Exploring the mechanism of action of Vanda tessellata extract for the treatment of osteoarthritis through network pharmacology, molecular modelling and experimental assays.

The present study employed a comprehensive approach of network pharmacology, molecular dynamic simulation and in-vitro assays to investigate the underlying mechanism of the anti-osteoarthritic potential of Vanda tessellata extract (VTE). Thirteen active compounds of VTE were retrieved from the literature and the IMPPAT database. All of these passed the drug likeness and oral bioavailability parameters. A total of 535 VTE targets and 2577 osteoarthritis related targets were obtained. The compound-target-disease network analysis revealed vanillin, daucosterol, gigantol and syringaldehyde as the core key components. Protein-protein interaction analysis revealed BCL2, FGF2, ICAM 1, MAPK1, MMP1, MMP2, MMP9, COX2, STAT3 and ESR1 as the hub genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed AGE-RAGE signalling pathway, HIF-1 signalling pathway and ESR signalling pathway as the major signalling pathway of VTE involved in treating osteoarthritis. Molecular docking analysis showed daucosterol and gigantol to have good binding affinity with BCL2, ESR1 and MMP9, and the results were further confirmed through molecular dynamics simulation analysis. The mechanism predicted by network pharmacology was validated in vitro on IL-1ß-induced SW982 synovial cells. VTE did not show any cytotoxicity and inhibited the migration of SW982 cells. VTE inhibited the expression level of IL-6, IL-8, TNF-α, PGE-2, MMP-2 and MMP-9 in a dose-dependent manner. VTE inhibited nuclear translocation of NF- κß and suppressed phosphorylation of p38, extracellular signal-regulated kinase (ERK), and c-Jun NH2-terminal kinase (JNK) of the mitogen-activated protein kinase (MAPK) signalling pathway. The results showed that VTE exerted an anti-osteoarthritic effect by a multi-target, multi-component and multi-signalling pathway approach.

GMXPolymer: a generated polymerization algorithm based on GROMACS.

CONTEXT: This work introduces a method for generating generalized structures of amorphous polymers using simulated polymerization and molecular dynamics equilibration, with a particular focus on amorphous polymers. The techniques and algorithms used in this method are described in the main text, and example input scripts are provided for the GMXPolymer code, which is based on the GROMACS molecular dynamics package. To demonstrate the efficacy of our method, we apply it to different glassy polymers exhibiting varying degrees of functionality, polarity, and rigidity. The reliability of the method is validated by comparing simulation results with experimental data in various structural and thermal properties, both of which show excellent agreement. METHODS: This work implements the GMXPolymer simulated polymerization algorithm on the GROMACS program. GMXPolymer code controls the main polymerization loop. The energy minimizations and molecular dynamics simulations use the GROMACS program called by the GMXPolymer code. A new ITP file is generated when a new bond is formed, and the necessary additions to the ITP file are made to include new bonds, angles, and dihedrals. In preparing the ITP file of the monomer, the charge of the reactive atom must be modified before the code runs so that it is a correct value after bonding.

Theoretical study on the design of allosteric inhibitors of diabetes associated protein PTP1B.

The protein tyrosine phosphatase 1B (PTP1B) is a critical therapeutic target for type 2 diabetes mellitus (T2DM). Many PTP1B inhibitors have been reported, however, most of them lack high specificity and have adverse effects. Designing effective PTP1B inhibitors requires understanding the molecular mechanism of action between inhibitors and PTP1B. To this end, molecular dynamics (MD) simulations and molecular mechanics Poisson Boltzmann Surface Area (MM-PB/SA) methods were used to observe the binding patterns of compounds with similar pentacyclic triterpene parent ring structures but different inhibition abilities. Through structure and energy analysis, we found that the positions of cavities and substituents significantly affect combining capacity. Besides, we constructed a series of potential inhibitor molecules using LUDI and rational drug design methods. The ADMET module of Discovery Studio 2020 was used to predict the properties of these inhibitor molecules. Lastly, we obtained compounds with low toxicity and significant inhibitory activity. The study will contribute to the treatment of T2DM.

Insights into the structure and activation mechanism of some class B1 GPCR family members.

In humans, 15 genes encode the class B1 family of GPCRs, which are polypeptide hormone receptors characterized by having a large N-terminal extracellular domain (ECD) and receive signals from outside the cell to activate cellular response. For example, the insulinotropic polypeptide (GIP) stimulates the glucose-dependent insulinotropic polypeptide receptor (GIPR), while the glucagon receptor (GCGR) responds to glucagon by increasing blood glucose levels and promoting the breakdown of liver glycogen to induce the production of insulin. The glucagon-like peptides 1 and 2 (GLP-1 and GLP-2) elicit a response from glucagon-like peptide receptor types 1 and 2 (GLP1R and GLP2R), respectively. Since these receptors are implicated in the pathogenesis of diabetes, studying their activation is crucial for the development of effective therapies for the condition. With more structural information being revealed by experimental methods such as X-ray crystallography, cryo-EM, and NMR, the activation mechanism of class B1 GPCRs becomes unraveled. The available crystal and cryo-EM structures reveal that class B1 GPCRs follow a two-step model for peptide binding and receptor activation. The regions close to the C-termini of hormones interact with the N-terminal ECD of the receptor while the regions close to the N-terminus of the peptide interact with the TM domain and transmit signals. This review highlights the structural details of class B1 GPCRs and their conformational changes following activation. The roles of MD simulation in characterizing those conformational changes are briefly discussed, providing insights into the potential structural exploration for future ligand designs.

Fasting insulinemia as biomarker of illness relapse in patients with severe mental illness?

Severe Mental Illness (SMI) is often associated with metabolic alteration and/or metabolic syndrome, which may determine an increased mortality due to a further increased cardiovascular risk. The relationship with metabolic syndrome is often bidirectional, resulting in a pathoplastic effect of these dysmetabolisms. Among the several hormones involved, insulin appears to play a key role, albeit not entirely clear. The aim of our real-world cross-sectional observational study is to investigate a set of metabolic biomarkers of illness relapse/recurrence/onset in a cohort of 310 adult SMI inpatients consecutively admitted to the Psychiatry Clinic of the Azienda Ospedaliero Universitaria of Marche, in Ancona (Italy), between February 2021 and February 2024. According to the stepwise multivariate regression model, a higher number of acute episodes per year was positively predicted by the age of illness onset, the lifetime number of suicidal attempts and fasting insulinemia and negatively by the participant's age. A second stepwise multivariate regression model using only the metabolic characteristics as independent variables, found that a higher number of acute episodes per year was predicted positively by the fasting insulinemia and red blood cells and negatively by the abdominal circumference. Overall, our findings could provide practical implications for the treatment and management of SMI patients, emphasizing the importance of monitoring and managing metabolic factors, particularly insulinemia, metabolic syndrome and insulin resistance. Finally, insulinemia could potentially act as metabolic biomarker of illness relapse, though more larger and longitudinal studies should be carried out to confirm these results.

Rational design and computational evaluation of a multi-epitope vaccine for monkeypox virus: Insights into binding stability and immunological memory.

Multi-epitope vaccines strategically tackle rapidly mutating viruses by targeting diverse epitopes from different proteins, providing a comprehensive and adaptable immune protection approach for enhanced coverage against various viral variants. This research employs a comprehensive approach that includes the mapping of immune cells activating epitopes derived from the six structural glycoproteins (A29L, A30L, A35R, L1R, M1R, and E8L) of Monkeypox virus (Mpox). A total of 7 T-cells-specific epitopes, 13 B-cells-specific epitopes, and 5 IFN-γ activating epitopes were forecasted within these glycoproteins. The selection process focused on epitopes indicating high immunogenicity and favorable binding affinity with multiple MHC alleles. Following this, a vaccine has been formulated by incorporating the chosen epitopes, alongside adjuvants (PADRE peptide) and various linkers (EAAAK, GPGPG, and AAY). The physicochemical properties and 3D structure of the multi-epitope hybrid vaccine were analysed for characterization. MD simulations were employed to predict the binding stability between the vaccine and various pathogen recognition receptors such as TLRs (TLR1, TLR2, TLR4, and TLR6), as well as both class I and II MHC, achieved through hydrogen bonding and hydrophobic interactions. Through in silico cloning and immune simulation, it was observed that the multi-epitopes vaccine induced a robust memory immune response upon booster doses, forecasting protective immunity upon viral challenge. This protective immunity was characterized by the production of IgM + IgG antibodies, along with release of inflammatory cytokines like IFN-γ, and IL12, and the activation of various immune cells. This study offers valuable insights into the potential of a multi-epitope vaccine targeting the Mpox virus.

Phytochemical Targeting of Nerve Growth Factor by Thymoquinone and Cuscutin: A Molecular Dynamics Simulation Study.

Background Nerve growth factor (NGF) is a novel target of pain therapeutics for oral cancer, and it plays a main role in the nociception of chronic pain. Surgery, along with chemotherapy or radiotherapy, is the gold standard for treating patients, but the side effects are significant as well. Newer effective interventions with natural phytochemicals could improve patient compliance and enhance the quality of life among patients with oral cancer. A literature search revealed a positive correlation between NGF and oral cancer pain. Nigella sativa (N. sativa) and Cuscuta reflexa (C. reflexa) have proven anticancer effects, but their activity with NGF is unexplored. Aims and objectives We aimed to identify the potential phytochemicals in N. sativa and C. reflexa. We also checked the NGF-blocking activity of the phytochemicals. Molecular docking and molecular dynamic (MD) simulations evaluated the binding energy and stability between the NGF protein and selected phytochemical ligands. Materials and methods We obtained protein NGF structure from UniProt (ID: 4EDX, P01138, Beta-nerve growth factor), ligand (thymoquinone) structure using PubChem ID: 10281, and ligand (cuscutin) structure using PubChem ID: 66065. Maestro protein (Schrödinger Inc., Mannheim, Germany) was used for molecular docking. Desmond Simulation Package (Schrödinger Inc., Mannheim, Germany) was used to model MD for 100 nanoseconds (ns). We have assessed the interaction between the protein and ligands by root mean square deviation (RMSD) values.  Results The interaction of thymoquinone and cuscutin with NGF was assessed. While interacting with thymoquinone, there was mild fluctuation from 0.6 Å to 2.5 Å up to 80 ns and ended up at 4.8 Å up to 100 ns. While interacting with cuscutin, mild fluctuation was seen from 0.8 Å to 4.8 Å till 90 ns and ended at 6.4 Å up to 100 ns. We found a stable interaction between our drug combination and the NGF receptor. Conclusion We have identified a stable interaction between thymoquinone, cuscutin, and NGF by our MD simulations. Hence, it could be used as an NGF inhibitor for pain relief and to control tumor progression. Further in vitro and in vivo evaluations of this novel drug combination with phytochemicals will help us understand their biological activities and potential clinical applications in oral cancer therapeutics.

Dataset on anti-human insulin-degrading enzyme activities of cyclic tetra peptides: Insight from insilico approach.

In this work, the biochemical activities of seven cyclic peptides were investigated using the insilico approach. The materials used in this work were Spartan 14 for quantum chemical analysis, molecular operating environment software for molecular docking and ADMETSAR 2.0 for pharmacokinetic investigation. The calculated features obtained for each compound were explored and it was observed that the molecules used in this research have potential anti-human insulin-degrading enzyme activities. Also, (3S,6S,9S)-9-((R)-1-(benzyloxy)ethyl)-6-methyl-3-(4-methylphenethyl)-1,4,7,10-tetraazacyclododecane-2,5,8,11-tetraone (compound 2) with highest binding affinity (-7.95349026 kcal/mol) possess utmost ability to inhibit human insulin-degrading enzyme (PDB id: 2g56) than other investigated compounds and acarbose (referenced compound). The pharmacokinetic analysis for compound 2 was examined and compared to the predicted report for the referenced compound.

Computational Insights for interactions between NsP2 and NsP3 of CHIKV and Hormones through DFT computations and Molecular Dynamics Simulations.

The non-structural protein (nsP2 & nsP3) of the CHIKV is responsible for the transmission of viral infection. The main role of nsp is involved in the transcription process at an early stage of the infection. In this work, authors have studied the impact of nsP2 and nsP3 of CHIKV on hormones present in the human body using a computational approach. The ten hormones of chemical properties such as 4-Androsterone-2,17-dione, aldosterone, androsterone, corticosterone, cortisol, cortisone, estradiol, estrone, progesterone and testosterone were taken as a potency. From the molecular docking, the binding energy of the complexes is estimated, and cortisone was found to be the highest negative binding energy (-6.57 kcal/mol) with the nsP2 protease and corticosterone with the nsP3 protease (-6.47 kcal/mol). This is based on the interactions between hormones and NsP2/NsP3, which are types of noncovalent intermolecular interactions categorized into three types: electrostatic interactions, van der Waals interactions, and hydrogen-bonding. To validate the docking results, molecular dynamics simulations and MM-GBSA methods were performed. The change in enthalpy, entropy, and free energy were calculated using MM-GBSA methods. The nsP2 and nsP3 protease of CHIKV interact strongly with the cortisone and corticosterone with free energy changes of -20.55 & -36.08 kcal/mol, respectively.

Very Strong Hydrogen Bond in Nitrophthalic Cocrystals.

This work presents the studies of a very strong hydrogen bond (VSHB) in biologically active phthalic acids. Research on VSHB comes topical due to its participation in many biological processes. The studies cover the modelling of intermolecular interactions and phthalic acids with 2,4,6-collidine and N,N-dimethyl-4-pyridinamine complexes with aim to obtain a VSHB. The four synthesized complexes were studied by experimental X-ray, IR, and Raman methods, as well as theoretical Car-Parrinello Molecular Dynamics (CP-MD) and Density Functional Theory (DFT) simulations. By variation of the steric repulsion and basicity of the complex' components, a very short intramolecular hydrogen bond was achieved. The potential energy curves calculated by the DFT method were characterized by a low barrier (0.7 and 0.9 kcal/mol) on proton transfer in the OHN intermolecular hydrogen bond for 3-nitrophthalic acid with either 2,4,6-collidine or N,N-dimethyl-4-pyridinamine cocrystals. Moreover, the CP-MD simulations exposed very strong bridging proton dynamics in the intermolecular hydrogen bonds. The accomplished crystallographic and spectroscopic studies indicate that the OHO intramolecular hydrogen bond in 4-nitrophthalic cocrystals is VSHB. The influence of a strong steric effect on the geometry of the studied cocrystals and the stretching vibration bands of the carboxyl and carboxylate groups was elaborated.

Cyclic-di-GMP induces inflammation and acute lung injury through direct binding to MD2.

BACKGROUND: Severe bacterial infections can trigger acute lung injury (ALI) and acute respiratory distress syndrome, with bacterial pathogen-associated molecular patterns (PAMPs) exacerbating the inflammatory response, particularly in COVID-19 patients. Cyclic-di-GMP (CDG), one of the PAMPs, is synthesized by various Gram-positve and Gram-negative bacteria. Previous studies mainly focused on the inflammatory responses triggered by intracellular bacteria-released CDG. However, how extracellular CDG, which is released by bacterial autolysis or rupture, activates the inflammatory response remains unclear. METHODS: The interaction between extracellular CDG and myeloid differentiation protein 2 (MD2) was investigated using in vivo and in vitro models. MD2 blockade was achieved using specific inhibitor and genetic knockout mice. Site-directed mutagenesis, co-immunoprecipitation, SPR and Bis-ANS displacement assays were used to identify the potential binding sites of MD2 on CDG. RESULTS: Our data show that extracellular CDG directly interacts with MD2, leading to activation of the TLR4 signalling pathway and lung injury. Specific inhibitors or genetic knockout of MD2 in mice significantly alleviated CDG-induced lung injury. Moreover, isoleucine residues at positions 80 and 94, along with phenylalanine at position 121, are essential for the binding of MD2 to CDG. CONCLUSION: These results reveal that extracellular CDG induces lung injury through direct interaction with MD2 and activation of the TLR4 signalling pathway, providing valuable insights into bacteria-induced ALI mechanisms and new therapeutic approaches for the treatment of bacterial co-infection in COVID-19 patients.

Synthesis, biological evaluation, molecular docking, MD simulation and DFT analysis of new 3-hydroxypyridine-4-one derivatives as anti-tyrosinase and antioxidant agents.

In the present study, ten new substituted 3-hydroxypyridine-4-one derivatives were synthesized in a four-step method, and their chemical structures were confirmed using various spectroscopic techniques. Subsequently, the inhibitory activities of these derivatives against tyrosinase enzyme and their antioxidant activities were evaluated. Amongest the synthesized compounds, 6b bearing a 4-OH-3-OCH3 substitution was found to be a promising tyrosinase inhibitor with an IC50 value of 25.82 µM, which is comparable to the activity of kojic acid as control drug. Kinetic study indicated that compound 6b is a competitive inhibitor of tyrosinase enzyme, which was confirmed by molecular docking results. The molecular docking study and MD simulation showed that compound 6b was properly placed within the tyrosinase binding pocket and interacted with key residues, which is consistent with its biological activity. The DFT analysis demonstrated that compound 6b is kinetically more stable than the other compounds. In addition, compounds 6a and 6b exhibited the best antioxidant activities. The findings indicate that compound 6b could be a promising lead for further studies.

Identification of novel NLRP3 inhibitors as therapeutic options for epilepsy by machine learning-based virtual screening, molecular docking and biomolecular simulation studies.

The NOD-Like Receptor Protein-3 (NLRP3) inflammasome is a key therapeutic target for the treatment of epilepsy and has been reported to regulate inflammation in several neurological diseases. In this study, a machine learning-based virtual screening strategy has investigated candidate active compounds that inhibit the NLRP3 inflammasome. As machine learning-based virtual screening has the potential to accurately predict protein-ligand binding and reduce false positives outcomes compared to traditional virtual screening. Briefly, classification models were created using Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) machine learning methods. To determine the most crucial features of a molecule's activity, feature selection was carried out. By utilizing 10-fold cross-validation, the created models were analyzed. Among the generated models, the RF model obtained the best results as compared to others. Therefore, the RF model was used as a screening tool against the large chemical databases. Molecular operating environment (MOE) and PyRx software's were applied for molecular docking. Also, using the Amber Tools program, molecular dynamics (MD) simulation of potent inhibitors was carried out. The results showed that the KNN, SVM, and RF accuracy was 0.911 %, 0.906 %, and 0.946 %, respectively. Moreover, the model has shown sensitivity of 0.82 %, 0.78 %, and 0.86 % and specificity of 0.95 %, 0.96 %, and 0.98 % respectively. By applying the model to the ZINC and South African databases, we identified 98 and 39 compounds, respectively, potentially possessing anti-NLRP3 activity. Also, a molecular docking analysis produced ten ZINC and seven South African compounds that has comparable binding affinities to the reference drug. Moreover, MD analysis of the two complexes revealed that the two compounds (ZINC000009601348 and SANC00225) form stable complexes with varying amounts of binding energy. The in-silico studies indicate that both compounds most likely display their inhibitory effect by inhibiting the NLRP3 protein.

C ucumis melo compounds: A new avenue for ALR-2 inhibition in diabetes mellitus.

Diabetes mellitus (DM) is a prominent contributor to morbidity and mortality in developed nations, primarily attributable to vascular complications such as atherothrombosis occurring in the coronary arteries. Aldose reductase (ALR2), the main enzyme in the polyol pathway, catalyzes the conversion of glucose to sorbitol, leading to a significant buildup of reactive oxygen species in different tissues. It is therefore a prime candidate for therapeutic targeting, and extensive study is currently underway to discover novel natural compounds that can inhibit it. Cucumis melo (C. melo) has a long history as a lipid-lowering ethanopharmaceutical plant. In this study, compounds derived from C. melo were computationally evaluated as possible lead candidates. Various computational filtering methods were employed to assess the drug-like properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles of the compounds. The compounds were subsequently addressed to analysis of their interactions, molecular docking, and molecular dynamics simulation studies. When compared to the conventional therapeutic compounds, three compounds exhibited enhanced binding affinity and intra-molecular residue interactions, resulting in increased stability and specificity. Consequently, four potent inhibitors, namely PubChem CIDs 119205, 65373, 6184, and 332427, have been identified. These inhibitors exhibit promising potential as pharmacological targets for the advancement of novel ALR-2 inhibitors.

Identification of 2-(N-aryl-1,2,3-triazol-4-yl) quinoline derivatives as antitubercular agents endowed with InhA inhibitory activity.

The spread of drug-resistant tuberculosis strains has become a significant economic burden globally. To tackle this challenge, there is a need to develop new drugs that target specific mycobacterial enzymes. Among these enzymes, InhA, which is crucial for the survival of Mycobacterium tuberculosis, is a key target for drug development. Herein, 24 compounds were synthesized by merging 4-carboxyquinoline with triazole motifs. These molecules were then tested for their effectiveness against different strains of tuberculosis, including M. bovis BCG, M. tuberculosis, and M. abscessus. Additionally, their ability to inhibit the InhA enzyme was also evaluated. Several molecules showed potential as inhibitors of M. tuberculosis. Compound 5n displayed the highest efficacy with a MIC value of 12.5 µg/mL. Compounds 5g, 5i, and 5n exhibited inhibitory effects on InhA. Notably, 5n showed significant activity compared to the reference drug Isoniazid. Molecular docking analysis revealed interactions between these molecules and their target enzyme. Additionally, the molecular dynamic simulations confirmed the stability of the complexes formed by quinoline-triazole conjugate 5n with the InhA. Finally, 5n underwent in silico analysis to predict its ADME characteristics. These findings provide promising insights for developing novel small compounds that are safe and effective for the global fight against tuberculosis.

Discovery of ICOS-targeted small molecules using affinity selection mass spectrometry screening.

Inducible T cell co-stimulator (ICOS) is a positive immune checkpoint receptor expressed on the surface of activated T cells, which could promote cell function after being stimulated with ICOS ligand (ICOS-L). Although clinical benefits have been reported in the ICOS modulation-based treatment for cancer and autoimmune disease, current modulators are restricted in biologics, whereas ICOS-targeted small molecules are lacking. To fill this gap, we performed an affinity selection mass spectrometry (ASMS) screening for ICOS binding using a library of 15,600 molecules. To the best of our knowledge, this is the first study that utilizes ASMS screening to discover small molecules targeting immune checkpoints. Compound 9 with a promising ICOS/ICOS-L inhibitory profile (IC50 = 29.38 ± 3.41 µM) was selected as the template for the modification. Following preliminary structure-activity relationship (SAR) study and molecular dynamic (MD) simulation revealed the critical role of the ortho-hydroxy group on compound 9 in the ICOS binding, as it could stabilize the interaction via the hydrogen bond formation with residuals on the glycan, and the depletion could lead to an activity lost. This work validates a promising inhibitor for the ICOS/ICOS-L interaction, and we anticipate future modifications could provide more potent modulators for this interaction.

Exploring the anti-protozoal mechanisms of Syzygium aromaticum phytochemicals targeting Cryptosporidium parvum lactate dehydrogenase through molecular dynamics simulations.

Cryptosporidium parvum (C. parvum), a protozoan parasite, is known to induce significant gastrointestinal disease in humans. Lactate dehydrogenase (LDH), a protein of C. parvum, has been identified as a potential therapeutic target for developing effective drugs against infection. This study utilized a computational drug discovery approach to identify potential drug molecules against the LDH protein of C. parvum. In the present investigation, we conducted a structure-based virtual screening of 55 phytochemicals from the Syzygium aromaticum (S. aromaticum). This process identified four phytochemicals, including Gallotannin 23, Eugeniin, Strictinin, and Ellagitannin, that demonstrated significant binding affinity and dynamic stability with LDH protein. Interestingly, these four compounds have been documented to possess antibacterial, antiviral, anti-inflammatory, and antioxidant properties. The docked complexes were simulated for 100 ns using Desmond to check the dynamic stability. Finally, the free binding energy was computed from the last 10ns MD trajectories. Gallotannin 23 and Ellagitannin exhibited considerable binding affinity and stability with the target protein among all four phytochemicals. These findings suggest that these predicted phytochemicals from S. aromaticum could be further explored as potential hit candidates for developing effective drugs against C. parvum infection. The in vitro and in vivo experimental validation is still required to confirm their efficacy and safety as LDH inhibitors.

Polyphenolic metacyclophane as a radical scavenger for therapeutic activation: a computational study.

Modeling antioxidants for improved human health is a prime area of research. Inclusion complexes exhibit antioxidant activity. Supramolecular scaffolds like calixtyrosol are anticipated to have considerable antioxidant and therapeutic activity. In this study, we have designed 30 polyphenolic metacyclophanes and investigated their antioxidant properties. Exceptional O─H bond dissociation energy of 44 kcal/mol is reported for a metacyclophane with acyl urea linkage. This may be explained through a cooperative effect of localization of spin density distribution and an intramolecular hydrogen bonding of the corresponding radical. Further, the pharmacokinetics and toxicity analysis screened eight drug-like candidates. The interaction of the eight screened molecules with the Lysozyme transport protein and SOD protein has been studied using the molecular docking approach. Lastly, the MD simulations are performed to analyze the conformational changes of the transport protein after complexation with the proposed molecules. Comprehensive analyses including density functional studies of physiological parameters, favorable pharmacokinetics, toxicity, molecular docking, and MD simulations affirmed polyphenolic metacyclophane XXI as a radical scavenging and drug-like candidate.

Thiazolo-pyridopyrimidines: An in silico evaluation as a lead for CDK4/6 inhibition, synthesis and cytotoxicity screening against breast cancer cell lines.

Introduction: Pyridopyrimidines belong to a class of compounds characterized by the presence of nitrogen as heteroatoms. These compounds exhibit diverse biological effects, particularly showing promise as anticancer agents, including actions that inhibit CDK4/6. Methods: We designed and synthesized a range of substituted thiazolo-pyridopyrimidines (4a-p). Computational ADME/T analysis and molecular docking were performed using the crystal structure of CDK4/6. Subsequently, we synthesized the top-scoring compounds, characterized them using IR, NMR, and Mass spectroscopy, and assessed their impact on MCF-7 and MDAMB-231 cell lines using the SRB assay. To further evaluate stability, molecular dynamics simulations were conducted for the two most promising compounds within the binding site. Results: The docking scores indicated stronger interactions for compounds 4a, 4c, 4d, and 4g. As a result, these specific compounds (4a, 4c, 4d, and 4g) were chosen for synthesis and subsequent screening to assess their cytotoxic effects. Remarkably, compounds 4c and 4a exhibited the most promising activity in terms of their IC50 values across both tested cell lines. Furthermore, molecular dynamics simulation studies uncovered an elevated level of stability within the 4c-6OQO complex. Conclusion: By integrating insights from computational, in vitro, and molecular dynamics simulation findings, compound 4c emerges as a leading candidate for future investigations. The presence of a polar hydroxyl group at the C2 position of the 8-phenyl substitution on the pyridopyrimidine rings appears to contribute to the heightened activity of the compound. Further enhancements to cytotoxic potential could be achieved through structural refinements.

Modulation of α-synuclein aggregation amid diverse environmental perturbation.

Intrinsically disordered protein α-synuclein (αS) is implicated in Parkinson's disease due to its aberrant aggregation propensity. In a bid to identify the traits of its aggregation, here we computationally simulate the multi-chain association process of αS in aqueous as well as under diverse environmental perturbations. In particular, the aggregation of αS in aqueous and varied environmental condition led to marked concentration differences within protein aggregates, resembling liquid-liquid phase separation (LLPS). Both saline and crowded settings enhanced the LLPS propensity. However, the surface tension of αS droplet responds differently to crowders (entropy-driven) and salt (enthalpy-driven). Conformational analysis reveals that the IDP chains would adopt extended conformations within aggregates and would maintain mutually perpendicular orientations to minimize inter-chain electrostatic repulsions. The droplet stability is found to stem from a diminished intra-chain interactions in the C-terminal regions of αS, fostering inter-chain residue-residue interactions. Intriguingly, a graph theory analysis identifies small-world-like networks within droplets across environmental conditions, suggesting the prevalence of a consensus interaction patterns among the chains. Together these findings suggest a delicate balance between molecular grammar and environment-dependent nuanced aggregation behavior of αS.