Bringing Molecular Dynamics Simulation Data into View

Discovery of novel PARP1 inhibitors through computational drug design approaches

BACKGROUND

Triple-negative breast cancer (TNBC) is the most frequent malignancy in women. It is a prevalent condition, representing 15-20 % of all breast cancer cases, characterized by its aggressive subtype and unfavorable prognosis.

OBJECTIVES

The main aim of this study is to find and develop a potential novel therapeutic candidate for TNBC treatment utilizing luteolin derivatives compounds.

METHODS

In this study, we used the stable TNBC protein structure from the Protein Data Bank (PDB) and selected luteolin, a bioactive compound known for its anti-cancer properties, to design potential anti-cancer drugs using computational methods. Structural activity relationship methodologies were used to evaluate active and inactive outcomes using pass prediction scores. Furthermore, we employed in-silico methods such as ADMET, drug-likeness evaluation, DFT quantum calculations, and Frontier Molecular Orbitals (HOMO and LUMO). Afterwards, we performed molecular docking for binding affinity and molecular dynamics simulations over 200 ns to validate interactions with TNBC protein RESULTS: Our results demonstrated that the ligands DM02, DM06, DM07, and DM09 did not violate Lipinski rules, and their reduced HOMO-LUMO energy gap indicates enhanced chemical reactivity and interaction with biological targets. The drug's maximum softness and minimum hardness values showed rapid metabolism and no hepatotoxicity, carcinogenicity, skin sensitization, or aquatic toxicity. Molecular docking studies revealed that DM02 and DM09, luteolin derivatives, have the highest binding affinity with the TNBC protein (PDB ID 5HA9) and our study confirms their stable interactions with the protein, suggesting potential therapeutic agents for TNBC.

CONCLUSIONS

Our computational data suggest that Luteolin derivatives have the potential to be utilized as therapeutic agents for TNBC. However, further experimental validation is needed to validate these findings.

α-Mangostin Exhibits Antitumor Activity Against NCI-H1975 Cells via the EGFR/STAT3 Pathway: An Experimental and Molecular Simulation Study

Non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations have brought great challenges to the medical treatment in the world. Current treatment strategies, such as EGFR tyrosine kinase inhibitors (TKIs), have reached certain achievements, however, patients inevitably experienced resistance after undergoing a period of treatment with these drugs. Hence, more novel therapy strategies need to be urgently developed. Natural compounds have become popular topics in drug development. α-Mangostin, which is derived from mangosteen, possesses multiple biological properties, yet the antitumor mechanism against NSCLC has not been further elucidated. In this study, an MTT assay, Western blotting, a colony formation assay, and flow cytometry were performed to detect the antitumor activity of α-Mangostin on NSCLC cell NCI-H1975. Molecular docking and molecular dynamics simulations were performed to analyze the interactions between α-Mangostin and the core target proteins. The results indicated that α-Mangostin exerts its antitumor activity by inhibiting cell proliferation and migration, reducing cell cycle arrest, promoting cell apoptosis, and regulating the phosphorylation expression levels of EGFR and signal transducer and activator of transcription 3 (STAT3). Moreover, the results of the molecular simulation study revealed the potential binding mode of α-Mangostin to EGFR and STAT3. In summary, we characterized that α-Mangostin may be used as a potent pro-drug against NSCLC via the EGFR/STAT3 pathway.

Identification and characterisation of a novel EhOrc1/Cdc6 from the human pathogen Entamoeba histolytica: an in silico approach

The onset of a pre-replication complex on origin commences DNA replication. The Origin recognition complex (Orc), Cell division cycle protein 6 (Cdc6), and the minichromosome maintenance (Mcm) replicative helicase, along with Chromatin licensing and DNA replication factor 1 (Cdt1), make up the pre-replication complex in eukaryotes. Eukaryotic Orc is made up of six subunits, designated Orc1-6 while monomeric Cdc6 has sequence similarity with Orc1. However, Orc has remained unexplored in the protozoan parasite Entamoeba histolytica. Here we report a single functional Orc1/Cdc6 protein in E. histolytica. Its structural and functional aspects have been highlighted by a detailed in silico analysis that reflects physicochemical characteristics, predictive 3D structure modelling, protein-protein interaction studies, molecular docking and simulation. This in silico study provides insight into EhOrc1/Cdc6 and points out that E. histolytica carries pre-replication machinery that is less complex than higher eukaryotes and closer to archaea. Additionally, it lays the groundwork for future investigations into the methods of origin recognition, and anomalies of cell cycle observed in this enigmatic parasite.Communicated by Ramaswamy H. Sarma.

Exploring cotton plant compounds for novel treatments against brain-eating Naegleria fowleri: An In-silico approach

To find potential inhibitors of Naegleria fowleri S-adenosyl-L-homocysteine hydrolase (NfSAHH), a brain-eating parasite, structure-based drug design was adopted. N. fowlerica causes primary amebic meningoencephalitis (PAM), a fatal central nervous system (CNS) disorder if untreated. NfSAHH protein (PDB ID: 5v96), involved in parasite growth and gene regulation, was targeted and screened against 163 metabolites from Gossypium hirsutum (cotton plant). With the aid of different software and web tools, the metabolites were subjected to several analyses. The RMSD was evaluated to validate our molecular docking strategy. Neplanocin A, a common anti-parasitic medication, was used as a reference to select top ligands for post-docking studies. Significant interactions were observed with residues THR-198, HIS-395, and MET-400. The drug-likeness of the top fifty hits was analyzed using Lipinski, Ghose, Veber, Egan, and Muegge rules. The top ten compounds following Lipinski's RO5 were studied regarding medicinal chemistry, pharmacokinetic simulation, and Swiss target prediction. Advanced strategies, including molecular dynamic simulations, binding energy calculations, and principal component analysis, were employed for the top three hits, namely curcumin, heliocide H2, and piceid, which indicated that heliocide H2 is the most promising candidate, while curcumin and piceid may need further optimization to improve their stability. Overall, the top ten phytochemicals, dotriacontanol, melissic acid, curcumin, 6,6'-dimethoxygossypol, phytosphingosine 2, methyl stearate, stearic acid, piceid, heliocide H2, and 6-methoxygossypol, reported in our study, are worthy enough to be subjected to in vivo and in vitro experimentation to find a novel drug to treat PAM.

A combined in silico approach to design peptide ligands with increased receptor-subtype selectivity

G-protein coupled receptors are major drug targets that change their conformation upon binding of ligands to their extracellular binding pocket to transduce the signal to intracellular G-proteins or arrestins. In drug screening campaigns, computational methods are frequently used to predict binding affinities for chemical compounds in silico before experimental testing. Some of these methods take into consideration the inherent flexibility of the ligand and to some extent also of the receptor. Due to high structural flexibility, peptide ligands are exceptionally difficult to handle and approaches to effectively sample in silico receptor-peptide ligand interactions are limited. Here we describe a pipeline starting from microseconds molecular dynamics simulations of receptor and receptor ligand complexes to find reasonable starting conformations and derive constraints for subsequent flexible docking of peptide ligands, using Rosetta's FlexPepDock approach. We applied this approach to predict binding affinities for dynorphin and its variants to members of the opioid receptor family. Using an ensemble of docking poses, Rosetta's fixbb protein design method explored the sequence space at defined positions, to enhance binding affinities, aiming to increase subtype selectivity towards κ-opioid receptor while decreasing it towards μ-opioid receptor. The results of our computations were validated experimentally in a related study (Zangrandi et al., 2024[1]). Four out of six proposed variants lead to a significant increase in subtype selectivity in favor of κ-opioid receptor, highlighting the potential of our approach to design subtype selective peptide variants. The established workflow may also apply for other receptor types activated by peptide ligands.

The Multi-Target Action Mechanism for the Anti-Periodontitis Effect of Astragali radix Based on Bioinformatics Analysis and In Vitro Verification

Background:Astragali radix is a traditional Chinese medicine with potential therapeutic effects on periodontitis; however, its underlying mechanisms require further investigation. Methods: We employed network pharmacology, molecular docking, molecular dynamics simulations, and in vitro experiments to explore the potential actions and mechanisms of Astragali radix in treating periodontitis. Results: A total of 17 compounds (including the most prevalent one, Kaempferol) from Astragali radix and 464 corresponding targets were identified, from which five major active ingredients were selected based on the drug-active ingredient and periodontitis gene network. Protein-protein interaction (PPI) network analysis identified the top ten core potential targets, seven of which possess suitable crystal structures for molecular docking. These include interleukin-6 (IL6), tumor necrosis factor (TNF), AKT serine/threonine kinase 1 (AKT1), interleukin-1β (IL1β), prostaglandin G/H synthase-2 (PTGS2), matrix metalloproteinase-9 (MMP9), and caspase-3 (CASP3). Additionally, 58 Gene Ontology (GO) terms and 146 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified. The five major active ingredients and seven core targets mentioned above were subjected to molecular docking analysis using Discovery Studio 2019 software. Molecular dynamic simulations confirmed a stable interaction between the CASP3 and the Kaempferol ligand system. In vitro experiments indicated that Kaempferol significantly inhibited lipopolysaccharide (LPS)-induced apoptosis in human periodontal ligament stem cells and reduced the expression levels of IL6, CASP3 and MMP9. Conclusions: This study systematically elucidates that the primary active ingredients derived from Astragali radix exert their pharmacological effects (including anti-inflammation and anti-apoptosis) primarily by interacting with multiple targets. These findings establish a promising foundation for the targeted application of Astragali radix in the treatment of periodontitis.

Comparative assessment of different anti-CD147/Basigin 2 antibodies as a potential therapeutic anticancer target by molecular modeling and dynamic simulation

Cluster of differentiation 147 (CD147) is an attractive target for anticancer therapy since it is pivotal in developing and progressing several of malignant tumors in the context of its high expression levels. Although anti-CD147 antibodies by different laboratories are designed for the Ig-like domains of CD147, there is a demand to provide priority among these anti-CD147 antibodies for developing of therapeutic anti-CD147 antibody before experimental validations. This study uses molecular docking and dynamic simulation techniques to compare the binding modes and affinities of nine antibody models against the Ig-like domains of CD147. After obtaining the model antibodies by homology modeling via Robetta, we predicted the CDRs of nine antibodies and the epitopes of CD147 to reach more accurate results for antigen affinity in molecular docking. Next, from HADDOCK 2.4., we meticulously handpicked the most superior model clusters (Z-Score: - 2.5 to - 1.2) and identified that meplazumab had higher affinities according to the success rate as the percentage of a scoring scale. We achieved stable simulations of CD147-antibody interaction. Our outcomes hold hypothetical importance for further experimental cancer research on the design and development of the relevant model antibodies.

Investigation into in silico and in vitro approaches for inhibitors targeting MCM10 in Leishmania donovani: a comprehensive study

Visceral Leishmaniasis (VL), the second neglected tropical disease caused by various Leishmania species, presents a significant public health challenge due to limited treatment options and the absence of vaccines. The agent responsible for visceral leishmaniasis, also referred to as "black fever" in India, is Leishmania donovani. This study focuses on L. donovani Minichromosome maintenance 10 (LdMcm10), a crucial protein in the DNA replication machinery, as a potential therapeutic target in Leishmania therapy using in silico and in vitro approaches. We employed bioinformatics tools, molecular docking, and molecular dynamics simulations to predict potential inhibitors against the target protein. The research revealed that the target protein lacks homologues in the host, emphasizing its potential as a drug target. Ligands from the DrugBank database were screened against LdMcm10 using PyRx software. The top three compounds, namely suramin, vapreotide, and pasireotide, exhibiting the best docking scores, underwent further investigation through molecular dynamic simulation and in vitro analysis. The observed structural dynamics suggested that LdMcm10-ligand complexes maintained consistent binding throughout the 300 ns simulation period, with minimal variations in their backbone. These findings suggest that these three compounds hold promise as potential lead compounds for developing new drugs against leishmaniasis. In vitro experiments also demonstrated a dose-dependent reduction in L. donovani viability for suramin, vapreotide, and pasireotide, with computed IC50 values providing quantitative metrics of their anti-leishmanial efficacy. The research offers a comprehensive understanding of LdMcm10 as a drug target and provides a foundation for further investigations and clinical exploration, ultimately advancing drug discovery strategies for leishmaniasis treatment.

Rational Design Engineering of 5-Aminolevulinate Synthase with Activity and Stability Enhancement

5-Aminolevulinic acid synthase (ALAS) is the key rate-limiting enzyme in the synthesis of the vital biosynthetic intermediate 5-aminolevulinic acid (ALA). However, its catalytic efficiency is compromised due to its low activity and poor stability. Here, we obtained the mutant I325M/V390Y/H391I (T6), which exhibited a 7.0-fold increase in specific activity (2.53 U/mg) compared to the wild type through the application of isothermal compressibility (βT) perturbation engineering in conjunction with two thermal stability prediction algorithms. Moreover, molecular dynamics simulations indicate that positive changes in intermolecular interactions, the substrate channel, and the binding pocket account for the improved catalytic activity of T6. Furthermore, T6 was immobilized on magnetic chitosan nanoparticles, maintaining 73.5% of its original activity after 10 reaction cycles. Overall, combination approaches were employed to construct a superior ALAS variant, providing a novel concept for the synthesis of ALA and a valuable benchmark for optimizing industrial enzymes in related fields.

Computational Exploration of Phenolic Compounds from Endophytic Fungi as α-Glucosidase Inhibitors for Diabetes Management

Diabetes has become a global epidemic, affecting even the younger people on an alarming scale. Inhibiting intestinal α-glucosidase is one of the key approaches to managing type 2 diabetes (T2D). In the present study, phenolic compounds (PCs) produced by endophytic fungi as potential α-glucosidase inhibitors (AGIs) are explored through ADMET profiling, molecular docking, and molecular dynamics (MD) Simulations. After 150 PCs were screened for their drug-likeness and toxicity properties, 45 molecules were selected. These were subjected to molecular docking studies against human N-terminal maltase-glucoamylase (NtMGAM). Based on binding energy and IC50 values, the best five PCs from different chemical classes (depsidones, phenolic acids, butenolides, furanones, and polyketides) were studied for their binding dynamics with NtMGAM employing all-atom MD simulations. Among the five ligands analyzed, the methybutyrolactone III (BUT)-NtMGAM complex exhibited significantly higher active site flexibility, indicating a conformational change in response to ligand binding. BUT interacted specifically with both key residues, Asp443 and Phe575, critical for enzyme-inhibitor stability. These interactions, coupled with increased flexibility, suggest enhanced stabilization of BUT in the active site pocket. BUT also exhibited one of the most favorable toxicity profiles among molecules analyzed using ProTox 3.0. Molecular mechanics Poisson-Boltzmann surface area calculations confirmed that BUT had the highest binding energy (-35.01 kcal/mol) driven by substantial van der Waals and electrostatic interactions. Another butenolide derivative, aspernolide (ALD) ranked second in the binding energy score (-31.13 kcal/mol). These findings suggest that PCs possessing butenolide scaffolds, like BUT and ALD, hold great promise as potential AGIs for managing T2D. These findings, however, need to be further validated through in vivo experimentation.

Deciphering olfactory receptor binding mechanisms: a structural and dynamic perspective on olfactory receptors

Olfactory receptors, classified as G-protein coupled receptors (GPCRs), have been a subject of scientific inquiry since the early 1950s. Historically, investigations into the sensory mechanisms of olfactory receptors were often confined to behavioral characteristics in model organisms or the expression of related proteins and genes. However, with the development of cryo-electron microscopy techniques, it has gradually become possible to decipher the specific structures of olfactory receptors in insects and humans. This has provided new insights into the binding mechanisms between odor molecules and olfactory receptors. Furthermore, due to the rapid advancements in related fields such as computer simulations, the prediction and exploration of odor molecule binding to olfactory receptors have been progressively achieved through molecular dynamics simulations. Through this comprehensive review, we aim to provide a thorough analysis of research related to the binding mechanisms between odor molecules and olfactory receptors from the perspectives of structural biology and molecular dynamics simulations. Finally, we will provide an outlook on the future of research in the field of olfactory receptor sensory mechanisms.

Synthesis, Characterization, and antiviral evaluation of New Chalcone-Based Imidazo[1,2-a]pyridine Derivatives: Insights from in vitro and in silico Anti-HIV studies

Given the ease of synthetic accessibility and the promising biological profile demonstrated by both imidazo[1,2-a]pyridine and Chalcone derivatives, a series of Chalcone-based imidazo[1,2-a]pyridine derivatives were synthesized and characterized using 1H NMR, 13C NMR, Mass Spectrometry and FTIR techniques. Density functional theory (DFT) was employed to investigate the structural and electronic properties, providing insights into potential reactive sites. The synthesized compounds were evaluated in vitro for their antiviral properties against human immunodeficiency virus type-1 (HIV-1) and human immunodeficiency virus type-2 (HIV-2) in MT-4 cells. Furthermore, Molecular docking studies show strong binding affinities with HIV-1 reverse transcriptase and HIV-2 protease. To further understand the dynamic behavior and stability of these interactions, molecular dynamics (MD) simulations were conducted. The MD results indicated stable binding conformations of the ligands within the active sites, with low RMSD and RMSF values throughout the simulation, confirming the robustness of these interactions. ADME predictions suggested acceptable pharmacokinetic profiles, though solubility remains a limitation for these compounds. Although the in vitro antiviral activity was limited, the combination of in vitro and in silico approaches provided valuable insights, guiding further structural optimization to improve bioavailability and enhance the therapeutic potential of these derivatives.

The Potential Mechanism of Alpiniae oxyphyllae Fructus Against Hyperuricemia: An Integration of Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation, and In Vitro Experiments

Background: Alpiniae oxyphyllae Fructus (AOF) is a medicinal and edible resource that holds potential to ameliorate hyperuricemia (HUA), yet its mechanism of action warrants further investigation. Methods: We performed network pharmacology, molecular docking, molecular dynamics simulation, and in vitro experiments to investigate the potential action and mechanism of AOF against HUA. Results: The results indicate that 48 potential anti-HUA targets for 4 components derived from AOF were excavated and predicted through public databases. Gene Ontology (GO) enrichment analysis indicated that there are 190 entries related to biological process, 24 entries related to cellular component, 42 entries related to molecular function, and 44 entries related to Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. The results of molecular docking showed that the main active ingredients of AOF may have potential therapeutic effects on immune system disorders and inflammation caused by HUA by binding to targets including peroxisome-proliferator-activated receptor gamma (PPARG), estrogen receptor 1 (ESR1), prostaglandin G/H synthase 2 (PTGS2), and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). Subsequently, we further determined the stability of the complex between the core active ingredient and the core target proteins by molecular dynamics simulation. The results of cell experiments demonstrated that stigmasterol as the core active ingredient derived from AOF significantly upregulated the expression levels of ESR1 and PPARG (p < 0.001) to exert an anti-HUA effect. Conclusions: In summary, we have systematically elucidated that the mechanism of main active ingredients derived from AOF mainly exert their pharmacological effects by acting on multiple targets in this study. Our studies will provide a scientific basis for the precise development and utilization of AOF.

Targeting serotonin receptors with phytochemicals - an in-silico study

The potential of natural phytochemicals in mitigating depression has been supported by substantial evidence. This study evaluated a total of 88 natural phytochemicals with potential antidepressant properties by targeting serotonin (5-HT) receptors (5-HT1A, 5-HT4, and 5-HT7) using molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, internal coordinates normal mode analysis (NMA), molecular dynamics simulation (MDS), and free energy calculation. Five evaluated compounds (Genistein, Kaempferol, Daidzein, Peonidin, and glycitein) exhibited favorable pharmacokinetic properties and improved binding scores, indicating their potential as effective antidepressants. Redocking and superimposition analysis of 5-HT with cocrystal structures validated these findings. Furthermore, NMA, MDS, and free energy calculations confirmed the stability and deformability of the ligand-receptor complexes, suggesting that these phytochemicals can effectively interact with 5-HT receptors to modulate depressive symptoms. These powerful phytochemicals, abundantly found in soybeans, fruits, vegetables, and herbs, represent a promising avenue for developing natural treatments for depression. Further in vitro and in vivo studies are warranted to explore their efficacy in alleviating stress and depression through their interactions with 5-HT receptors.

Leveraging computer-aided design and artificial intelligence to develop a next-generation multi-epitope tuberculosis vaccine candidate

Background

Tuberculosis (TB) remains a global public health challenge. The existing Bacillus Calmette-Guérin vaccine has limited efficacy in preventing adult pulmonary TB, necessitating the development of new vaccines with improved protective effects.

Methods

Computer-aided design and artificial intelligence technologies, combined with bioinformatics and immunoinformatics approaches, were used to design a multi-epitope vaccine (MEV) against TB. Comprehensive bioinformatics analyses were conducted to evaluate the physicochemical properties, spatial structure, immunogenicity, molecular dynamics (MD), and immunological characteristics of the MEV.

Results

We constructed a MEV, designated ZL12138L, containing 13 helper T lymphocyte epitopes, 12 cytotoxic T lymphocyte epitopes, 8 B-cell epitopes, as well as Toll-like receptor (TLR) agonists and helper peptides. Bioinformatics analyses revealed that ZL12138L should exhibit excellent immunogenicity and antigenicity, with no toxicity or allergenicity, and had potential to induce robust immune responses and high solubility, the immunogenicity score was 4.14449, the antigenicity score was 0.8843, and the immunological score was 0.470. Moreover, ZL12138L showed high population coverage for human leukocyte antigen class I and II alleles, reaching 92.41% and 90.17%, respectively, globally. Molecular docking analysis indicated favorable binding affinity of ZL12138L with TLR-2 and TLR-4, with binding energies of -1173.4 and -1360.5 kcal/mol, respectively. Normal mode analysis and MD simulations indicated the stability and dynamic properties of the vaccine construct. Immune simulation predictions suggested that ZL12138L could effectively activate innate and adaptive immune cells, inducing high levels of Type 1 T helper cell cytokines.

Conclusions

This study provides compelling evidence for ZL12138L as a promising TB vaccine candidate. Future research will focus on experimental validation and further optimization of the vaccine design.

Reviewability and supportability: New complementary principles to empower research software practices

In today's scientific landscape, research software has evolved from being a supportive tool to becoming a fundamental driver of discovery, particularly in life sciences. Beyond its roots in software engineering, research software now plays a crucial role in facilitating efficient data analysis and enabling the exploration of complex natural phenomena. The advancements in simulations and modeling through research software have significantly accelerated the pace of scientific research while reducing associated costs. This growing reliance underscores the importance of software in ensuring reproducibility - a cornerstone of scientific rigor and trustworthiness. Although verifying reproducibility presents challenges, well-developed and openly accessible research software enhances transparency and aids in the early detection of errors. Although verifying reproducibility can be challenging, well-developed and accessible research software improves transparency and facilitates error detection. This mini-review examines the characteristics of research software and summarizes the key events that have shaped its development, alongside changes in requirements and guidelines. Moreover, we propose two additional principles - reviewability and supportability - complementing the widely accepted FAIR principles (Findability, Accessibility, Interoperability, and Reusability). These new principles aim to improve the efficiency and effectiveness of software evaluation during the peer review process. Through this review, we aim to assist scientists, especially those without extensive software development expertise, in understanding best practices for developing research software and the underlying motivations driving these practices.

Carotenoid Interactions with PCSK9: Exploring Novel Cholesterol-Lowering Strategies

Background/Objectives: This study investigated the potential of green algae-derived carotenoids as natural inhibitors of the proprotein convertase subtilisin/kexin type 9 (PCSK9), a key regulator of cholesterol metabolism. PCSK9 promotes the degradation of low-density lipoprotein receptors (LDLR), thereby increasing blood cholesterol levels and elevating the risk of cardiovascular diseases. Methods/Results: We screened the pharmacophore fit score of 27 carotenoids with PCSK9 and identified 14 that were analyzed for binding affinity and molecular interactions. Astaxanthin, siphonaxanthin, and prasinoxanthin were identified as the top candidates, demonstrating strong binding affinity (-10.5, -10.3, and -9.4 Kcal/mol, respectively) and stable interactions with several known key residues within the active site of PCSK9, including Pro-331, Arg-357, Cys-358, Val-359, Asp-360, Ile-416, Leu-436, Thr-437, Pro-438, Leu-440, Arg-458, Val-460, Trp-461, Arg-476, Cys-477, Ala-478, Ala-649, Val-650, and Asp-651. Density functional theory analysis confirmed the stability of astaxanthin and its favorable electronic properties, suggesting its potential as an effective inhibitor. Molecular dynamics simulations of the PCSK9-astaxanthin complex revealed sustained structural stability and key interactions critical for maintaining the functional integrity of the protein. Conclusions: These findings provide evidence that specific carotenoids, particularly astaxanthin, may offer a cost-effective alternative to existing PCSK9 inhibitors, providing a potential approach for managing cholesterol levels and reducing cardiovascular risk. Pre-clinical and clinical validations are required to confirm the therapeutic potential of these compounds.

Computer-aided rational design of a mRNA vaccine against Guanarito mammarenavirus

PURPOSE

Guanarito mammarenavirus (GTOV) is a highly pathogenic virus that leads to Venezuelan hemorrhagic fever (VHF). Despite being a severe disease, there are currently no commercially available drugs or vaccines for its prevention.

METHODS

Here we computationally formulated a mRNA vaccine construct (VC) from the genome of GTOV to produce immunity against its infections. Two proteins, namely zinc-finger motif protein (NP_899220.1), and nucleocapsid protein (NP_899211.1) were screened as potential candidates for downstream analysis.

RESULTS

We determined the T and B cell epitopes of the candidate proteins. The resulting epitopes were analyzed, and the best epitopes were utilized in the formation of the peptide vaccine construct. The secondary and tertiary structures of the peptide construct were predicted and validated. Docking was conducted to check the binding energy of the designed peptide vaccine with the human immune receptors, namely TLR2 and TLR4. Our designed vaccine showed stable interactions with the HLA molecules, as verified through normal mode and MD simulation analysis. The immune simulation results indicated a positive immune response against the construct. A potentially stable mRNA vaccine was formulated by adding of sequences such as the Kozak, Goblin 5' UTR, tPA-signal peptide, MITD, 3' UTRs, and a poly(A) tail to the peptide vaccine construct. Lastly, the expression probability of the mRNA vaccine was confirmed in the expression system of E. coli strain K12.

CONCLUSION

The designed vaccine showed the potential to elicit an immune response against the GTOV infection; however, experimental validation is recommended to verify the in-silico findings of this study.

Bioinformatics Analysis and Experimental Findings Reveal the Therapeutic Actions and Targets of Cyathulae Radix Against Type 2 Diabetes Mellitus

Objective: This study elucidated the mechanistic role of Cyathulae Radix (CR) in type 2 diabetes mellitus (T2DM) through bioinformatics analysis and experimental validation. Methods: Components and targets of CR were retrieved from the traditional Chinese medical systems pharmacology, while potential T2DM targets were obtained from GeneCards and Online Mendelian Inheritance in Man databases. Intersecting these datasets yielded target genes between CR and T2DM. Differential genes were used for constructing a protein-protein interaction network, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking and dynamics simulations were performed using AutoDock and GROMACS, respectively, and in vitro experiments validated the results. Experiments evaluated the effect of CR on T2DM pancreatic β-cells. Results: Bioinformatics analysis identified four active compounds of CR, 157 related genes, and 5431 T2DM target genes, with 141 shared targets. Key targets such as JUN, MAPK1, and MAPK14 were identified through topological analysis of the PPI network. GO analysis presented 2663 entries, while KEGG analysis identified 161 pathways. The molecular docking results demonstrated favorable binding energy between the core components and the core proteins. Among them, JUN-rubrosterone, MAPK1-rubrosterone, and MAPK14-rubrosterone deserved further investigation. Molecular dynamics results indicated that all of them can form stable binding interactions. CR could inhibit the expression of JUN, MAPK1, and MAPK14, promote insulin secretion, alleviate apoptosis, and regulate autophagy in INS-1 cells. Conclusion: This study suggests CR approach to T2DM management by multitarget and multipathway provides a scientific basis for further research on the hypoglycemic effect of CR.

Novel chiral phthalimides: Antimicrobial evaluation and docking study against Acinetobacter baumannii's OmpA protein

Antibiotics have been a vital component in the fight against microbial diseases for over 75 years, saving countless lives. However, the global rise of multi-drug-resistance (MDR) bacterial infections is pushing us closer to a post-antibiotic era where common infections may once again become lethal. To combat MDR Acinetobacter baumannii, we investigated chiral phthalimides and used molecular docking to identify potential targets. Outer membrane protein A (OmpA) is crucial for A. baumannii resistant to antibiotics, making it a pathogen of great concern due to its high mortality rate and limited treatment options. In this study, we evaluated three distinct compounds against the OmpA protein: FIA (2-(1,3-dioxoindolin-2yl)-3-phenylpropanoic acid), FIC (2-(1,3-dioxoindolin-2yl)-4-(methylthio) butanoic acid), and FII (3-(1,3-dioxoindolin-2yl)-3-phenylpropanoic acid). Molecular docking results showed that these three compounds exhibited strong interactions with the OmpA protein. Molecular dynamics (MD) simulation analysis further confirmed the stability and binding efficacy of these compounds with OmpA. Their antimicrobial activities were assessed using the agar well diffusion method, revealing that FIA had an optimal zone of inhibition of 24 mm. Additionally, the minimum inhibitory concentrations (MIC) of these compounds were determined, demonstrating their bactericidal properties against A. baumannii, with MICs of 11 μg/μL for FIA, 46 μg/μL for FIC, and 375 μg/μL for FII. In vitro cytotoxicity data indicated that none of the three compounds were hemolytic when exposed to human red blood cells. This finding is particularly significant as it highlights the superior efficacy of FIA against A. baumannii compared to the other compounds. With thorough pharmacokinetic validations, these chiral phthalimides are promising alternative therapeutic options for treating infections caused by A. baumannii, offering new hope in the face of rising antibiotic resistance.

Deciphering the toxicological and computational assessment of Verbascum yemenese.: Integrating phytochemistry and bioinformatics tools

This study explores the phytochemical composition and biological activities of Verbascum yemenense, a plant known for its medicinal properties. The plant extract revealed a rich presence of bioactive compounds that exhibited significant antioxidant properties against free radicals. The enzyme inhibition potential was particularly notable against cholinesterases (AChE: 2.56 mg GALAE/g; BChE: 1.98 mg GALAE/g), and tyrosinase (87.94 mg KAE/g), α-glucosidase suggesting potential therapeutic applications in neurodegenerative diseases, skin disorders and diabetes. Molecular docking studies and Molecular Dynamics simulations, providing insights into the interaction mechanisms of the identified compounds with the target proteins. Molecular docking studies revealed high binding affinities of the phytoconstituents, with compounds like VY4 and phyllanthusol-A (VY15) showing substantial docking scores against AChE (-9.840 kcal/mol) and BChE (-9.853 kcal/mol), respectively. For instance, the RMSD values during the MD simulations for compound VY17 in the AML complex showed a stable conformation, fluctuating within a range of 0.75 Å to 1.75 Å, indicating a strong and consistent interaction with the enzyme. MESP studies highlighted VY17's distinctive electrostatic features, notably a pronounced electronegative region, which might contribute to its binding efficiency. These findings suggest that V. yemenense is a promising candidate for developing novel therapeutic agents.

A molecular dynamics simulations analysis of repurposing drugs for COVID-19 using bioinformatics methods

A number of multidisciplinary methods have piqued the interest of researchers as means to accelerate and lower the cost of medication creation. The goal of this research was to find target proteins and then select a lead drug against SARS-CoV-2. The three-dimensional structure is taken from the RCSB PDB using its specific PDB ID 6lu7. Virtual screening based on pharmacophores is performed using Molecular Operating Environment software. We looked for a potent inhibitor in the FDA-approved database. For docking, AutoDock Vina uses Pyrx. The compound-target protein binding interactions were tested using BIOVIA Discovery Studio. The stability of protein and inhibitor complexes in a physiological setting was investigated using Desmond's Molecular Dynamics Simulation (MD simulation). According to our findings, we repurpose the FDA-approved drugs ZINC000169677008 and ZINC000169289767, which inhibit the activity of the virus's main protease (6lu7). The scientific community will gain from this finding, which might create new medicine. The novel repurposed chemicals were promising inhibitors with increased efficacy and fewer side effects.Communicated by Ramaswamy H. Sarma.

Exploring the interplay between Porphyromonas gingivalis KGP gingipain, herpes virus MicroRNA-6, and Icp4 transcript in periodontitis: Computational and clinical insights

BACKGROUND

Porphyromonas gingivalis, a major pathogen in periodontitis, produces KGP (Lys-gingipain), a cysteine protease that enhances bacterial virulence by promoting tissue invasion and immune evasion. Recent studies highlight microRNAs' role in viral latency, potentially affecting lytic replication through host mechanisms. Herpes virus (HSV) establishes latency via interactions between microRNA-6 (miRH-6) and the ICP4 transcription factor in neural ganglia. This suggests a potential link between periodontitis and HSV-induced latency. This study aims to identify and validate the insilico inhibitory interaction of P. gingivalis KGP with ICP4 transcripts and correlate the presence of viral latency-associated transcript micro-RNA-6 with periodontitis.

METHODS

Computational docking analysis was performed to investigate the potential interaction between ICP4 and KGP gingipain. The binding energy and RMSD ligand values were calculated to determine the interaction's strength. Ten patients with recurrent clinical attachment loss despite conventional therapy were included in the clinical study. Subgingival tissue samples were collected post-phase I therapy, and HSV microRNA-6 presence was detected via polymerase chain reaction and confirmed through gel electrophoresis.

RESULTS

Computational docking identified the ICP4-KGP gingipain complex with the lowest binding energy (-288.29 kJ mol^1) and an RMSD ligand of 1.5 Angstroms, indicating strong interaction potential. Gel electrophoresis confirmed miRH-6 presence in all samples.

CONCLUSION

The identification of miRNA-6 in periodontitis patients and the strong interaction potential between P. gingivalis KGP gingipain and ICP4 transcripts indicate a possible link between bacterial virulence factors and viral latency dynamics in periodontal tissues. These results highlight the complex interplay between oral pathogens, viral microRNAs, and host immune responses in periodontitis.

Structure-function relationship of dynorphin B variants using naturally occurring amino acid substitutions

Dynorphins (Dyn) represent the subset of endogenous opioid peptides with the highest binding affinity to kappa opioid receptors (KOPrs). Activation of the G-protein-coupled pathway of KOPrs has strong anticonvulsant effects. Dyn also bind to mu (MOPrs) and delta opioid receptors (DOPrs) with lower affinity and can activate the β-arrestin pathway. To fully exploit the therapeutic potential of dynorphins and reduce potential unwanted effects, increased selectivity for KOPrs combined with reduced activation of the mTOR complex would be favorable. Therefore, we investigated a series of dynorphin B (DynB) variants, substituted in one or two positions with naturally occurring amino acids for differential opioid receptor activation, applying competitive radio binding assays, GTPγS assays, PRESTO-Tango, and Western blotting on single-opioid receptor-expressing cells. Seven DynB derivatives displayed at least 10-fold increased selectivity for KOPrs over either MOPrs or DOPrs. The highest selectivity for KOPrs over MOPrs was obtained with DynB_G3M/Q8H, and the highest selectivity for KOPrs over DOPrs was obtained with DynB_L5S. Increased selectivity for KOPr over MOPr and DOPr was based on a loss of affinity or potency at MOPr and DOPr rather than a higher affinity or potency at KOPr. This suggests that the investigated amino acid exchanges in positions 3, 5, and 8 are of higher importance for binding and activation of MOPr or DOPr than of KOPr. In tests for signal transduction using the GTPγS assay, none of the DynB derivatives displayed increased potency. The three tested variants with substitutions of glycine to methionine in position 3 displayed reduced efficacy and are, therefore, considered partial agonists. The two most promising activating candidates were further investigated for functional selectivity between the G-protein and the β-arrestin pathway, as well as for activation of mTOR. No difference was detected in the respective read-outs, compared to wild-type DynB. Our data indicate that the assessment of affinity to KOPr alone is not sufficient to predict either potency or efficacy of peptidergic agonists on KOPr. Further assessment of downstream pathways is required to allow more reliable predictions of in vivo effects.

Aldose reductase inhibitory and antiglycation properties of phytoconstituents of Cichorium intybus: Potential therapeutic role in diabetic retinopathy

Diabetic vascular complication including diabetic retinopathy is a major morbidity in Saudia Arabia. The polyol pathway aka aldose reductase (AR) pathway has gained significant association with diabetic retinopathy with regard to chronically enhanced glucose metabolism. Considerable research has been put forth to develop more effective therapeutic strategies to overcome the overwhelming challenges of vascular complications associated with diabetes. In this regard, constituents of Cichorium intybus can offer strong AR inhibitory potential because of their strong antidiabetic properties. Therefore, aim of this study was to investigate the AR inhibitory as well as antiglycation potential of C. intybus extract/compounds. The preliminary in vitro results showed that methanolic extract of C. intybus could significantly inhibit AR enzyme and advanced glycation end product formation. Eventually, based on previous studies and reviews, we selected one hundred fifteen C. intybus root constituents and screened them through Lipinski's rule of five and ADMET analysis. Later, after molecular docking analysis of eight compounds, five best were selected for molecular dynamics simulation to deduce their binding affinity with the AR enzyme. Finally, three out of five compounds were further tested in vitro for their AR inhibitory potential and antiglycation properties. Enzyme assay and kinetic studies showed that all the three tested compounds were having potent AR inhibitory properties, although to a lesser extent than ellagic acid and tolrestat. Similarly, kaempferol showed strong antiglycation property equivalent to ellagic acid, but greater than aminoguanidine. Intriguingly, significant reduction in sorbitol accumulation in RBCs by the tested compounds substantiated strong AR inhibition by these compounds. Moreover, decrease in sorbitol accumulation under high glucose environment also signifies the potential application of these compounds in diabetic retinopathy and other vascular complications. Thus, in sum, the in silico and in vitro studies combinedly showed that C. intybus root is a treasure for therapeutic compounds and can be explored further for drug development against diabetic retinopathy.

Identification of novel natural compounds against CFTR p.Gly628Arg pathogenic variant

Cystic fibrosis transmembrane conductance regulator (CFTR) protein is an ion channel found in numerous epithelia and controls the flow of water and salt across the epithelium. The aim of our study to find natural compounds that can improve lung function for people with cystic fibrosis (CF) caused by the p.Gly628Arg (rs397508316) mutation of CFTR protein. The sequence of CFTR protein as a target structure was retrieved from UniProt and PDB database. The ligands that included Armepavine, Osthole, Curcumin, Plumbagine, Quercetin, and one Trikafta (R*) reference drug were screened out from PubChem database. Autodock vina software carried out docking, and binding energies between the drug and the target were included using docking-score. The following tools examined binding energy, interaction, stability, toxicity, and visualize protein-ligand complexes. The compounds having binding energies of -6.4, -5.1, -6.6, -5.1, and - 6.5 kcal/mol for Armepavine, Osthole, Curcumin, Plumbagine, Quercetin, and R*-drug, respectively with mutated CFTR (Gly628Arg) structure were chosen as the most promising ligands. The ligands bind to the mutated CFTR protein structure active sites in hydrophobic bonds, hydrogen bonds, and electrostatic interactions. According to ADMET analyses, the ligands Armepavine and Quercetin also displayed good pharmacokinetic and toxicity characteristics. An MD simulation for 200 ns was also established to ensure that Armepavine and Quercetin ligands attached to the target protein favorably and dynamically, and that protein-ligand complex stability was maintained. It is concluded that Armepavine and Quercetin have stronger capacity to inhibit the effect of mutated CFTR protein through improved trafficking and restoration of original function.

Design principles for molecular animation

Molecular visualization is a powerful way to represent the complex structure of molecules and their higher order assemblies, as well as the dynamics of their interactions. Although conventions for depicting static molecular structures and complexes are now well established and guide the viewer's attention to specific aspects of structure and function, little attention and design classification has been devoted to how molecular motion is depicted. As we continue to probe and discover how molecules move - including their internal flexibility, conformational changes and dynamic associations with binding partners and environments - we are faced with difficult design challenges that are relevant to molecular visualizations both for the scientific community and students of cell and molecular biology. To facilitate these design decisions, we have identified twelve molecular animation design principles that are important to consider when creating molecular animations. Many of these principles pertain to misconceptions that students have primarily regarding the agency of molecules, while others are derived from visual treatments frequently observed in molecular animations that may promote misconceptions. For each principle, we have created a pair of molecular animations that exemplify the principle by depicting the same content in the presence and absence of that design approach. Although not intended to be prescriptive, we hope this set of design principles can be used by the scientific, education, and scientific visualization communities to facilitate and improve the pedagogical effectiveness of molecular animation.

Overcoming Resistance in Cancer Therapy: Computational Exploration of PIK3CA Mutations, Unveiling Novel Non-Toxic Inhibitors, and Molecular Insights Into Targeting PI3Kα

Phosphoinositide-3-kinases (PI3 K) are pivotal regulators of cell signaling implicated in various cancers. Particularly, mutations in the PIK3CA gene encoding the p110α catalytic subunit drive oncogenic signaling, making it an attractive therapeutic target. Our study conducted in silico exploration of 31 PIK3CA mutations across breast, endometrial, colon, and ovarian cancers, assessing their impacts on response to PI3Kα inhibitors and identifying potential non-toxic inhibitors and also elucidating their effects on protein stability and flexibility. Specifically, we observed significant alterations in the stability and flexibility of the PI3 K protein induced by these mutations. Through molecular docking analysis, we evaluated the binding interactions between the selected inhibitors and the PI3 K protein. The filtration of ligands involved calculating chemical descriptors, incorporating Veber and Lipinski rules, as well as IC50 values and toxicity predictions. This process reduced the initial dataset of 1394 ligands to 12 potential non-toxic inhibitors, and four reference inhibitors with significant biological activity in clinical trials were then chosen based on their physico-chemical properties. This analysis revealed Lig5's exceptional performance, exhibiting superior affinity and specificity compared to established reference inhibitors such as pictilisib. Lig5 formed robust binding interactions with the PI3 K protein, suggesting its potential as a highly effective therapeutic agent against PI3 K-driven cancers. Furthermore, molecular dynamics simulations provided valuable insights into Lig5's stability and its interactions with PI3 K over 100 ns. These simulations supported Lig5's potential as a versatile inhibitor capable of effectively targeting various mutational profiles of PI3 K, thereby mitigating issues related to resistance and toxicity commonly associated with current inhibitors.

Structure based screening and molecular docking with dynamic simulation of natural secondary metabolites to target RNA-dependent RNA polymerase of five different retroviruses

Viral diseases pose a serious global health threat due to their rapid transmission and widespread impact. The RNA-dependent RNA polymerase (RdRp) participates in the synthesis, transcription, and replication of viral RNA in host. The current study investigates the antiviral potential of secondary metabolites particularly those derived from bacteria, fungi, and plants to develop novel medicines. Using a virtual screening approach that combines molecular docking and molecular dynamics (MD) simulations, we aimed to discover compounds with strong interactions with RdRp of five different retroviruses. The top five compounds were selected for each viral RdRp based on their docking scores, binding patterns, molecular interactions, and drug-likeness properties. The molecular docking study uncovered several metabolites with antiviral activity against RdRp. For instance, cytochalasin Z8 had the lowest docking score of -8.9 (kcal/mol) against RdRp of SARS-CoV-2, aspulvinone D (-9.2 kcal/mol) against HIV-1, talaromyolide D (-9.9 kcal/mol) for hepatitis C, aspulvinone D (-9.9 kcal/mol) against Ebola and talaromyolide D also maintained the lowest docking score of -9.2 kcal/mol against RdRp enzyme of dengue virus. These compounds showed remarkable antiviral potential comparable to standard drug (remdesivir -7.4 kcal/mol) approved to target RdRp and possess no significant toxicity. The molecular dynamics simulation confirmed that the best selected ligands were firmly bound to their respective target proteins for a simulation time of 200 ns. The identified lead compounds possess distinctive pharmacological characteristics, making them potential candidates for repurposing as antiviral drugs against SARS-CoV-2. Further experimental evaluation and investigation are recommended to ascertain their efficacy and potential.

Research into how carvacrol and metformin affect several human proteins in a hyperglycemic condition: A comparative study in silico and in vitro

Carvacrol (CV) is an organic compound found in the essential oils of many aromatic herbs. It is nearly unfeasible to analyze all the current human proteins for a query ligand using in vitro and in vivo methods. This study aimed to clarify whether CV possesses an anti-diabetic feature via Docking-based inverse docking and molecular dynamic (MD) simulation and in vitro characterization against a set of novel human protein targets. Herein, the best poses of CV docking simulations according to binding energy ranged from -7.9 to -3.5 (kcal/mol). After pathway analysis of the protein list through GeneMANIA and WebGestalt, eight interacting proteins (DPP4, FBP1, GCK, HSD11β1, INSR, PYGL, PPARA, and PPARG) with CV were determined, and these proteins exhibited stable structures during the MD process with CV. In vitro application, statistically significant results were achieved only in combined doses with CV or metformin. Considering all these findings, PPARG and INSR, among these target proteins of CV, are FDA-approved targets for treating diabetes. Therefore, CV may be on its way to becoming a promising therapeutic compound for treating Diabetes Mellitus (DM). Our outcomes expose formerly unexplored potential target human proteins, whose association with diabetic disorders might guide new potential treatments for DM.

An integrated in silico approach for the identification of novel potential drug target and chimeric vaccine against Neisseria meningitides strain 331401 serogroup X by subtractive genomics and reverse vaccinology

Neisseria meningitidis, commonly known as the meningococcus, leads to substantial illness and death among children and young adults globally, revealing as either epidemic or sporadic meningitis and/or septicemia. In this study, we have designed a novel peptide-based chimeric vaccine candidate against the N. meningitidis strain 331,401 serogroup X. Through rigorous analysis of subtractive genomics, two essential cytoplasmic proteins, namely UPI000012E8E0(UDP-3-O-acyl-GlcNAc deacetylase) and UPI0000ECF4A9(UDP-N-acetylglucosamine acyltransferase) emerged as potential drug targets. Additionally, using reverse vaccinology, the outer membrane protein UPI0001F4D537 (Membrane fusion protein MtrC) identified by subcellular localization and recognized for its known indispensable role in bacterial survival was identified as a novel chimeric vaccine target. Following a careful comparison of MHC-I, MHC-II, T-cell, and B-cell epitopes, three epitopes derived from UPI0001F4D537 were linked with three types of linkers-GGGS, EAAAK, and the essential PADRE-for vaccine construction. This resulted in eight distinct vaccine models (V1-V8). Among them V1 model was selected as the final vaccine construct. It exhibits exceptional immunogenicity, safety, and enhanced antigenicity, with 97.7 % of its residues in the Ramachandran plot's most favored region. Subsequently, the vaccine structure was docked with the TLR4/MD2 complex and six different HLA allele receptors using the HADDOCK server. The docking resulted in the lowest HADDOCK score of 39.3 ± 9.0 for TLR/MD2. Immune stimulation showed a strong immune response, including antibodies creation and the activation of B-cells, T Cytotoxic cells, T Helper cells, Natural Killer cells, and interleukins. Furthermore, the vaccine construct was successfully expressed in the Escherichia coli system by reverse transcription, optimization, and ligation in the pET-28a (+) vector for the expression study. The current study proposes V1 construct has the potential to elicit both cellular and humoral responses, crucial for the developing an epitope-based vaccine against N. meningitidis strain 331,401 serogroup X.

Bioinformatics-Driven mRNA-Based Vaccine Design for Controlling Tinea Cruris Induced by Trichophyton rubrum

Tinea cruris, a dermatophyte fungal infection predominantly caused by Trichophyton rubrum and Epidermophyton floccosum, primarily affects the groin, pubic region, and adjacent thigh. Its recurrence is frequent, attributable to repeated fungal infections in susceptible individuals, especially those with onychomycosis or tinea pedis, which act as reservoirs for dermatophytes. Given the persistent nature of tinea cruris, vaccination emerges as a promising strategy for fungal infection management, offering targeted, durable protection against various fungal species. Vaccines stimulate both humoral and cell-mediated immunity and are administered prophylactically to prevent infections while minimizing the risk of antifungal resistance development. Developing fungal vaccines is challenging due to the thick fungal cell wall, similarities between fungal and human cells, antigenic variation, and evolutionary resemblance to animals, complicating non-toxic target identification and T-cell response variability. No prior research has shown an mRNA vaccine for T. rubrum. Hence, this study proposes a novel mRNA-based vaccine for tinea cruris, potentially offering long-term immunity and reducing reliance on antifungal medications. This study explores the complete proteome of T. rubrum, identifying potential protein candidates for vaccine development through reverse vaccinology. Immunogenic epitopes from these candidates were mapped and integrated into multitope vaccines and reverse translated to construct mRNA vaccines. Then, the mRNA was translated and computationally assessed for physicochemical, chemical, and immunological attributes. Notably, 1,3-beta-glucanosyltransferase, CFEM domain-containing protein, cell wall galactomannoprotein, and LysM domain-containing protein emerged as promising vaccine targets. Antigenic, immunogenic, non-toxic, and non-allergenic cytotoxic T lymphocyte, helper T lymphocyte, and B lymphocyte epitopes were selected and linked with appropriate linkers and Toll-like receptor (TLR) agonist adjuvants to formulate vaccine candidates targeting T. rubrum. The protein-based vaccines underwent reverse translation to construct the mRNA vaccines, which, after inoculation, were translated again by host ribosomes to work as potential components for triggering the immune response. After that, molecular docking, normal mode analysis, and molecular dynamic simulation confirmed strong binding affinities and stable complexes between vaccines and TLR receptors. Furthermore, immune simulations of vaccines with and without adjuvant demonstrated activation of immune responses, evidenced by elevated levels of IgG1, IgG2, IgM antibodies, cytokines, and interleukins. There was no significant change in antibody production between vaccines with and without adjuvants, but adjuvants are crucial for activating the innate immune response via TLRs. Although mRNA vaccines hold promise against fungal infections, further research is essential to assess their safety and efficacy. Experimental validation is crucial for evaluating their immunogenicity, effectiveness, and safety.

Exploring the most promising anti - Depressant drug targeting Microtubule Affinity Receptor Kinase 4 involved in Alzheimer's Disease through molecular docking and molecular dynamics simulation

Alzheimer's Disease (AD) is the prevailing type of neurodegenerative illness, characterised by the accumulation of amyloid beta plaques. The symptoms associated with AD are memory loss, emotional variability, and a decline in cognitive functioning. To date, the pharmaceuticals currently accessible in the marketplace are limited to symptom management. According to several research, antidepressants have demonstrated potential efficacy in the management of AD. In this particular investigation, a total of 24 anti-depressant medications were selected as ligands, while the Microtubule Affinity Receptor Kinase 4 (MARK4) protein was chosen as the focal point of our study. The selection of MARK4 was based on its known involvement in the advancement of AD and other types of malignancies, rendering it a highly prospective target for therapeutic interventions. The initial step involved doing ADMET analysis, which was subsequently followed by molecular docking of 24 drugs. This was succeeded by molecular dynamics simulation and molecular mechanics generalised Born surface area (MMGBSA) calculations. Upon conducting molecular docking experiments, it has been determined that the binding affinities observed fall within the range of -5.5 kcal/mol to -9.0 kcal/mol. In this study, we selected six anti-depressant compounds (CID ID - 4184, 2771, 4205, 5533, 4543, and 2160) based on their binding affinities, which were determined to be -9.0, -8.7, -8.4, -8.3, -8.2, and -8.2, respectively. Molecular dynamics simulations were conducted for all six drugs, with donepezil serving as the control drug. Various analyses were performed, including basic analysis and post-trajectory analysis such as free energy landscape (FEL), polarizable continuum model (PCM), and MMGBSA calculations. Based on the findings from molecular dynamics simulations and the MMGBSA analysis, it can be inferred that citalopram and mirtazapine exhibit considerable potential as anti-depressant agents. Consequently, these compounds warrant further investigation through in vitro and in vivo investigations in the context of treating AD.

Pathways to a Shiny Future: Building the Foundation for Computational Physical Chemistry and Biophysics in 2050

In the last quarter-century, the field of molecular dynamics (MD) has undergone a remarkable transformation, propelled by substantial enhancements in software, hardware, and underlying methodologies. In this Perspective, we contemplate the future trajectory of MD simulations and their possible look at the year 2050. We spotlight the pivotal role of artificial intelligence (AI) in shaping the future of MD and the broader field of computational physical chemistry. We outline critical strategies and initiatives that are essential for the seamless integration of such technologies. Our discussion delves into topics like multiscale modeling, adept management of ever-increasing data deluge, the establishment of centralized simulation databases, and the autonomous refinement, cross-validation, and self-expansion of these repositories. The successful implementation of these advancements requires scientific transparency, a cautiously optimistic approach to interpreting AI-driven simulations and their analysis, and a mindset that prioritizes knowledge-motivated research alongside AI-enhanced big data exploration. While history reminds us that the trajectory of technological progress can be unpredictable, this Perspective offers guidance on preparedness and proactive measures, aiming to steer future advancements in the most beneficial and successful direction.

Antibacterial potential of Propolis: molecular docking, simulation and toxicity analysis

The issue of antibiotic resistance in pathogenic microbes is a global concern. This study was aimed to explore in silico and in vitro analysis of the antibacterial efficacy of different natural ligands against bacterial activity. The ligands included in the study were Propolis Neoflavanoide 1, Carvacrol, Cinnamaldehyde, Thymol, p-benzoquinone, and Ciprofloxacin (standard drug S*). The outcomes of molecular docking revealed that Propolis Neoflavaniode-1 showed a highly significant binding energy of - 7.1 and - 7.2 kcal/mol for the two gram-positive bacteria, as compared to the gram-negative bacteria. All ligands demonstrated acute toxicity (oral, dermal), except for Propolis Neoflavanoide 1 and S* drugs, with a confidence score range of 50-60%. Using a molecular dynamic simulation approach, we investigated Propolis Neoflavaniode-1's potential for therapeutic use in more detail. An MD simulation lasting 100 ns was performed using the Desmond Simulation software to examine the conformational stability and steady state of Propolis Neoflavaniode-1 in protein molecule complexes. Additionally, in vitro studies confirmed the antimicrobial activity of Propolis Neoflavaniode 1 by increasing the zone of inhibition against Gram-positive bacteria, p < 0.005 as compared to gram-negative bacteria. This study revealed the promising antibacterial efficacy of Propolis Neoflavaniode 1, demonstrated through robust in silico analyses, minimal toxicity, and confirmed in vitro antimicrobial activity, suggesting its potential as a viable alternative to combat antibiotic resistance.

Development of a subunit vaccine against the cholangiocarcinoma causing Opisthorchis viverrini: a computational approach

Opisthorchis viverrini is the etiological agent of the disease opisthorchiasis and related cholangiocarcinoma (CCA). It infects fish-eating mammals and more than 10 million people in Southeast Asia suffered from opisthorchiasis with a high fatality rate. The only effective drug against this parasite is Praziquantel, which has significant side effects. Due to the lack of appropriate treatment options and the high death rate, there is a dire need to develop novel therapies against this pathogen. In this study, we designed a multi-epitope chimeric vaccine design against O. viverrini by using immunoinformatics approaches. Non-allergenic and immunogenic MHC-1, MHC-2, and B cell epitopes of three candidate proteins thioredoxin peroxidase (Ov-TPx-1), cathepsin F1 (Ov-CF-1) and calreticulin (Ov-CALR) of O. viverrini, were predicted to construct a potent multiepitope vaccine. The coverage of the HLA-alleles of these selected epitopes was determined globally. Four vaccine constructs made by different adjuvants and linkers were evaluated in the context of their physicochemical properties, antigenicity, and allergenicity. Protein-protein docking and MD simulation found that vaccines 3 was more stable and had a higher binding affinity for TLR2 and TLR4 immune receptors. In-silico restriction cloning of vaccine model led to the formation of plasmid constructs for expression in a suitable host. Finally, the immune simulation showed strong immunological reactions to the engineered vaccine. These findings suggest that the final vaccine construct has the potential to be validated by in vivo and in vitro experiments to confirm its efficacy against the CCA causing O. viverrini.

Discovery of a novel pyrido[1,2-a]thiazolo[5,4-d]pyrimidinone derivatives with excellent potency against acetylcholinesterase

As mimetic compounds of the natural alkaloid mackinazolinone, forty pyrido[1,2-a]thiazolo[5,4-d] pyrimidinone were designed and synthesized from a bioisosterism approach. The structure of these compounds was confirmed through analysis using 1H NMR, 13C NMR, and HRMS techniques. All the compounds were evaluated for their anticholinesterase activities and cytotoxicity on normal cells (293 T) by the Ellman method and methyl thiazolyl tetrazolium (MTT) method in vitro. and the structure-activity relationships (SARs) were summarized. The results showed that most of the compounds effectively inhibited acetylcholinesterase (AChE) in the micromolar range with weak cytotoxicity. Compound 7o exhibited the best inhibitory activity against AChE, displaying an IC50 values of 1.67 ± 0.09 µM and an inhibitory constant Ki of 11.31 µM as a competitive inhibitor to AChE. Molecular docking indicated that compound 7o may bind to AChE via hydrogen bond and π-π stacking. Further molecular dynamics (MD) simulations indicated a relatively low binding free energy (- 27.91 kJ·mol-1) of compound 7o with AChE. In summary, the collective findings suggested that 7o was promising as a potential novel drug candidate worthy of further investigation for the treatment of Alzheimer's disease.

Synthesis, computational docking and molecular dynamics studies of a new class of spiroquinoxalinopyrrolidine embedded chromanone hybrids as potent anti-cholinesterase agents

Novel structurally intriguing heterocycles embedded with spiropyrrolidine, quinoxaline and chromanone units were synthesized in good yields using a [Bmim]Br accelerated multicomponent reaction strategy. The key step of the reaction is 1,3-dipolar cycloaddition involving highly functionalized dipolarophile, viz. 3-benzylidenechroman-4-one, to afford spiroquinoxalinopyrrolidine embedded chromanone hybrid heterocycles. The formation of spiro products occurs via two C-C, two N-C and one C-N bonds possessing four adjoining stereogenic centers, two of which are spiro carbons. The newly synthesized spiro compounds showed potent acetylcholinesterase and butyrylcholinesterase inhibitory activities. Moreover, compounds with fluorine displayed the highest AChE (3.20 ± 0.16 μM) and BChE (18.14 ± 0.06 μM) inhibitory activities. Further, docking studies, followed by all-atom molecular dynamics, showed results that are consistent with in vitro experimental findings. Although docking scores for the synthesized derivatives were higher than those of the standard drug, MD MMPBSA results showed better binding of synthesized derivatives (-93.5 ± 11.9 kcal mol-1) compared to the standard drug galantamine (-66.2 ± 12.3 kcal mol-1) for AChE but exhibited similar values (-98.1 ± 11.2 and -97.9 ± 11.5 kcal mol-1) for BChE. These differences observed in drug binding with AChE/BChE are consistent with RMSD, RMSF, LIG plots, and FEL structural analysis. Taken together, these derivatives could be potential candidates as inhibitors of AChE and BChE.

Identification of Prospective Ebola Virus VP35 and VP40 Protein Inhibitors from Myxobacterial Natural Products

The Ebola virus (EBOV) is a lethal pathogen causing hemorrhagic fever syndrome which remains a global health challenge. In the EBOV, two multifunctional proteins, VP35 and VP40, have significant roles in replication, virion assembly, and budding from the cell and have been identified as druggable targets. In this study, we employed in silico methods comprising molecular docking, molecular dynamic simulations, and pharmacological properties to identify prospective drugs for inhibiting VP35 and VP40 proteins from the myxobacterial bioactive natural product repertoire. Cystobactamid 934-2, Cystobactamid 919-1, and Cittilin A bound firmly to VP35. Meanwhile, 2-Hydroxysorangiadenosine, Enhypyrazinone B, and Sorangiadenosine showed strong binding to the matrix protein VP40. Molecular dynamic simulations revealed that, among these compounds, Cystobactamid 919-1 and 2-Hydroxysorangiadenosine had stable interactions with their respective targets. Similarly, molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations indicated close-fitting receptor binding with VP35 or VP40. These two compounds also exhibited good pharmacological properties. In conclusion, we identified Cystobactamid 919-1 and 2-Hydroxysorangiadenosine as potential ligands for EBOV that target VP35 and VP40 proteins. These findings signify an essential step in vitro and in vivo to validate their potential for EBOV inhibition.

Identification of lead compound screened from the natural products atlas to treat renal inflammasomes using molecular docking and dynamics simulation

One of the most prevalent ailments is kidney disease. Effective therapies for chronic renal disease are hard to come by. As a result, there is significant clinical and social interest to predict and develop novel compounds to treat renal disorders. So, specific natural products have been employed in this study because they have protective effects against kidney diseases. When taken orally, natural products can help protect against or lessen the severity of the kidney damage caused by high fructose intake, a high-fat diet, and both Type I and Type 2 diabetes. Reduced podocyte injury, a contributor to albuminuria in diabetic nephropathy, reduces renal endothelial barrier function disruption due to hyperglycemia, as well as urinary microalbumin excretion and glomerular hyperfiltration. Multiple natural products have been shown to protect the kidneys from nephrotoxic chemicals such as LPS, gentamycin, alcohol, nicotine, lead, and cadmium, all of which can persuade acute kidney injury (AKI) or chronic kidney disease (CKD). Natural compounds inhibit regulatory enzymes for controlling inflammation-related diseases. For this, use computational methods such as drug design to identify novel flavonoid compounds against kidney diseases. Drug design via computational methods gaining admiration as a swift and effective technique to identify lead compounds in a shorter time at a low cost. In this in-silico study, we screened The Natural Product Atlas based on a structure-based pharmacophore query. Top hits were analyzed for ADMET analysis followed by molecular docking and docking validation. Finally, the lead compound was simulated for a period of 200 ns and trajectories were studied for stability. We found that NPA024823 showed promising binding and stability with the AIM2. This research work aims to predict novel anti-inflammatory compounds against kidney diseases to inhibit kidney inflammasome by targeting the AIM2 protein. So, in initial preclinical research, there will be lower failure rates that demonstrate safety profiles against predicted compounds.Communicated by Ramaswamy H. Sarma.

Potential molecular mechanisms of Huangqin Tang for liver cancer treatment by network pharmacology and molecular dynamics simulations

OBJECTIVE

This study aims to investigate the mechanism of Huangqin Tang in treating liver cancer.

METHODS

Active ingredients and corresponding targets of Huangqin Tang were obtained from the Traditional Chinese Medicine Systems Pharmacology Database. Differentially expressed genes in liver cancer were identified from mRNA expression data. A protein-protein interaction (PPI) network was constructed using differentially expressed genes and Huangqin Tang targets. Random walk with restart (RWR) analysis was performed on the PPI network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted. A drug-active ingredient-gene interaction network was established, and molecular docking and molecular dynamics simulations were performed. Finally, the stability of binding between CDK1 and oroxylin was tested according to cellular thermal shift assay (CETSA).

RESULTS

160 active ingredients, 239 targets, and 1093 differentially expressed genes were identified. RWR analysis identified 10 potential targets for liver cancer. Enrichment analysis revealed protein kinase regulator activity and Steroid hormone biosynthesis as significant pathways. Molecular docking suggested a stable complex between oroxylin A and CDK1. CETSA demonstrated that the combination of oroxylin A and CDK1 increased the stability of CDK1, and the combination efficiency was high.

CONCLUSION

Huangqin Tang may treat liver cancer by targeting CDK1 with oroxylin A. Protein kinase regulator activity and Steroid hormone biosynthesis pathways may play a role in liver cancer treatment with Huangqin Tang. This study provides insight into the mechanistic basis of Huangqin Tang for liver cancer treatment.

Phytoconstituents of Artemisia Annua as potential inhibitors of SARS CoV2 main protease: an in silico study

BACKGROUND

In November 2019, the world faced a pandemic called SARS-CoV-2, which became a major threat to humans and continues to be. To overcome this, many plants were explored to find a cure.

METHODS

Therefore, this research was planned to screen out the active constituents from Artemisia annua that can work against the viral main protease Mpro as this non-structural protein is responsible for the cleavage of replicating enzymes of the virus. Twenty-five biocompounds belonging to different classes namely alpha-pinene, beta-pinene, carvone, myrtenol, quinic acid, caffeic acid, quercetin, rutin, apigenin, chrysoplenetin, arteannunin b, artemisinin, scopoletin, scoparone, artemisinic acid, deoxyartemisnin, artemetin, casticin, sitogluside, beta-sitosterol, dihydroartemisinin, scopolin, artemether, artemotil, artesunate were selected. Virtual screening of these ligands was carried out against drug target Mpro by CB dock.

RESULTS

Quercetin, rutin, casticin, chrysoplenetin, apigenin, artemetin, artesunate, sopolin and sito-gluside were found as hit compounds. Further, ADMET screening was conducted which represented Chrysoplenetin as a lead compound. Azithromycin was used as a standard drug. The interactions were studied by PyMol and visualized in LigPlot. Furthermore, the RMSD graph shows fluctuations at various points at the start of simulation in Top1 (Azithromycin) complex system due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points resulting in increased RMSD with a time frame of 50 ns. But this change remains stable after the extension of simulation time intervals till 100 ns. On other side, the Top2 complex system remains highly stable throughout the time scale. No such structural dynamics were observed bu the ligand attached to the active site residues binds strongly.

CONCLUSION

This study facilitates researchers to develop and discover more effective and specific therapeutic agents against SARS-CoV-2 and other viral infections. Finally, chrysoplenetin was identified as a more potent drug candidate to act against the viral main protease, which in the future can be helpful.

Decrypting the multi-genome data for chimeric vaccine designing against the antibiotic resistant Yersinia pestis

Yersinia pestis, the causative agent of plague, is a gram-negative bacterium that can be fatal if not treated properly. Three types of plague are currently known: bubonic, septicemic, and pneumonic plague, among which the fatality rate of septicemic and pneumonic plague is very high. Bubonic plague can be treated, but only if antibiotics are used at the initial stage of the infection. But unfortunately, Y. pestis has also shown resistance to certain antibiotics such as kanamycin, minocycline, tetracycline, streptomycin, sulfonamides, spectinomycin, and chloramphenicol. Despite tremendous progress in vaccine development against Y. pestis, there is no proper FDA-approved vaccine available to protect people from its infections. Therefore, effective broad-spectrum vaccine development against Y. pestis is indispensable. In this study, vaccinomics-assisted immunoinformatics techniques were used to find possible vaccine candidates by utilizing the core proteome prepared from 58 complete genomes of Y. pestis. Human non-homologous, pathogen-essential, virulent, and extracellular and membrane proteins are potential vaccine targets. Two antigenic proteins were prioritized for the prediction of lead epitopes by utilizing reverse vaccinology approaches. Four vaccine designs were formulated using the selected B- and T-cell epitopes coupled with appropriate linkers and adjuvant sequences capable of inducing potent immune responses. The HLA allele population coverage of the T-cell epitopes selected for vaccine construction was also analyzed. The V2 constructs were top-ranked and selected for further analysis on the basis of immunological, physicochemical, and immune-receptor docking interactions and scores. Docking and molecular dynamic simulations confirmed the stability of construct V2 interactions with the host immune receptors. Immune simulation analysis anticipated the strong immune profile of the prioritized construct. In silico restriction cloning ensured the feasible cloning ability of the V2 construct in the expression system of E. coli strain K12. It is anticipated that the designed vaccine construct may be safe, effective, and able to elicit strong immune responses against Y. pestis infections and may, therefore, merit investigation using in vitro and in vivo assays.

Enumeration of olive derived lignan, pinoresinol for activity against recent Omicron variant spike protein for structure-based drug design, DFT, molecular dynamics simulations, and MMGBSA studies

The coronavirus disease 2019 (COVID-19) was first found in Wuhan, China, in December 2019. Because the virus spreads quickly, it quickly became a global worry. Coronaviridae is the family that contains both SARS-CoV-2 and the viruses that came before (i.e., MERS-CoV and SARS-CoV). Recent sources portray that the COVID-19 virus has affected 344,710,576 people worldwide and killed about 5,598,511 people in the last 2 years. The B.1.1.529 strain, later called "Omicron," was named a Variant of Concern on November 24, 2021. The SARS-CoV-2 virus has gone through a never-ending chain of changes that have never happened before. As a result, it has many different traits. Most of these changes have occurred in the spike protein, where antibodies bind. Because of these changes, the Omicron type is very contagious and easy to pass on. There have been a lot of studies done to try to figure out this new challenge in the COVID-19 strains race, but there is still a lot that needs to be explained. This study focuses on virtual screening, docking, and molecular dynamic analysis; we aimed to identify therapeutic candidates for the SARS-CoV-2 variant Omicron based on their ability to inhibit non-structural proteins. We investigate the prediction of the properties of a substantial database of drug molecules obtained from the OliveNet™ database. Compounds that did not exhibit adequate gastrointestinal absorption and failed the Lipinski test are not considered for further research. The filtered compounds were coupled with our primary target, SARS-CoV-2 Omicron spike protein. We focused on SARS-CoV-2 Omicron spike protein and filtering potent olive compounds. Pinoresinol, the most likely candidate, is bound best (- 8.5 kcal/mol). Pinoresinol's strong interaction with the active site made the complex's dynamic structure more resilient. MD simulations explain the protein-ligand complex's stability and function. Pinoresinol may be a promising SARS-CoV-2 Omicron spike protein receptor lead drug, and additional research may assist the scientific community.

Synaptic vesicle protein 2A mitigates parthanatos via apoptosis-inducing factor in a rat model of pharmacoresistant epilepsy

AIMS

Synaptic vesicle protein 2A (SV2A) is a unique therapeutic target for pharmacoresistant epilepsy (PRE). As seizure-induced neuronal programmed death, parthanatos was rarely reported in PRE. Apoptosis-inducing factor (AIF), which has been implicated in parthanatos, shares a common cytoprotective function with SV2A. We aimed to investigate whether parthanatos participates in PRE and is mitigated by SV2A via AIF.

METHODS

An intraperitoneal injection of lithium chloride-pilocarpine was used to establish an epileptic rat model, and phenytoin and phenobarbital sodium were utilized to select PRE and pharmacosensitive rats. The expression of SV2A was manipulated via lentivirus delivery into the hippocampus. Video surveillance was used to assess epileptic ethology. Biochemical tests were employed to test hippocampal tissues following a successful SV2A infection. Molecular dynamic calculations were used to simulate the interaction between SV2A and AIF.

RESULTS

Parthanatos core index, PARP1, PAR, nuclear AIF and MIF, γ-H2AX, and TUNEL staining were all increased in PRE. SV2A is bound to AIF to form a stable complex, successfully inhibiting AIF and MIF nuclear translocation and parthanatos and consequently mitigating spontaneous recurrent seizures in PRE. Moreover, parthanatos deteriorated after the SV2A reduction.

SIGNIFICANCE

SV2A protected hippocampal neurons and mitigated epileptic seizures by inhibiting parthanatos via binding to AIF in PRE.

Computational analysis of sodium-dependent phosphate transporter SLC20A1/PiT1 gene identifies missense variations C573F, and T58A as high-risk deleterious SNPs

SLC20A1/PiT1 is a sodium-dependent inorganic phosphate transporter, initially recognized as the retroviral receptor for Gibbon Ape Leukemia Virus in humans. SNPs in SLC20A1 is associated with Combined Pituitary Hormone Deficiency and Sodium Lithium Counter transport. Using in silico techniques, we have screened the nsSNPs for their deleterious effect on the structure and function of SLC20A1. Screening with sequence and structure-based tools on 430 nsSNPs, filtered 17 nsSNPs which are deleterious. To evaluate the role of these SNPs, protein modeling and MD simulations were performed. A comparative analysis of model generated with SWISS-MODEL and AlphaFold shows that many residues are in the disallowed region of Ramachandran plot. Since SWISS-MODEL structure has a 25-residue deletion, the AlphaFold structure was used to perform MD simulation for equilibration and structure refinement. Further, to understand perturbation of energetics, we performed in silico mutagenesis and ΔΔG calculation using FoldX on MD refined structures, which yielded SNPs that are neutral (3), destabilizing (12) and stabilizing (2) on protein structure. Furthermore, to elucidate the impact of SNPs on structure, we performed MD simulations to discern the changes in RMSD, Rg, RMSF and LigPlot of interacting residues. RMSF profiles of representative SNPs revealed that A114V (neutral) and T58A (positive) were more flexible & C573F (negative) was more rigid compared to wild type, which is also reflected in the changes in number of local interacting residues in LigPlot and ΔΔG. Taken together, our results show that SNPs can lead to structural perturbations and impact the function of SLC20A1 with potential implications for disease.Communicated by Ramaswamy H. Sarma.

Potential Inhibitors of Lumpy Skin Disease's Viral Protein (DNA Polymerase): A Combination of Bioinformatics Approaches

Lumpy skin disease (LSD), caused by a virus within the Poxviridae family and Capripoxvirus genus, induces nodular skin lesions in cattle. This spreads through direct contact and insect vectors, significantly affecting global cattle farming. Despite the availability of vaccines, their efficacy is limited by poor prophylaxis and adverse effects. Our study aimed to identify the potential inhibitors targeting the LSDV-encoded DNA polymerase protein (gene LSDV039) for further investigation through comprehensive analysis and computational methods. Virtual screening revealed rhein and taxifolin as being potent binders among 380 phytocompounds, with respective affinities of -8.97 and -7.20 kcal/mol. Canagliflozin and tepotinib exhibited strong affinities (-9.86 and -8.86 kcal/mol) among 718 FDA-approved antiviral drugs. Simulating the molecular dynamics of canagliflozin, tepotinib, rhein, and taxifolin highlighted taxifolin's superior stability and binding energy. Rhein displayed compactness in RMSD and RMSF, but fluctuated in Rg and SASA, while canagliflozin demonstrated stability compared to tepotinib. This study highlights the promising potential of using repurposed drugs and phytocompounds as potential LSD therapeutics. However, extensive validation through in vitro and in vivo testing and clinical trials is crucial for their practical application.

Analyzing molecular signatures in preeclampsia and fetal growth restriction: Identifying key genes, pathways, and therapeutic targets for preterm birth

Background

Intrauterine growth restriction (IUGR) and preeclampsia (PE) are intricately linked with specific maternal health conditions, exhibit shared placental abnormalities, and play pivotal roles in precipitating preterm birth (PTB) incidences. However, the molecular mechanism underlying the association between PE and IUGR has not been determined. Therefore, we aimed to analyze the data of females with PE and those with PE + IUGR to identify the key gene(s), their molecular pathways, and potential therapeutic interactions.

Methods

In this study, a comprehensive relationship analysis of both PE and PE + IUGR was conducted using RNA sequence datasets. Using two datasets (GSE148241 and GSE114691), differential gene expression analysis via DESeq2 through R-programming was performed. Gene set enrichment analysis was performed using ClusterProfiler, protein‒protein interaction (PPI) networks were constructed, and cluster analyses were conducted using String and MCODE in Cytoscape. Functional enrichment analyses of the resulting subnetworks were performed using ClueGO software. The hub genes were identified under both conditions using the CytoHubba method. Finally, the most common hub protein was docked against a library of bioactive flavonoids and PTB drugs using the PyRx AutoDock tool, followed by molecular dynamic (MD) simulation analysis. Pharmacokinetic analysis was performed to determine the ADMET properties of the compounds using pkCSM.

Results

We identified eight hub genes highly expressed in the case of PE, namely, PTGS2, ENG, KIT, MME, CGA, GAPDH, GPX3, and P4HA1, and the network of the PE + IUGR gene set demonstrated that nine hub genes were overexpressed, namely, PTGS2, FGF7, FGF10, IL10, SPP1, MPO, THBS1, CYBB, and PF4. PTGS2 was the most common hub gene found under both conditions (PE and PEIUGR). Moreover, the greater (-9.1 kcal/mol) molecular binding of flavoxate to PTGS2 was found to have satisfactory pharmacokinetic properties compared with those of other compounds. The flavoxate-bound PTGS2 protein complex remained stable throughout the simulation; with a ligand fit to protein, i.e., a RMSD ranging from ∼2.0 to 4.0 Å and a RMSF ranging from ∼0.5 to 2.9 Å, was observed throughout the 100 ns analysis.

Conclusion

The findings of this study may be useful for treating PE and IUGR in the management of PTB.

Biomimetic MDSCs membrane coated black phosphorus nanosheets system for photothermal therapy/photodynamic therapy synergized chemotherapy of cancer

Photothermal therapy is favored by cancer researchers due to its advantages such as controllable initiation, direct killing and immune promotion. However, the low enrichment efficiency of photosensitizer in tumor site and the limited effect of single use limits the further development of photothermal therapy. Herein, a photo-responsive multifunctional nanosystem was designed for cancer therapy, in which myeloid-derived suppressor cell (MDSC) membrane vesicle encapsulated decitabine-loaded black phosphorous (BP) nanosheets (BP@ Decitabine @MDSCs, named BDM). The BDM demonstrated excellent biosafety and biochemical characteristics, providing a suitable microenvironment for cancer cell killing. First, the BDM achieves the ability to be highly enriched at tumor sites by inheriting the ability of MDSCs to actively target tumor microenvironment. And then, BP nanosheets achieves hyperthermia and induces mitochondrial damage by its photothermal and photodynamic properties, which enhancing anti-tumor immunity mediated by immunogenic cell death (ICD). Meanwhile, intra-tumoral release of decitabine induced G2/M cell cycle arrest, further promoting tumor cell apoptosis. In vivo, the BMD showed significant inhibition of tumor growth with down-regulation of PCNA expression and increased expression of high mobility group B1 (HMGB1), calreticulin (CRT) and caspase 3. Flow cytometry revealed significantly decreased infiltration of MDSCs and M2-macrophages along with an increased proportion of CD4+, CD8+ T cells as well as CD103+ DCs, suggesting a potentiated anti-tumor immune response. In summary, BDM realizes photothermal therapy/photodynamic therapy synergized chemotherapy for cancer.