Interactions between polymeric nanoparticles and different buffers as investigated by zeta potential measurements and molecular dynamics simulations

Zeta potential is an essential surface parameter in the characterization of nanoparticles, determined at the interface of loosely bound ions (diffuse layer) at the nanoparticle surface and free ions in solution. The ionic concentration and pH of the solution are known to, by definition, influence the composition of the diffuse layer and zeta potential accordingly. Thus, to fix the solution's pH for valid zeta potential measurements, buffers are frequently used. However, an issue that remains largely neglected is that buffers could also additionally alter the electrokinetic properties of nanoparticles through specific molecular interactions. Therefore, a thorough molecular understanding of buffer-nanoparticle interactions is needed to correctly implement zeta potential results. Thus, in order to study nanoparticle-buffer interactions, we first adopted a simple experimental approach of measuring zeta potential of common polymeric nanoparticle systems at different buffer concentrations, pH, and nanoparticle-buffer fraction ratios. We observed that zwitterionic/cationic buffer molecules impart significant interference to the electrokinetic properties of structurally diverse polymer nanoparticles, by causing zeta potential suppression or even inversion during the experiments. In parallel, advancement in computation resources nowadays allow studying intermolecular interactions of nanoparticles and other complex molecules by molecular dynamics (MD) simulations. Thus, by performing MD simulations for six different polymeric nanomaterials with commonly used buffer molecules, we found that noncovalent interactions play a significant role in altering the observed zeta potential values, which may contribute to erroneous results and false particle characterizations if not taken properly into account in zeta potential measurements.</p

High-Throughput Molecular Dynamics-Based Alchemical Free Energy Calculations for Predicting the Binding Free Energy Change Associated with the Selected Omicron Mutations in the Spike Receptor-Binding Domain of SARS-CoV-2

The ongoing pandemic caused by SARS-CoV-2 has gone through various phases. Since the initial outbreak, the virus has mutated several times, with some lineages showing even stronger infectivity and faster spread than the original virus. Among all the variants, omicron is currently classified as a variant of concern (VOC) by the World Health Organization, as the previously circulating variants have been replaced by it. In this work, we have focused on the mutations observed in omicron sub lineages BA.1, BA.2, BA.4 and BA.5, particularly at the receptor-binding domain (RBD) of the spike protein that is responsible for the interactions with the host ACE2 receptor and binding of antibodies. Studying such mutations is particularly important for understanding the viral infectivity, spread of the disease and for tracking the escape routes of this virus from antibodies. Molecular dynamics (MD) based alchemical free energy calculations have been shown to be very accurate in predicting the free energy change, due to a mutation that could have a deleterious or a stabilizing effect on either the protein itself or its binding affinity to another protein. Here, we investigated the significance of five spike RBD mutations on the stability of the spike protein binding to ACE2 by free energy calculations using high throughput MD simulations. For comparison, we also used conventional MD simulations combined with a Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) based approach, and compared our results with the available experimental data. Overall, the alchemical free energy calculations performed far better than the MM-GBSA approach in predicting the individual impact of the mutations. When considering the experimental variation, the alchemical free energy method was able to produce a relatively accurate prediction for N501Y, the mutant that has previously been reported to increase the binding affinity to hACE2. On the other hand, the other individual mutations seem not to have a significant effect on the spike RBD binding affinity towards hACE2

Luteolin attenuates diabetic nephropathy via inhibition of metalloenzymes in rats

Objective: To investigate the renoprotective effects of luteolin on diabetes in rats. Methods: One week after administration of streptozotocin 55 mg/kg intraperitoneally, rats were given 25, 50, and 75 mg/kg/day of luteolin orally for another eight weeks. At the end of the experiment, body weight, blood glucose level, biochemical parameters for renal function (serum creatinine, blood urea nitrogen, uric acid, serum albumin, and total protein), kidney histology, matrix metalloproteinase (MMP)-2, MMP-9, and histone deacetylase 2 (HDAC-2) expression, and malondialdehyde, myeloperoxidase, and hydroxyproline content in renal tissue were evaluated. High glucose-induced damage using NRK-52E cell line was studied to evaluate cell viability and metalloenzyme expression. Additionally, in silico studies including docking and molecular dynamics simulations were conducted. Results: MMP-2, MMP-9, and HDAC-2 expressions were significantly increased in high glucose-induced NRK-52E cells and the renal tissue of diabetic rats. However, these changes were reversed by luteolin at the administered doses. Additionally, luteolin significantly reduced oxidative stress, inflammation, and fibrosis, as well as improved biochemical parameters in diabetic rats. Furthermore, luteolin at the examined doses markedly alleviated diabetes-induced histopathological changes in renal tissues. Conclusions: Luteolin effectively attenuates streptozotocin-induced diabetic nephropathy in rats by inhibiting MMP-2, MMP-9, and HDAC-2 expression, and reducing oxidative stress and inflammation

Identification of HPr kinase/phosphorylase inhibitors

Funding Information: This research was supported by funds from the ICAR-National Dairy Research Institute and a fellowship awarded by the Council of Scientific & Industrial Research, India (Suman Kapila and Sandeep Kumar) and by the Åbo Akademi University research mobility programme within the research profiling area “Drug Development and Diagnostics” (R.B.). The Sigrid Jusélius Foundation, Biocenter Finland Bioinformatics and Drug Discovery and Chemical Biology networks, CSC IT Center for Science, Joe, Pentti and Tor Borg Memorial Fund and Prof. Mark Johnson and Dr. Jukka Lehtonen are gratefully acknowledged for the excellent computational infrastructure at the Åbo Akademi University. This work contributes also to the activities within the strategic research profiling area Solutions for Health at Åbo Akademi University (Academy of Finland, # 336355). Publisher Copyright: © 2022, The Author(s).Enterococcus faecalis, a gram-positive bacterium, is among the most common nosocomial pathogens due to its limited susceptibility to antibiotics and its reservoir of the genes coding for virulence factors. Bacterial enzymes such as kinases and phosphorylases play important roles in diverse functions of a bacterial cell and, thus, are potential antibacterial drug targets. In Gram-positive bacteria, HPr Kinase/Phosphorylase (HPrK/P), a bifunctional enzyme is involved in the regulation of carbon catabolite repression by phosphorylating/dephosphorylating the histidine-containing phosphocarrier protein (HPr) at Ser46 residue. Deficiencies in HPrK/P function leads to severe defects in bacterial growth. This study aimed at identifying novel inhibitors of E. faecalis HPrK/P from a commercial compound library using structure-based virtual screening. The hit molecules were purchased and their effect on enzyme activity and growth of resistant E. faecalis was evaluated in vitro. Furthermore, docking and molecular dynamics simulations were performed to study the interactions of the hit compounds with HPrK/P. Among the identified hit molecules, two compounds inhibited the phosphorylation of HPr as well as significantly reduced the growth of resistant E. faecalis in vitro. These identified potential HPrK/P inhibitors open new research avenues towards the development of novel antimicrobials against resistant Gram-positive bacteria.Peer reviewe

Semi‐solid 3D printing of mesoporous silica nanoparticle‐incorporated xeno‐free nanomaterial hydrogels for protein delivery

Abstract Multifunctional biomaterial inks are in high demand for adapting hydrogels in biomedical applications through three‐dimensional (3D) printing. Our previously developed xeno‐free system consisting of anionic cellulose nanofibers (T‐CNF) and methacrylated galactoglucomannan (GGMMA) as a photo(bio)polymer provides high‐performance ink fidelity in extrusion‐based 3D printing. The fusion between nanoparticles and this biomaterial‐ink system is a promising yet challenging avenue worth exploring, due to the colloidal stability of T‐CNF being sensitive to electrostatic interactions. Mesoporous silica nanoparticles (MSNs), with their robust ceramic matrix and fine‐tunable surface chemistries, are well‐established nanocarriers for different biologicals. Here, we fabricated MSNs with different surface modifications resulting in a net surface charge ranging from highly negative to highly positive to develop printable MSNs‐laden nanocomposite biomaterial inks. We utilized rheology as a comprehensive tool to address the matrix interactions with differently surface‐charged MSNs. Fluorescently labeled bovine serum albumin (FITC‐BSA) was used as a model protein for MSN loading, whereby negatively or neutral‐charged MSNs were found suitable to formulate FITC‐BSA‐loaded biomaterial inks of T‐CNF/GGMMA. Depending on the particles’ surface charge, FITC‐BSA showed different release profiles and preserved its stability after release. Lastly, the proof‐of‐concept to deliver large‐sized biological cargo with MSN‐laden nanocomposite biomaterial inks was established via the 3D printing technique

Pharmacoinformatics and molecular dynamics simulation studies reveal potential covalent and FDA-approved inhibitors of SARS-CoV-2 main protease 3CL(pro)

The SARS-CoV-2 was confirmed to cause the global pandemic of coronavirus disease 2019 (COVID-19). The 3-chymotrypsin-like protease (3CLpro), an essential enzyme for viral replication, is a valid target to combat SARS-CoV and MERS-CoV. In this work, we present a structure-based study to identify potential covalent inhibitors containing a variety of chemical warheads. The targeted Asinex Focused Covalent (AFCL) library was screened based on different reaction types and potential covalent inhibitors were identified. In addition, we screened FDA-approved protease inhibitors to find candidates to be repurposed against SARS-CoV-2 3CLpro. A number of compounds with significant covalent docking scores were identified. These compounds were able to establish a covalent bond (C-S) with the reactive thiol group of Cys145 and to form favorable interactions with residues lining the substrate-binding site. Moreover, paritaprevir and simeprevir from FDA-approved protease inhibitors were identified as potential inhibitors of SARS-CoV-2 3CLpro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CLpro were characterized by molecular dynamics (MD) simulations. The identified compounds are potential inhibitors worthy of further development as COVID-19 drugs. Importantly, the identified FDA-approved anti-hepatitis-C virus (HCV) drugs paritaprevir and simeprevir could be ready for clinical trials to treat infected patients and help curb COVID-19. Communicated by Ramaswamy H. Sarma.status: publishe

Development of Aptamer-DNAzyme Based Metal-Nucleic Acid Frameworks for Gastric Cancer therapy

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Molecular dynamics simulations in drug discovery and pharmaceutical development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application pos-sibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substan-tially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies