Interacting binding insights and conformational consequences of the differential activity of cannabidiol with two endocannabinoid-activated G-protein-coupled receptors

Molecular Dynamic Simulations for Biopolymers with Biomedical Applications

Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its use in biomedical engineering for biopolymer materials has only recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: (A) Computer-aided design (CAD/CAM) utilizes specialized software to design and model biopolymers for various biomedical applications. This technology allows researchers to create precise three-dimensional models of biopolymers, taking into account their chemical, structural, and functional properties. These models can be used to enhance the structure of biopolymers and improve their effectiveness in specific medical applications. (B) Finite element analysis, a computational technique used to analyze and solve problems in engineering and physics. This approach divides the physical domain into small finite elements with simple geometric shapes. This computational technique enables the study and understanding of the mechanical and structural behavior of biopolymers in biomedical environments. (C) Molecular dynamics (MD) simulations involve using advanced computational techniques to study the behavior of biopolymers at the molecular and atomic levels. These simulations are fundamental for better understanding biological processes at the molecular level. Studying the wide-ranging uses of MD simulations in biopolymers involves examining the structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton's equations of motion for all-atom systems, producing spatial trajectories for each atom. This provides valuable insights into properties such as water absorption on biopolymer surfaces and interactions with solid surfaces, which are crucial for assessing biomaterials. This review provides a comprehensive overview of the various applications of MD simulations in biopolymers. Additionally, it highlights the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.

GPER binding site detection and description: A flavonoid-based docking and molecular dynamics simulations study

Flavonoids, a phenolic compounds class widely distributed in the plant kingdom, have attracted much interest for their implications on several health and disease processes. Usually, the consumption of this type of compounds is approximately 1 g/d, primarily obtained from cereals, chocolate, and dry legumes ensuring its beneficial role in maintaining the homeostasis of the human body. In this context, in cancer disease prominent data points to the role of flavonoids as adjuvant treatment aimed at the regression of the disease. GPER, an estrogen receptor on the cell surface, has been postulated as a probable orchestrator of the beneficial effects of several flavonoids through modulation/inhibition of various mechanisms that lead to cancer progression. Therefore, applying pocket and cavity protein detection and docking and molecular dynamics simulations (MD), we generate, from a cluster composed of 39 flavonoids, crucial insights into the potential role as GPER ligands, of Puerarin, Isoquercetin, Kaempferol 3-O-glucoside and Petunidin 3-O-glucoside, aglycones whose sugar moiety delimits a new described sugar-acceptor sub-cavity into the cavity binding site on the receptor, as well as of the probable activation mechanism of the receptor and the pivotal residues involved in it. Altogether, our results shed light on the potential use of the aforementioned flavonoids as GPER ligands and for further evaluations in in vitro and in vivo assays to elucidate their probable anti-cancer activity.

Peptide-based allosteric inhibitor targets TNFR1 conformationally active region and disables receptor-ligand signaling complex

Tumor necrosis factor (TNF) receptor 1 (TNFR1) plays a pivotal role in mediating TNF induced downstream signaling and regulating inflammatory response. Recent studies have suggested that TNFR1 activation involves conformational rearrangements of preligand assembled receptor dimers and targeting receptor conformational dynamics is a viable strategy to modulate TNFR1 signaling. Here, we used a combination of biophysical, biochemical, and cellular assays, as well as molecular dynamics simulation to show that an anti-inflammatory peptide (FKCRRWQWRMKK), which we termed FKC, inhibits TNFR1 activation allosterically by altering the conformational states of the receptor dimer without blocking receptor-ligand interaction or disrupting receptor dimerization. We also demonstrated the efficacy of FKC by showing that the peptide inhibits TNFR1 signaling in HEK293 cells and attenuates inflammation in mice with intraperitoneal TNF injection. Mechanistically, we found that FKC binds to TNFR1 cysteine-rich domains (CRD2/3) and perturbs the conformational dynamics required for receptor activation. Importantly, FKC increases the frequency in the opening of both CRD2/3 and CRD4 in the receptor dimer, as well as induces a conformational opening in the cytosolic regions of the receptor. This results in an inhibitory conformational state that impedes the recruitment of downstream signaling molecules. Together, these data provide evidence on the feasibility of targeting TNFR1 conformationally active region and open new avenues for receptor-specific inhibition of TNFR1 signaling.

Synergetic effect of β-asarone and cannabidiol against Aβ aggregation in vitro and in vivo

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disorder, and it is unlikely that any single drug or intervention will be very successful. The pathophysiology of Alzheimer's disease involves a range of complicated biological processes, including the accumulation of beta-amyloid protein and tau protein. Given the complexity of AD and amyloid accumulation, a combination of interventions remains to be further explored. Here, we investigated the potential of combining β-asarone and cannabidiol (CBD) as a treatment for AD. The study analyzed the combined effects of these two phytochemicals on beta-amyloid (Aβ) protein aggregation and toxicity in bulk solution, in cells as well as in C.elegans. We detailed the morphological and size changes of Aβ40 aggregates in the presence of β-asarone and cannabidiol. More importantly, the presence of both compounds synergistically inhibited apoptosis and downregulated relative gene expression in cells, and that it may also slow aging, decrease the rate of paralysis, enhance learning capacity, and boost autophagy activity in C.elegans. Our studies suggest that multiple drugs, like β-asarone and CBD, may be potentially developed as a medicinal adjunct in the treatment of AD, although further clinical trials are needed to determine the efficacy and safety of this combination treatment in humans.

Structural Basis of the Binding Mode of the Antineoplastic Compound Motixafortide (BL-8040) in the CXCR4 Chemokine Receptor

Modulation of the CXCL12-CXCR4 signaling axis is of the utmost importance due to its central involvement in several pathological disorders, including inflammatory diseases and cancer. Among the different currently available drugs that inhibit CXCR4 activation, motixafortide-a best-in-class antagonist of this GPCR receptor-has exhibited promising results in preclinical studies of pancreatic, breast, and lung cancers. However, detailed information on the interaction mechanism of motixafortide is still lacking. Here, we characterize the motixafortide/CXCR4 and CXCL12/CXCR4 protein complexes by using computational techniques including unbiased all-atom molecular dynamics simulations. Our microsecond-long simulations of the protein systems indicate that the agonist triggers changes associated with active-like GPCR conformations, while the antagonist favors inactive conformations of CXCR4. Detailed ligand-protein analysis indicates the importance of motixafortide's six cationic residues, all of which established charge-charge interactions with acidic CXCR4 residues. Furthermore, two synthetic bulky chemical moieties of motixafortide work in tandem to restrict the conformations of important residues associated with CXCR4 activation. Our results not only elucidate the molecular mechanism by which motixafortide interacts with the CXCR4 receptor and stabilizes its inactive states, but also provide essential information to rationally design CXCR4 inhibitors that preserve the outstanding pharmacological features of motixafortide.

Identification of Molecular Determinants in iRhoms1 and 2 That Contribute to the Substrate Selectivity of Stimulated ADAM17

The metalloprotease ADAM17 is a key regulator of the TNFα, IL-6R and EGFR signaling pathways. The maturation and function of ADAM17 is controlled by the seven-membrane-spanning proteins iRhoms1 and 2. The functional properties of the ADAM17/iRhom1 and ADAM17/iRhom2 complexes differ, in that stimulated shedding of most ADAM17 substrates tested to date can be supported by iRhom2, whereas iRhom1 can only support stimulated shedding of very few ADAM17 substrates, such as TGFα. The first transmembrane domain (TMD1) of iRhom2 and the sole TMD of ADAM17 are important for the stimulated shedding of ADAM17 substrates by iRhom2. However, little is currently known about how the iRhoms interact with different substrates to control their stimulated shedding by ADAM17. To provide new insights into this topic, we tested how various chimeras between iRhom1 and iRhom2 affect the stimulated processing of the EGFR-ligands TGFα (iRhom1- or 2-dependent) and EREG (iRhom2-selective) by ADAM17. This uncovered an important role for the TMD7 of the iRhoms in determining their substrate selectivity. Computational methods utilized to characterize the iRhom1/2/substrate interactions suggest that the substrate selectivity is determined, at least in part, by a distinct accessibility of the substrate cleavage site to stimulated ADAM17. These studies not only provide new insights into why the substrate selectivity of stimulated iRhom2/ADAM17 differs from that of iRhom1/ADAM17, but also suggest new approaches for targeting the release of specific ADAM17 substrates.