-cadherins may help us understand the ancestral and derived states of classical cadherin-mediated adhesion mechanisms. Here, using bead aggregation assays, we found that DN-cadherin EC1–11 and DE-cadherin EC1–6 exhibit Ca2+-dependent adhesive properties. Using high-speed atomic force microscopy (HS-AFM) imaging in solution, we showed that both DN- and DE-cadherin ectodomains share a common morphological framework consisting of a strand-like and a globule-like portion. Furthermore, the DN-cadherin EC repeats were highly variable, flexible in morphology, and with at least three bendable sites, one of which is located in EC6–11 and can act as a flexible hinge. Our findings provide insights into diversification of classical cadherin-mediated adhesion mechanisms. (180 words or less)

Structural design principles for specific ultra-high affinity interactions between colicins/pyocins and immunity proteins

The interactions of the antibiotic proteins colicins/pyocins with immunity proteins is a seminal model system for studying protein–protein interactions and specificity. Yet, a precise and quantitative determination of which structural elements and residues determine their binding affinity and specificity is still lacking. Here, we used comparative structure-based energy calculations to map residues that substantially contribute to interactions across native and engineered complexes of colicins/pyocins and immunity proteins. We show that the immunity protein α1–α2 motif is a unique structurally-dissimilar element that restricts interaction specificity towards all colicins/pyocins, in both engineered and native complexes. This motif combines with a diverse and extensive array of electrostatic/polar interactions that enable the exquisite specificity that characterizes these interactions while achieving ultra-high affinity. Surprisingly, the divergence of these contributing colicin residues is reciprocal to residue conservation in immunity proteins. The structurally-dissimilar immunity protein α1–α2 motif is recognized by divergent colicins similarly, while the conserved immunity protein α3 helix interacts with diverse colicin residues. Electrostatics thus plays a key role in setting interaction specificity across all colicins and immunity proteins. Our analysis and resulting residue-level maps illuminate the molecular basis for these protein–protein interactions, with implications for drug development and rational engineering of these interfaces.

PDBrenum: a webserver and program providing Protein Data Bank files renumbered according to their UniProt sequences

The Protein Data Bank (PDB) was established at Brookhaven National Laboratories in 1971 as an archive for biological macromolecular crystal structures. In the beginning the archive held only seven structures but in early 2021, the database has more than 170,000 structures solved by X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and other methods. Many proteins have been studied under different conditions (e.g., binding partners such as ligands, nucleic acids, or other proteins; mutations and post-translational modifications), thus enabling comparative structure-function studies. However, these studies are made more difficult because authors are allowed by the PDB to number the amino acids in each protein sequence in any manner they wish. This results in the same protein being numbered differently in the available PDB entries. In addition to the coordinates, there are many fields that contain information regarding specific residues in the sequence of each protein in the entry. Here we provide a webserver and Python3 application that fixes the PDB sequence numbering problem by replacing the author numbering with numbering derived from the corresponding UniProt sequences. We obtain this correspondence from the SIFTS database from PDBe. The server and program can take a list of PDB entries and provide renumbered files in mmCIF format and the legacy PDB format for both asymmetric unit files and biological assembly files provided by PDBe. The server can also take a list of UniProt identifiers (“P04637” or “P53_HUMAN”) and return the desired files.AvailabilitySource code is freely available at https://github.com/Faezov/PDBrenum. The webserver is located at: http://dunbrack3.fccc.edu/[email protected] or [email protected].

Bisphenol-C is the strongest bifunctional ERα-agonist and ERβ-antagonist due to magnified halogen bonding

We reported that bisphenol AF (BPAF) works as an agonist for estrogen receptor (ER) ERα but as an antagonist for ERβ. Similar results were observed for bisphenol E analogs (BPE-X) such as BPE-F, BPE-Cl, and BPE-Br, each consisting of a series of a tri-halogenated methyl group CX3 in the central alkyl moiety. It was demonstrated that the electrostatic halogen bond based on the dispersion force of halogen atoms is a major driving force in the activities of bifunctional ERα-agonist and ERβ-antagonist. Since the chlorine atoms present in bisphenol C (BPC) exist in a π-π conjugated system due to the presence of an adjacent C = C double bond, we intended to prove that BPC is also a bifunctional ERα-agonist and ERβ-antagonist exhibiting greatly enhanced agonist/antagonist activities. BPC was evaluated for its ability to activate ERα and ERβ in the luciferase reporter gene assay using HeLa cells. With high receptor-binding ability to both ERs, BPC was found to be fully active for ERα but inactive for ERβ. BPC’s definite antagonist activity in ERβ was revealed by its inhibitory activity against 17β-estradiol. Thus, BPC is a bifunctional ERα-agonist and ERβ-antagonist. These agonist/antagonist activities were discovered to be extremely high among series of halogen-containing bisphenol compounds. This comparative structure-activity study revealed that the ascending order of ERα-agonist and ERβ-antagonist activities was BPE-F ≪ BPE-Cl ≲ BPAF < BPE-Br ≪ BPC. The highly intensified receptor interaction of BPC is attributable to the presence of an n-π-π-n conjugation system mediated through the >C = CCl2 double bond.