PBPK Modeling Approach to Predict the Behavior of Drugs Cleared by Metabolism in Pregnant Subjects and Fetuses

This study aimed to develop a physiologically based pharmacokinetic (PBPK) model that simulates metabolically cleared compounds' pharmacokinetics (PK) in pregnant subjects and fetuses. This model accounts for the differences in tissue sizes, blood flow rates, enzyme expression levels, plasma protein binding, and other physiological factors affecting the drugs' PK in both the pregnant woman and the fetus. The PBPKPlus™ module in GastroPlus® was used to model the PK of metoprolol, midazolam, and metronidazole for both non-pregnant and pregnant groups. For each of the three compounds, the model was first developed and validated against PK data in healthy non-pregnant volunteers and then applied to predict the PK in the pregnant groups. The model accurately described the PK in both the non-pregnant and pregnant groups and explained well the differences in the plasma concentration due to pregnancy. When available, the fetal plasma concentration, placenta, and fetal tissue concentrations were also predicted reasonably well at different stages of pregnancy. The work described the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for metabolically cleared compounds.

Predictive Modeling of Proteins Encoded by a Plant Virus Sheds a New Light on Their Structure and Inherent Multifunctionality

Plant virus genomes encode proteins that are involved in replication, encapsidation, cell-to-cell, and long-distance movement, avoidance of host detection, counter-defense, and transmission from host to host, among other functions. Even though the multifunctionality of plant viral proteins is well documented, contemporary functional repertoires of individual proteins are incomplete. However, these can be enhanced by modeling tools. Here, predictive modeling of proteins encoded by the two genomic RNAs, i.e., RNA1 and RNA2, of grapevine fanleaf virus (GFLV) and their satellite RNAs by a suite of protein prediction software confirmed not only previously validated functions (suppressor of RNA silencing [VSR], viral genome-linked protein [VPg], protease [Pro], symptom determinant [Sd], homing protein [HP], movement protein [MP], coat protein [CP], and transmission determinant [Td]) and previously identified putative functions (helicase [Hel] and RNA-dependent RNA polymerase [Pol]), but also predicted novel functions with varying levels of confidence. These include a T3/T7-like RNA polymerase domain for protein 1AVSR, a short-chain reductase for protein 1BHel/VSR, a parathyroid hormone family domain for protein 1EPol/Sd, overlapping domains of unknown function and an ABC transporter domain for protein 2BMP, and DNA topoisomerase domains, transcription factor FBXO25 domain, or DNA Pol subunit cdc27 domain for the satellite RNA protein. Structural predictions for proteins 2AHP/Sd, 2BMP, and 3A? had low confidence, while predictions for proteins 1AVSR, 1BHel*/VSR, 1CVPg, 1DPro, 1EPol*/Sd, and 2CCP/Td retained higher confidence in at least one prediction. This research provided new insights into the structure and functions of GFLV proteins and their satellite protein. Future work is needed to validate these findings.

In silico exploration of venlafaxine, a potential non-tricyclic antidepressant in a liposomal formulation for nose-to-brain drug delivery

OBJECTIVE

Non-tricyclic antidepressants (non-TCAs) work by preventing the intake of norepinephrine and serotonin. Therefore, the aim of this study was to identify a potent non-TCAs and to develop liposomal formulation, characterize and to determine the drug release study across model of dialysis membrane via in vitro and in silico techniques.

METHODS

The in silico docking analysis identified venlafaxine (VLF) as the best non-TCAs with the depressant targets (PDB ID: 3PBL and 4BVN). VLF-loaded liposomal formulation was prepared by the thin-film hydration technique and characterized by physicochemical properties, including entrapment efficacy, in vitro drug release, particle size analysis, and FTIR. Moreover, this article also compares VLF and VLF-loaded with liposome carriers (LPs) based on nose-to-brain drug delivery approaches to treating depression.

RESULTS

Drug release profiles of the optimal liposomal formulation of VLF-LPs were examined in the high entrapment efficiency 94.13 ± 1.20% was attained at 224 nm, composed of spherical particles having a mean particle size of 191 ± 2.0 nm, a polydispersity index of 0.281 ± 0.06 and zeta potential of -20.3 mV. The best formulation of VLF-LPs was more effective than oral VLF treatment, as shown by the in vitro drug release data.

CONCLUSION

The results show that the VLF-LPs formulation is a promising potential platform for application in nose-to-brain drug delivery. Thus, highlighting the robustness of the intranasal drug delivery system with enhanced pharmaceutical properties, efficacy, and bioavailability for the anti-depression effect.

Dihydropyrimidine derivatives as MDM2 inhibitors

One of the chief pathways to regulate p53 levels is MDM2 protein, which negatively controls p53 by direct inhibition. Many cancers overproduce MDM2 protein to interrupt p53 functions. Therefore, impeding MDM2's binding to p53 can reactivate p53 in tumor cells may suggest an effective approach for tumor therapy. Here, some Monastrol derivatives were designed in silico as MDM2 inhibitors, and their initial cytotoxicity was evaluated in vitro on MFC-7 and MDA-MB-231 cells. A small library of Monastrol derivatives was created, and virtual screening (VS) was performed on them. The first-ranked compound, which was extracted from VS, and the other six compounds 5a-5f were selected to carry out the single-docking and docking with explicit waters. The compound with the best average results was then subjected to molecular dynamic (MD) simulation. Compounds 5a-5f were chemically synthesized and evaluated in vitro for their initial cytotoxicity on MFC-7 and MDA-MB-231 cells by MTT assay. The best compound was compound 5d with ΔGave  = -10.35 kcal/mol. MD simulation revealed a median potency in comparison with Nutlin-3a. The MTT assay confirmed the docking and MD experiments. 5d has an IC50 of 60.09 μM on MCF-7 cells. We attempted to use Monastrol scaffold as a potent inhibitor of MDM2 rather than an Eg5 inhibitor using in silico modification. The results obtained from the in silico and in vitro evaluations were noteworthy and warranted much more effort in the future.

Designing a Multi-epitope Vaccine against the SARS-CoV-2 Variant based on an Immunoinformatics Approach

BACKGROUND

SARS-CoV-2 is a life-threatening virus in the world. Scientific evidence indicates that this pathogen will emerge again in the future. Although the current vaccines have a pivotal role in the control of this pathogen, the emergence of new variants has a negative impact on their effectiveness.

OBJECTIVES

Therefore, it is urgent to consider the protective and safe vaccine against all subcoronavirus species and variants based on the conserved region of the virus. Multi-epitope peptide vaccine (MEV), comprised of immune-dominant epitopes, is designed by immunoinformatic tools and it is a promising strategy against infectious diseases.

METHODS

Spike glycoprotein and nucleocapsid proteins from all coronavirus species and variants were aligned and the conserved region was selected. Antigenicity, toxicity, and allergenicity of epitopes were checked by a proper server. To robust the immunity of the multi-epitope vaccine, cholera toxin b (CTB) and three HTL epitopes of tetanus toxin fragment C (TTFrC) were linked at the N-terminal and C-terminal of the construct, respectively. Selected epitopes with MHC molecules and the designed vaccines with Toll-like receptors (TLR-2 and TLR-4) were docked and analyzed. The immunological and physicochemical properties of the designed vaccine were evaluated. The immune responses to the designed vaccine were simulated. Furthermore, molecular dynamic simulations were performed to study the stability and interaction of the MEV-TLRs complexes during simulation time by NAMD (Nanoscale molecular dynamic) software. Finally, the codon of the designed vaccine was optimized according to Saccharomyces boulardii.

RESULTS

The conserved regions of spike glycoprotein and nucleocapsid protein were gathered. Then, safe and antigenic epitopes were selected. The population coverage of the designed vaccine was 74.83%. The instability index indicated that the designed multi-epitope was stable (38.61). The binding affinity of the designed vaccine to TLR2 and TLR4 was -11.4 and -11.1, respectively. The designed vaccine could induce humoral and cellular immunity.

CONCLUSION

In silico analysis showed that the designed vaccine is a protective multi-epitope vaccine against SARS-CoV-2 variants.

Differential Signaling Pathways in Medulloblastoma: Nano-biomedicine Targeting Non-coding Epigenetics to Improve Current and Future Therapeutics

BACKGROUND

Medulloblastomas (MDB) are malignant, aggressive brain tumors that primarily affect children. The survival rate for children under 14 is approximately 72%, while for ages 15 to 39, it is around 78%. A growing body of evidence suggests that dysregulation of signaling mechanisms and noncoding RNA epigenetics play a pivotal role in this disease.

METHODOLOGY

This study conducted an electronic search of articles on websites like PubMed and Google. The current review also used an in silico databases search and bioinformatics analysis and an extensive comprehensive literature search for original research articles and review articles as well as retrieval of current and future medications in clinical trials.

RESULTS

This study indicates that several signaling pathways, such as sonic hedgehog, WNT/β-catenin, unfolded protein response mediated ER stress, notch, neurotrophins and TGF-β and ERK, MAPK, and ERK play a crucial role in the pathogenesis of MDB. Gene and ncRNA/protein are also involved as an axis long ncRNA to sponge micro-RNAs that affect downstream signal proteins expression and translation affection disease pathophysiology, prognosis and present potential target hit for drug repurposing. Current treatment options include surgery, radiation, and chemotherapy; unfortunately, the disease often relapses, and the survival rate is less than 5%. Therefore, there is a need to develop more effective treatments to combat recurrence and improve survival rates.

CONCLUSION

This review describes various MDB disease hallmarks, including the signaling mechanisms involved in pathophysiology, related-causal genes, epigenetics, downstream genes/epigenes, and possibly the causal disease genes/non-protein coding (nc)RNA/protein axis. Additionally, the challenges associated with MDB treatment are discussed, along with how they are being addressed using nano-technology and nano-biomedicine, with a listing of possible treatment options and future potential treatment modalities.

A Review on Molecular Docking As an Interpretative Tool for Molecular Targets in Disease Management

One of the most often utilized methods for drug discovery is molecular docking. With docking, one may discover new therapeutically relevant molecules by targeting the molecule and predicting the target-ligand interactions as well as different conformation of ligand at various positions. The prediction signifies the effectiveness of the molecule or the developed molecule having different affinity with target. Drug discovery plays an important role in the development of a new drug molecule of different moiety attached to it, which leads us in the management of several diseases. In silico approach led us to identification of numerous diseases caused by virus, fungi, bacteria, protozoa, and other microorganisms that affect human health. By means of computational approach, we can categorize disease symptoms and use the drugs available for such types of warning signs. After the docking process, molecular dynamics computational technique helps in the simulation of the physical movement of atoms and molecules for a fixed period of time, giving a view of the dynamic evaluation of the system. This review is an attempt to illustrate the role of molecular docking in drug development.

Toxicological Profiling of Potential Shikimate Kinase Inhibitors Against Mycobacterium tuberculosis

Over the last decade, Mycobacterium tuberculosis has mutated into a putative 'superbug', as treatments against it have failed due to increasing antimicrobial resistance. As a result, the rising incidence of multidrug-resistant tuberculosis (MDR-TB) is posing a significant public health threat, thus, the need to develop effective drugs for MDR-TB has become an urgent priority. To identify new drug candidates for the treatment of MDR-TB, the present study was based on mycobacterial shikimate kinase (MtSK) as the pharmacological target. One hundred potential MtSK inhibitors were identified from literature and database searches to identify compounds that were designed to specifically function as MtSK antagonists. The ADME properties of these compounds were evaluated by using the SwissADME web tool. ProTox-II software was also used to investigate any potential endocrine disrupting effects, mediated through their interaction with oestrogenic and/or androgenic receptors. This study also aimed to predict LD50 values of potential drug candidates that would be active against the standard H37Rv strain of M. tuberculosis, by using the ProTox-II in silico tool. The molecules for which no structural hazard alerts were identified with these software tools were further subjected to molecular docking analyses and molecular dynamic simulations to estimate their ability to interact with the MtSK enzyme. Preliminary results from SwissADME indicated that 30 molecules were drug-like, due to their physicochemical and pharmacokinetic properties. However, subsequent analysis with ToxTree and ProTox-II indicated that only three of these 30 drug-like molecules were suitable for taking forward into further in vitro experiments. This study, which is based on the use of commonly used open-source in silico tools, identified new MtSK ligands for potential use in the development of new drugs for the therapeutic management of tuberculosis. An initial prediction of their safety profile was also generated.

Design, Synthesis and Molecular Docking Studies of Pyrazoline Derivatives as PI3K Inhibitors

AIM

Design, synthesis and molecular docking studies of quinoline/naphthalene containing pyrazoline derivatives as PI3K inhibitors.

BACKGROUND

Phosphatidylinositol 3-kinases (PI3Ks) belong to the family of enzymes, which are associated with various cellular functions such as cell growth, proliferation, differentiation etc. Overexpression or any changes in these functions may result in various abnormalities, which in turn cause cancer.

OBJECTIVES

To perform synthesis and molecular docking studies of quinoline/naphthalene containing pyrazoline derivatives as PI3K inhibitors.

METHODS

2-Chloroquinoline-3-carbaldehyde was synthesized by a reaction of acetanilide and POCl3. The latter was reacted with substituted acetophenones to synthesize chalcones, which were reacted with substituted phenyl hydrazines to yield pyrazoline derivatives (Series I). Similarly, pchloro benzaldehyde was reacted with 2-acetonapthone to yield chalcone with substituted phenyl hydrazines to yield pyrazoline derivatives (Series II).

RESULTS

The synthetic compounds were subjected to molecular modelling experiments using Schrodinger 2016 software and evaluated in silico for their PI3K binding affinities. All the compounds had better docking scores than AMG-319 (-4.36 Kcal/mol) and comparable docking scores with PI-103 (-6.83 Kcal/mol).

CONCLUSION

Compounds 5 and 3 had the best docking scores (-7.85 and -7.17 Kcal/mol, respectively). The synthesized compounds have better docking scores than the reference drug AMG-319. As a result, they might be used as lead molecules in investigating PI3K inhibitors.

Cholinesterase Inhibitory and In Silico Toxicity Assessment of Thirty-Four Isoquinoline Alkaloids - Berberine as the Lead Compound

BACKGROUND

Cholinesterase (ChE) inhibitors used currently in clinics for the treatment of Alzheimer's disease (AD) are the most prescribed drug class with nitrogen-containing chemical formula. Galanthamine, the latest generation anti-ChE drug, contains an isoquinoline structure.

OBJECTIVE

The aim of the current study was to investigate the inhibitory potential of thirty-four isoquinoline alkaloids, e.g. (-)-adlumidine, β-allocryptopine, berberine, (+)-bicuculline, (-)-bicuculline, (+)-bulbocapnine, (-)-canadine, (±)-chelidimerine, corydaldine, (±)-corydalidzine, (-)-corydalmine, (+)-cularicine, dehydrocavidine, (+)-fumariline, (-)-fumarophycine, (+)-α-hydrastine, (+)-isoboldine, 13-methylcolumbamine, (-)-norjuziphine, norsanguinarine, (-)-ophiocarpine, (-)-ophiocarpine-Noxide, oxocularine, oxosarcocapnine, palmatine, (+)-parfumine, protopine, (+)-reticuline, sanguinarine, (+)-scoulerine, (±)-sibiricine, (±)-sibiricine acetate, (-)-sinactine, and (-)-stylopine isolated from several Fumaria (fumitory) and Corydalis species towards acetyl- (AChE) and butyrylcholinesterase (BChE) by microtiter plate assays. The alkaloids with strong ChE inhibition were proceeded to molecular docking simulations as well as in silico toxicity screening for their mutagenic capacity through VEGA QSAR (AMES test) consensus model and VEGA platform as statistical approaches. The inputs were evaluated in a simplified molecular input-line entry system (SMILES).

METHODS

ChE inhibition assays indicated that the highest AChE inhibition was caused by berberine (IC50: 0.72 ± 0.04 μg/mL), palmatine (IC50: 6.29 ± 0.61 μg/mL), β-allocryptopine (IC50: 10.62 ± 0.45 μg/mL), (-)-sinactine (IC50: 11.94 ± 0.44 μg/mL), and dehydrocavidine (IC50: 15.01 ± 1.87 μg/mL) as compared to that of galanthamine (IC50: 0.74 ± 0.01 μg/mL), the reference drug with isoquinoline skeleton. Less number of the tested alkaloids exhibited notable BChE inhibition. Among them, berberine (IC50: 7.67 ± 0.36 μg/mL) and (-)-corydalmine (IC50: 7.78 ± 0.38 μg/mL) displayed a stronger inhibition than that of galanthamine (IC50: 12.02 ± 0.25 μg/mL). The mutagenic activity was shown for β-allocryptopine, (+)- and (-)-bicuculline, (±)-corydalidzine, (-)-corydalmine, (+)-cularicine, (-)- fumarophycine, (-)-norjuziphine, (-)-ophiocarpine-N-oxide, (+)-scoulerine, (-)-sinactine, and (-)- stylopine by means of in silico experiments.

RESULTS

The results obtained by molecular docking simulations of berberine, palmatine, and (-)- corydalmine suggested that the estimated free ligand-binding energies of these compounds inside the binding domains of their targets are reasonable to make them capable of establishing strong polar and nonpolar bonds with the atoms of the active site amino acids.

CONCLUSION

Our findings revealed that berberine, palmatin, and (-)-corydalmine stand out as the most promising isoquinoline alkaloids in terms of ChE inhibition. Among them, berberine has displayed a robust dual inhibition against both ChEs and could be evaluated further as a lead compound for AD.

Combined in silico and in vitro approaches to identify P-glycoprotein-inhibiting pesticides

The P-glycoprotein (P-gp) efflux pump plays a major role in xenobiotic detoxification. The inhibition of its activity by environmental contaminants remains however rather little characterised. The present study was designed to develop a combination of different approaches to identify P-gp inhibitors among a large number of pesticides using in silico and in vitro models. First, the prediction performance of four web tools was evaluated alone or in combination using a set of recently marketed drugs. The best combination of web tools-AdmetSAR2.0/PgpRules/pkCSM-was next used to predict P-gp activity inhibition by 762 pesticides. Among the 187 pesticides predicted to be P-gp inhibitors, 11 were tested in vitro for their ability to inhibit the efflux of reference substrates (rhodamine 123 and Hoechst 33342) in P-gp overexpressing MCF7R cells and to inhibit the efflux of the reference substrate rhodamine 123 in the Caco-2 cell monolayer. In MCF7R cell assays, ivermectin B1a, emamectin B1 benzoate, spinosad, dimethomorph and tralkoxydim inhibited P-gp activity; ivermectin B1a, emamectin B1 benzoate and spinosad were determined to be stronger inhibitors (half-maximal inhibitory concentration [IC50 ] of 3 ± 1, 5 ± 1 and 7 ± 1 µM, respectively) than dimethomorph and tralkoxydim (IC50 of 102 ± 7 and 88 ± 7 µM, respectively). Ivermectin B1a, emamectin B1 benzoate, spinosad and dimethomorph also inhibited P-gp activity in Caco-2 cell monolayer assays, with dimethomorph being a weaker P-gp inhibitor. These combined approaches could be used to identify P-gp inhibitors among food contaminants, but need to be optimised and adapted for high-throughput screening.

Tracing the pathways and mechanisms involved in the anti-breast cancer activity of glycyrrhizin using bioinformatics tools and computational methods

A complete investigation to understand the pathways that could be affected by glycyrrhizin (licorice), as anti-breast cancer (BC) agent, has not been performed to date. This study aims to investigate the pathways involved in the anti-cancer activity of glycyrrhizin against BC. For this purpose, the target genes of glycyrrhizin were obtained from the ChEMBL database. The BC-associated genes for three types of BC (breast carcinoma, malignant neoplasm of breast, and triple-negative breast neoplasms) were retrieved from DisGeNET. The target genes of glycyrrhizin and the BC-associated genes were compared, and the genes with disease specificity index (DSI) > 0.6 were selected for further evaluation using in silico methods. The protein-protein interaction (PPI) network was constructed, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. The potential complexes were further evaluated using molecular dynamics (MD) simulation. The results revealed that among 80 common genes, ten genes had DSI greater than 0.6, which included POLK, TACR2, MC3R, TBXAS1, HH1R, SLCO4A1, NPY2R, ADRA2C, ADRA1A, and SLCO2B1. The binding affinity of glycyrrhizin to the cognate proteins and binding characteristics were assessed using molecular docking and binding free energy calculations (MM/GBSA). POLK, TBXAS1, and ADRA1A showed the highest binding affinity with -8.9, -9.3, and -9.6 kcal/mol, respectively. The final targets had an association with BC at several stages of tumor growth. By affecting these targets, glycyrrhizin could influence and control BC efficiently. MD simulation suggested the pathways triggered by the complex glycyrrhizin-ADRA1A were more likely to happen.Communicated by Ramaswamy H. Sarma.

Reduction of monoclonal antibody viscosity using interpretable machine learning

Early identification of antibody candidates with drug-like properties is essential for simplifying the development of safe and effective antibody therapeutics. For subcutaneous administration, it is important to identify candidates with low self-association to enable their formulation at high concentration while maintaining low viscosity, opalescence, and aggregation. Here, we report an interpretable machine learning model for predicting antibody (IgG1) variants with low viscosity using only the sequences of their variable (Fv) regions. Our model was trained on antibody viscosity data (>100 mg/mL mAb concentration) obtained at a common formulation pH (pH 5.2), and it identifies three key Fv features of antibodies linked to viscosity, namely their isoelectric points, hydrophobic patch sizes, and numbers of negatively charged patches. Of the three features, most predicted antibodies at risk for high viscosity, including antibodies with diverse antibody germlines in our study (79 mAbs) as well as clinical-stage IgG1s (94 mAbs), are those with low Fv isoelectric points (Fv pIs < 6.3). Our model identifies viscous antibodies with relatively high accuracy not only in our training and test sets, but also for previously reported data. Importantly, we show that the interpretable nature of the model enables the design of mutations that significantly reduce antibody viscosity, which we confirmed experimentally. We expect that this approach can be readily integrated into the drug development process to reduce the need for experimental viscosity screening and improve the identification of antibody candidates with drug-like properties.

Antibody-dependent enhancement and neutralization against CVB4 investigated in vitro and in silico through an agent-based model

The infection with coxsackievirus B4 (CVB4) can be enhanced in vitro by antibodies directed against the viral capsid protein VP4. In peripheral blood mononuclear cells, antibody-dependent enhancement (ADE) of CVB4 infection leads to the production of interferon alpha (IFN-α). To investigate ADE of CVB4-induced production of IFN-α, an agent-based model was constructed with enhancing and neutralizing antibodies. The model recapitulates viral neutralization and ADE in silico. The enhancing and neutralizing activities of serum samples were evaluated in vitro to confront the model predictions with experimental results. Increasing the incubation time of CVB4 with serum samples improves virus neutralization in silico as well as in vitro. It also results in ADE at lower antibody numbers in silico, which is confirmed in vitro with IFN-α production at lower serum concentrations. Furthermore, incubation of CVB4 with serum at a low temperature does not induce IFN-α production in vitro. Thus, taken together our results suggest that enhancing antibodies bind cryptic epitopes, more accessible with longer incubation time and at higher temperature due to changes in capsid conformation, consistent with previous results indicating that enhancing antibodies are anti-VP4 antibodies.

HPTLC Stability Indicating Analytical Method of Andrographolide and 5-fluorouracil with Network Pharmacology Analysis against Cancer

BACKGROUND

Herbal drugs when used in combination with chemotherapeutic drugs can reduce the side effects and increase the efficacy by acting on multiple targets. Andrographolide (AG), a diterpene lactone isolated from Andrographis paniculata Nees, is a bioactive compound with anticancer potential, and 5-fluorouracil (FU), a pyrimidine analogue, is used in the treatment of cancer. Both drugs are used to formulate combination nanoformulation to increase absorption, thereby increasing their oral bioavailability.

OBJECTIVE

The study aimed to develop and validate stability indicating simultaneous HPTLC method for quantification of FU and AG in combination nanoformulation along with in silico docking and network pharmacology analysis to understand the interaction between the drugs and cancer targets.

METHODS

Chromatographic separation was performed using mobile phase chloroform: methanol: formic acid (9: 0.5: 0.5, v/v/v) on HPTLC silica plates 60 F254 as a stationary phase using UV-Vis detector and HPTLC scanner at 254 nm. Further, in silico docking analysis was performed to predict the binding affinity of AG and FU with different proteins and network pharmacology to find out the exact biomolecular relationship of AG and FU in alleviating cancer.

RESULTS

The data from the calibration curve showed a good linear regression relationship with r² = 0.9981 (FU) and r² = 0.9977 (AG) in the concentration range of 0.1-2.0 μg/mL. The developed method was validated according to the ICH guidelines. Stability studies showed changes in peak patterns and areas. Bioinformatic and network pharmacology analyses of AG and FU with target proteins and genes associated with cancer play a multimechanistic role in alleviating cancer.

CONCLUSION

The developed method has been concluded to be robust, simple, precise, reproducible, accurate, and stability indicating for simultaneous quantification of AG and FU, and the molecular interaction studies have further indicated that the combination nanoformulation of AG and FU could be effective against cancer.

Insight into intermolecular binding mechanism of apatinib mesylate and human alpha-1-acid glycoprotein: combined multi-spectroscopic approaches with in silico

Apatinib mesylate (APM), an oral tyrosine kinase inhibitor, has a good anti-tumor activity in the treatment of various cancers, particularly in advanced non-small cell lung cancer. In this study, the intermolecular binding mechanism between APM and human alpha-1-acid glycoprotein (HAG) was investigated by combining multi-spectroscopic approaches with in silico techniques. The findings revealed that APM gave rise to the fluorescence quenching of HAG by forming a ground-state complex between APM and HAG with a stoichiometric ratio of 1:1, and APM has a moderate affinity for HAG as the binding constant of APM and HAG of approximately 105 M-1, which was larger than the APM-HAG complex. The findings from thermodynamic parameter analysis indicated that the dominant driving forces for the formation of the APM-HAG complex were van der Waals forces, hydrogen bonding and hydrophobic interactions, which were also verified with site-probe studies and molecular docking. The findings from in silico study indicated that APM inserted into the opening of the hydrophobic cavity of HAG, leads to a slight conformational change in the HAG, which was verified by circular dichroism (CD) measurements, that was, the beta sheet level of HAG decreased. Additionally, the results of synchronous and 3D fluorescence spectroscopies confirmed the decline in hydrophobicity of the microenvironment around Trp and Tyr residues. Moreover, some common metal ions such as Cu2+, Mg2+, Fe3+, Ca2+, and Zn2+ could cause the alteration in the binding constant of APM with HAG, leading to the change in the efficacy of APM. It will be expected that these study findings are to provide useful information for further understanding pharmacokinetic and structural modifications of APM.Communicated by Ramaswamy H. Sarma.

A combined in silico approaches of 2D-QSAR, molecular docking, molecular dynamics and ADMET prediction of anti-cancer inhibitor activity for actinonin derivatives

Inhibition of human mitochondrial peptide deformylase (HsPDF) plays a major role in reducing growth, proliferation, and cellular cancer survival. In this work, a series of 32 actinonin derivatives for HsPDF (PDB: 3G5K) inhibitor's anticancer activity was computationally analyzed for the first time, using an in silico study considering 2D-QSAR modeling, and molecular docking studies, and validated by molecular dynamics and ADMET properties. The results of multilinear regression (MLR) and artificial neural networks (ANN) statistical analysis reveal a good correlation between pIC50 activity and the seven (7) descriptors. The developed models were highly significant with cross-validation, the Y-randomization test and their applicability range. In addition, all considered data sets show that the AC30 compound, exhibits the best binding affinity (docking score = -212.074 kcal/mol and H-bonding energy = -15.879 kcal/mol). Furthermore, molecular dynamics simulations were performed at 500 ns, confirming the stability of the studied complexes under physiological conditions and validating the molecular docking results. Five selected actinonin derivatives (AC1, AC8, AC15, AC18 and AC30), exhibiting best docking score, were rationalized as potential leads for HsPDF inhibition, in well agreement with experimental outcomes. Furthermore, based on the in silico study, new six molecules (AC32, AC33, AC34, AC35, AC36 and AC37) were suggested as HsPDF inhibition candidates, which would be combined with in-vitro and in-vivo studies to perspective validation of their anticancer activity. Indeed, the ADMET predictions indicate that these six new ligands have demonstrated a fairly good drug-likeness profile.

Docking, Synthesis, and In vitro Anti-depressant Activity of Certain Isatin Derivatives

BACKGROUND

In vitro, the molecular docking method has been suggested for estimating the biological affinity of the pharmacophores with physiologically active compounds. It is the latter stage in molecular docking, and the docking scores are examined using the AutoDock 4.2 tool program. The chosen compounds can be evaluated for in vitro activity based on the binding scores, and the IC50 values can be computed.

OBJECTIVE

The purpose of this work was to create methyl isatin compounds as potential antidepressants, compute physicochemical characteristics, and carry out docking analysis.

METHODS

The protein data bank of the RCSB (Research Collaboratory for Structural Bioinformatics) was used to download the PDB structures of monoamine oxidase (PDB ID: 2BXR) and indoleamine 2,3-dioxygenase (PDB ID: 6E35). Based on the literature, methyl isatin derivatives were chosen as the lead chemicals. By determining their IC50 values, the chosen compounds were tested for in vitro anti-depressant activity.

RESULTS

The binding scores for the interactions of SDI 1 and SD 2 with indoleamine 2,3 dioxygenase were found to be -10.55 kcal/mol and -11.08 kcal/mol, respectively, while the scores for their interactions with monoamine oxidase were found to be -8.76 kcal/mol and -9.28 kcal/mol, respectively, using AutoDock 4.2. The relationship between biological affinity and pharmacophore electrical structure was examined using the docking technique. The chosen compounds were tested for their ability to inhibit MAO, and the IC50 values for each were found to be 51.20 and 56, respectively.

CONCLUSION

This investigation has identified many novel and effective MAO-A inhibitors from the family of chemicals known as methyl isatin derivatives. Lead optimization was applied to the SDI 1 and SDI 2 derivatives. The superior bioactivity, pharmacokinetic profile, BBB penetration, pre-ADMET profiles, such as HIA (human intestinal absorption) and MDCK (Madin-Darby canine kidney), plasma protein binding, toxicity assessment, and docking outcomes, have been obtained. According to the study, synthesised isatin 1 and SDI 2 derivatives exhibited a stronger MAO inhibitory activity and effective binding energy, which may help prevent stress-induced depression and other neurodegenerative disorders caused by a monoamine imbalance.

Ganoderma adspersum (Ganodermataceae): Investigation of Its Secondary Metabolites and the Antioxidant, Antimicrobial, and Cytotoxic Potential of Its Extracts

Ganoderma is a genus of wood-degrading mushrooms with medicinal importance. Most Ganoderma species have been studied extensively for their secondary metabolites, biological activities, and ecological value. In this study, the biological activities of the extracts of G. adspersum growing wild on Morus alba trees in the region of Western Thrace (Greece) were evaluated, and the petroleum ether, dichloromethanolic, and methanolic extracts were studied further for their secondary metabolites. Six substances were isolated by chromatographic (Clumn Chromatography (C.C.), High Performance Liquid Chromatography (HPLC)) and spectroscopic methods (Nuclear Magnetic Resonance (NMR)), which were classified in the following categories: (a) unsaturated fatty acids: cis-oleic acid (1); (b) sterols: ergosta-7,22-dien-3-one (2), ergosta-7,22-dien-3-ol (3), and ergosta-5,7,22-trien-3-ol (4); and (c) lanostane-type triterpenoids: applanoxidic acid G (5) and applanoxidic acid A (6). Finally, the biological activities of the extracts were estimated for their antioxidant, antimicrobial, and cytotoxic potential. The methanolic extract of G. adspersum showed the highest total antioxidant activity. The results of the antimicrobial activities indicated that all of the extracts had a minimum inhibitory concentration (MIC) ranging between 39.1 and 312.5 μg/mL. The evaluation of the cytotoxic activity of the samples showed once again that the methanolic extract was the most potent among the examined extracts, with half-maximal inhibitory concentration (IC50) values of 19.22 μg/mL (Hep2c cells), 32.9 μg/mL (RD cells), and 8.94 μg/mL (L2OB cells). Moreover, the bioactivity scores of the isolated secondary metabolites were calculated using the online computer software program Molinspiration. The compounds showed promising bioactivity scores for drug targets.

Bio-Guided Assay of Ephedra foeminea Forssk Extracts and Anticancer Activities: In Vivo, In Vitro, and In Silico Evaluations

Ephedra is one of the oldest known medicinal plants and the largest genera of the Ephedraceae family. In vivo antitumor evaluation of Ephedra foeminea revealed that ethyl acetate (EtOAc) was the most bioactive fraction. Bio-guided fractionation of EtOAc fraction afforded nine compounds isolated for the first time from the plant species. Macrocyclic spermine alkaloids (1,9), proanthocyanidins (2,4,5), quinoline alkaloids (7,8), phenolic (3), and nucleoside (6) were identified and elucidated by spectroscopic analyses including 1D and 2D NMR, ESI-MS-MS spectrometry. The tested compounds exhibited moderate anticancer activity, except for the kynurenic acid derivative (6-mKYNA) which showed significant cytotoxicity and remarkable inhibition of CA-19.9 and CA-125 tumor biomarkers. In-silico study was conducted to determine the anti-proliferative mechanism of 6-mKYNA by using the CK2 enzyme active site. Moreover, the ADME computational study suggested that 6-mKYNA is an effective candidate with a promising pharmacokinetic profile and therapeutic potential against various types of cancer.

A new benzophenanthridine alkaloid from stem bark of Zanthoxylum rhetsa and its biological activities

A new benzophenanthridine alkaloid 6-butanoyldihydrochelerythrine (1) and five known alkaloids 6-acetonyldihydronitidine (2), 6-acetonyldihydrochelerythrine (3), isocorydine (4), (O)-methyltembamide (5), N-(4-methoxyphenethyl)benzamide (6) were isolated from the stem barks of Zanthoxylum rhetsa. These structures were elucidated by 1D, 2D NMR spectroscopy and by mass spectrometry. This is the first time that compounds 2-6 were identified from Zanthoxylum rhetsa and the first time that compounds 4 and 6 were identified from the genus Zanthoxylum. Bioactivity results of isolated compounds showed that 1, 2, 5 and 6 exhibited inhibitory activity against MCF7 and A549 cell lines, while 3 showed the inhibitory activity against A549 cell line; all isolated compounds 1-6 inhibited at least two strain microorganisms; compound 4 showed angiotensin II converting enzyme inhibitory activity in vitro with IC50 value of 65.58 µM and in silico with a docking score of -11.52 kcal/mol.

Identification of potential inhibitors targeting Ebola virus VP35 protein: a computational strategy

Ebola virus (EBOV) poses a severe threat as a highly infectious pathogen, causing devastating hemorrhagic fever in both humans and animals. The EBOV virus VP35 protein plays a crucial role in viral replication and exhibits the ability to suppress the host interferon cascade, leading to immune system depletion. As a potential drug target, VP35 protein inhibition holds promise for combating EBOV. To discover new drug candidates, we employed a computer-aided drug design approach, focusing on compounds capable of inhibiting VP35 protein replication. In this connection, a pharmacophore model was generated using molecular interactions between the VP35 protein and its inhibitor. ZINC and Cambridge database were screened using validated pharmacophore model. Further the compounds were filtered based on Lipinski's rule of five and subjected to MD simulation and relative binding free energy calculation. Six compounds manifest a significant docking score and strong binding interaction towards VP35 protein. MD simulations further confirmed the remarkable stability of these six complexes. Relative binding free energy calculations also showed significant ΔG value in the range of -132.3 and -49.3 kcal/mol. This study paves the way for further optimization of these compounds as potential inhibitors of VP35, facilitating subsequent experimental in vitro studies.Communicated by Ramaswamy H. Sarma.

An in silico micro-multiphysics agent-based approach for simulating bone regeneration in a mouse femur defect model

Bone defects represent a challenging clinical problem as they can lead to non-union. In silico models are well suited to study bone regeneration under varying conditions by linking both cellular and systems scales. This paper presents an in silico micro-multiphysics agent-based (micro-MPA) model for bone regeneration following an osteotomy. The model includes vasculature, bone, and immune cells, as well as their interaction with the local environment. The model was calibrated by time-lapsed micro-computed tomography data of femoral osteotomies in C57Bl/6J mice, and the differences between predicted bone volume fractions and the longitudinal in vivo measurements were quantitatively evaluated using root mean square error (RMSE). The model performed well in simulating bone regeneration across the osteotomy gap, with no difference (5.5% RMSE, p = 0.68) between the in silico and in vivo groups for the 5-week healing period - from the inflammatory phase to the remodelling phase - in the volume spanning the osteotomy gap. Overall, the proposed micro-MPA model was able to simulate the influence of the local mechanical environment on bone regeneration, and both this environment and cytokine concentrations were found to be key factors in promoting bone regeneration. Further, the validated model matched clinical observations that larger gap sizes correlate with worse healing outcomes and ultimately simulated non-union. This model could help design and guide future experimental studies in bone repair, by identifying which are the most critical in vivo experiments to perform.

Brasiliensic acid: in vitro cytotoxic and genotoxic, in vivo acute toxicity and in silico pharmacological prediction of a new promising molecule

Brasiliensic acid (Bras) is a chromanone isolated from Calophyllum brasiliense Cambèss. bark extracts with confirmed potential activity on gastric ulcer and Helicobacter pylori infection. This study aimed to investigate the in vitro and in vivo toxicity of Bras and molecular docking studies on its interactions with the H. pylori virulence factors and selected gastric cancer-related proteins. Cytotoxicity was evaluated by alamarBlue© assay, genotoxicity by micronucleus and comet assays, and on cell cycle by flow cytometry, using Chinese hamster epithelial ovary cells. Bras was not cytotoxic to CHO-K1 cells, and caused no chromosomal aberrations, nor altered DNA integrity. Furthermore, Bras inhibited damages to DNA by H2O2 at 1.16 µM. No cell cycle arrest was observed, but apoptosis accounted for 31.2% of the cell death observed in the CHO-K1 at 24 h incubation of the IC50. Oral acute toxicity by Hippocratic screening test in mice showed no relevant behavioral change/mortality seen up to 1,000 mg/kg. The molecular docking approach indicated potential interactions between Bras and the various targets for peptic ulcer and gastric cancer, notably CagA virulence factor of H. pylori and VEGFR-2. In conclusion, Bras is apparently safe and an optimization for Bras can be considered for gastric ulcer and cancer.Communicated by Ramaswamy H. Sarma.

In silico study revealed the inhibitory activity of selected phytomolecules of C. rotundus against VacA implicated in gastric ulcer

Gastric ulcer is associated with weakening of the mucous coating of the stomach and damages to the intestinal lining. It is caused by H. pylori assisted by enzymes including VacA, which necessitates the need for inhibitors of VacA. Bioactive compounds from Cyperus rotundus have been documented to have anti-inflammatory activities. However, the mechanism of action of the phytochemicals is not characterized. This research aimed to assess, in silico, the potential of selected bioactive compounds against VacA based on the binding to its active sites. VacA and bioactive compounds structures were obtained from protein database and PubChem webserver, respectively. All compounds, including 2 controls, omeprazole and cimetidine were docked against the protein using AutoDock Vina and screened based on the binding energy. The selected complexes were subjected to pharmacokinetics and toxicity screening. Finally, molecular dynamics simulation and MMPBSA were carried out on two best compounds. 17 compounds interacted with the active site of VacA with higher binding affinities, with 7 of them - aureusidine, catechin, chlorogenic acid, isorhamnetin, isovitexin, oreintin, and vitexin having the best behaviours based on ADMET and druglikeness screening. Molecular dynamics and MMPBSA experiments of two of the hits corroborated good stability and binding energy for Ellagic Acid and Scirpusin B (ΔG = -14.38 and -13.20 kcal mol-1, respectively). These phytochemicals showed good pharmacokinetic profiles with respect to the control drugs. This study revealed that the identified compounds of C. rotundus may serve as VacA inhibitors and may be potent candidates for novel drug formulations in gastric ulcer treatment.Communicated by Ramaswamy H. Sarma.