Computational Study Research Articles

A novel polyethersulfone ultrafiltration membrane with enhanced permeability and antifouling ability via melamine-modified metal-organic framework

The trade-off between permeability and selectivity, as well as membrane fouling remains a major challenge in membrane application, impacting the performance and lifespan. Herein, a novel approach has been proposed, involving the incorporation of melamine-modified Metal-Organic Frameworks (MOFs) into Polyethersulfone (PES) ultrafiltration membranes. The modified MOFs exhibit stable anchoring to the membrane surface through hydrogen bonding, forming a hydration layer that enhances resistance to foulants. Moreover, the MOF framework channels facilitate water transport via providing additional pathways. The optimized melamine-MOF modified membranes achieve a permeability of 50 L/m2.h and a 97.8 % bovine serum albumin (BSA) rejection. The antifouling experiment demonstrates an 87 % fouling recovery ratio (FRR) for the modified membrane. A computational study has been conducted to investigate the interaction between UiO-66 and melamine using molecular dynamics (MD) simulations. The simulations validated the formation of hydrogen bonds and confirmed previous findings. Overall, the melamine-modified MOF exhibits high permeability and antifouling ability due to its excellent hydrophilic properties, which offer promising application prospects in wastewater reclamation.

Protective effect of kaempferol glucoside against lipopolysaccharide-caused acute lung injury via targeting Nrf2/NF-κB/NLRP3/GSDMD: Integrating experimental and computational studies

Protective effect of kaempferol glucoside against lipopolysaccharide-caused acute lung injury via targeting Nrf2/NF-κB/NLRP3/GSDMD: Integrating experimental and computational studies

A Computational Investigation on Chitosan Derivatives using Pharmacophore- based Screening, Molecular Docking, and Molecular Dynamics Simulations against Kaposi Sarcoma.

Cancer is one of the most dangerous illnesses to the human body due to its severity and progressive nature. Kaposi's Sarcoma (KS) tumor can appear as painless purple spots on the legs, foot, or face. This cancer develops in the lining of lymph arteries and blood vessels. Along with the enlargement of lymph nodes, the vaginal region and the mouth portion are the additional target areas of KS. DNA-binding proteins known as Sox proteins are found in all mammals and belong to the HMG box superfamily. They controlled a wide range of developmental procedures, such as the formation of the germ layer, the growth of organs, and the selection of the cell type. Human developmental abnormalities and congenital illnesses are frequently caused by the deletion or mutation of the Sox protein. The purpose of this study is to determine the promising Kaposi's sarcoma inhibitors through computational studies. In this present study computational approaches were used to evaluate the anti- carcinogenic efficacy against Kaposi's sarcoma. Ligand-based pharmacophore screening was performed utilising four different chemical libraries (Asinex, Chembridge, Specs, and NCI Natural products (NSC)) depending on the top hypothesis. The top hits were examined using molecular docking, absorption, distribution, metabolism and excretion. Highest occupied molecular orbital and lowest unoccupied molecular orbital were analysed to determine the lead compounds' biological and pharmacological efficacy. The results of the study indicated that the leading candidates were possible SOX protein inhibitors. A pharmacophore model to inhibit the production of SOX protein in Kaposi Sarcoma was generated in this computational experiment using a set of 19 Chitosan compounds. The results revealed that the top hits responded to all of the pharmacological druglikening criteria and had the best interaction residues, fitness scores, and docking scores. The resulting leads might be potential Kaposi's Sarcoma alternative treatments.

Dynamics of hydrogen storage in subsurface saline aquifers: A computational and experimental pore-scale displacement study

The catastrophic effects of climate change can be mitigated by transitioning to renewable energy sources such as wind, solar, and hydropower while utilizing hydrogen (H2) as an energy carrier. As renewable fuel sources are intermittent and location-specific, large-scale, long-term storage options for H2 must be explored with high necessity. Subsurface hydrogen storage in saline aquifers provides a vital scope to store H2 gas in available pore voids with minimal environmental risk. In this work, a highly heterogeneous porous micromodel was used to study the immiscible two-phase dynamics at high-temperature, high-pressure saline aquifer conditions using computational fluid dynamics (CFD) simulation based on volume of fluid (VOF) method. A set of microfluidic experiments were carried out under atmospheric conditions to validate the numerical model. The VOF model was observed to show good agreement with microfluidic experiments. An unstable displacement pattern with viscous fingering was observed during various flow conditions that captured high pressure (15 and 25 MPa) and temperature conditions (323 and 343 K). It was observed that fingering displacement of brine limits the storage spaces for hydrogen, which consequently follows the high permeable path. As a result, only 0.272 fraction of brine was invaded by the H2 at a temperature of 323 K and pressure of 15 MPa. A comparison between H2-brine and nitrogen (N2)-brine flow dynamics revealed a 46% less storage capacity of porous media for H2. Formations bearing high temperature (343 K) showed an 11.27% increase in H2 storage capacity, while pressure increase had negligible effect. At low capillary number (Ca), more snap-off effects resulted in higher trapping of H2 gas. This study aims to provide meaningful insights into the complexities of flow dynamics and displacement patterns that are crucial for optimizing hydrogen storage efficiency in saline aquifers and for potential ‘white’ hydrogen production.

Computational Study of Lactucine and its Derivatives to Investigate its Anti-cancerous Properties Targeting Apoptosis-inducing Protein

Background: Lactucine is related to the sesquiterpene lactone group of naturally occurring compounds and has a variety of pharmacological effects including anticancer properties found in Chicory, Wormwood, Laurus nobilis, Pyrethrum, Chamomile, etc. Lactucine has an anticancer effect which may induce apoptosis in cancerous cells and protect other cells from getting infected. Objective: In this study, Lactucine and its derivatives were screened, and performed their in silico docking study with the proteins involved in the apoptosis-inducing effect in human leukemia cancer. Methods: The three-dimensional structure of lactucine and its derivatives were retrieved in the SDF format. Active sites of protein structures were determined by Sitemap. LigPrep module was used for geometrical refining of chemical structures of lactucine and its derivatives. The protein preparation wizard of Maestro (Schrodinger) was used for protein preparation. From the receptor-complex structure, the cocrystallized ligands were removed from the active site position of the receptor chain. All ligands were docked using default Glide settings for a grid centered on the ligand and structure. Flexible docking was performed using the extra precision (XP) feature of Glide module. The best docking poses for the lactucine and their derivatives were selected based on their docking score. The ADMET properties of lactucine 15- oxalate have been predicted by admetSAR software. Results: Proteins and ligands three-dimensional structures were retrieved from PDB and Pubchem databases, respectively. All lactucine derivatives suitably docked on the apoptosis-inducing proteins with ample Glide scores Lactucin 15-oxalate interacts with proteins which are responsible for apoptosis with a maximum of six H-bonds. Other types of interactions are also involved, like Pi-cation, Pi-Pi stacking, salt bridges, and halogen bonds. Protein CDK-4 has shown the highest number of H-bond (LYS142 salt bridges), ALA16, VAL14, ASP99, LYS35, TYR17, and ASN145) with the Lactucin 15-oxalate. ADMET properties of lactucin 15-oxalate met with the criteria of being eligible to be a novel drug for the treatment of human leukemia cancer. The Dock score of both the Dasatinib drug and the lactucine-15-oxalate with the apoptosis-inducing protein stipulates that the selected ligand has equitable interaction with the target proteins. Conclusion: In this study, lactucine derivatives were docked with apoptosis-inducing proteins for the prediction of its anticancer effect. Lactucin15-oxalate has shown the highest binding affinity for the CDK-4 target and can be used as a lead compound for cancer treatment. Glide and Dock score for docking of lactucin 15-oxalate with CDK-4, well as the number of hydrogen bonding, is in agreement to use this ligand for study. These in silico results are valuable to proceed with the in vitro and in vivo studies related to the anti-cancer role of lactucin 15-oxalate.

An efficient synthesis, structural analysis, and computational studies of benzothiazole derivatives activated by formic acid under solvent-free conditions

In the present work, formic acid was used as a low-cost and eco-friendly catalyst to synthesize 2-(2-hydroxyphenyl)benzothiazole (HB) through a cycloaddition process in a solvent-free reaction medium. Imine molecule was synthesized with the help of acetic acid (B). The ring closure and formation of the thiazole moiety give acetic acid distinctiveness as a catalyst. The cyclization of fused HB failed without an acid catalyst. The chemical structures were characterized using microanalysis techniques such as IR, 1H-NMR, and 13C-NMR. The obtained FT-IR spectra were compared to theoretical data using the B3LYP/6-31G* level of theory. The electronic characteristics of molecules can be predicted utilizing wave function-dependent features, such as Average localized ionization energy (ALIE), Localized orbital locator (LOL), Electron localized function (ELF), Reduced density gradient (RDG), and Noncovalent interactions NCI studies, which have provided a wealth of knowledge. The molecular docking study was investigated to explore binding energy and interaction type. Docking analysis displayed binding energies (kcal/mol) of HB with values of -8.29, -6.80, -6.68, -7.43, and -6.69 of acetylcholinesterase (AChE) and butylcholinesterase (BuChE)), SARS-CoV-2 main protease (Mpro), human immunodeficiency virus reverse transcription (HIV RT)) and cytochrome (P450), respectively, which was the most active compound against all receptors. The dramatic improvement of the proposed approach over the existing methods can be used to derive an efficient and successful route for the synthesis of HB. This process provides a fresh and high-yield method for the synthesis of benzimidazoles.

Computational study on the binding mechanism of allosteric drug TNO155 inhibiting SHP2E76A.

E76A mutations of SHP2 have been reported to associate with genetic developmental diseases and cancers, and TNO155 is one of the effective inhibitors targeted to the allosteric site 1, which has already entered the clinical stage. However, the detailed binding mechanism between them still needs further clarification at micro-atomic level. In this study, the binding mechanism of TNO155 inhibiting SHP2E76A and the superiorities of TNO155 at binding affinity and dynamic interactive behavior with SHP2E76A were probed utilizing a series of computational drug design technologies. The results show that SHP2E76A forms tighter interaction with TNO155 compared to SHP099. SHP2E76A-TNO155 exhibits the largest electrostatic interaction among all complex systems, which can be manifested by the strong hydrogen bond interactions formed by two electrically charged residues, Arg111 and Glu250. Notably, in SHP2E76A-TNO155 system, Asp489 makes an additional substantial beneficial contribution. The E76A mutation brings stronger residue positive correlation and a larger conformation fluctuation between N-CH2 and PTP domains, resulting in tighter binding betweenTNO155and SHP2E76A. This study offers valuable insights for the further design and development of novel SHP2E76A allosteric inhibitors.

Toward Designing Reactive Metal Clusters for Dinitrogen Activation: A Guideline Based on N2 Initial Adsorption.

Gas-phase metal clusters are ideal models to explore transition-metal-mediated N2 activation mechanism. However, the effective design and search of reactive clusters in N2 activation are currently hindered by the lack of clear guidelines. Inspired by the Sabatier principle, we discovered in this work that N2 initial adsorption energy (ΔEads) is an important parameter to control the N2 activation reactivity of metal clusters in the gas phase. This mechanistic insight obtained from high-level calculations rationalizes the N2 activation reactivity of many previously reported metal clusters when combined with the known factor determining the N≡N cleavage process. Furthermore, based on this guideline of ΔEads, we successfully designed several new reactive clusters for cleaving N≡N triple bond under mild conditions, including FeV2S2-, TaV2C2-, and TaV2C3-, the high N2 activation reactivity of which has been fully corroborated in our gas phase experiments employing mass spectrometry with collision-induced dissociation. The importance of ΔEads revealed in this work not only reshapes our understanding of N2 activation reactions in the gas phase but also could have implication for other N2 activation processes in the condensed phase. The more general establishment of this new perspective on N2 activation reactivity warrants future experimental and computational studies.

Cyanide Addition to Diiron and Diruthenium Bis-Cyclopentadienyl Complexes with Bridging Hydrocarbyl Ligands

We conducted a joint synthetic, spectroscopic and computational study to explore the reactivity towards cyanide (from Bu4NCN) of a series of dinuclear complexes based on the M2Cp2(CO)3 scaffold (M = Fe, Ru; Cp = η5-C5H5), namely [M2Cp2(CO)2(µ-CO){µ,η1:η2-CH=C=CMe2}]BF4 (1Fe-Ru), [Ru2Cp2(CO)2(µ-CO){µ,η1:η2-C(Ph)=CHPh}]BF4 (2Ru) and [M2Cp2(CO)2(µ-CO){µ-CN(Me)(R)}]CF3SO3 (3Fe-Ru). While the reaction of 1Fe with Bu4NCN resulted in prevalent allenyl deprotonation, preliminary CO-NCMe substitution in 1Ru enabled cyanide addition to both the allenyl ligand (resulting in the formation of a h1:h2-allene derivative, 5A) and the two metal centers (affording 5B1 and 5B2). The mixture of 5B1-2 was rapidly converted into 5A in heptane solution at 100 °C, with 5A being isolated with a total yield of 60%. Following carbonyl-chloride substitution in 2Ru, CN− was incorporated as a terminal ligand upon Cl− displacement, to give the alkenyl complex 6 (84%). The reactivity of 3Fe and 3Ru is strongly influenced by both the metal element, M, and the aminocarbyne substituent, R. Thus, 7aRu was obtained with a 74% yield from cyanide attack on the carbyne in 3aRu (R = Cy, cyclohexyl), whereas the reaction involving the diiron counterpart 3aFe yielded an unclean mixture of the metastable 7aFe and the CO/CN− substitution product 8aFe. The cyano-alkylidene complexes 7aRu (R = Cy) and 7bFe (R = Me) underwent CO loss and carbene to carbyne conversion in isopropanol at 60–80 °C, giving 8aRu (48%) and 8bFe (71%), respectively. The novel compounds 5A, 5B1-2, 6 and 7aRu were characterized by IR and NMR spectroscopy, with the structure of 7aRu further elucidated by single crystal X-ray diffraction analysis. Additionally, the DFT-optimized structures of potential isomers of 5A, 5B1-2 and 6 were calculated.

Novel Drug Repurposing Strategy as an Alternative Therapeutic Concept for Scrub Typhus Using Computational Studies

Novel Drug Repurposing Strategy as an Alternative Therapeutic Concept for Scrub Typhus Using Computational Studies

Electrophilic Hydrosilylation of Electron‐Rich Alkenes Derived from Enamines

AbstractThe low‐electron count, air‐stable, platinum complexes [Pt(ItBu’)(ItBu)][BArF] (C1) (ItBu=1,3‐di‐tert‐butylimidazol‐2‐ylidene), [Pt(SiPh)3(ItBuiPr)2][BArF] (C2) (ItBuiPr=1‐tert‐butyl‐3‐iso‐propylimidazol‐2‐ylidene), [Pt(SiPh)3(ItBuMe)2][BArF] (C3), [Pt(GePh3)(ItBuiPr)2][BArF] (C4), [Pt(GePh)3(ItBuMe)2][BArF] (C5) and [Pt(GeEt)3(ItBuMe)2][BArF] (C6) (ItBuMe=1‐tert‐butyl‐3‐methylimidazol‐2‐ylidene) are efficient catalysts (particularly the germyl derivatives) in both the silylative dehydrocoupling and hydrosilylation of electron rich alkenes derived from enamines. The steric hindrance exerted by the NHC ligand plays an important role in the selectivity of the reaction. Thus, bulky ligands are selective towards the silylative dehydrocoupling process whereas less sterically hindered promote the selective hydrosilylation reaction. The latter is, in addition, regioselective towards the β‐carbon atom of both internal and terminal enamines, leading to β‐aminosilanes. Moreover, the syn stereochemistry of the amino and silyl groups implies an anti Si−H bond addition across the double bond. All these facts point to a mechanistic picture that, according to experimental and computational studies, involves a non‐classical hydrosilylation process through an outer‐sphere mechanism in which a formal nucleophilic addition of the enamine to the silicon atom of a platinum σ‐SiH complex is the key step. This is in sharp contrast with the classical Chalk–Harrod mechanism prevalent in platinum chemistry.

Comparative Analysis of Micrometer-Sized Particle Deposition in the Olfactory Regions of Adult and Pediatric Nasal Cavities: A Computational Study

Direct nose-to-brain drug delivery, a promising approach for treating neurological disorders, faces challenges due to anatomical variations between adults and children. This study aims to investigate the spatial particle deposition of micron-sized particles in the nasal cavity among adult and pediatric subjects. This study focuses on the olfactory region considering the effect of intrasubject parameters and particle properties. Two child and two adult nose models were developed based on computed tomography (CT) images, in which the olfactory region of the four nasal cavity models comprises 7% to 10% of the total nasal cavity area. Computational Fluid Dynamics (CFD) coupled with a discrete phase model (DPM) was implemented to simulate the particle transport and deposition. To study the deposition of micrometer-sized drugs in the human nasal cavity during a seated posture, particles with diameters ranging from 1 to 100 μm were considered under a flow rate of 15 LPM. The nasal cavity area of adults is approximately 1.2 to 2 times larger than that of children. The results show that the regional deposition fraction of the olfactory region in all subjects was meager for 1–100 µm particles, with the highest deposition fraction of 5.7%. The deposition fraction of the whole nasal cavity increased with the increasing particle size. Crucially, we identified a correlation between regional deposition distribution and nasal cavity geometry, offering valuable insights for optimizing intranasal drug delivery.

A Computational Study of the Mechanism and Kinetics of the 4-Methyl Aniline Reaction with OH Radicals

A Computational Study of the Mechanism and Kinetics of the 4-Methyl Aniline Reaction with OH Radicals

Selective Oxidation of sp-Bonded Carbon in Graphdiyne/Carbon Nanotubes Heterostructures to Form Dominant Epoxy Groups for Two-Electron Oxygen Reduction.

Two-electron oxygen reduction reaction (2e- ORR) is of great significance to H2O2 production and reversible nonalkaline Zn-air batteries (ZABs). Multiple oxygen-containing sp2-bonded nanocarbons have been developed as electrocatalysts for 2e- ORR, but they still suffer from poor activity and stability due to the limited and mixed active sites at the edges as well as hydrophilic character. Herein, graphdiyne (GDY) with rich sp-C bonds is studied for enhanced 2e- ORR. First, computational studies show that GDY has a favorable formation energy for producing five-membered epoxy ring-dominated groups, which is selective toward the 2e- ORR pathway. Then based on the difference in chemical activity of sp-C bonds in GDY and sp2-C bonds in CNTs, we experimentally achieved conductive and hydrophobic carbon nanotubes (CNTs) covering O-modified GDY (CNTs/GDY-O) through a mild oxidation treatment combined with an in situ CNTs growth approach. Consequently, the CNTs/GDY-O exhibits an average Faraday efficiency of 91.8% toward H2O2 production and record stability over 330 h in neutral media. As a cathode electrocatalyst, it greatly extends the lifetime of 2e- nonalkaline ZABs at both room and subzero temperatures.

Mechanical anisotropy on reduced ballistic limit of phosphorene by cone wave reflection：A computational study

Two-dimensional materials, such as phosphorene, exhibit exceptional electrical and mechanical properties, offering promising prospects for both electronic and mechanical applications. To design more mechanically reliable devices using phosphorene, exploring its mechanical performance, especially impact resistance, is necessary. Here, coarse-grained molecular dynamics simulations are presented to study the mechanical responses of phosphorene under ballistic impact. Interestingly, size-dependent behaviors have been observed, which could be attributed to a coupling effect of cone wave reflection and membrane size. Owing to significant differences in Young’s modulus between the armchair and zigzag direction in phosphorene, mechanical wave propagation exhibits substantial anisotropy in a single-layer phosphorene membrane. A critical membrane size has been identified, below which cone wave reflections from the boundaries can induce perforation: a phenomenon particularly relevant to micro-ballistic testing of two-dimensional material membranes. The effect of boundary shape on reduction in ballistic limit has been studied, in which all the phosphorene sheets in the study are elliptical while the axial ratio of the ellipses is varied from 0.54 to 1.85. The axial ratio 0.69 is proven to maximize the strain amplification induced by cone wave reflection, thus leading to the biggest reduction in ballistic impact for phosphorene. A unitless indicator based on atomic Green-Lagrange strain has been proposed, which can effectively quantify the boundary shape effect on the reduced ballistic limit. Our findings provide timely guidance for the design of future nanodevices using phosphorene with high impact resistance.

Experimental and Computational Study Toward Identifying Active Sites of Supported SnOx Nanoparticles for Electrochemical CO2 Reduction Using Machine-Learned Interatomic Potentials.

SnOx has received great attention as an electrocatalyst for CO2 reduction reaction (CO2RR), however; it still suffers from low activity. Moreover, the atomic-level SnOx structure and the nature of the active sites are still ambiguous due to the dynamism of surface structure and difficulty in structure characterization under electrochemical conditions. Herein, CO2RR performance is enhanced by supporting SnO2 nanoparticles on two common supports, vulcan carbon and TiO2. Then, electrolysis of CO2 at various temperatures in a neutral electrolyte reveals that the application window for this catalyst is between 12 and 30°C. Furthermore, this study introduces a machine learning interatomic potential method for the atomistic simulation to investigate SnO2 reduction and establish a correlation between SnOx structures and their CO2RR performance. In addition, selectivity is analyzed computationally with density functional theory simulations to identify the key differences between the binding energies of *H and *CO2 -, where both are correlated with the presence of oxygen on the nanoparticle surface. This study offers in-depth insights into the rational design and application of SnOx-based electrocatalysts for CO2RR.

TEMPLATE-ENGINEERED TRIVALENT IRON AND CHROMIUM CONTAINING MACROCYCLIC COMPLEXES: CHARACTERIZATION AND IN VITRO STUDIES

A novel series of tetraaza macrocyclic complexes of biological importance was synthesized by “in situ” template reaction between triethylenetetramine and dibenzoylmethane in the presence of trivalent Fe and Cr metal salts in 1:1:1 molar ratio. These complexes are represented by molecular formula [M(C[Formula: see text]H[Formula: see text]N[Formula: see text]X]X2; [Formula: see text](III) and Cr(III); [Formula: see text], NO[Formula: see text], −OAc; C[Formula: see text]H[Formula: see text]N[Formula: see text] ligand. The reported complexes were characterized by using various physicochemical and spectroscopic techniques including elemental analyses, molar conductance, thermo-gravimetric analysis, FTIR, UV–Visible and mass spectral studies. The results obtained from analytical techniques and spectroscopic techniques together suggested the complexes have a square pyramidal geometry. Various computational studies were performed including molecular docking and modeling. Further, macrocyclic complexes were also screened for their “in vitro” antimicrobial activity against selected bacterial and fungal strains. The antioxidant activity of these complexes was also evaluated. Some of the complexes were found to possess remarkable antimicrobial activity and antioxidant activity. However, complex [Fe(C[Formula: see text]H[Formula: see text]N[Formula: see text](NO[Formula: see text]](NO[Formula: see text] was found to be most potent against selected bacterial and fungal strains. On the other hand, complex [Cr(C[Formula: see text]H[Formula: see text]N[Formula: see text](NO[Formula: see text]](NO[Formula: see text] was found to show best antioxidant activity with lowest value of IC[Formula: see text].

EXPRESS: Synchronizing the Supply of Components for Automotive Assembly amid Chip Shortages and Other Supply Delays

The push for more battery-powered electric vehicles (BEV), the COVID-19 pandemic, and other global supply chain destabilizing events (e.g., the war in Ukraine), have made it necessary for manufacturers to consider innovative approaches to sourcing and materials management. This study assesses the value of sharing delivery due date updates, which are then used to convert spent time into a fraction of the expected total time for order fulfillment (i.e., progress updates), to synchronize the delivery of components for an automotive manufacturer who, amid long and variable lead times for semiconductor chips, maintains a strategy of waiting for the delivery of all needed parts before commencing production. Having progress updates in a fractional form puts numerical bounds (i.e., 0 to 100%) on the shared information, and this facilitates closed-form analytical comparisons. We develop analytical models to show decreases in expected assembly-related costs based on the progress update information shared between two suppliers— one supplier has a shorter and more reliable order fulfillment lead time than the other. When there are more than two suppliers, we use a simulation model to estimate the expected value of sharing progress updates. Our results show that increasing the frequency of shared progress updates, and having more suppliers share progress updates, results in increased cost-savings percentages. However, the opposite occurs with increasing uncertainty in suppliers’ delivery lead times. The computational study provides support for the existence of a critical mass level of suppliers needed to achieve a given percentage cost saving. This study can help automakers to make informed decisions on encouraging information sharing among suppliers, by first creating a critical mass of suppliers to share progress updates. Our investigations also help show the conditions in which to best leverage such information sharing strategies while waiting for the delivery of all needed components prior to production.

Charting the Cannabis plant chemical space with computational metabolomics

IntroductionThe chemical classification of Cannabis is typically confined to the cannabinoid content, whilst Cannabis encompasses diverse chemical classes that vary in abundance among all its varieties. Hence, neglecting other chemical classes within Cannabis strains results in a restricted and biased comprehension of elements that may contribute to chemical intricacy and the resultant medicinal qualities of the plant.ObjectivesThus, herein, we report a computational metabolomics study to elucidate the Cannabis metabolic map beyond the cannabinoids.MethodsMass spectrometry-based computational tools were used to mine and evaluate the methanolic leaf and flower extracts of two Cannabis cultivars: Amnesia haze (AMNH) and Royal dutch cheese (RDC).ResultsThe results revealed the presence of different chemical compound classes including cannabinoids, but extending it to flavonoids and phospholipids at varying distributions across the cultivar plant tissues, where the phenylpropnoid superclass was more abundant in the leaves than in the flowers. Therefore, the two cultivars were differentiated based on the overall chemical content of their plant tissues where AMNH was observed to be more dominant in the flavonoid content while RDC was more dominant in the lipid-like molecules. Additionally, in silico molecular docking studies in combination with biological assay studies indicated the potentially differing anti-cancer properties of the two cultivars resulting from the elucidated chemical profiles.ConclusionThese findings highlight distinctive chemical profiles beyond cannabinoids in Cannabis strains. This novel mapping of the metabolomic landscape of Cannabis provides actionable insights into plant biochemistry and justifies selecting certain varieties for medicinal use.

The interaction of thiocyanate with peptides-A computational study.

According to the Hofmeister series, thiocyanate is the strongest "salting in" anion. In fact, it has a strong denaturant activity against the native state of globular proteins. A molecular level rationalization of the Hofmeister series is still missing, and therefore the denaturant activity of thiocyanate also awaits a robust explanation. In the last years, different types of experimental studies have shown that thiocyanate is capable to directly interact with both polar and nonpolar groups of polypeptide chains. This finding has been scrutinized via a careful computational procedure based on density functional theory approaches. The results indicate that thiocyanate is able to make H-bonds via both the nitrogen and sulfur atom, and to make strong van der Waals interactions with almost all the groups of polypeptide chains, regardless of their polarity.