Multi-functional dual-layer nanofibrous membrane for prevention of postoperative pancreatic leakage

Postoperative pancreatic leakage due to pancreatitis in patients is a life-threatening surgical complication. The majority of commercial barriers are unable to meet the demands for pancreatic leakage due to poor adhesiveness, toxicity, and inability to degrade. In this study, we fabricated mitomycin-c and thrombin-loaded multifunctional dual-layer nanofibrous membrane with a combination of alginate, PCL, and gelatin to resolve the leakage due to suture line disruption, promote hemostasis, wound healing, and prevent postoperative tissue adhesion. Electrospinning was used to fabricate the dual-layer system. The study results demonstrated that high gelatin and alginate content in the inner layer decreased the fiber diameter and water contact angle, and crosslinking allowed the membrane to be more hydrophilic, making it highly biodegradable, and adhering firmly to the tissue surfaces. The results of in vitro biocompatibility and hemostatic assay revealed that the dual-layer had a higher cell proliferation and showed effective hemostatic properties. Moreover, the in vivo studies and in silico molecular simulation indicated that the dual layer was covered at the wound site, prevented suture disruption and leakage, inhibited hemorrhage, and reduced postoperative tissue adhesion. Finally, the study results proved that dual-layer multifunctional nanofibrous membrane has a promising therapeutic potential in preventing postoperative pancreatic leakage.

Preliminary insights on the mutational spectrum of BRCA1 and BRCA2 genes in Pakhtun ethnicity breast cancer patients from Khyber Pakhtunkhwa (KP), Pakistan

Gene mutations are a source of genetic instability which fuels the progression of cancer. Mutations in BRCA1 and BRCA2 are considered as major drivers in the progression of breast cancer and their detection indispensable for devising therapeutic and management approaches. The current study aims to identify novel pathogenic and recurrent mutations in BRCA1 and BRCA2 in Pakhtun population from the Khyber Pakhtunkhwa. To determine the BRCA1 and BRCA2 pathogenic mutation prevalence in Pakhtun population from KP, whole exome sequencing of 19 patients along with 6 normal FFPE embedded blocks were performed. The pathogenicity of the mutations were determined and they were further correlated with different hormonal, sociogenetic and clinicopathological features. We obtained a total of 10 mutations (5 somatic and 5 germline) in BRCA1 while 27 mutations (24 somatic and 3 germline) for BRCA2. Five and seventeen pathogenic or deleterious mutations were identified in BRCA1 and BRCA2 respectively by examining the mutational spectrum through SIFT, PolyPhen-2 and Mutation Taster. Among the SNVs, BRCA1 p.P824L, BRCA2 p. P153Q, p.I180F, p.D559Y, p.G1529R, p.L1576F, p.E2229K were identified as mutations of the interaction sites as predicted by the deep algorithm based ISPRED-SEQ prediction tool. SAAFEQ-SEQ web-based algorithm was used to calculate the changes in free energy and effect of SNVs on protein stability. All SNVs were found to have a destabilizing effect on the protein. ConSurf database was used to determine the evolutionary conservation scores and nature of the mutated residues. Gromacs 4.5 was used for the molecular simulations. Ramachandran plots were generated using procheck server. STRING and GeneMania was used for prediction of the gene interactions. The highest number of mutations (BRCA1 7/10, 70 %) were on exon 9 and (BRCA2, 11/27; 40 %) were on exon 11. 40 % and 60 % of the BRCA2 mutations were associated Grade 2 and Grade 3 tumors respectively. The present study reveals unique BRCA1 and BRCA2 mutations in Pakhtun population. We further suggest sequencing of the large cohorts for further characterizing the pathogenic mutations.

The mechanism of epigallocatechin-3-gallate inhibiting the antigenicity of β-lactoglobulin under pH 6.2, 7.4 and 8.2: Multi-spectroscopy and molecular simulation methods

The antigenicity of β-lactoglobulin (β-LG) can be influenced by pH values and reduced by epigallocatechin-3-gallate (EGCG). However, a detailed mechanism concerning EGCG decreasing the antigenicity of β-LG at different pH levels lacks clarity. Here, we explore the inhibition mechanism of EGCG on the antigenicity of β-LG at pH 6.2, 7.4 and 8.2 using enzyme-linked immunosorbent assay, multi-spectroscopy, mass spectrometry and molecular simulations. The results of Fourier transform infrared spectroscopy (FTIR) and circular dichroism (CD) elucidate that the noncovalent binding of EGCG with β-LG induces variations in the secondary structure and conformations of β-LG. Moreover, EGCG inhibits the antigenicity of β-LG the most at pH 7.4 (98.30 %), followed by pH 6.2 (73.18 %) and pH 8.2 (36.24 %). The inhibitory difference is attributed to the disparity in the number of epitopes involved in the interacting regions of EGCG and β-LG. Our findings suggest that manipulating pH conditions may enhance the effectiveness of antigenic inhibitors, with the potential for further application in the food industry.

Tackling antibiotic contaminations in wastewater with novel Modified-MOF nanostructures: A study of molecular simulations and DFT calculations

The contamination of wastewater with antibiotics has emerged as a critical global challenge, with profound implications for environmental integrity and human well-being. Adsorption techniques have been meticulously investigated and developed to mitigate and alleviate their effects. In this study, we have investigated the adsorption behaviour of Erythromycin (ERY), Gentamicin (GEN), Levofloxacin (LEVO), and Metronidazole (MET) antibiotics as pharmaceutical contaminants (PHCs) on amide-functionalized (RC (=O)NH2)/MIL-53 (Al) (AMD/ML53A), using molecular simulations and density functional theory (DFT) calculations. Based on our DFT calculations, it becomes apparent that the adsorption tendencies of antibiotics are predominantly governed by the presence of AMD functional groups on the adsorbent surface. Specifically, hydrogen bonding (HB) and van der Waals (vdW) interactions between antibiotics and AMD groups serve as the primary mechanisms facilitating adsorption. Furthermore, we have observed that the adsorption behaviors of these antibiotics are influenced by their respective functional groups, molecular shapes, and sizes. Our molecular simulations delved into how the AMD/ML53A surfaces interact with antibiotics as PHCs. Moreover, various chemical quantum descriptors based on Frontier Molecular Orbitals (FMO) were explored to elucidate the extent of AMD/ML53A adsorption and to assess potential alterations in their electronic properties throughout the adsorption process. Monte Carlo simulation showed that ERY molecules adsorb stronger to the adsorbent in acidic and basic conditions than other contaminants, with high energies: -404.47 kcal/mol in acidic and -6375.26 kcal/mol in basic environments. Molecular dynamics (MD) simulations revealed parallel orientation for the ERY molecule's adsorption on AMD/ML53A with 80% rejection rate. In conclusion, our study highlighted the importance of modeling in developing practical solutions for removing antibiotics as PHCs from wastewater. The insights gained from our calculations can facilitate the design of more effective adsorption materials, ultimately leading to a more hygienic and sustainable ecosystem.

Unveiling the mechanisms behind high CO2 adsorption by the selection of suitable ionic liquids incorporated into a ZIF-8 metal organic framework: A computational approach

There is growing focus on the crucial task of effectively capturing carbon dioxide (CO2) from the atmosphere to mitigate environmental consequences. Metal-organic frameworks (MOFs) have been used to replace many conventional materials in gas separation, and the incorporation of ionic liquids (ILs) into porous MOFs has shown promise as a new technique for improving CO2 capture and separation. However, the driving force underlying the electronic modulation of MOF nanostructures and the mechanisms behind their high CO2 adsorption remain unclear. This study reports the effect of encapsulating different imidazolium ILs in porous ZIF-8, to clarify the adsorption mechanism of CO2 using density functional theory (DFT)-based approaches. For this purpose, a range of anions, including bis(trifluoromethylsulfonyl)imide [NTf2], methanesulfonate [MeSO3], and acetate [AC], were combined with the 1-ethyl-3-methylimidazolium [EMIM]+ cation. [EMIM]+-based ILs@ZIF-8 composites were computationally investigated to identify suitable materials for CO2 capture. First, the intermolecular and intramolecular interactions between [EMIM]+ and different anions were examined in detail, and their effects on CO2 adsorption were explored. Subsequently, the integration of these ILs into the ZIF-8 solid structure was studied to reveal how their interactions influenced the CO2 adsorption behavior. Our results demonstrate that the incorporation of ILs strongly affects the adsorption capability of CO2, which is highly dependent on the nature of the ILs inside the ZIF-8 framework. DFT simulations further confirmed that the incorporation of ILs into ZIF-8 led to superior CO2 capture compared to isolated ILs and pristine ZIF-8. This improvement was attributed to the mutual interactions between the ILs and ZIF-8, which effectively fine-tuned CO2 adsorption within the composite structure. This understanding may act as a general guide for gaining more insight into the interfacial interactions between ILs and ZIFs structures and how these molecular-level interactions can help predict the selection of ILs for CO2 adsorption and separation, thereby addressing environmental challenges with greater precision and effectiveness.

A data-guided approach for the evaluation of zeolites for hydrogen storage with the aid of molecular simulations

CONTEXT

This study employs a data-guided approach to evaluate zeolites for hydrogen storage, utilizing molecular simulations. The development of efficient and practical hydrogen storage materials is crucial for advancing clean energy technologies. Zeolites have shown promise as potential candidates due to their unique porous structure and tunable properties. However, the selection and design of suitable zeolites for hydrogen storage remain challenging. Therefore, this work aims to address this materials science question by utilizing molecular simulations and data-guided approaches to evaluate zeolites' performance for hydrogen storage. The results obtained from this study provide valuable insights into the evaluation of zeolites for hydrogen storage. Through molecular simulations, we analyze the adsorption behavior of hydrogen molecules in various zeolite structures. The performance of different zeolite frameworks in terms of hydrogen storage capacity, adsorption energy, and diffusion properties is assessed. Linde type A zeolite (LTA) had the highest capacity with a hydrogen capacity of 4.8wt% out of the 233 investigated zeolites. Furthermore, we investigate the influence of different factors such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) on the hydrogen storage performance of zeolites. The results show that Di, D, and M have a negative effect on the percentage weight capacity, while GSA and VSA have the highest positive contribution to the percentage weight. This study, therefore, provides new insights into the factors that affect their hydrogen storage capacity by exhibiting the importance of considering multiple factors when evaluating the performance of zeolites and demonstrates the potential of combining different computational methods to provide a more comprehensive understanding of materials. The current study contributes to the understanding of zeolite-based materials for hydrogen storage applications, aiding in the development of more efficient and practical hydrogen storage systems.

METHODS

Computational techniques were employed to investigate the hydrogen storage properties of zeolites. Molecular simulations were performed using classical force fields and molecular dynamics methods. The calculations were carried out at a force field level of theory with the GGA functional. To accurately capture the thermodynamics and kinetics of hydrogen adsorption, enhanced sampling techniques such as Monte Carlo simulations and molecular dynamics with metadynamics were utilized. We employed Grand Canonical Monte Carlo (GCMC) simulations to model hydrogen adsorption in zeolite structures for hydrogen storage. Our approach involved performing a substantial number of Monte Carlo steps (10,000) to ensure system equilibration and precise results. We defined a cutoff distance for particle interactions as 12.5 Ǻ and considered 0.000e framework charge per cell and 0.000e sorbate charge in energy calculations. The choice of an appropriate simulation cell size (50 × 50 × 50) Ǻ was crucial, mirroring real-world conditions. We specified lower and upper fugacity values (1 to 10 atm) to capture the range of gas pressures in the simulations. These methodical steps collectively enabled us to accurately model hydrogen adsorption within zeolites, forming the core of our hydrogen storage evaluation. In this research, we utilized DFT calculations to thoroughly investigate the interactions between zeolites and hydrogen. We employed pseudopotentials to describe electron behavior in zeolite systems, choosing them in line with DFT norms and basis set compatibility. Our simulation cell design replicated zeolite periodicity and eliminated boundary effects. Pre-geometry optimization was performed with HyperChem29, ensuring stable conformations with strict convergence criteria. We utilized 6-31 + G(d) and LanL2DZ basis sets for light and heavy atoms, aligning with field standards for computational efficiency and precision. A machine learning algorithm was used to rank the importance of various structural features such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) and how they affect the capacity of the zeolites. Machine learning analysis was performed with the Scikit-learn library, an open-source Python tool. We employed a range of machine learning models, including SVMs, random forests, and neural networks, primarily for data analysis and feature extraction. Pearson correlation analysis, a classical statistical technique, was used to evaluate linear relationships between variables and assess the strength and direction of these relationships. It served as a complementary tool to understand the interplay of variables in our dataset, distinguishing it from machine learning algorithms. Further quantum chemical calculations were also performed to calculate the adsorption energy, global reactivity electronic descriptors, and natural bond orbital analysis in order to provide insights into the interaction of the zeolites with hydrogen. The simulations and data analysis were performed using BIOVIA material studio software, Gaussian, and Origin Pro software.

Sequence-Dependent Conformational Transitions of Disordered Proteins During Condensation

Intrinsically disordered proteins (IDPs) can form biomolecular condensates through phase separation. It is recognized that the conformation of IDPs in the dense and dilute phases as well as at the interfaces of condensates can critically impact the resulting properties associated with their functionality. However, a comprehensive understanding of the conformational transitions of IDPs during condensation remains elusive. In this study, we employ a coarse-grained polyampholyte model, comprising an equal number of oppositely charged residues-glutamic acid and lysine-whereby conformations and phase behavior can be readily tuned by altering the protein sequence. By manipulating the sequence patterns from perfectly alternating to block-like, we obtain chains with ideal-like conformations to semi-compact structures in the dilute phase, while in the dense phase, the chain conformation is approximately that of an ideal chain, irrespective of the protein sequence. By performing simulations at different concentrations, we find that the chains assemble from the dilute phase through small oligomeric clusters to the dense phase, accompanied by a gradual swelling of the individual chains. We further demonstrate that these findings are applicable to several naturally occurring proteins involved in the formation of biological condensates. Concurrently, we delve deeper into the chain conformations within the condensate, revealing that chains at the interface show a strong sequence dependence, but remain more collapsed than those in the bulk-like dense phase. This study addresses critical gaps in our knowledge of IDP conformations within condensates as a function of protein sequence.

Biophysical and docking study on the interaction of anticancer drugs encorafenib and binimetinib with human serum albumin

The utilization of BRAF and MEK inhibitors in combination therapy has demonstrated superior outcomes in the treatment of melanoma as compared to monotherapy. In the present scenario, the combination therapy of Encorafenib (ENC), a BRAF inhibitor, and Binimetinib (BINI), a MEK inhibitor, has been identified as one of the most efficacious treatment modalities for this malignancy. Investigations of protein binding, particularly with human serum albumin (HSA), are essential to understand drug performance and enhance therapeutic outcomes. The investigation of the interplay between small molecule drugs and HSA is of paramount importance, given that such interactions can exert a substantial influence on the pharmacokinetics of these therapeutic agents. The present study aims to bridge these lacunae by implementing a comprehensive approach that integrates fluorescence spectroscopy (FS), isothermal titration calorimetry (ITC), far-ultraviolet circular dichroism (far-UV CD), and molecular simulations. Through analysis of the fluorescence quenching of HSA at three distinct temperatures, it was ascertained that the association constants for the complexes formed between drugs and HSA were of the magnitude of 104 M-1. This suggests that the interactions between the compounds and albumin were moderate and comparable. Simultaneously, the investigation of fluorescence indicated a contrasting binding mechanism for the two inhibitors: ENC predominantly binds to HSA through enthalpic interaction, while BINI/HSA is stabilized by entropic contributions. The data obtained was confirmed through experimental procedures conducted using the ITC method. The results of ligand-competitive displacement experiments indicate that ENC and BINI can bind to HSA within subdomain IIA, specifically Sudlow site I. However, far-UV CD studies show that there are no notable alterations in the structure of HSA upon binding with either of the two inhibitors. Ultimately, the results were supported by computational molecular analysis, which identified the key interactions that contribute to the stabilization of the two ligand/HSA complexes.

Influence pathways of nanocrystalline cellulose on the digestibility of corn starch: Gelatinization, structural properties, and α-amylase activity perspective

This work focused on the pathways by which NCC regulated the digestibility of corn starch. The addition of NCC changed the viscosity of the starch during pasting, improved the rheological properties and short-range order of the starch gel, and finally formed a compact, ordered, and stable gel structure. In this respect, NCC affected the digestion process by changing the properties of the substrate, which reduced the degree and rate of starch digestion. Moreover, NCC induced changes in the intrinsic fluorescence, secondary conformation, and hydrophobicity of α-amylase, which lowered its activity. Molecular simulation analyses suggested that NCC bonded with amino acid residues (Trp 58, Trp 59, and Tyr 62) at the active site entrance via hydrogen bonding and van der Waals forces. In conclusion, NCC decreased CS digestibility by modifying the gelatinization and structural properties of starch and inhibiting α-amylase activity. This study provides new insights into the mechanisms by which NCC regulates starch digestibility, which could be beneficial for the development of functional foods to tackle type 2 diabetes.

Unveiling the interdomain dynamics of type II DNA topoisomerase through all-atom simulations: Implications for understanding its catalytic cycle

Type IIA DNA topoisomerases are complex molecular nanomachines that manage topological states of the DNA molecule in the cell and play a crucial role in cellular processes such as cell division and transcription. They are also established targets of cancer chemotherapy. Starting from the available crystal structure of a fully catalytic topoisomerase IIA homodimer from Saccharomyces cerevisiae, we constructed three states of this molecular motor primarily changing the configurations of the DNA segment bound in the DNA gate and performed μs-long all-atom molecular simulations. A comprehensive analysis revealed a sliding motion within the DNA gate and a teamwork between the N-gate and DNA gate that may be associated with the necessary molecular events that allow passage of the T-segment of DNA. The observed movement of the ATPase dimer relative to the DNA domain was reflected in different interaction patterns between the K-loops of the transducer domain and the B-A-B form of the bound DNA. Based on the obtained results, we mapped simulated configurations to the structures in the proposed catalytic cycle through which type IIA topoisomerases exert their function and discussed the possible transition events. The results extend our understanding of the mechanism of action of type IIA topoisomerases and provide an atomistic interpretation of some of the observed features of these molecular motors.

Cyclic-polymer grafted colloids in spherical confinement: insights for interphase chromosome organization

Interphase chromosomes are known to organize non-randomly in the micron-sized eukaryotic cell nucleus and occupy certain fraction of nuclear volume, often without mixing. Using extensive coarse-grained simulations, we model such chromosome structures as colloidal particles whose surfaces are grafted by cyclic polymers. This model system is known as Rosetta. The cyclic polymers, with varying polymerization degrees, mimic chromatin loops present in interphase chromosomes, while the rigid core models the chromocenter section of the chromosome. Our simulations show that the colloidal chromosome model provides a well-separated particle distribution without specific attraction between the chain monomers. As the polymerization degree of the grafted cyclic chains decreases while maintaining the total chromosomal length (e.g., the more potent activity of condensin-family proteins), the average chromosomal volume becomes smaller, inter-chromosomal contacts decrease, and chromocenters organize in a quasi-crystalline order reminiscent of a glassy state. This order weakens for polymer chains with a characteristic size on the order of the confinement radius. Notably, linear-polymer grafted particles also provide the same chromocenter organization scheme. However, unlike linear chains, cyclic chains result in less contact between the polymer layers of neighboring chromosome particles, demonstrating the effect of DNA breaks in altering genome-wide contacts. Our simulations show that polymer-grafted colloidal systems could help decipher 3D genome architecture along with the fractal globular and loop-extrusion models.

Discovery of a novel 1,3,4-oxadiazol-2-one-based NLRP3 inhibitor as a pharmacological agent to mitigate cardiac and metabolic complications in an experimental model of diet-induced metaflammation

Inspired by the recent advancements in understanding the binding mode of sulfonylurea-based NLRP3 inhibitors to the NLRP3 sensor protein, we developed new NLRP3 inhibitors by replacing the central sulfonylurea moiety with different heterocycles. Computational studies evidenced that some of the designed compounds were able to maintain important interaction within the NACHT domain of the target protein similarly to the most active sulfonylurea-based NLRP3 inhibitors. Among the studied compounds, the 1,3,4-oxadiazol-2-one derivative 5 (INF200) showed the most promising results being able to prevent NLRP3-dependent pyroptosis triggered by LPS/ATP and LPS/MSU by 66.3 ± 6.6% and 61.6 ± 11.5% and to reduce IL-1β release (35.5 ± 8.8% μM) at 10 μM in human macrophages. The selected compound INF200 (20 mg/kg/day) was then tested in an in vivo rat model of high-fat diet (HFD)-induced metaflammation to evaluate its beneficial cardiometabolic effects. INF200 significantly counteracted HFD-dependent "anthropometric" changes, improved glucose and lipid profiles, and attenuated systemic inflammation and biomarkers of cardiac dysfunction (particularly BNP). Hemodynamic evaluation on Langendorff model indicate that INF200 limited myocardial damage-dependent ischemia/reperfusion injury (IRI) by improving post-ischemic systolic recovery and attenuating cardiac contracture, infarct size, and LDH release, thus reversing the exacerbation of obesity-associated damage. Mechanistically, in post-ischemic hearts, IFN200 reduced IRI-dependent NLRP3 activation, inflammation, and oxidative stress. These results highlight the potential of the novel NLRP3 inhibitor, INF200, and its ability to reverse the unfavorable cardio-metabolic dysfunction associated with obesity.

Neutron Reflectometry and Molecular Simulations Demonstrate HIV-1 Nef Homodimer Formation on Model Lipid Bilayers

The HIV-1 Nef protein plays a critical role in viral infectivity, high-titer replication in vivo, and immune escape of HIV-infected cells. Nef lacks intrinsic biochemical activity, functioning instead through interactions with diverse host cell signaling proteins and intracellular trafficking pathways. Previous studies have established an essential role for Nef homodimer formation at the plasma membrane for most if not all its functions. Here we combined neutron reflectometry of full-length myristoylated Nef bound to model lipid bilayers with molecular simulations based on previous X-ray crystal structures of Nef homodimers. This integrated approach provides direct evidence that Nef associates with the membrane as a homodimer with its structured core region displaced from the membrane for partner protein engagement. Parallel studies of a dimerization-defective mutant, Nef-L112D, demonstrate that the helical dimerization interface present in previous crystal structures stabilizes the membrane-bound dimer. X-ray crystallography of the Nef-L112D mutant in complex with the SH3 domain of the Nef-associated host cell kinase Hck revealed a monomeric 1:1 complex instead of the 2:2 dimer complex formed with wild-type Nef. Importantly, the crystal structure of the Nef-L112D core and SH3 interface are virtually identical to the wild-type complex, indicating that this mutation does not affect the overall Nef fold. These findings support the intrinsic capacity of Nef to homodimerize at lipid bilayers using structural features present in X-ray crystal structures of dimeric complexes.

Hesperetin-Cu(II) complex as potential α-amylase and α-glucosidase inhibitor: Inhibition mechanism and molecular docking

Inhibition of α-amylase and α-glucosidase activity is an effective way for controlling postprandial blood glucose-related diabetes. The study found that hesperetin-Cu(II) complex (Hsp-Cu(II)) exhibited a stronger inhibitory ability on α-amylase and α-glucosidase compared to hesperetin (Hsp), with smaller IC₅₀ values of Hsp-Cu(II) (60.3 ± 0.9 µM for α-amylase; 1.25 ± 0.03 µM for α-glucosidase) than Hsp (115.6 ± 1.1 µM for α-amylase; 55.2 ± 0.1 µM for α-glucosidase). Interestingly, Hsp-Cu(II) and acarbose exerted a synergistic effect on inhibition of α-glucosidase. The binding affinities of Hsp-Cu(II) to α-amylase and α-glucosidase were strong with the Ka values (binding constant) in the magnitude order of 10⁵, which was 9 times larger than Hsp. After interacting, Hsp-Cu(II) reduced α-helix contents of α-amylase and α-glucosidase, resulting in a looser conformation of these two enzymes. Molecular simulations manifested that Hsp-Cu(II) bound to the active center of enzymes driven by hydrogen bonds and interacted with the key catalytic amino acids (α-amylase: Gln63, Asp300 and His305; α-glucosidase: Tyr158, Asp215, Glu277 and Glu411), altering the conformation of enzymes, blocking the entrance of substrates, ultimately reducing the activities of α-glucosidase and α-amylase. This study has demonstrated that Hsp-Cu(II) may be a promising candidate of functional nutritional additive and medicine for the prevention of diabetes.

An inclusive study of deleterious missense PAX9 variants using user-friendly tools reveals structural, functional alterations, as well as potential therapeutic targets

Mutations in the PAX9 are responsible for non-syndromic tooth agenesis in humans, although their structural and functional consequences on protein phenotype, stability, and posttranslational modifications (PTMs) have not yet been adequately investigated. This in silico study focuses on retrieving the six most deleterious mutations (L21P, R26W, R28P, G51S, I87F, and K91E) of PAX9 that has been linked to severe oligodontia. Several computational algorithm methods were used to determine the deleterious effects of PAX9 mutations. Analysis of gene ontology, protein interactions, and PTMs indicated significant functional changes caused by PAX9 mutations. The structural superimposition of the wild-type and mutant PAX9 variants revealed structural changes in locations that were present in the structures of all six variations. The conserved domain analysis revealed that the areas shared by all six variations contained unique sections that lacked DNA binding or protein-protein interaction sites, suggesting prospective drug target sites for functional restoration. The protein-protein interaction network showed KDM5B as PAX9's strongest interacting partner similar to MSX1. The PAX9 protein's structural conformations, compactness, stiffness, and function may all be impacted by changes, according to MD simulations. In addition, research on cell lines and animal models may be valuable in establishing their specific roles in functional annotations.

Adsorption of the hydrophobic organic pollutant hexachlorobenzene to phyllosilicate minerals

Hexachlorobenzene (HCB), a representative of hydrophobic organic chemicals (HOC), belongs to the group of persistent organic pollutants (POPs) that can have harmful effects on humans and other biota. Sorption processes in soils and sediments largely determine the fate of HCB and the risks arising from the compound in the environment. In this context, especially HOC-organic matter interactions are intensively studied, whereas knowledge of HOC adsorption to mineral phases (e.g., clay minerals) is comparatively limited. In this work, we performed batch adsorption experiments of HCB on a set of twelve phyllosilicate mineral sorbents that comprised several smectites, kaolinite, hectorite, chlorite, vermiculite, and illite. The effect of charge and size of exchangeable cations on HCB adsorption was studied using the source clay montmorillonite STx-1b after treatment with nine types of alkali (M+: Li, K, Na, Rb, Cs) and alkaline earth metal cations (M2+: Mg, Ca, Sr, Ba). Molecular modeling simulations based on density functional theory (DFT) calculations to reveal the effect of different cations on the adsorption energy in a selected HCB-clay mineral system accompanied this study. Results for HCB adsorption to minerals showed a large variation of solid-liquid adsorption constants Kd over four orders of magnitude (log Kd 0.9-3.3). Experiments with cation-modified montmorillonite resulted in increasing HCB adsorption with decreasing hydrated radii of exchangeable cations (log Kd 1.3-3.8 for M+ and 1.3-1.4 for M2+). DFT calculations predicted (gas phase) adsorption energies (- 76 to - 24 kJ mol-1 for M+ and - 96 to - 71 kJ mol-1 for M2+) showing a good correlation with Kd values for M2+-modified montmorillonite, whereas a discrepancy was observed for M+-modified montmorillonite. Supported by further calculations, this indicated that the solvent effect plays a relevant role in the adsorption process. Our results provide insight into the influence of minerals on HOC adsorption using HCB as an example and support the relevance of minerals for the environmental fate of HOCs such as for long-term source/sink phenomena in soils and sediments.

Carbosilane ruthenium metallodendrimer as alternative anti-cancer drug carrier in triple negative breast cancer mouse model: A preliminary study

The carbosilane metallodendrimer G₁-[[NCPh(o-N)Ru(η6- p-cymene)Cl]Cl]₄ (CRD13), based on an arene Ru(II) complex coordinated to imino-pyridine surface groups, has been conjugated with anti-cancer drugs. Ruthenium in the positively-charged dendrimer structure allows this nanoparticle to be considered as an anticancer drug carrier, made more efficient because ruthenium has anticancer properties. The ability of CRD13 to form complexes with Doxorubicin (DOX), 5-Fluorouracil (5-Fu), and Methotrexate (MTX) has been evaluated using zeta potential measurement, transmission electron microscopy (TEM) and computer simulation. The results show that it forms stable nanocomplexes with all those drugs, enhancing their effectiveness against MDA-MB-231 cancer cells. In vivo tests indicate that the CRD13/DOX system caused a decrease of tumor weight in mice with triple negative breast cancer. However, the tumors were most visibly reduced when naked dendrimers were injected.

Structure-based drug design of novel M. tuberculosis InhA inhibitors based on fragment molecular orbital calculations

2-trans enoyl-acyl carrier protein reductase (InhA) is a promising target for developing novel chemotherapy agents for tuberculosis, and their inhibitory effects on InhA activity were widely investigated by the physicochemical experiments. However, the reason for the wide range of their inhibitory effects induced by similar agents was not explained by only the difference in their chemical structures. In our previous molecular simulations, a series of heteroaryl benzamide derivatives were selected as candidate inhibitors against InhA, and their binding properties with InhA were investigated to propose novel derivatives with higher binding affinity to InhA. In the present study, we extended the simulations for a series of 4-hydroxy-2-pyridone derivatives to search widely for more potent inhibitors against InhA. Using ab initio fragment molecular orbital (FMO) calculations, we elucidated the specific interactions between InhA residues and the derivatives at an electronic level and highlighted key interactions between InhA and the derivatives. The FMO results clearly indicated that the most potent inhibitor has strong hydrogen bonds with the backbones of Tyr158, Thr196, and NADH of InhA. This finding may provide informative structural concepts for designing novel 4-hydroxy-2-pyridone derivatives with higher binding affinity to InhA. Our previous and present molecular simulations could provide important guidelines for the rational design of more potent InhA inhibitors.

Effect of starch-catechin interaction on regulation of starch digestibility during hot-extrusion 3D printing: Structural analysis and simulation study

Recent developments of hot-extrusion 3D printing (HE-3DP) have made it possible to manipulate starch digestibility. This work investigated the regulating mechanism of starch-catechin (EC) interactions on rice starch digestibility during HE-3DP by using modern analytical techniques and computational models. The results showed that the HE-3DP processing with starch-EC interactions could significantly decrease the starch digestibility (p < 0.05) due to the formation of ordered structures including short-range ordered structure, nano-aggregates and V-type crystalline structure. Meanwhile, molecular dynamics simulations were performed to reveal the mechanism of EC as an enzyme inhibitor to enhance the resistant starch contents of rice starch to 46.1%. Results showed that EC could loosely attach to starch chains, thereby facilitating binding to Trp59 of pancreatic α-amylase and preventing starch from binding to its active pocket. These findings provide useful structural information for EC to reduce starch digestibility in the HE-3DP environment.

Development and characterization of chlorophyll-amended montmorillonite clays for the adsorption and detoxification of benzene

After disasters, such as forest fires and oil spills, high levels of benzene (> 1 ppm) can be detected in the water, soil, and air surrounding the disaster site, which poses a significant health risk to human, animal, and plant populations in the area. While remediation methods with activated carbons have been employed, these strategies are limited in their effectiveness due to benzene's inherent stability and limited retention to most surfaces. To address this problem, calcium and sodium montmorillonite clays were amended with a mixture of chlorophyll (a) and (b); their binding profile and ability to detoxify benzene were characterized using in vitro, in silico, and well-established ecotoxicological (ecotox) bioassay methods. The results of in vitro isothermal analyses indicated that chlorophyll-amended clays showed an improved binding profile in terms of an increased binding affinity (Kf = 668 vs 67), increased binding percentage (52% vs 11%), and decreased rates of desorption (28% vs 100%), compared to the parent clay. In silico simulation studies elucidated the adsorption mechanism and validated that the addition of the chlorophyll to the clays increased the adsorption of benzene through Van der Waals forces (i.e., aromatic π-π stacking and alkyl-π interactions). The sorbents were also assessed for their safety and ability to protect sensitive ecotox organisms (Lemna minor and Caenorhabditis elegans) from the toxicity of benzene. The inclusion of chlorophyll-amended clays in the culture medium significantly reduced benzene toxicity to both organisms, protecting C. elegans by 98-100% from benzene-induced mortality and enhancing the growth rates of L. minor. Isothermal analyses, in silico modeling, and independent bioassays all validated our proof of concept that benzene can be sequestered, tightly bound, and stabilized by chlorophyll-amended montmorillonite clays. These novel sorbents can be utilized during disasters and emergencies to decrease unintentional exposures from contaminated water, soil, and air.

Identification of novel and potential PPARγ stimulators as repurposed drugs for MCAO associated brain degeneration

Peroxisome proliferator-activated receptor-gamma (PPARγ) has been shown to have therapeutic promise in the treatment of ischemic stroke and is supported by several studies. To identify possible PPARγ activators, the current study used an in silico technique in conjunction with molecular simulations and in vivo validation. FDA-approved drugs were evaluated using molecular docking to determine their affinity for PPARγ. The findings of molecular simulations support the repurposing of rabeprazole and ethambutol for the treatment of ischemic stroke. Adult Sprague Dawley rats were subjected to transient middle cerebral artery occlusion (t-MCAO). Five groups were made as a sham-operated, t-MCAO group, rabeprazole +t-MCAO, ethambutol +t-MCAO, and pioglitazone +t-MCAO. The neuroprotective effects of these drugs were evaluated using the neurological deficit score and the infarct area. The inflammatory mediators and signaling transduction proteins were quantified using Western blotting, ELISA, and immunohistochemistry. The repurposed drugs mitigated cerebral ischemic injury by PPARγ mediated downregulation of nods like receptor protein 3 inflammasomes (NLRP3), tumor necrosis factor-alpha (TNF-α), cyclooxygenase 2 (COX-2), nuclear factor kappa-light-chain-enhancer of activated B cells (p-NF-kB), and c-Jun N-terminal kinase (p-JNK). Our data demonstrated that rabeprazole and ethambutol have neuroprotective potential via modulating the cytoprotective stress response, increasing cellular survival, and balancing homeostatic processes, and so may be suitable for future research in stroke therapy.

Theoretical investigation of Chitosan-Assisted Controlled Release of Digestive System Antitumor Drug Fluorouracil

5-Fluorouracil (5-FU) has been applied to treat pancreatic cancer, which is one of the most common types of digestive system tumors. However, due to poor tumor selectivity, 5-FU's therapeutic effect has certain limitations. 5-FU's activity and selectivity against tumor cells can be improved by chitosan assisted drug delivery systems. Understanding the atomic interaction mechanism between chitosan and 5-FU is important. In this work, the interactions between 5-FU and different types of chitosan were systematically investigated by using molecular dynamics (MD) simulation. Based on the radial distribution function and the free energy calculation, our results demonstrate that the functional groups of chitosan could greatly regulate the interaction behavior between chitosan and 5-FU. Moreover, 5-FU could gradually release from chitosan at a more acidic pH (tumor tissues) environment. These results revealed the underlying atomic interaction mechanism between 5-FU and chitosan at various pH levels, and may be helpful in the design of chitosan-based drug delivery systems.

Atomistic Simulations of Thermal Unfolding

This tutorial will provide a practical overview of the use of atomistic simulations to study thermal unfolding of biomolecules, in particular small proteins and RNA oligomers. The tutorial focuses on the use of atomistic, all atom simulations of biomolecules in explicit solvent, to study (reversible) thermal unfolding. The simulation methods described here have also been applied to study biomolecules using implicit solvent and coarse-grained models. We do not intend to provide an up-to-date review of the vast literature of biomolecular dynamics, enhanced sampling methods, force field developments, and applications of these methods. The purpose of this tutorial is to provide basic guidelines into the use of these methods to the starting scientist.

Molecular dynamics simulations, docking and MMGBSA studies of newly designed peptide-conjugated glucosyloxy stilbene derivatives with tumor cell receptors

In this work, for the first time, we designed derivatives of beta-D-glucosyloxy-3-hydroxy-trans-stiblene-2-carboxylic acid (GHS), by conjugating GHS with tumor targeting peptides RPARPAR and GGKRPAR to target over-expressed receptors in tumor cells. The sequences RPARPAR and GGKRPAR are known to target the neuropilin1 (NRP1) receptor due to the C-terminal Arg domain; however, their effectiveness has never been examined with other commonly over-expressed receptors in tumor cells, particularly of chronic lymphocytic leukemia that include integrin α1β1 and CD22. By conjugating these peptides with GHS, which is known for its inherent anti-cancer properties, the goal is to further enhance tumor cell targeting by developing compounds that can target multiple receptors. The physicochemical properties of the conjugates and individual peptides were analyzed using Turbomole and COSMOthermX20 in order to determine their hydrogen bond accepting and donating capabilities. The web server POCASA was used in order to determine the surface cavities and binding pockets of the three receptors. To explore the binding affinities, we conducted molecular docking studies with the peptides and the conjugates with each of the receptors. After molecular docking, the complexes were analyzed using Protein-Ligand Interaction Profiler to determine the types of interactions involved. Molecular dynamics simulation studies were conducted to explore the stability of the receptor-ligand complexes. Our results indicated that in most cases the conjugates showed higher binding and stability with the receptors. Additionally, highly stable complexes of conjugates were obtained with CD22, NRP1 and in most cases with the integrin α1β1 receptor as well. The binding energies were calculated for each of the receptor ligand complexes through trajectory analysis using MMGBSA studies. SwissADME studies revealed that the compounds showed low GI absorption and were not found to be CYP inhibitors and had bioavailability score that would allow them to be considered as potential drug candidates. Overall, our results for the first time show that the designed conjugates can target multiple over-expressed receptors in tumor cells and may be potentially developed as future therapeutics for targeting tumor cells.

Alpha-lipoic acid analogues in the regulation of redox balance in epilepsy: A molecular docking and simulation study

OBJECTIVE

Oxidative stress is one of the pathophysiological mechanisms implicated in drug-resistant epilepsy. Recurrent seizures and prolonged treatment with anti-seizure medicines (ASMs) can produce reactive oxygen species (ROS) resulting in neuronal cell damage, cell toxicity, and cell death. This damage may contribute to the loss of efficacy of anti-seizure medicines. Add-on therapy with antioxidants, neuroimmunophilins, and polyphenols may thus be beneficial in drug-resistant epilepsy. In vitro and in vivo studies have shown a significant improvement in drug efficacy and seizure suppression using co-treatment of anti-seizure medication with naturally available antioxidants including alpha-lipoic acid (α-lipoic acid) from walnut; however, the underlying mechanisms of action remain to be fully understood.

METHODS

We undertook molecular docking and molecular dynamics simulations to determine whether alpha-lipoic acid and related analogues interacted with the human manganese superoxide dismutase (MnSOD) protein, a member of the oxidative metabolic pathway. The 3D structure of the compounds and the protein were retrieved from protein and chemical databases, binding sites were identified and ligand-protein interactions were performed.

RESULTS

Alpha-lipoic acid and various analogues docked within a human MnSOD binding region. Docking results were validated by molecular dynamic simulation. The CMX-2043 analogue showed strong binding with MnSOD compared to alpha-lipoic acid and other analogues.

SIGNIFICANCE

Our findings provide new insights into additional mechanisms of action, which may in part, account for the antioxidant properties associated with alpha-lipoic acid and related analogues. The results support further in vitro and in vivo evaluation of these compounds to better understand their potential as add-on therapy for ASM treatment in epilepsy.

Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action

Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the membrane protein rod opsin. While the mechanisms underlying the noxious effects of the mutated protein are not completely understood, a common feature is the functional protein conformational loss. Here, the wild type and 39 adRP rod opsin mutants were subjected to mechanical unfolding simulations coupled to the graph theory-based protein structure network analysis.

A robust computational model was inferred and in vitro validated in its ability to predict endoplasmic reticulum retention of adRP mutants, a feature linked to the mutation-caused misfolding. The structure-based approach could also infer the structural determinants of small chaperone action on misfolded protein mutants with therapeutic implications.

The approach is exportable to conformational diseases linked to missense mutations in any membrane protein.

High-viscosity Pickering emulsion stabilized by amphiphilic alginate/SiO2 via multiscale methodology for crude oil-spill remediation

The separation of crude oil from oily water and collection of the emulsion constituents has attracted significant attention. We demonstrate that the relationships between inherent dynamic factors and the performance of a Pickering emulsion stabilized by SiO₂ particles with adsorbed hydrophobically modified sodium alginate derivatives (HMSA), a natural pH-sensitive polysaccharide, can be clarified via a multi-scale methodology. Functionalization of the silica surface with HMSA controls particle dispersibility, as verified by turbidity and stability analyses, the zeta potential, and transmission electron microscopy measurements. The interaction mechanism between HMSA and SiO₂ nanoparticles was elucidated by both experimental adsorption measurements and computer simulations, which showed qualitative consistency. The aggregation/disaggregation of HMSA/SiO₂ particles achieved by tuning the pH of the solution facilitated reversible dispersibility/collectability behavior. Overall, a high-viscosity Pickering emulsion system based on particle-particle and droplet-droplet interactions, which can be filtered for the recovery of spilled crude oil, was demonstrated.

Expression, purification and structural characterization of resveratrol synthase from Polygonum cuspidatum

Polygonum cuspidatum, an important medicinal plant in China, is a rich source of resveratrol compounds, and its synthesis related resveratrol synthase (RS) gene is highly expressed in stems. The sequence of the resveratrol synthase was amplified with specific primers. Sequence comparison showed that it was highly homologous to the STSs. The RS gene of Polygonum cuspidatum encodes 389 amino acids and has a theoretical molecular weight of 42.4 kDa, which is called PcRS1. To reveal the molecular basis of the synthesized resveratrol activity of PcRS1, we expressed the recombinant protein of full-length PcRS1 in Escherichia coli, and soluble protein products were produced. The collected products were purified by Ni-NTA chelation chromatography and appeared as a single band on SDS-PAGE. In order to obtain higher purity PcRS1, SEC was used to purify the protein and sharp single peak, and DLS detected that the aggregation state of protein molecules was homogeneous and stable. In order to verify the enzyme activity of the high-purity PcRS1, the reaction product was detected at 303 nm. By predicting the structural information of monomer PcRS1 and PcRS1 ligand complexes, we analyzed the ligand binding pocket and protein surface electrostatic potential of the complex, and compared it with the highly homologous STSs protein structures of the iso-ligand. New structural features of protein evolution are proposed. PcRS1 obtained a more complete configuration and the optimal orientation of the active site residues, thus improving its catalytic capacity in resveratrol synthesis.

High-throughput screening to identify potential inhibitors of the Zα domain of the adenosine deaminase 1 (ADAR1)

Adenosine deaminases acting on RNA 1 (ADAR1) are enzymes involved in editing adenosine to inosine in the dsRNAs of cells associated with cancer development. The p150 isoform of ADAR1 is the only isoform containing the Zα domain that binds to both Z-DNA and Z-RNA. The Zα domain is suggested to modulate the immune response and could be a suitable target for antiviral treatment and cancer immunotherapy. In this study, we aimed to identify potential inhibitors for ADAR1 protein that bind the Zα domain using molecular docking and simulation tools. Virtual docking and molecular dynamics simulation approaches were used to screen the potential activity of 2115 FDA-approved compounds on the Zα domain of ADAR1 and filtered for to obtain the top-scoring hits. The top three compounds with the best XP Gscore—namely alendronate (−7.045), etidronate (−6.923), and zoledronate (−6.77)—were subjected to 50 ns simulations to characterize complex stability and identify the fundamental interactions that contribute to inhibition of the ADAR1 Zα domain. The three compounds were shown to interact with Lys169, Lys170, Asn173, and Tyr177 of the Zα domain-like helical backbone of Z-RNA. The study provides a comprehensive and novel insights of repurposes drugs for the inhibition of ADAR1 function.

Molecular Modelling and Simulations of Light Harvesting Decanuclear Ru-based Dendrimers for Artificial Photosynthesis

The structure of a decanuclear photo- and redox-active dendrimer based on Ru(II) polypyridine subunits, suitable as a light-harvesting multicomponent species for artificial photosynthesis, has been investigated by means of computer modelling. The compound has the general formula [Ru{(μ-dpp)Ru[(μ-dpp)Ru(bpy) 2 ] 2 } 3 ](PF 6 ) 20 ( Ru10 ; bpy =2,2'-bipyridine; dpp= 2,3-bis(2'-pyridyl)pyrazine). The stability of possible isomers of each monomer was investigated by performing classical molecular dynamics (MD) and quantum mechanics (QM) simulations on each monomer and comparing the results. The number of stable isomers is reduced to 36 with a prevalence of MER isomerism in the central core, as previously observed by NMR experiments. The simulations on decanuclear dendrimers suggest that the stability of the dendrimer is not linked to the stability of the individual monomers composing the dendrimer but rather governed by the steric constrains originated by the multimetallic assembly. Finally, the self-aggregation of Ru10 and the distribution of the counterions around the complexes is investigated using Molecular Dynamics both in implicit and explicit acetonitrile solution. In representative examples, with nine and four dendrimers, the calculated pair distribution function for the ruthenium centers suggests a self-aggregation mechanism where the dendrimers are approaching in small blocks and then aggregate all together. Scanning transmission electron microscopy complements the investigation, supporting the formation of different aggregates at various concentrations.

Investigation of the interaction between Chrysoeriol and xanthine oxidase using computational and in vitro approaches

Xanthine oxidase (XO) plays a vital role in inducing hyperuricemia and increasing the level of superoxide free radicals in blood, and is proved as an important target for gout. Chrysoeriol (CHE) is a natural flavone with potent XO inhibitory activity (IC₅₀ = 2.487 ± 0.213 μM), however, the mechanism of interaction is still unclear. Therefore, a comprehensive analysis of the interaction between CHE and XO was accomplished by enzyme kinetics, isothermal titration calorimetry (ITC), multi-spectroscopic methods, molecular simulation and ADMET. The results showed that CHE acted as a rapid reversible and competitive-type XO inhibitor and its binding to XO was driven by hydrogen bonding and hydrophobic interaction. Moreover, CHE exhibited a strong fluorescence quenching effect through a static quenching procedure and induced conformational changes of XO. Its binding pattern with XO was revealed by docking study and the binding affinity to XO was enhanced by the interactions with key amino acid residues in the active pocket of XO. Further, CHE showed good stability and pharmacokinetic behavior properties in molecule dynamic simulation and ADMET prediction. Overall, this study shed some light on the mechanism of interaction between CHE and XO, also provided some valuable information concerning the future therapeutic application of CHE as natural XO inhibitor.

In-silico immunoinformatic analysis of SARS-CoV-2 virus for the development of putative vaccine construct

COVID-19 (CoronaVirus disease 2019) is caused by the SARS-CoV-2 virus (severe acute respiratory syndrome corona virus 2). SARS-CoV-2 virus is highly contagious and affects the human respiratory tract resulting in symptoms such as high fever, body ache, cough, dysfunctions of tastebuds and smelling sense of body. The objective of the present study involves immunoinformatic analysis to predict COVID-19 protein for vaccine construct based on the genomic information SARS-CoV-2 virus. At present, as per WHO estimates, around 133 COVID-19 novel vaccines under development. Three amino acid sequences of SARS-CoV-2 were retrieved from the NCBI database for the analysis of vaccine construct. This study involves computational and immunoinformatic methods. The Immunoinformatic tools used in the present study are NetCTL server, IFN epitope server, Toxin PRED, BCPred, CTL + HTL + ADJUVANTS + LINKERS, AlgPredserver, VaxiJenserver, ProtParam to predict vaccine construct. The secondary and tertiary structure prediction is done by PSIPRED, I-TASSER, Galaxy refine, prosA + Ramachandran. Finally, docking of the vaccine constructs and ligand was done with the help of Cluspro 2.0. C-ImmSimm webserver to simulate the potential vaccine construct. The present study demonstrated three potential Vaccine constructs for the SARS-CoV-2 virus, which were docked with TLR8 (Toll-likereceptor8). Interestingly from these, all constructs one having a high potential for the inhibition effect of the SARS-CoV-2virus. Immunological simulation data shows significant elevated amount of memory B cell; also, the high response was seen in TH(Helper) and TC(cytotoxic) cell population from the vaccine construct proposed in the current study. Hence, these constructs are suitable vaccine candidates that might be useful in developing a novel vaccine.

Integrating single-molecule spectroscopy and simulations for the study of intrinsically disordered proteins

Over the last two decades, intrinsically disordered proteins and protein regions (IDRs) have emerged from a niche corner of biophysics to be recognized as essential drivers of cellular function. Various techniques have provided fundamental insight into the function and dysfunction of IDRs. Among these techniques, single-molecule fluorescence spectroscopy and molecular simulations have played a major role in shaping our modern understanding of the sequence-encoded conformational behavior of disordered proteins. While both techniques are frequently used in isolation, when combined they offer synergistic and complementary information that can help uncover complex molecular details. Here we offer an overview of single-molecule fluorescence spectroscopy and molecular simulations in the context of studying disordered proteins. We discuss the various means in which simulations and single-molecule spectroscopy can be integrated, and consider a number of studies in which this integration has uncovered biological and biophysical mechanisms.

A novel P38α MAPK activator Bruceine A exhibits potent anti-pancreatic cancer activity

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Bruceine A displays potent anti-pancreatic cancer activity in vitro and in vivo.

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Phosphoproteomic analyses identify bruceine A induces phosphorylation of p38α MAPK.

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Octet system and microscale thermophoresis reveal p38α MAPK has high affinity for bruceine A.

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Molecular simulations illustrate determinants of bruceine A binding with p38α MAPK.

Pancreatic cancer remains one of the cancers with the poorest prognosis bearing an overall 5-year survival rate of about 5%. Efficient new chemotherapic drugs are still highly desired. Here, bruceine A, a quassinoid identified from the dried fruits of Brucea javanica (L.) Merr., displayed the most potent anti-proliferation activity against pancreatic cancer in vitro and in vivo. Phosphoproteomic analysis revealed p38α MAPK phosphorylation was involved in bruceine A’s action in MIA PaCa-2 cells. Utilizing fortebio octet system and microscale thermophoresis, we found p38α MAPK had high affinity for bruceine A. Molecular docking and molecular dynamic simulations showed that bruceine A widely bound to residues (Leu171, Ala172, Met179, Thr180, Val183) in P-loop of p38α MAPK. Key determinants of bruceine A binding with P-loop of p38α MAPK were 19-C Created by potrace 1.16, written by Peter Selinger 2001-2019 ]]>O, 22-CH₃, 32-CH₃, and 34-CH₃. Taken together, our findings demonstrate that bruceine A binds directly to p38α MAPK, which can be used to probe the role of p38α MAPK phosphorylation in pancreatic cancer progression, and as a novel lead compound for pancreatic cancer therapy.

Assessment of transferable forcefields for protein simulations attests improved description of disordered states and secondary structure propensities, and hints at multi-protein systems as the next challenge for optimization

Continuous assessment of transferable forcefields for molecular simulations is essential to identify their weaknesses and direct improvement efforts. The latest efforts focused on better describing disordered proteins while retaining proper description of folded domains, important because forcefields of the previous generations produce overly compact disordered states. Such improvements should additionally alleviate the related problem of over-stabilized protein–protein interactions, which has been largely overlooked. Here we evaluated three state-of-the-art forcefields, current flagships of their respective developers, optimized for ordered and disordered proteins: CHARMM36m with its recommended corrected TIP3P* water, ff19SB with the recommended OPC water, and the 2019 a99SBdisp forcefield by D. E. Shaw Research with its modified TIP4P water; plus ff14SB with TIP3P as an example of the former generation of forcefields. Our evaluation entailed simulations of (i) multiple copies of a protein that is highly soluble yet undergoes weak dimerization, (ii) a disordered peptide with low, well-characterized alpha helical propensity, and (iii) a peptide known to form insoluble β-aggregates. Our results recapitulate ff14SB-TIP3P over-stabilizing aggregates and secondary structures and place a99SBdisp-TIP4PD at the other end i.e. predicting overly weak intermolecular interactions despite reasonably predicting secondary structure propensities. In-between, CHARMM36m-TIP3P* still over-stabilizes aggregates but predicts residue-wise alpha helical propensities in solution slightly better than ff19SB-OPC, while ff19SB-OPC poses the best prediction of weak dimerization of the soluble protein still predicting aggregation of the β-peptides. This independent assessment shows that the claimed forcefield improvements are real, but also that a right balance between noncovalent attraction and repulsion has not yet been reached. We thus propose developers to consider systems like those tested here in their forcefield tuning protocols. Last, the good performance of CHARMM36m-TIP3P* further shows that tuning 3-point water models might still be an alternative to the more costly 4-point models like OPC and TIP4PD.

Enhancing the stability of Geobacillus zalihae T1 lipase in organic solvents and insights into the structural stability of its variants

Critical to the applications of proteins in non-aqueous enzymatic processes is their structural dynamics in relation to solvent polarity. A pool of mutants derived from Geobacillus zalihae T1 lipase was screened in organic solvents (methanol, ethanol, propanol, butanol and pentanol) resulting in the selection of six mutants at initial screening (A83D/K251E, R21C, G35D/S195 N, K84R/R103C/M121I/T272 M and R106H/G327S). Site-directed mutagenesis further yielded quadruple mutants A83D/M121I/K251E/G327S and A83D/M121I/S195 N/T272 M, both of which had improved activity after incubation in methanol. The k_m and k_cat values of these mutants vary marginally with the wild-type enzyme in the methanol/substrate mixture. Thermally induced unfolding of mutants was accompanied with some loss of secondary structure content. The root mean square deviations (RMSD) and B-factors revealed that changes in the structural organization are intertwined with an interplay of the protein backbone with organic solvents. Spatially exposed charged residues showed correlations between the solvation dynamics of the methanol solvent and the hydrophobicity of the residues. The short distances of the radial distribution function provided the required distances for hydrogen bond formation and hydrophobic interactions. These dynamic changes demonstrate newly formed structural interactions could be targeted and incorporated experimentally on the basis of solvent mobility and mutant residues.

Structural aspects of rod opsin and their implication in genetic diseases

Vision in dim-light conditions is triggered by photoactivation of rhodopsin, the visual pigment of rod photoreceptor cells. Rhodopsin is made of a protein, the G protein coupled receptor (GPCR) opsin, and the chromophore 11-cis-retinal. Vertebrate rod opsin is the GPCR best characterized at the atomic level of detail. Since the release of the first crystal structure 20 years ago, a huge number of structures have been released that, in combination with valuable spectroscopic determinations, unveiled most aspects of the photobleaching process. A number of spontaneous mutations of rod opsin have been found linked to vision-impairing diseases like autosomal dominant or autosomal recessive retinitis pigmentosa (adRP or arRP, respectively) and autosomal congenital stationary night blindness (adCSNB). While adCSNB is mainly caused by constitutive activation of rod opsin, RP shows more variegate determinants affecting different aspects of rod opsin function. The vast majority of missense rod opsin mutations affects folding and trafficking and is linked to adRP, an incurable disease that awaits light on its molecular structure determinants. This review article summarizes all major structural information available on vertebrate rod opsin conformational states and the insights gained so far into the structural determinants of adCSNB and adRP linked to rod opsin mutations. Strategies to design small chaperones with therapeutic potential for selected adRP rod opsin mutants will be discussed as well.

Unseeded, spontaneous nucleation of spherulitic magnesium calcite

Most of the sedimentary carbonates deposited in the marine environments are composed of calcium carbonate minerals with varying amounts of incorporated Mg²⁺. However, understanding how interactions of impurities with carbonate and their incorporation affect sediments behavior remains a challenge. Here, a new insight is obtained by monitoring solution composition, morphology, and electrokinetic potential of carbonate particles formed in a spontaneous unseeded batch precipitation experiment using electrochemical and scanning electron microscopy methods. The solid composition and growth rate are extracted from changes in the bulk composition and fitted to chemical affinity rate law, revealing that the precipitation pathway consists of second-order dissolution and first-order precipitation. The molecular dynamics simulations show that the lattice strain induced by randomly substituting Ca²⁺ by Mg²⁺ stabilizes spherical nanoparticles and reduces their surface area and volume. Combining kinetics and thermodynamics insight, we conclude that variation in the carbonate bulk and interfacial energies, along with the solution supersaturation, lead to the dissolution-precipitation transformation pathway from Mg-rich to Mg-poor carbonate phase that preserves spherulitic morphology. Our findings are relevant for long-standing questions of how impurities influence diagenesis of carbonate sediments and spherulitic carbonate particles' origin.

Recent Force Field Strategies for Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.

Insights from molecular simulations about dead time markers in reversed-phase liquid chromatography

Among the most popular compounds to estimate the hold-up time in reversed-phase liquid chromatography (RPLC) are acetone and uracil, which are considered as too small and too polar, respectively, for retention by the hydrophobic stationary phase, although their observed elution behavior does not fully support this assumption. We investigate how acetone and uracil as solutes interact with the chromatographic interface through molecular dynamics simulations in an RPLC mesopore model of a silica-supported, endcapped, C₁₈ phase equilibrated with a water (W)‒acetonitrile (ACN) mobile phase. The simulation results provide a molecular-level explanation for the observed elution behavior of acetone and uracil, but also question whether true dead time markers for RPLC exist. Both solutes have a density maximum in the interfacial region in addition to a low presence in the bonded-phase region, but these density peaks clearly differ from the adsorption and partitioning peaks of true analytes. Acetone partially behaves like a co-solvent of ACN and partially like the analyte acetophenone. Like ACN, acetone can be found in the first and second layer of solvent molecules at the silica surface; like acetophenone, acetone adsorbs to the bonded-phase chains by orienting its polar group to the bulk region to sustain hydrogen bonds with W molecules. Uracil behavior is governed by a need for extensive hydrogen-bond coordination by W molecules. Uracil adsorbs to the very edge of the bonded-phase chains, on the bulk-region side of the ACN density maximum in the interfacial region. Further penetration into the chains is prevented by the absence of W molecules, which are not found deeper in the bonded phase, except at the silica surface. Contrary to true analytes, accumulation of uracil and acetone in the interfacial region ceases at an equimolar presence of W and ACN in the mobile phase (at 70‒80% ACN volume fraction). Uracil achieves a closer approximation of the stationary-phase limit than acetone, but carries the risk of HILIC retention at high ACN fraction in the mobile phase.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

Computational modelling of flavivirus dynamics: The ins and outs

Enveloped viruses such as the flaviviruses represent a significant burden to human health around the world, with hundreds of millions of people each year affected by dengue alone. In an effort to improve our understanding of the molecular basis for the infective mechanisms of these viruses, extensive computational modelling approaches have been applied to elucidate their conformational dynamics. Multiscale protocols have been developed to simulate flavivirus envelopes in close accordance with biophysical data, in particular derived from cryo-electron microscopy, enabling high-resolution refinement of their structures and elucidation of the conformational changes associated with adaptation both to host environments and to immunological factors such as antibodies. Likewise, integrative modelling efforts combining data from biophysical experiments and from genome sequencing with chemical modification are providing unparalleled insights into the architecture of the previously unresolved nucleocapsid complex. Collectively, this work provides the basis for the future rational design of new antiviral therapeutics and vaccine development strategies targeting enveloped viruses.

Current Progress in Understanding the Structure and Function of Sweet Taste Receptor

The sweet taste receptor, which was identified approximately 20 years ago, mediates sweet taste recognition in humans and other vertebrates. With the development of genomics, metabonomics, structural biology, evolutionary biology, physiology, and neuroscience, as well as technical advances in these areas, our understanding of this important protein has resulted in substantial progress. This article reviews the structure, function, genetics, and evolution of the sweet taste receptor and offers meaningful insights into this G protein-coupled receptor, which may be helpful guidances for personalized feeding, diet, and medicine. Prospective directions for research on sweet taste receptors have also been proposed.

New insights on the role of ROS in the mechanisms of sonoporation-mediated gene delivery

Reactive oxygen species (ROS) are hypothesized to play a role in the sonoporation mechanisms. Nevertheless, the acoustical phenomenon behind the ROS production as well as the exact mechanisms of ROS action involved in the increased cell membrane permeability are still not fully understood. Therefore, we investigated the key processes occurring at the molecular level in and around microbubbles subjected to ultrasound using computational chemistry methods. To confirm the molecular simulation predictions, we measured the ROS production by exposing SonoVue® microbubbles (MBs) to ultrasound using biological assays. To investigate the role of ROS in cell membrane permeabilization, cells were subjected to ultrasound in presence of MBs and plasmid encoding reporter gene, and the transfection level was assessed using flow cytometry. The molecular simulations showed that under sonoporation conditions, ROS can form inside the MBs. These radicals could easily diffuse through the MB shell toward the surrounding aqueous phase and participate in the permeabilization of nearby cell membranes. Experimental data confirmed that MBs favor spontaneous formation of a host of free radicals where HO was the main ROS species after US exposure. The presence of ROS scavengers/inhibitors during the sonoporation process decreased both the production of ROS and the subsequent transfection level without significant loss of cell viability. In conclusion, the exposure of MBs to ultrasound might be the origin of chemical effects, which play a role in the cell membrane permeabilization and in the in vitro gene delivery when generated in its proximity.

Synthesis, bioactivity and binding energy calculations of novel 3-ethoxysalicylaldehyde based thiosemicarbazone derivatives

In recent decade, the entrance of α-N-heterocyclic thiosemicarbazones derivates (Triapne, COTI-2 and DpC) in clinical trials for cancer and HIV-1 has vastly increased the interests of medicinal chemists towards this class of organic compounds. In the given study, a series of eighteen new (3a-r) 3-ethoxy salicylaldehyde-based thiosemicarbazones (TSC), bearing aryl and cycloalkyl substituents, were synthesized and assayed for their pharmacological potential against carbonic anhydrases (hCA I and hCA II), cholinesterases (AChE and BChE) and α-glycosidase. The hCA I isoform was inhibited by these novel 3-ethoxysalicylaldehyde thiosemicarbazone derivatives (3a-r) in low nanomolar levels, the Ki of which differed between 144.18 ± 26.74 and 454.92 ± 48.32 nM. Against the physiologically dominant isoform hCA II, the novel compounds demonstrated K_is varying from 110.54 ± 14.05 to 444.12 ± 36.08 nM. Also, these novel derivatives (3a-r) effectively inhibited AChE, with Ki values in the range of 385.38 ± 45.03 to 983.04 ± 104.64 nM. For BChE was obtained with Ki values in the range of 400.21 ± 35.68 to 1003.02 ± 154.27 nM. For α-glycosidase the most effective Ki values of 3l, 3n, and 3q were with Ki values of 12.85 ± 1.05, 16.03 ± 2.84, and 19.16 ± 2.66 nM, respectively. Moreover, the synthesized TCSs were simulated using force field methods whereas the binding energies of the selected compounds were estimated using MM-GBSA method. The findings indicate the present novel 3-ethoxy salicylaldehyde-based thiosemicarbazones to be excellent hits for pharmaceutical applications.

Conformational properties of inulin, levan and arabinan studied by molecular dynamics simulations

Inulin, levan and arabinan are the polysaccharides that consist of exclusively furanose units. To date, their conformational features studied at the molecular scale have remained largely unexplained. To tackle this issue, we have performed a series of explicit-solvent molecular dynamics simulations, carried out within the furanose-dedicated force field. None of the polysaccharides exhibits a single, dominating structure type. Instead, they create a large number of separated conformational states originating from the intensive rotation around the φ and ω glycosidic angles. 2₁-helices are the preferential conformational forms for all compounds but they appear only locally, at the length of several consecutive residues. The flexibility of all three furanose-based polysaccharides is much greater in relation to the (1-4)-linked pyranose polysaccharides and is comparable to that of (1-6)-linked pyranoses. The dynamic geometries of both furanose rings and glycosidic linkages are nearly unchanged independently if considering them at the level of mono-, di- or polysaccharides.

How N-(pyridin-4-yl)pyridin-4-amine and its methyl and nitro derivatives are arranged in the interlayer space of zirconium sulfophenylphosphonate: a problem solved by experimental and calculation methods

Classical molecular simulation methods were used for a description of an arrangement of intercalated molecules N-(pyridin-4-yl)pyridin-4-amine (AH) and its derivatives, 3-methyl-N-(pyridin-4-yl)pyridin-4-amine (AMe), and 3-nitro-N-(pyridin-4-yl)pyridin-4-amine (ANO2) within a layered structure of zirconium 4-sulfophenylphosphonate. The intercalated molecules were placed between SO₃H groups of the host layers. Their mutual positions and orientations were solved by molecular simulation methods and compared with the presented experimental results. Final calculated data showed differences of partially disordered arrangement of the intercalated molecules between zirconium 4-sulfophenylphosphonate layers. The calculation results revealed a dense net of hydrogen bonds connecting water molecules and the guests in the interlayer space and the sulfo groups of the host layers. We calculated the dipole moments of the AH, AMe and ANO2 guests in the final models in order to illustrate potential use of these materials in non-linear optics.

Predictive compression of molecular dynamics trajectories

Molecular dynamics simulations help to understand the complex behavior of molecules. The output of such a simulation describes the trajectories of individual atoms as snapshots of atom positions in time. Many compression schemes were developed to reduce the amount of data needed for storing long trajectories. This is achieved by limiting the precision of coordinates, encoding differences instead of absolute values, dimensionality reduction by principal component analysis, or by using polynomials approximating vertex trajectories. However, compression schemes using actual bonds between atoms have not been utilized to their full potential. Therefore, we developed a lossy compression method that captures the local, mostly rotational movement of atoms with respect to their bonded neighbors and predicts their positions in each frame. This allows full control over the data distortion. In our experiments, the method achieves data rates which are substantially better than the rates achieved by competing methods at the same error level.

How to learn from inconsistencies: Integrating molecular simulations with experimental data

Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modeling tool to interpret experimental measurements, and to use experimental data to refine our biophysical models. Thus, explicit integration and synergy between molecular simulations and experiments is fundamental for furthering our understanding of biological processes. This is especially true in the case where discrepancies between measured and simulated observables emerge. In this chapter, we provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions. We distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where experiments are used more generally to refine transferable models. We discuss different philosophies and attempt to unify them in a single framework. Until now, such integration between experiments and simulations have mostly been applied to equilibrium data, and we discuss more recent developments aimed to analyze time-dependent or time-resolved data.

Computational approaches in cancer multidrug resistance research: Identification of potential biomarkers, drug targets and drug-target interactions

Like physics in the 19th century, biology and molecular biology in particular, has been fertilized and enhanced like few other scientific fields, by the incorporation of mathematical methods. In the last decades, a whole new scientific field, bioinformatics, has developed with an output of over 30,000 papers a year (Pubmed search using the keyword "bioinformatics"). Huge databases of mass throughput data have been established, with ArrayExpress alone containing more than 2.7 million assays (October 2019). Computational methods have become indispensable tools in molecular biology, particularly in one of the most challenging areas of cancer research, multidrug resistance (MDR). However, confronted with a plethora of different algorithms, approaches, and methods, the average researcher faces key questions: Which methods do exist? Which methods can be used to tackle the aims of a given study? Or, more generally, how do I use computational biology/bioinformatics to bolster my research? The current review is aimed at providing guidance to existing methods with relevance to MDR research. In particular, we provide an overview on: a) the identification of potential biomarkers using expression data; b) the prediction of treatment response by machine learning methods; c) the employment of network approaches to identify gene/protein regulatory networks and potential key players; d) the identification of drug-target interactions; e) the use of bipartite networks to identify multidrug targets; f) the identification of cellular subpopulations with the MDR phenotype; and, finally, g) the use of molecular modeling methods to guide and enhance drug discovery. This review shall serve as a guide through some of the basic concepts useful in MDR research. It shall give the reader some ideas about the possibilities in MDR research by using computational tools, and, finally, it shall provide a short overview of relevant literature.