In silico validation revealed the role of SCN5A mutations and their genotype-phenotype correlations in Brugada syndrome

BACKGROUND

Brugada syndrome (BrS) is a rare genetic disease that causes sudden cardiac death (SCD) and arrhythmia. SCN5A pathogenic variants (about 30% of diagnosed patients) are responsible for BrS.

AIMS

Lack of knowledge regarding molecular characteristics and the correlation between genotype and phenotype interfere with the risk stratification and finding the optimal treatment in Vietnam. Therefore, we identified SCN5A variants and evaluated the genotype-phenotype correlation of BrS on 117 Vietnamese probands.

MATERIALS AND METHODS

The clinical characteristics and blood samples of BrS patients were collected. To determine SCN5A variants, Sanger sequencing was conducted, and subsequently, these variants were analyzed by bioinformatic tools.

RESULTS

In this cohort, the overall rate of detected variants in SCN5A was 25.6%, which could include both pathogenic and benign variants. In genetic testing, 21 SCN5A variants were identified, including eight novels and 15 published variants. Multiple bioinformatic tools were used to predict variant effect with c.551A>G, c.1890+14G>A, c.3338C>T, c.3578G>A, and c.5484C>T as benign, while other variants were predicted as disease-causing. The family history of SCD (risk ratio [RR] = 4.324, 95% CI: 2.290-8.269, p < 0.001), syncope (RR = 3.147, 95% CI: 1.668-5.982, p = 0.0004), and ventricular tachycardia/ventricular fibrillation (RR = 3.406, 95% CI: 1.722-5.400, p = 0.0035) presented a significantly higher risk in the SCN5A (+) group, consisting of individuals carrying any variant in the SCN5A gene, compared to SCN5A (-) individuals.

CONCLUSION

The results contribute to clarifying the impact of SCN5A variants on these phenotypes. Further follow-up studies need to be carried out to understand the functional effects of these SCN5A variants on the severity of BrS.

Role of multi-targeted bioactive natural molecules and their derivatives in the treatment of Alzheimer's disease: an insight into structure-activity relationship

Alzheimer's disease (AD) is a complex neurodegenerative disorder involving cognitive dysfunction like short-term memory and behavioral changes as the disease progresses due to other unaltered physiological factors. The solution for this problem is Multi-targeted Drugs (MTDs), which can affect multiple determinants to realize the multifunctional effects. Acetylcholinesterase (AChE) inhibitors donepezil, rivastigmine, galantamine, and N-methyl-D-aspartate (NMDA) receptor antagonist memantine are FDA-approved drugs used to treat AD symptomatically. The key objective of this review is to understand multitargeted bioactive natural molecules that could be considered as leads for further development as effective drugs for treating AD, along with understanding its pharmacology and structure-activity relationship (SAR). Understanding the molecular mechanism of the AD pathophysiology, the role of existing drugs, treatment of AD via amyloid beta (Aβ) plaque, and neurofibrillary tangle (NFT) inhibition by natural bioactive molecules were also discussed in the review. The current quest and recent advancements with natural bioactive compounds like physostigmine, resveratrol, curcumin, and catechins, along with the study of in silico SAR, were reported in the present study. This review summarises the structural properties required for bioactive natural molecules to show anti-Alzheimer's activity by emphasizing on SAR of several bioactive natural molecules targeting various AD pathologies, their key molecular interactions that are critical for target specificity, their role as multitargeted ligands, used with adjunctive therapy for AD followed by related US patents granted recently. This article highlights the significance of the structural features of natural bioactive molecules in the treatment of AD and establishes a connection between them.Communicated by Ramaswamy H. Sarma.

Clostridium perfringens sialidase interaction with Neu5Ac α-Gal sialic acid receptors by in-silico observation and its impact on monolayers cellular behavior structure

Objective

This study aims to evaluate the effect of Clostridium perfringens sialidase treatment on monolayer cell behavior using computational screening and an in vitro approach to demonstrate interaction between enzyme-based drugs and ligands in host cells.

Materials and Methods

The in silico study was carried out by molecular docking analysis used to predict the interactions between atoms that occur, followed by genetic characterization of sialidase from a wild isolate. Sialidase, which has undergone further production and purification processes exposed to chicken embryonic fibroblast cell culture, and observations-based structural morphology of cells compared between treated cells and normal cells without treatment.

Results

Based on an in silico study, C. perfringens sialidase has an excellent binding affinity with Neu5Acα (2.3) Gal ligand receptor with Gibbs energy value (∆G)-7.35 kcal/mol and Ki value of 4.11 µM. Wild C. perfringens isolates in this study have 99.1%-100% similarity to the plc gene, NanH, and NanI genes, while NanJ shows 93.18% similarity compared to the reference isolate from GenBank. Sialidase at 750 and 150 mU may impact the viability, cell count, and cell behavior structure of fibroblast cells by significantly increasing the empty area and perimeter of chicken embryo fibroblast (CEF) cells, while at 30 mU sialidase shows no significant difference compared with mock control.

Conclusion

Sialidase-derived C. perfringens has the capacity to compete with viral molecules for attachment to host sialic acid based on in silico analysis. However, sialidase treatment has an impact on monolayer cell fibroblasts given exposure to high doses.

Artificial intelligence for neurodegenerative experimental models

INTRODUCTION

Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials.

METHODS

Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research.

RESULTS

Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability.

DISCUSSION

AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data.

HIGHLIGHTS

There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery.

Identification of potential key genes related to idiopathic male infertility using RNA-sequencing data: an in-silico approach

Among reproductive health problems, idiopathic infertility affects married couples. The current diagnosis of male infertility focuses on the concentration, motility, and morphology of sperm in the ejaculate. Since the molecular mechanism of idiopathic infertility is unknown, identification of Differentially Expressed Genes (DEGs) among the control and idiopathic infertile male can shed light on diagnosis and treatment. Here, we analyzed the dataset GSE65683 to identify DEGs in idiopathic human sperm in three groups of patients: (i) Timed Intercourse (TIC); (ii) Intrauterine Insemination (IUI); and (iii) Assisted Reproductive Technology (ART). The enrichment analysis was carried out using DAVID (Database for Annotation, Visualization and Integrated Discovery) and GeneCodis for the DEGs. Protein-Protein Interaction (PPI) network of these DEGs were constructed using the STRING database. The network parameters such as degree and betweenness were calculated to select the important hubs. In total, 118 DEGs in TIC, 446 in IUI, and 188 in ART were identified. PPI network was constructed and identified critical top hub genes such as ACTB, BTBD6, EIF2S3, EIF3A, EIF4E, POLR2L, RPL4, RPL7, RPS11, RPL13, RPS15, RPL23, RPL27, RPL9, RPLP0 and UBA52 that may play an essential role in idiopathic male infertility. Thus, the identified hub genes may provide an insight into the molecular mechanism and contribute to discovering novel therapeutic targets and developing new strategies for idiopathic male infertility.

Metabolomic profile, anti-trypanosomal potential and molecular docking studies of Thunbergia grandifolia

Trypanosomiasis is a protozoan disease transmitted via Trypanosoma brucei. This study aimed to examine the metabolic profile and anti-trypanosomal effect of methanol extract of Thunbergia grandifolia leaves. The liquid chromatography-high resolution electrospray ionisation mass spectrometry (LC-HRESIMS) revealed the identification of fifteen compounds of iridoid, flavonoid, lignan, phenolic acid, and alkaloid classes. The extract displayed a promising inhibitory activity against T. brucei TC 221 with MIC value of 1.90 μg/mL within 72 h. A subsequent in silico analysis of the dereplicated compounds (i.e. inverse docking, molecular dynamic simulation, and absolute binding free energy) suggested both rhodesain and farnesyl diphosphate synthase as probable targets for two compounds among those dereplicated ones in the plant extract (i.e. diphyllin and avacennone B). The absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling of diphyllin and avacennone were calculated accordingly, where both compounds showed acceptable drug-like properties. This study highlighted the antiparasitic potential of T. grandifolia leaves.

In silico selection of aptamers for bacterial toxins detection

The most commonly used toxins in biological warfare are staphylococcal enterotoxin B (3SEB), cholera toxin (1XTC), and botulinum toxin (3BTA). Uncovering novel strategies for identifying these toxins is paramount; therefore, aptamers are used for this purpose. Aptamers are single-stranded DNA or RNA oligonucleotides selected via Systematic Evolution of Ligands by Exponential Enrichment (SELEX) with high binding affinity and specificity against target molecules. However, SELEX in vitro is tedious; hence, adopting alternative in silico molecular docking approaches is necessary. We aimed to conduct molecular docking with accessible tools and obtain RNA aptamers. First, 4,820,095 sequences obtained from an initial library of 9.5 × 109 Python script sequences were used. The GraphClust program was used to create representative groups or clusters, and the DoGSiteScorer (https://proteins.plus/) was used to conduct binding site detection of the proteins: 5DO4 (thrombin), 3SEB, 1XTC, and 3BTA. rDock, HDock, and PatchDock were adopted, combining different docking program results (consensus scoring), to improve receptor-ligand prediction. An analysis of the poses and root mean square deviation (RMSD) was performed, and 468 structurally different aptamers were obtained. The DoGSiteScorer program predicted the binding site of each protein to direct the interaction with the aptamer. Candidate aptamers for 3SEB, 1XTC, and 3BTA were selected according to the pose value considering the closeness of the interaction with a lower mean of 45.923 Å, 45.854 Å, and 72.490 Å, respectively.Communicated by Ramaswamy H. Sarma.

Genetic diversity of Gallus sp. in Southeast Asia based on d-lopp: In silico study

Objective

This study was conducted to analyze the matrilineal structure of Gallus sp. in Southeast Asia, especially in the D-loop region.

Materials and Method

A total of 563 sequences from eight countries (Laos, Myanmar, Vietnam, Malaysia, Indonesia, Cambodia, the Philippines, and Thailand) in Southeast Asia are used in this study. Data collected from National Center for Biotechnology Information (NCBI) regarding the genus Gallus sp. in a Southeast Asian country. Data analysis was performed using MEGA 7.2 and DnaSP v6.

Results

In the haplotype found in Gallus sp. in Southeast Asia, there are 89 haplotypes. Using a neighbor-joining (Nj) analysis, 89 haplotypes found three haplogroups for Gallus sp. in Southeast Asia. In Southeast Asia, the genetic diversity of the d-loop is exceptionally high, with a haplotype diversity value of 0.524 to 1.

Conclusion

D-loop cannot be used as a specific marker for breeds or country-specifics.

Biological evaluation, docking studies, and in silico ADME prediction of some pyrimidine and pyridine derivatives as potential EGFRWT and EGFRT790M inhibitors

Herein, a set of pyridine and pyrimidine derivatives were assessed for their impact on the cell cycle and apoptosis. Human breast cancer (MCF7), hepatocellular carcinoma (HEPG2), larynx cancer (HEP2), lung cancer (H460), colon cancers (HCT116 and Caco2), and hypopharyngeal cancer (FADU), and normal Vero cell lines were used. Compounds 8 and 14 displayed outstanding effects on the investigated cell lines and were further tested for their antioxidant activity in MCF7, H460, FADU, HEP2, HEPG2, HCT116, Caco2, and Vero cells by measuring superoxide dismutase (SOD), malondialdehyde content (MDA), reduced glutathione (GSH), and nitric oxide (NO) content. Besides, Annexin V-FITC apoptosis detection and cell cycle DNA index using the HEPG-2 cell line were established on both compounds as well. Furthermore, compounds 8 and 14 were assessed for their EGFR kinase (Wild and T790M) inhibitory activities, revealing eligible potential. Additionally, molecular docking, ADME, and SAR studies were carried out for the investigated candidates.

Novel Anthranilic Acid Hybrids-An Alternative Weapon against Inflammatory Diseases

Anti-inflammatory drugs are used to relieve pain, fever, and inflammation while protecting the cardiovascular system. However, the side effects of currently available medications have limited their usage. Due to these adverse effects, there is a significant need for new drugs. The current trend of research has shifted towards the synthesis of novel anthranilic acid hybrids as anti-inflammatory agents. Phenyl- or benzyl-substituted hybrids exerted very good anti-inflammatory effects in preventing albumin denaturation. To confirm their anti-inflammatory effects, additional ex vivo tests were conducted. These immunohistochemical studies explicated the same compounds with better anti-inflammatory potential. To determine the binding affinity and interaction mode, as well as to explain the anti-inflammatory activities, the molecular docking simulation of the compounds was investigated against human serum albumin. The biological evaluation of the compounds was completed, assessing their antimicrobial activity and spasmolytic effect. Based on the experimental data, we can conclude that a collection of novel hybrids was successfully synthesized, and they can be considered anti-inflammatory drug candidates-alternatives to current therapeutics.

Carcinogenesis and Prognostic Utility of Arginine Methylation-Related Genes in Hepatocellular Cancer

Protein arginine methylation is among the most important post-translational modifications and has been studied in cancers such as those of the lung and breast. However, comparatively less has been investigated regarding hepatocellular carcinoma, with an annual incidence of almost one million cases. Through using in silico methods, this study examined arginine methylation-related gene expression and methylation levels, and alongside network and enrichment analysis attempted to find how said genes can drive tumorigenesis and offer possible therapeutic targets. We found a robust relationship among the selected methylation genes, with ⅞ showing prognostic value regarding overall survival, and a medley of non-arginine methylation pathways also being highlighted through the aforementioned analysis. This study furthers our knowledge of the methylation and expression patterns of arginine histone methylation-related genes, offering jumping points for further wet-lab studies.

Illicium verum L. (Star Anise) Essential Oil: GC/MS Profile, Molecular Docking Study, In Silico ADME Profiling, Quorum Sensing, and Biofilm-Inhibiting Effect on Foodborne Bacteria

Illicium verum, or star anise, has many uses ranging from culinary to religious. It has been used in the food industry since ancient times. The main purpose of this study was to determine the chemical composition, antibacterial, antibiofilm, and anti-quorum sensing activities of the essential oil (EO) obtained via hydro-distillation of the aerial parts of Illicium verum. Twenty-four components were identified representing 92.55% of the analyzed essential oil. (E)-anethole (83.68%), limonene (3.19%), and α-pinene (0.71%) were the main constituents of I. verum EO. The results show that the obtained EO was effective against eight bacterial strains to different degrees. Concerning the antibiofilm activity, trans-anethole was more effective against biofilm formation than the essential oil when tested using sub-inhibitory concentrations. The results of anti-swarming activity tested against P. aeruginosa PAO1 revealed that I. verum EO possesses more potent inhibitory effects on the swarming behavior of PAO1 when compared to trans-anethole, with the percentage reaching 38% at a concentration of 100 µg/mL. The ADME profiling of the identified phytocompounds confirmed their important pharmacokinetic and drug-likeness properties. The in silico study using a molecular docking approach revealed a high binding score between the identified compounds with known target enzymes involved in antibacterial and anti-quorum sensing (QS) activities. Overall, the obtained results suggest I. verum EO to be a potentially good antimicrobial agent to prevent food contamination with foodborne pathogenic bacteria.

Utilizing In Silico Approaches to Investigate the Signaling Pathway's Crucial Function in Pennisetum glaucum Under Thermal Stress

Pearl millet (Pennisetum glaucum (L.)) is a remarkable cereal crop known for its ability to thrive in challenging environmental conditions. Despite its resilience, the intricate molecular mechanisms behind its toughness remain a mystery. To address this knowledge gap, we conducted advanced next-generation RNA sequencing. This approach allowed us to compare the gene expression profiles of pearl millet seedlings exposed to heat stress with those grown under standard conditions. Our main focus was on the shoots of 13-day-old pearl millet plants, which we subjected to a brief heat stress episode at 50°C for 60 seconds. Within the vast genomic landscape comprising 36 041 genes, we successfully identified a set of 10 genes that exhibited significant fold changes, ranging from 11 to 14-fold compared to the control conditions. These 10 genes were previously unknown to have such substantial changes in expression compared to the control. To uncover the functional significance hidden within these transcriptomic findings, we utilized computational tools such as MEME, String, and phylogenetic tree analysis. These efforts collectively revealed conserved domains within the transcriptomic landscape, hinting at potential functions associated with these genetic sequences. Of particular note, the distinct transcriptomic patterns specific to pearl millet leaves under thermal stress shed light on intricate connections to fundamental biological processes. These processes included the Ethylene-activated signaling pathway, Regulation of intracellular signal transduction, Negative regulation of signal transduction, Protein autophosphorylation, and Intracellular signal transduction. Together, these processes provide insight into the molecular strategies employed by pearl millet to overcome thermal stress challenges. By integrating cutting-edge RNA sequencing techniques and computational analyses, we have embarked on unraveling the genetic components and pathways that empower pearl millet's resilience in the face of adversity. This newfound understanding has the potential to not only advance our knowledge of plant stress responses but also contribute to enhancing crop resilience in challenging environmental conditions.

Study Models of Drug-Drug Interactions Involving P-Glycoprotein: The Potential Benefit of P-Glycoprotein Modulation at the Kidney and Intestinal Levels

P-glycoprotein (P-gp) is a crucial membrane transporter situated on the cell's apical surface, being responsible for eliminating xenobiotics and endobiotics. P-gp modulators are compounds that can directly or indirectly affect this protein, leading to changes in its expression and function. These modulators can act as inhibitors, inducers, or activators, potentially causing drug-drug interactions (DDIs). This comprehensive review explores diverse models and techniques used to assess drug-induced P-gp modulation. We cover several approaches, including in silico, in vitro, ex vivo, and in vivo methods, with their respective strengths and limitations. Additionally, we explore the therapeutic implications of DDIs involving P-gp, with a special focus on the renal and intestinal elimination of P-gp substrates. This involves enhancing the removal of toxic substances from proximal tubular epithelial cells into the urine or increasing the transport of compounds from enterocytes into the intestinal lumen, thereby facilitating their excretion in the feces. A better understanding of these interactions, and of the distinct techniques applied for their study, will be of utmost importance for optimizing drug therapy, consequently minimizing drug-induced adverse and toxic effects.

In Silico Design of a New Epitope-Based Vaccine against Grass Group 1 Allergens

Allergic diseases are a global public health problem that affects up to 30% of the population in industrialized societies. More than 40% of allergic patients suffer from grass pollen allergy. Grass pollen allergens of group 1 and group 5 are the major allergens, since they induce allergic reactions in patients at high rates. In this study, we used immunoinformatic approaches to design an effective epitope-based vaccine against the grass group 1 allergens. After the alignment of all known pollen T-cell and B-cell epitopes from pollen allergens available in the public databases, the epitope GTKSEVEDVIPEGWKADTSY was identified as the most suitable for further analyses. The target sequence was subjected to immunoinformatics analyses to predict antigenic T-cell and B-cell epitopes. Population coverage analysis was performed for CD8+ and CD4+ T-cell epitopes. The selected T-cell epitopes (VEDVIPEGW and TKSEVEDVIPEGWKA) covered 78.87% and 98.20% of the global population and 84.57% and 99.86% of the population of Europe. Selected CD8+, CD4+ T-cell and B-cell epitopes have been validated by molecular docking analysis. CD8+ and CD4+ T-cell epitopes showed a very strong binding affinity to major histocompatibility complex (MHC) class I (MHC I) molecules and MHC class II (MHC II) molecules with global energy scores of -72.1 kcal/mol and -89.59 kcal/mol, respectively. The human IgE-Fc (PDB ID 4J4P) showed a lower affinity with B-cell epitope (ΔG = -34.4 kcal/mol), while the Phl p 2-specific human IgE Fab (PDB ID 2VXQ) had the lowest binding with the B-cell epitope (ΔG = -29.9 kcal/mol). Our immunoinformatics results demonstrated that the peptide GTKSEVEDVIPEGWKADTSY could stimulate the immune system and we performed ex vivo tests showed that the investigated epitope activates T cells isolated from patients with grass pollen allergy, but it is not recognized by IgE antibodies specific for grass pollen allergens. This confirms the importance of such studies to establish universal epitopes to serve as a basis for developing an effective vaccine against a particular group of allergens. Further in vivo studies are needed to validate the effectiveness of such a vaccine against grass pollen allergens.

In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases.

In silico co-crystal design: Assessment of the latest advances

Pharmaceutical co-crystals represent a growing class of crystal forms in the context of pharmaceutical science. They are attractive to pharmaceutical scientists because they significantly expand the number of crystal forms that exist for an active pharmaceutical ingredient and can lead to improvements in physicochemical properties of clinical relevance. At the same time, machine learning is finding its way into all areas of drug discovery and delivers impressive results. In this review, we attempt to provide an overview of machine learning, deep learning and network-based recommendation approaches applied to pharmaceutical co-crystallization. We also present crystal structure prediction as an alternative to machine learning approaches.

Evaluation of potential bacterial protease inhibitor properties of selected hydroxyquinoline derivatives: an in silico docking and molecular dynamics simulation approach

Antimicrobial drug resistance (AMR) is a severe global threat to public health. The increasing emergence of drug-resistant bacteria requires the discovery of novel antibacterial agents. Quinoline derivatives have previously been reported to exhibit antimalarial, antiviral, antitumor, antiulcer, antioxidant and, most interestingly, antibacterial properties. In this study, we evaluated the binding affinity of three newly designed hydroxyquinolines derived from sulfanilamide (1), 4-amino benzoic acid (2) and sulfanilic acid (3) towards five bacterial protein targets (PDB ID: 1JIJ, 3VOB, 1ZI0, 6F86, 4CJN). The three derivatives were designed considering the amino acid residues identified at the active site of each protein involved in the binding of each co-crystallized ligand and drug-likeness properties. The ligands displayed binding energy values with the target proteins ranging from -2.17 to -8.45 kcal/mol. Compounds (1) and (3) showed the best binding scores towards 1ZI0/3VOB and 1JIJ/4CJN, respectively, which may serve as new antibiotic scaffolds. Our in silico results suggest that sulfanilamide (1) or sulfanilic acid (3) hydroxyquinoline derivatives have the potential to be developed as bacterial inhibitors, particularly MRSA inhibitors. But before that, it must go through the proper preclinical and clinical trials for further scientific validation. Further experimental studies are warranted to explore the antibacterial potential of these compounds through preclinical and clinical studies.Communicated by Ramaswamy H. Sarma.

In silico analysis of the antidepressant fluoxetine and similar drugs as inhibitors of the human protein acid sphingomyelinase: a related SARS-CoV-2 inhibition pathway

Acid Sphingomyelinase (ASM) is a human phosphodiesterase that catalyzes the metabolism of sphingomyelin (SM) to ceramide and phosphocholine. ASM is involved in the plasma membrane cell repair and is associated with the lysosomal inner lipid membrane by nonbonding interactions. The disruption of those interaction would result in ASM release into the lysosomal lumen and consequent degradation of its structure. Furthermore, SARS-CoV-2 infection has been linked with ASM activation and with a ceramide domain formation in the outer leaflet of the plasma membrane that is thought to be crucial for the viral particles recognition by the host cells. In this study, we have explored in silico the behavior of fluoxetine and related drugs as potential inhibitors of ASM. Theoretically, these drugs would be able to overpass lysosomal membrane and reach the interactions that sustain ASM structure, breaking them and inhibiting the ASM. The analyses of docking data indicated that fluoxetine allocated mainly in the N-terminal saposin domain via nonbonding interactions, mostly of hydrophobic nature. Similar results were obtained for venlafaxine, citalopram, atomoxetine, nisoxetine and fluoxetine's main metabolite norfluoxetine. In conclusion, it was observed that the saposin allocation may be a good indicative of the drugs inhibition mechanism, once this domain is responsible for the binding of ASM to lysosomal membrane and some of those drugs have previously been reported to inhibit the phosphodiesterase by releasing its structure in the lysosomal lumen. Our MD data also provides some insight about natural ligand C18 sphingomyelin conformations on saposin.Communicated by Ramaswamy H. Sarma.

Structural and functional validation of a cloned parasporin from Bacillus thuringiensis isolate KAU 41 native to Western Ghats of India

Parasporins of Bacillus thuringiensis (Bt) exhibit specific toxicity to cancer cells. PCR based mining has identified apoptosis inducing parasporin in KAU41 Bt isolate from the Western Ghats of India. The study aimed to clone and overexpress the parasporin of native KAU41 Bt isolate for determining structural and functional characteristics of the protein. Parasporin gene was cloned in pGEM-T, sequenced, sub-cloned in pET30+ and overexpressed in Escherichia coli. The expressed protein was characterized by SDS-PAGE and in silico methods. Cytotoxicity of cleaved peptide was assessed by MTT assay. SDS-PAGE displayed a 31 kDa protein (rp-KAU41) overexpressed. Upon proteinase K digestion, the protein was cleaved into 29 kDa peptide which was found to be cytotoxic to HeLa cells. The protein has a deduced sequence of 267 amino acids with β-strands folding pattern of crystal protein. Even though rp-KAU41 shared a 99.15% identity to chain-A of non-toxic crystal protein, it only showed a less similarity to the existing parasporins like PS4 (38%) and PS5 (24%) in UPGMA analysis, emphasizing the novelty of rp-KAU41. The protein is predicted to have more similarity to the pore forming toxins of Aerolysin superfamily and an additional loop in rp-KAU41 may be contributing towards its cytotoxicity. The molecular docking with caspase 3 resulted in higher Z dock and Z rank score substantiating its role in the activation of intrinsic pathway of apoptosis. The recombinant parasporin protein, rp-KAU41 is presumed to belong to the Aerolysin superfamily. An interaction with caspase 3 substantiates its role in activating the intrinsic pathway of apoptosis in cancer cells.

In silico QSAR modeling to predict the safe use of antibiotics during pregnancy

The use of medicines during pregnancy is a growing public health concern due to the risk of developmental toxicity. Healthcare providers heavily rely on the FDA pregnancy risk categories (A, B, C, D, and X). Antibiotics are among the most prescribed drugs during pregnancy and are often listed under category B or C. However, the risk-benefit assessment may be lacking due to challenges in the clinical toxicology studies on pregnant women, such as ethical concerns. The primary focus of this study is to generate a model that predicts the safe use of antibiotics during pregnancy by using in silico approaches. Thus, a QSAR model was created to assess the FDA pregnancy category (B or C) of antibiotics. The dataset consisted of 97 antibiotics obtained from the FDA. A total of 6420 molecular descriptors were determined via multiple software and various machine learning algorithms were utilized. The performance of the models was measured using internal and external validation. The accuracy (ACC) values of the most successful model were 83.82% for the internal and 94.11% for the external validation. Sensitivity (SE), specificity (SP), MCC, and ROC values were 0.878, 0.778, 0.68, and 0.892 for the internal validation and 0.9, 1, 0.887, and 0.936 for the external validation, respectively. Kappa statistics also indicate that there was a substantial agreement for internal validation with 0.6765 and an almost perfect agreement for external validation with 0.8811. In conclusion, our model can be used as an initial step before pre-clinical and clinical studies to predict the safe use of antibiotics in pregnancy.

Indole-pyridine carbonitriles: multicomponent reaction synthesis and bio-evaluation as potential hits against diabetes mellitus

Background: Diabetes mellitus is a significant health disorder; therefore, researchers should focus on discovering new drug candidates. Methods: A series of indole-pyridine carbonitrile derivatives, 1-34, were synthesized through a one-pot multicomponent reaction and evaluated for antidiabetic and antioxidant potential. Results: In this library, 12 derivatives - 1, 2, 4, 5, 7, 8, 10-12, 14, 15 and 31 - exhibited potent inhibitory activities against α-glucosidase and α-amylase enzymes, in comparison to acarbose (IC50 = 14.50 ± 0.11 μM). Furthermore, kinetics, absorption, distribution, metabolism, excretion and toxicity and molecular docking studies were used to interpret the type of inhibition, binding energies and interactions of ligands with target enzymes. Conclusion: These results indicate that the compounds may be promising hits for controlling diabetes mellitus and its related complications.

Structure-Based In Silico Screening of Marine Phlorotannins for Potential Walrus Calicivirus Inhibitor

A new calicivirus isolated from a walrus was reported in 2004. Since unknown marine mammalian zoonotic viruses could pose great risks to human health, this study aimed to develop therapeutic countermeasures to quell any potential outbreak of a pandemic caused by this virus. We first generated a 3D model of the walrus calicivirus capsid protein and identified compounds from marine natural products, especially phlorotannins, as potential walrus calicivirus inhibitors. A 3D model of the target protein was generated using homology modeling based on two publicly available template sequences. The sequence of the capsid protein exhibited 31.3% identity and 42.7% similarity with the reference templates. The accuracy and reliability of the predicted residues were validated via Ramachandran plotting. Molecular docking simulations were performed between the capsid protein 3D model and 17 phlorotannins. Among them, five phlorotannins demonstrated markedly stable docking profiles; in particular, 2,7-phloroglucinol-6,6-bieckol showed favorable structural integrity and stability during molecular dynamics simulations. The results indicate that the phlorotannins are promising walrus calicivirus inhibitors. Overall, the study findings showcase the rapid turnaround of in silico-based drug discovery approaches, providing useful insights for developing potential therapies against novel pathogenic viruses, especially when the 3D structures of the viruses remain experimentally unknown.

Effects of algerian nettle (Urtica dioica L.) on benign prostatic hyperplasia and their mechanism of action elucidation: in vivo and in silico approaches

This study investigated the effect of Urtica dioica roots etheric extract (UDEE) on oxidative stress, and urine obstruction with histopathological examinations of prostatic and renal tissues,and suggests computational methods as a complementary method, to make a hypothesis on the overall effect of UDEE in the treatment of benign prostatic hyperplasia (BPH).Gas chromatography/mass spectrometry was utilised to characterise UDEE.BPH was induced in rats through daily subcutaneous injections of testosterone propionate. Rats were also orally administered UDEE or a vehicle. After four weeks, prostate weight, urine output, and biochemical markers were evaluated. UDEE treatment demonstrated significant regression of prostatic enlargement, improved biochemical and histopathological characteristics, and regulation of antioxidant activity levels. Phytosteroids stand out, act by inhibiting 5α-reductase and aromatase. This study provides an insight into treatment of BPH, demonstrating safety of this compound towards the kidney compared to finasteride without severe side effects.

The Content of Anthocyanins in Cowpea (Vigna unguiculata (L.) Walp.) Seeds and Contribution of the MYB Gene Cluster to Their Coloration Pattern

The intensively pigmented legumes belonging to Phaseolus and Vigna spp. are valued as an essential component of healthy nutrition due to their high content of flavonoids. In this context, we used the accessions of Vigna unguiculata with different colors of seed coats from the N.I. Vavilov All-Russian Institute of Plant Genetic Resources collection as the main object of this research. We applied confocal laser scanning microscopy, biochemical analysis, and wide in silico and molecular genetic analyses to study the main candidate genes for anthocyanin pigmentation within the MYB cluster on chromosome 5. We performed statistical data processing. The anthocyanin content ranged from 2.96 mg/100 g DW in reddish-brown-seeded cowpea accessions to 175.16 mg/100 g DW in black-seeded ones. Laser microscopy showed that the autofluorescence in cowpea seeds was mainly caused by phenolic compounds. The maximum fluorescence was observed in the seed coat, while its dark color, due to the highest level of red fluorescence, pointed to the presence of anthocyanins and anthocyanidins. Genes of the MYB cluster on chromosome 5 demonstrated a high homology and were segregated into a separate clade. However, amplification products were not obtained for all genes because of the truncation of some genes. Statistical analysis showed a clear correlation between the high content of anthocyanins in cowpea seeds and the presence of PCR products with primers Vigun05g0393-300-1.