ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties

Investigation of in silico studies for cytochrome P450 isoforms specificity

Cytochrome P450 (CYP450) enzymes comprise a highly diverse superfamily of heme-thiolate proteins that responsible for catalyzing over 90 % of enzymatic reactions associated with xenobiotic metabolism in humans. Accurately predicting whether chemicals are substrates or inhibitors of different CYP450 isoforms can aid in pre-selecting hit compounds for the drug discovery process, chemical toxicology studies, and patients treatment planning. In this work, we investigated in silico studies on CYP450s specificity over past twenty years, categorizing these studies into structure-based and ligand-based approaches. Subsequently, we utilized 100 of the most frequently prescribed drugs to test eleven machine learning-based prediction models which were published between 2015 and 2024. We analyzed various aspects of the evaluated models, such as their datasets, algorithms, and performance. This will give readers with a comprehensive overview of these prediction models and help them choose the most suitable one to do prediction. We also provide our insights for future research trend in both structure-based and ligand-based approaches in this field.

Targeting bacterial growth in biofilm conditions: rational design of novel inhibitors to mitigate clinical and food contamination using QSAR

Antimicrobial resistance (AMR) is a pressing global issue exacerbated by the abuse of antibiotics and the formation of bacterial biofilms, which cause up to 80% of human bacterial infections. This study presents a computational strategy to address AMR by developing three novel quantitative structure-activity relationship (QSAR) models based on molecular topology to identify potential anti-biofilm and antibacterial agents. The models aim to determine the chemo-topological pattern of Gram (+) antibacterial, Gram (-) antibacterial, and biofilm formation inhibition activity. The models were applied to the virtual screening of a commercial chemical database, resulting in the selection of 58 compounds. Subsequent in vitro assays showed that three of these compounds exhibited the most promising antibacterial activity, with potential applications in enhancing food and medical device safety.

Novel NO-TZDs and trimethoxychalcone-based DHPMs: design, synthesis, and biological evaluation as potential VEGFR-2 inhibitors

Novel series of nitric oxide-releasing thiazolidine-2,4-diones (NO-TZD-3a-d,5,6) and 3,4,5-trimethoxychalcone-based multifunctional 1,4-dihydropyrimidines (CDHPM-10a-g) have been designed and synthesised as potent broad-spectrum anticancer agents with potential VEGFR-2 inhibition. The designed analogs were evaluated for their anticancer activities towards a full panel of NCI-60 tumour cell lines and CDHPM-10a-g emerged mean %inhibitions ranging from 76.40 to 147.69%. Among them, CDHPM-10e and CDHPM-10f demonstrated the highest MGI% of 147.69 and 140.24%, respectively. Compounds CDHPM-10a,b,d-f showed higher mean %inhibitory activity than the reference drug sorafenib (MGI% = 105.46%). Superiorly, the hybrid CDHPM-10e displayed the highest potencies towards all the herein tested subpanels of nine types of cancer with MGI50 of 1.83 µM. Also, it revealed potent cytostatic single-digit micromolar activity towards the herein examined cancer cell lines. The designed compounds CDHPM-10a-g were exposed as potent non-selective broad-spectrum anticancer agents over all NCI subpanels with an SI range of 0.66-1.97. In addition, the target analog CDHPM-10e revealed potency towards VEGFR-2 kinase comparable to that of sorafenib with a sub-micromolar IC50 value of 0.11 µM. Also, CDHPM-10e could effectively induce Sub-G1-phase arrest and prompt apoptosis via caspase and p53-dependent mechanisms. Furthermore, CDHPM-10e revealed significant anti-metastatic activity as detected by wound healing assay. The modelling study implies that CDHPM-10e overlaid well with sorafenib and formed a strong H-bond in the DFG binding domain. The ADMET studies hinted out that CDHPM-10e met Pfizer's drug-likeness criteria. The presented novel potent anticancer agent merits further devotion as a new lead product in developing more chalcone-based VEGFR-2 inhibitors.

Comprehensive applications of the artificial intelligence technology in new drug research and development

Purpose

Target-based strategy is a prevalent means of drug research and development (R&D), since targets provide effector molecules of drug action and offer the foundation of pharmacological investigation. Recently, the artificial intelligence (AI) technology has been utilized in various stages of drug R&D, where AI-assisted experimental methods show higher efficiency than sole experimental ones. It is a critical need to give a comprehensive review of AI applications in drug R &D for biopharmaceutical field.

Methods

Relevant literatures about AI-assisted drug R&D were collected from the public databases (Including Google Scholar, Web of Science, PubMed, IEEE Xplore Digital Library, Springer, and ScienceDirect) through a keyword searching strategy with the following terms [("Artificial Intelligence" OR "Knowledge Graph" OR "Machine Learning") AND ("Drug Target Identification" OR "New Drug Development")].

Results

In this review, we first introduced common strategies and novel trends of drug R&D, followed by characteristic description of AI algorithms widely used in drug R&D. Subsequently, we depicted detailed applications of AI algorithms in target identification, lead compound identification and optimization, drug repurposing, and drug analytical platform construction. Finally, we discussed the challenges and prospects of AI-assisted methods for drug discovery.

Conclusion

Collectively, this review provides comprehensive overview of AI applications in drug R&D and presents future perspectives for biopharmaceutical field, which may promote the development of drug industry.

Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine

Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.

Molecular designing of potential environmentally friendly PFAS based on deep learning and generative models

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are widely used across a spectrum of industrial and consumer goods. Nonetheless, their persistent nature and tendency to accumulate in biological systems pose substantial environmental and health threats. Consequently, striking a balance between maximizing product efficiency and minimizing environmental and health risks by tailoring the molecular structure of PFAS has become a pivotal challenge in the fields of environmental chemistry and sustainable development. To address this issue, a computational workflow was proposed for designing an environmentally friendly PFAS by incorporating deep learning (DL) and molecular generative models. The hybrid DL architecture MolHGT+ based on heterogeneous graph neural network with transformer-like attention was applied to predict the surface tension, bioaccumulation, and hepatotoxicity of the molecules. Through virtual screening of the PFAS master database using MolHGT+, the findings indicate that incorporating the siloxane group and betaine fragment can effectively decrease both the bioaccumulation and hepatotoxicity of PFAS while preserving low surface tension. In addition, molecular generative models were employed to create a structurally diverse pool of novel PFASs with the aforementioned hit molecules serving as the initial template structures. Overall, our study presents a promising AI-driven method for advancing the development of environmentally friendly PFAS.

Combination of biotransformation and metabolomics reveals tolfenpyrad-induced hepatocytotoxicity

Tolfenpyrad (TFP) is an extensively used pesticide that inevitably leads to human exposure to both TFP and its transformation product residues. However, the biotransformation of TFP in humans has not been elucidated, and the toxicity of TFP along with its biotransformation products remains largely unknown. In this study, the biotransformation process of TFP was investigated using human liver microsomes and human hepatic cells. Endogenous metabolic changes in the cells were studied to investigate the hepatocytotoxicity of TFP at environmentally relevant concentrations. Fourteen phase I biotransformation products and four phase II TFP products were characterized, among which twelve products were identified for the first time. The oxidative product tolfenpyrad-benzoic acid (PT-CA) was particularly abundant and stable. Further hepatotoxicity assessments and metabolic studies demonstrated comparable metabolic profiles for TFP and PT-CA in HepG2 cells, with both significantly disrupting purine and glutathione metabolism. These processes are closely associated with oxidative stress, mitochondrial damage, and cell death. Our results provide novel perspectives on the biotransformation, metabolism, and hepatotoxicity of TFP, thereby highlighting the non-negligible toxicity of its crucial biotransformation product PT-CA in environmental risk assessments.

Exploring the pharmacological mechanisms of the flower of Rhododendron molle in rheumatoid arthritis rats based on metabolomics integrated network pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

As a traditional Chinese medicine, the flower of Rhododendron molle G. Don (RMF) is record in the Chinese pharmacopoeia, and is commonly utilized for treating rheumatoid arthritis (RA) in clinical practice. However, its precise mechanisms necessitate further exploration.

AIM OF THE STUDY

To expound the effective components, targets, metabolites, and pathways participated in RMF's anti-RA effects by metabolomics integrated network pharmacology.

MATERIALS AND METHODS

CIA rats were intragastric administered RMF for 2 weeks, following which the therapeutic effects were comprehensively evaluated. Serum metabolomics was adopted to investigate the differential metabolites (DEMs). UHPLC-Q-Exactive-MS method was applied to identify the components of RMF, and then network pharmacology was utilize to select the component-RA-targets. Molecular docking and Western blotting were utilized to validate the key targets.

RESULTS

RA symptoms were alleviated by RMF through the inhibition secretion of pro-inflammatory factors IL-1β, IL-6 and TNF-α, along with relief in bone destruction observed in CIA rats. Four targets, namely AKR1B1, TPH1, CYP1A1, and CYP1A2, were identified, along with their corresponding metabolites, namely D-glucose, D-mannose, L-tryptophan, 11-deoxycorticosterone, and 17α-hydroxyprogesterone. These were found to be involved in three key metabolic pathways: steroid hormone biosynthesis, tryptophan metabolism, and galactose metabolism. Additionally, five significant anti-RA active components were identified from RMF, including Rhodojaponin (Rj)-Ⅱ, Rj-Ⅲ, Rj-Ⅴ, Rj-Ⅵ, and quercetin.

CONCLUSIONS

The anti-RA mechanisms of RMF were investigated in this study, focusing on active components, upstream targets, and downstream metabolites. These findings lay a foundation for the clinical practice and drug development of RMF.

Design, synthesis and structure-activity relationship of novel 2-pyrimidinylindole derivatives as orally available anti-obesity agents

Due to the emerging global epidemic of obesity, developing safe and effective agents for anti-obesity is urgently needed. Our previous study found that 2-pyrimidinylindole derivative Wd3d exhibited potential anti-obesity activity. Herein, to further optimize the potential moiety, structural modifications were proceeded for two rounds in this study. Firstly, we designed, synthesized, and evaluated 36 new derivatives of 2-pyrimidinylindole scaffold with different substituents on the indole ring and pyrimidine ring to investigate their structure-activity relationship (SAR). Then, analogs with potent activity had the aldehyde group replaced with the acylhydrazone group to reduce cytotoxicity and improve metabolic stability. Detailed SAR studies and animal evaluation experiments led to the discovery of the compound 9ga, which significantly reduced TG accumulation with an EC50 value of 0.07 μM and showed relatively low cytotoxicity with an IC50 value of around 24 μM. Oral administration of 9ga effectively prevented the excessive growth of body weight and lessened fat mass as well as liver mass, decreased lipid accumulation in the liver and blood, and improved the heart injury parameter in the diet-induced obesity mouse model significantly better than Wd3d. A mechanism study showed that 9ga regulated the lipid metabolism during early adipogenesis by inhibiting PPARγ pathway. In conclusion, our study further highlights the anti-obesity potential of 2-pyrimidinylindole derivatives in diet-induced obesity.

The potential of Chlorella spp. as antiviral source against African swine fever virus through a virtual screening pipeline

African swine fever (ASF) causes high mortality in pigs and threatens global swine production. There is still a lack of therapeutics available, with two vaccines under scrutiny and no approved small-molecule drugs. Eleven (11) viral proteins were used to identify potential antivirals in in silico screening of secondary metabolites (127) from Chlorella spp. The metabolites were screened for affinity and binding selectivity. High-scoring compounds were assessed through in silico ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) predictions, compared to structurally similar drugs, and checked for off-target docking with prepared swine receptors. Molecular dynamics (MD) simulations determined binding stability while binding energy was measured in Molecular Mechanics - Generalized Born Surface Area (MMGBSA) or Poisson-Boltzmann Surface Area (MMPBSA). Only six (6) compounds passed until MD analyses, of which five (5) were stable after 100 ns of MD runs. Of these five compounds, only three had binding affinities that were comparable to or stronger than controls. Specifically, phytosterols 24,25-dihydrolanosterol and CID 4206521 that interact with the RNA capping enzyme (pNP868R), and ergosterol which bound to the Erv-like thioreductase (pB119L). The compounds identified in this study can be used as a theoretical basis for in vitro screening to develop potent antiviral drugs against ASFV.

Vanilla from Brazilian Atlantic Forest: In vitro and in silico toxicity assessment and high-resolution metabolomic analysis of Vanilla spp. ethanolic extracts

The natural vanilla market, which generates millions annually, is predominantly dependent on Vanilla planifolia, a species characterized by low genetic variability and susceptibility to pathogens. There is an increasing demand for natural vanilla, prized for its complex, authentic, and superior quality compared to artificial counterparts. Therefore, there is a necessity for innovative production alternatives to ensure a consistent and stable supply of vanilla flavors. In this context, vanilla crop wild relatives (WRs) emerge as promising natural sources of the spice. However, these novel species must undergo toxicity assessments to evaluate potential risks and ensure safety for consumption. This study aimed to assess the non-mutagenic and non-carcinogenic properties of ethanolic extracts from V. bahiana, V. chamissonis, V. cribbiana, and V. planifolia through integrated metabolomic profiling, in vitro toxicity assays, and in silico analyses. The integrated approach of metabolomics, in vitro assays, and in silico analyses has highlighted the need for further safety assessments of Vanilla cribbiana ethanolic extract. While the extracts of V. bahiana, V. chamissonis, and V. planifolia generally demonstrated non-mutagenic properties in the Ames assay, V. cribbiana exhibited mutagenicity at high concentrations (5000 μg/plate) in the TA98 strain without metabolic activation. This finding, coupled with the dose-dependent cytotoxicity observed in WST-1 (Water Soluble Tetrazolium) assays, a colorimetric method that assesses the viability of cells exposed to a test substance, underscores the importance of concentration in the safety evaluation of these extracts. Kaempferol and pyrogallol, identified with higher intensity in V. cribbiana, are potential candidates for in vitro mutagenicity. Although the results are not conclusive, they suggest the safety of these extracts at low concentrations. This study emphasizes the value of an integrated approach in providing a nuanced understanding of the safety profiles of natural products, advocating for cautious use and further research into V. cribbiana mutagenicity.

Human next-generation risk assessment of trichothecene toxicity

Trichothecenes are naturally occurring chemicals, produced by fungi, that can be found in contaminated crops. Trichothecenes have the potential to indirectly damage DNA and exacerbate genotoxic effects of genotoxicants. However, genotoxicity data for most trichothecenes are limited and data gaps remain. Here we use the γH2AX/pH3 assay to evaluate DNA damage in vitro of 13 trichothecenes. Three human cell lines (SH-SY5Y, ACHN, and HepG2) were exposed to each trichothecene (0.001-100 μM) to assess toxicity as models for the brain, kidney, and liver, respectively. Concentration-dependent induction of DNA damage, illustrated by γH2AX induction, was observed for all trichothecenes. In vitro-in vivo extrapolation (IVIVE) modeling was employed to support in vivo equivalent potency ranking and screen for risk potential. Diacetoxyscirpenol, T-2, and HT-2 had the highest genotoxic potency, notably in SH-SY5Y cells. Administered equivalent doses (AEDs) derived from IVIVE were compared against exposure data from French total diet studies to assess risk potential. AEDs derived for T-2 and HT-2 from the SH-SY5Y model were within 100-fold of exposure levels for infants aged one year or less. Overall, the potential for trichothecenes to damage DNA and higher exposures in infants highlights the need to investigate the cumulative effects across the broader trichothecene family.

Unlocking the potential of higher-molecular-weight 5-HT7R ligands: Synthesis, affinity, and ADMET examination

An increasing number of drugs introduced to the market and numerous repositories of compounds with confirmed activity have posed the need to revalidate the state-of-the-art rules that determine the ranges of properties the compounds should possess to become future drugs. In this study, we designed a series of two chemotypes of aryl-piperazine hydantoin ligands of 5-HT7R, an attractive target in search for innovative CNS drugs, with higher molecular weight (close to or over 500). Consequently, 14 new compounds were synthesised and screened for their receptor activity accompanied by extensive docking studies to evaluate the observed structure-activity/properties relationships. The ADMET characterisation in terms of the biological membrane permeability, metabolic stability, hepatotoxicity, cardiotoxicity, and protein plasma binding of the obtained compounds was carried out in vitro. The outcome of these studies constituted the basis for the comprehensive challenge of computational tools for ADMET properties prediction. All the compounds possessed high affinity to the 5-HT7R (Ki below 250 nM for all analysed structures) with good selectivity over 5-HT6R and varying affinity towards 5-HT2AR, 5-HT1AR and D2R. For the best compounds of this study, the expression profile of genes associated with neurodegeneration, anti-oxidant response and anti-inflammatory function was determined, and the survival of the cells (SH-SY5Y as an in vitro model of Alzheimer's disease) was evaluated. One 5-HT7R agent (32) was characterised by a very promising ADMET profile, i.e. good membrane permeability, low hepatotoxicity and cardiotoxicity, and high metabolic stability with the simultaneous high rate of plasma protein binding and high selectivity over other GPCRs considered, together with satisfying gene expression profile modulations and neural cell survival. Such encouraging properties make it a good candidate for further testing and optimisation as a potential agent in the treatment of CNS-related disorders.

Research trends of computational toxicology: a bibliometric analysis

BACKGROUND

Computational toxicology utilizes computer models and simulations to predict the toxicity of chemicals. Bibliometric studies evaluate the impact of scientific research in a specific field.

METHODS

A bibliometric analysis of the computational methods used in toxicity assessment was conducted on the Web of Science between 1977 and 2024 February 12.

RESULTS

Findings of this study showed that computational toxicology has evolved considerably over the years, moving towards more advanced computational methods, including machine learning, molecular docking, and deep learning. Artificial intelligence significantly enhances computational toxicology research by improving the accuracy and efficiency of toxicity predictions.

CONCLUSION

Generally, the study highlighted a significant rise in research output in computational toxicology, with a growing interest in advanced methods and a notable focus on refining predictive models to optimize drug properties using tools like pkCSM for more precise predictions.

Combined structure-based virtual screening and machine learning approach for the identification of potential dual inhibitors of ACC and DGAT2

Acetyl-coenzyme A carboxylase (ACC) and diacylglycerol acyltransferase 2 (DGAT2) are recognized as potential therapeutic targets for nonalcoholic fatty liver disease (NAFLD). Inhibitors targeting ACC and DGAT2 have exhibited the capacity to reduce hepatic fat in individuals afflicted with NAFLD. However, there are no reports of dual inhibitors targeting ACC and DGAT2 for the treatment of NAFLD. Here, we aimed to identify potential dual inhibitors of ACC and DGAT2 using an integrated in silico approach. Machine learning-based virtual screening of commercial molecule databases yielded 395,729 hits, which were subsequently subjected to molecular docking aimed at both the ACC and DGAT2 binding sites. Based on the docking scores, nine compounds exhibited robust interactions with critical residues of both ACC and DGAT2, displaying favorable drug-like features. Molecular dynamics simulations (MDs) unveiled the substantial impact of these compounds on the conformational dynamics of the proteins. Furthermore, binding free energy assessments highlighted the notable binding affinities of specific compounds (V003-8107, G340-0503, Y200-1700, E999-1199, V003-6429, V025-4981, V006-1474, V025-0499, and V021-8916) to ACC and DGAT2. The compounds proposed in this study, identified using a multifaceted computational strategy, warrant experimental validation as potential dual inhibitors of ACC and DGAT2, with implications for the future development of novel drugs targeting NAFLD.

High-throughput virtual screening of Streptomyces spp. metabolites as antiviral inhibitors against the Nipah virus matrix protein

Nipah virus (NiV) remains a significant global concern due to its impact on both the agricultural industry and human health, resulting in substantial economic and health consequences. Currently, there is no cure or commercially available vaccine for the virus. Therefore, it is crucial to prioritize the discovery of new and effective treatment options to prevent its continued spread. Streptomyces spp. are rich sources of metabolites known for their bioactivity against certain diseases; however, their potential as antiviral drugs against the Nipah virus remain unexplored. In this study, 6524 Streptomyces spp. metabolites were screened through in silico methods for their inhibitory effects against the Nipah virus matrix (NiV-M) protein, which assists in virion assembly of Nipah virus. Different computer-aided tools were utilized to carry out the virtual screening process: ADMET profiling revealed 913 compounds with excellent safety and efficacy profiles, molecular docking predicted the binding poses and associated docking scores of the ligands in their respective targets, MD simulations confirmed the binding stability of the top ten highest-scoring ligands in a 100 ns all-atom simulation, PCA elucidated simulation convergence, and MMPB(GB)SA calculations estimated the binding energies of the final candidate compounds and determined the key residues crucial for complex formation. Using in silico methods, we identified six metabolites targeting the main substrate-binding site and five targeting the dimerization site that exhibited excellent stability and strong binding affinity. We recommend testing these compounds in the next stages of drug development to confirm their effectiveness as therapeutic agents against Nipah virus.

Drug designing and toxicity screening of halogen and nitrogen-augmented catechin in sarcopenic obesity

In this study, the catechin structure was modified with Halogen and Nitrogen base at C-6 and C-8 Positions in Ring A. Pharmacokinetic parameters affirm the drug-likeness property of the designed compounds. Molecular Docking was performed for all the compounds towards the myostatin inhibition target (PDB: 3HH2). Such desirable quality of modified Catechin will create a spark in the novel drug discovery using acting as a bioenhancer. As a result, the present research is aimed to offer an overview of the structural simulation of Cl, F, I, NH2, NO2, and Br at C-6 and C-8 positions in A Ring A of Catechin. This preliminary evidence creates an impact on the novelsemi0synthetic drug discovery for the therapeutic management of sarcopenia.

Uncovering the antidiabetic potential of heart-friendly and diuretic bioactive compounds through computer-based drug design

Avicenna, a pioneer of modern medicine, recommended diuretic therapy to treat diabetes. Like Avicenna's approach, current medicine frequently prescribes oral antidiabetic pills with diuretic and hypoglycemic effects by blocking the absorption of sodium and glucose. To this end, the paper sought natural compounds with potential antidiabetic, cardioprotective, and diuretic properties through computer-based drug design (CADD) techniques, targeting the inhibition of SGLT2 proteins. We identified several bioactive compounds from various sources exhibiting potential multifunctionality through high-throughput virtual screening (HTVS) of vast compound libraries. Subsequent molecular docking and dynamics simulations were employed to assess these compounds' binding efficacy and stability with their respective targets, alongside ADMET prediction, to evaluate their pharmacokinetic and safety profiles. The top hits, phenylalanyltryptophan, tyrosyl-tryptophan, tyrosyl-tyrosine, celecoxib, and DIBOA trihexose, had superior docking scores ranging from -11,4 to -9,8 kcal/mol. The molecular dynamics simulations displayed steady interactions between target proteins and biocompounds throughout 100 ns without significant conformational shifts. These findings lay the groundwork for lead optimization and preclinical testing. This meticulous process ensures the safety and efficacy of potential treatments, marking a meaningful step toward developing innovative treatments for managing diabetes and its associated health complications.

Exploring antiviral activity of Betanin and Glycine Betaine against dengue virus type-2 in transfected Hela cells

Dengue virus (DENV) infection is a worldwide public health concern infecting approximately 400 million individuals and about 40,000 mortalities yearly. Despite this, no licensed or readily available antiviral medication is currently available specifically for DENV infection, and therapy is typically symptomatic. Therefore, the objective of the study was to investigate the antiviral activity of Beta vulgaris L. phytoconstituents against DENV-2 targeting NS3 protein. The antiviral activity of phytochemicals was examined through virtual ligand-based screening, antiviral inhibition and dosage response assays, western blotting analysis and MD simulations. We conducted toxicological, and pharmacokinetic analysis to assess plant-based natural compound's efficacy, safety, and non-toxic doses. Molecular docking and MD simulation results revealed that the nonstructural protein-3 (NS3) might prove as a funamental target for Betanin and Glycine Betaine against Dengue virus. Betanin and Glycine betaine were initially studied for their non-toxic doses in HeLa, CHO, and Vero cells via MTT assay. HeLa cells were transiently transfected with cloned vector pcDNA3.1/Zeo(+)/DENV-2 NS3 along with non-toxic doses (80 μM-10 μM) of selected phytochemicals. The dose-response assay illustrated downregulated expression of DENV-2 NS3 gene after administration of Betanin (IC50 = 4.35 μM) and Glycine Betaine (IC50 = 4.49 μM). Dose response analysis of Betanin (80 μM-10 μM) depicted the significant inhibition of NS3 protein expression as well. These results suggested downregulated expression of DENV-2 NS3 at mRNA and protein level portraying the DENV replication inhibition. Based on our study findings, NS3 protease is depicted as distinctive DENV-2 inhibitor target. We will channel our study further into in vitro characterization employing the mechanistic study to understand the role of host factors in anti-flavi therapeutic.

In silico evaluation of pharmacokinetic parameters, delivery, distribution and anticoagulative effects of new 4,7-dihydroxycoumarin derivative

In this study, pharmacological profiling and investigation of the anticoagulant activity of the newly synthesized coumarin derivative: (E)-3-(1-((4-hydroxy-3-methoxyphenyl)amino)ethylidene)-2,4-dioxochroman-7-yl acetate (L) were performed. The obtained results were compared with the parameters obtained for Warfarin (WF), which is a standard good oral anticoagulant. The estimated high binding affinity of L toward plasma proteins (PPS% value is > 90%) justifies the investigation of binding affinity and comparative analysis of L and WF to Human Serum Albumin (HSA) using the spectrofluorimetric method (296, 303 and 310 K) as well as molecular docking and molecular dynamics simulations. Compound L shows a very good binding affinity especially to the active site of WF (the active site I -subdomain IIA), quenching HSA fluorescence by a static process. Also, the finite element smeared model (Kojic Transport Model, KTM), which includes blood vessels and tissue, was implemented to compute the convective-diffusion transport of L and WF within the liver. Finally, compound L shows a high degree of inhibitory activity toward the VKOR receptor comparable to the inhibitory activity of WF. Stabilization and limited flexibility of amino acid residues in the active site of the VKOR after binding of L and WF indicates a very good inhibitory potential of compound L. The high affinity of the L for the VKOR enzyme (Vitamin K antagonist), as well as the structural similarity to commercial anticoagulants (WF), provide a basis for further studies and potential application in the treatment of venous thrombosis, pulmonary embolism and ischemic heart disease.Communicated by Ramaswamy H. Sarma.

Identification of CXCR4 inhibitors as a key therapeutic small molecule in renal fibrosis

The final stage of almost all chronic kidney diseases is renal fibrosis. Simple wounds or persistent inflammation can cause tissue inflammation, which, in the case of the kidney, results in scarring. Vascular sclerosis, tubulointerstitial fibrosis and glomerular fibrosis are all types of kidney fibrosis. Renal damage and fibrosis are caused by elevated expression of CXCR4. This study aimed to identify possible pharmacological agents which could bind to and inhibit isoform I of CXCR4 and determine their strength of interactions. The I-TASSER, Galaxyweb and Robetta were used to predict and refine the structure of the CXCR4 protein. ModBase was used to improve the loops, and then the quality was evaluated by using the ERRAT value (92.15) and Ramachandran plot. The improved 3D structure was subjected to small molecule database docking using Maestro (from Schrodinger) and the glide module. GROMACS was used to simulate molecules with the three top low glide scores and the best ADME properties. The best glide score was achieved by ligand ID 4990 (-11.5). Simulations, free energy landscape and residue decomposition analysis revealed that 4990 interacted more consistently with CXCR4 than the other two small molecules.Communicated by Ramaswamy H. Sarma.

Screening of promising molecules against potential drug targets in Yersinia pestis by integrative pan and subtractive genomics, docking and simulation approach

This study focuses on Yersinia pestis, the bacterium responsible for plague, which posed a severe threat to public health in history. Despite the availability of antibiotics treatment, the emergence of antibiotic resistance in this pathogen has increased challenges of controlling the infections and plague outbreaks. The development of new drug targets and therapies is urgently needed. This research aims to identify novel protein targets from 28 Y. pestis strains by the integrative pan-genomic and subtractive genomics approach. Additionally, it seeks to screen out potential safe and effective alternative therapies against these targets via high-throughput virtual screening. Targets should lack homology to human, gut microbiota, and known human 'anti-targets', while should exhibit essentiality for pathogen's survival and virulence, druggability, antibiotic resistance, and broad spectrum across multiple pathogenic bacteria. We identified two promising targets: the aminotransferase class I/class II domain-containing protein and 3-oxoacyl-[acyl-carrier-protein] synthase 2. These proteins were modeled using AlphaFold2, validated through several structural analyses, and were subjected to molecular docking and ADMET analysis. Molecular dynamics simulations determined the stability of the ligand-target complexes, providing potential therapeutic options against Y. pestis.

Exploring Antimicrobial Potency, ADMET, and Optimal Drug Target of a Non-ribosomal Peptide Sevadicin from Bacillus pumilus, through In Vitro Assay and Molecular Dynamics Simulation

The current study was designed to explore the biosynthetic potential of sevadicin in Bacillus pumilus species and its interaction with bacterial drug target molecules. The non-ribosomal peptide (NRP) cluster in B. pumilus SF-4 was preliminarily confirmed using PCR-based screening, and the bioactivity of strain SF-4 culture extract was assessed against a set of human pathogenic strains. The susceptibility assay showed that strain SF-4 extract had higher inhibitory concentrations (312-375 µg/mL) than ciprofloxacin. Genome mining of B. pumilus strains (n = 22) using AntiSMASH and BAGEL identified sevadicin coding biosynthetic gene cluster only in strain SF-4, constitutes of two core biosynthetic genes, three additional biosynthetic genes, two transport-related genes, and one regulatory gene. The molecular docking of sevadicin with various putative bacterial drug targets such as dihydropteroate, muramyl ligase E, topoisomerase, penicillin-binding protein, and in vitro safety analyses were conducted with detailed ADMET screening. The results showed that sevadicin makes hydrophobic interaction with MurE (PDB ID: 1E8C and 4C13) via hydrogen bonding, suggesting bacterial growth inhibition by disrupting the cell wall synthesis pathway and exhibiting a secure biosafety profile. The stability and compactness of sevadicin/MurE complexes were assessed via molecular dynamic simulation using RMSD, RMSF, and Rg. The simulation results revealed the binding stability of sevadicin/MurE complexes and indicated that the complexes can't be easily deformed. In conclusion, the current study explored the biosynthesis of sevadicin in B. pumilus for the first time and found that sevadicin inhibits bacterial growth by inhibiting cell wall synthesis via targeting the MurE enzyme and exhibits no toxicity.

Synthesis, crystal structure analysis, computational modelling and evaluation of anti-cervical cancer activity of novel 1,5-dicyclooctyl thiocarbohydrazone

Thiocarbazones are widely used as bioactive and pharmaceutical intermediates in medicinal chemistry and have been shown to exhibit diverse biological and pharmacological activities such as antimicrobial, anticancer, anti-viral, anti-convulsant and anti-inflammatory etc. In continuation of our interest in biologically active heterocycles and in an attempt to synthesize a spiro derivative, 1,2,4,5-tetraazaspiro[5.7]tridecane-3-thione, herein, the synthesis of 1,5-dicyclooctyl thiocarbohydrazone (3) has been reported via reaction of the cyclooctanone and thiocarbohydrazide. The structure was assigned on the basis of detailed spectral analysis and also confirmed by X-ray crystal studies. The Hirshfeld surface analysis indicates that the most significant interaction is S⋯H (12.7%). The presentation of mechanistic aspects regarding the plausible route of its formation has also been included. The first hyperpolarizability (β0) was found to be 10.22 × 10-30 esu, which indicates that the compound exhibits good non-linear optical properties. The density functional theory (DFT) method has been used to characterize the spectroscopic properties and vibrational analysis of 1,5-dicyclooctyl thiocarbohydrazone (3) theoretically. The compound and cisplatin (standard) were screened for their antiproliferative activity against the human cervical cancer cell line (SiHa) and they exhibited significant activity with IC50 values of 250 μM and 15 μM, respectively. The inhibitory nature of the title compound against viral oncoprotein E6 was confirmed by studies using molecular docking analysis. The results of biological activity and in silico analysis indicate that the synthesized molecule could act as a precursor for the synthesis of new heterocyclic derivatives of medicinal importance.

Investigating the antioxidant potential and mechanism of a hydrazide bioactive component of garlic: insights from density functional theory calculations, drug-likeness and molecular docking studies

Glutathione remains one of the most efficient antioxidant compounds in living systems, and the biological abilities of hydrazides have been well documented in literature. This study highlights the phytochemical constituents of garlic and the separation of the bioactive benzoic acid, 4-chloro- 1-(4-methoxyphenyl) hydrazide (BA4C) using gas chromatography-mass spectroscopy (GC-MS) technique. Preliminary phytochemical screening reveals the presence of alkaloids, saponins, flavonoids, tannins, terpenoids, steroids and phenols. Computationally, compound BA4C was optimized using the B3LYP/aug-cc-PVDZ DFT method. Spectroscopic studies of the compound involved analysis of the vibrational FT-IR frequencies and the modes of vibrations. Frontier molecular orbitals analysis records an energy gap of 4.3391 eV; NBO studies reveal that the compound has strong perturbation energies of 246 kcal/mol and 269 kcal/mol among its intramolecular interactions such as π *C12 - C13 to π *C14 - C15 and π *C11 - C16 to π *C14 - C15, respectively. According to the visualization of non-covalent interactions, steric repulsions were observed at the core of the phenyl and benzene rings. However, other regions of the compound depict a significant balance of forces between steric repulsions and van der Waals forces. To significantly deduce the reducing power of compound BA4C, electrons were found to be highly localized at the methoxy and hydrazide moieties significantly implying their propensity to donate electrons to oxidized systems. Furthermore, ADMET analysis reveals that the compound has two hydrogen donors. Most significantly, the compound binds to NADPH dehydrogenase (5V4P) and glutathione reductase (1XAN) with binding energies of - 6.0 kcal/mol and - 8.0 kcal/mol showing considerable favourable binding feasibility as well as forming plural hydrogen bonds with the amino acid residues. Notably, BA4C was bonded at the active site of 1XAN, which implies the ability of the compound for the reduction of oxidized glutathione.

Synthesis, biosimulation and pharmacological evaluation of benzimidazole derivatives with antihypertensive multitarget effect

In this study, we synthesized a series of seven benzimidazole derivatives incorporating the structural acidic framework of angiotensin II (Ang II) type 1 receptor (AT1R) antagonists (ARA-II) employing a three-step reaction sequence. The chemical structures were confirmed by 1H NMR, 13C NMR and mass spectral data. Through biosimulation, compounds 1-7 were identified as computational safe hits, thus, best candidates underwent ex vivo testing against two distinct mechanisms implicated in hypertension: antagonism of the Ang II type 1 receptor and the blockade of calcium channel. Molecular docking studies helped to understand at the molecular level the dual vasorelaxant effects with the recognition sites of the AT1R and the L-type calcium channel. In an in vivo spontaneously hypertensive rat model (SHR), intraperitoneally administration of compound 1 at 20 mg/kg resulted in a 25 % reduction in systolic blood pressure, demonstrating both ex vivo vasorelaxant action and in vivo antihypertensive multitarget efficacy. ©2024 Elsevier.

Reduced estrogenic risks of a sunscreen additive: Theoretical design and evaluation of functionally improved salicylates

Salicylic esters (SEs), the widely used ultraviolet (UV) absorbers in sunscreen products, have been found to have health risks such as skin sensitization and estrogenic effects. This study aims to design SE substitutes that maintain high UV absorbance while reducing estrogenicity. Using molecular docking and Gaussian09 software for initial assessments and further application of a combination of two-dimensional and three-dimensional quantitative structure-activity relationships (2D-QSAR and 3D-QSAR, respectively) models, we designed 73 substitutes. The best-performing molecules, ethylhexyl salicylate (EHS)-5 and EHS-15, significantly reduced estrogenicity (44.54 % and 17.60 %, respectively) and enhanced UV absorbance (249.56 % and 46.94 %, respectively). Through screening for human health risks, we found that EHS-5 and EHS-15 were free from skin sensitivity and eye irritation and exhibited reduced skin permeability compared with EHS. Furthermore, the photolysis and synthetic pathways of EHS-5 and EHS-15 were deduced, demonstrating their good photodegradability and potential synthesizability. In addition, we analyzed the mechanisms underlying the changes in estrogenic effects and UV absorption properties. We identified covalent hydrogen bond basicity and acidity Propgen value for atomic molecular properties and the highest occupied molecular orbital eigenvalue as the main factors affecting the estrogenic effect and UV absorbance of SEs, respectively. This study focuses on the design and screening of SEs, exhibiting enhanced functionality, reduced health risks, and synthetic feasibility.

Finer Particle Size Distribution and Potential Higher Toxicity of Elemental Carbon and Polycyclic Aromatic Hydrocarbons Emitted by Ships after Fuel Oil Quality Improvement

Ship emissions are a significant source of air pollution, and the primary policy to control is fuel oil quality improvement. However, the impact of this policy on particle size distribution and composition characteristics remains unclear. Measurements were conducted on nine different vessels (ocean-going vessels, coastal cargo ships, and inland cargo ships) to determine the impact of fuel upgrading (S < 0.1% m/m marine gas oil (MGO) vs S < 0.5% m/m heavy fuel oil (HFO)) on elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs) emitted by ships. (1) Fuel improvement significantly reduced EC and PAH emission, by 31 ± 25 and 45 ± 38%, respectively. However, particle size distributions showed a trend toward finer particles, with the peak size decreasing from DP = 0.38-0.60 μm (HFO) to DP = 0.15-0.25 μm (MGO), and the emission factor of DP < 100 nm increased. (2) Changes in emission characteristics led to an increase in the toxicity of ultrafine particulate matter. (3) Ship types and engine conditions affected the EC and PAH particle size distributions. Inland ships have a more concentrated particle size distribution. Higher loads result in higher emissions. (4) The composition and engine conditions of fuel oils jointly affected pollutant formation mechanisms. MGO and HFO exhibited opposite EC emissions when emitting the same level of PAHs.

Unlocking the potential of signature-based drug repurposing for anticancer drug discovery

Cancer is the leading cause of death worldwide and is often associated with tumor relapse even after chemotherapeutics. This reveals malignancy is a complex process, and high-throughput omics strategies in recent years have contributed significantly in decoding the molecular mechanisms of these complex events in cancer. Further, the omics studies yield a large volume of cancer-specific molecular signatures that promote the discovery of cancer therapy drugs by a method termed signature-based drug repurposing. The drug repurposing method identifies new uses for approved drugs beyond their intended initial therapeutic use, and there are several approaches to it. In this review, we discuss signature-based drug repurposing in cancer, how cancer omics have revolutionized this method of drug discovery, and how one can use the cancer signature data for repurposed drug identification by providing a step-by-step procedural handout. This modern approach maximizes the use of existing therapeutic agents for cancer therapy or combination therapy to overcome chemotherapeutics resistance, making it a pragmatic and efficient alternative to traditional resource-intensive and time-consuming methods.

SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability

Artificial intelligence (AI) has emerged as a pivotal force in enhancing productivity across various sectors, with its impact being profoundly felt within the pharmaceutical and biotechnology domains. Despite AI's rapid adoption, its integration into scientific research faces resistance due to myriad challenges: the opaqueness of AI models, the intricate nature of their implementation, and the issue of data scarcity. In response to these impediments, we introduce SmartCADD, an innovative, open-source virtual screening platform that combines deep learning, computer-aided drug design (CADD), and quantum mechanics methodologies within a user-friendly Python framework. SmartCADD is engineered to streamline the construction of comprehensive virtual screening workflows that incorporate a variety of formerly independent techniques─spanning ADMET property predictions, de novo 2D and 3D pharmacophore modeling, molecular docking, to the integration of explainable AI mechanisms. This manuscript highlights the foundational principles, key functionalities, and the unique integrative approach of SmartCADD. Furthermore, we demonstrate its efficacy through a case study focused on the identification of promising lead compounds for HIV inhibition. By democratizing access to advanced AI and quantum mechanics tools, SmartCADD stands as a catalyst for progress in pharmaceutical research and development, heralding a new era of innovation and efficiency.

Identification of indole-grafted pyrazolopyrimidine and pyrazolopyridine derivatives as new anti-cancer agents: Synthesis, biological assessments, and molecular modeling insights

In the current medical era, developing new PIM-1 inhibitors stands as a significant approach to cancer management due to the pivotal role of PIM-1 kinase in promoting cell survival, proliferation, and drug resistance in various cancers. This study involved designing and synthesizing new derivatives of pyrazolo[1,5-a]pyrimidines (6a-i) and pyrazolo[3,4-b]pyridines (10a-i) as potential anti-cancer agents targeting PIM-1 kinase. The cytotoxicity was screened on three cancer cell lines: A-549 (lung), PANC-1 (pancreatic), and A-431 (skin), alongside MRC5 normal lung cells to assess selectivity. Several pyrazolo[1,5-a]pyrimidines (6b, 6c, 6g, 6h, and 6i) and pyrazolo[3,4-b]pyridine (10f) demonstrated notable anticancer properties, particularly against A-549 lung cancer cells (IC50 range: 1.28-3.52 μM), also they exhibited significantly lower toxicity towards MRC5 normal cells. Thereafter, the compounds were evaluated for their inhibitory activity against PIM-1 kinase. Notably, 10f, bearing a 4-methoxyphenyl moiety, demonstrated good inhibition of PIM-1 with an IC50 of 0.18 μM. Additionally, 10f induced apoptosis and arrested cell cycle progression in A-549 cells. Molecular docking and dynamics simulations provided insights into the binding interactions and compounds' stability with PIM-1 kinase. The results highlight these compounds, especially 10f, as promising selective anticancer agents targeting PIM-1 kinase.

Discovery of novel CXCR4 inhibitors for the treatment of inflammation by virtual screening and biological evaluation

C-X-C chemokine receptor type 4 (CXCR4) exerts considerable influence on the pathogenesis of inflammatory disorders and offers a potent avenue for drug intervention. This research utilizes a hybrid virtual screening methodology constructed using computer-aided drug design to discover novel CXCR4 inhibitors for the treatment of inflammation. First, a compound library was screened by Lipinski's five rules and adsorption, distribution, metabolism, excretion and toxicity properties. Second, the HypoGen algorithm was used in constructing a 3D-QSAR pharmacophore model and verify it layer by layer, and the obtained optimal pharmacophore 1 (Hypo 1) was used as a 3D query for compound screening. Then, hit compounds were obtained through molecular docking (Libdock and CDOCKER). The toxicity of the compounds to MDA-MB-231 cells was evaluated in vitro, and their binding affinity to the target was evaluated according to how they compete with 12G5 antibody for CXCR4 on the surfaces of the MDA-MB-231 cells. Compound Hit14 showed the strongest binding affinity among the hit compounds and inhibited cell migration and invasion in Matrigel invasion and wound healing assay at a concentration of 100 nM, demonstrating a better effect than AMD3100. Western Blot experiments further showed that Hit14 blocked the CXCR4/CXCL12-mediated phosphorylation of Akt. Meanwhile, cellular thermal displacement assay analysis showed that CXCR4 protein bound to Hit14 had high thermal stability. Finally, through in vivo experiments, we found that Hit14 inhibited mouse ear inflammation and reduced ear swelling and damage. Therefore, Hit14 is a promising drug for the further development of CXCR4 inhibitors for inflammation treatment.

Pomegranate Peel Extract as 6-Phosphogluconate Dehydrogenase (6PGD) Inhibitor for Treatment of Breast Cancer

Targeting the enzymes of Pentose Phosphate Pathway (PPP) has been emerged as a novel strategy for treatment of cancer. 6-phosphogluconate dehydrogenase (6PGD) is third enzyme of PPP and converts 6-phosphogluconate (6-PG) into ribulose 5-phosphate (R-5-P) and produces NADPH. The overexpression of 6PGD has been reported in many human cancers especially in breast cancer and is emerged as the potential anti-cancer drug target. The current study is focused to screen an already established library of plant extracts against 6PGD, among which Pomegranate peel extract showed significant 6PGD inhibitory activity with IC50 value = 0.090 μg/mL. Pomegranate peel competitively inhibited NADP+ and 6-phosphogluconate to 6PGD enzyme having Ki constant value = 12.72 ± 5.54 ng/mL. Moreover, anti-breast cancer activity against MCF-7 cells determined Pomegranate peel as the potent inhibitor of cancerous cells with IC50 value = 3.138 μg/mL. Toxicity profiling of pomegranate peel extract (2000mg/kg) did not show any adverse effect on mice. Moreover, Ont the base of literature a library of known compounds of pomegranate was prepared and established and screened against 6PGD for the identification of actual responsible phytochemicals of 6PGD activity by using molecular docking. Computational tools were used to evaluate selected potent hits. Out of 26 compounds, three potent phytochemicals (Procyanidin, Delphinidin and Cyanidin) exhibited the best binding affinities with 6PGD. In addition, these phytochemicals displayed the best favorable hydrogen bonding, binding energy, and protein-ligand interactions as compare to 3PG. Molecular dynamics simulation suggested that these hits form a stable binding complex with the active site of 6PGD. These findings suggest that Pomegranate peel and its secondary metabolites as the potent inhibitors of 6PGD and the best drug candidate for treatment of breast cancer.

Structural Reorganization Mechanism of the Aβ42 Fibril Mediated by N-Substituted Oligopyrrolamide ADH-353

The inhibition of amyloid-β (Aβ) fibrillation and clearance of Aβ aggregates have emerged as a potential pharmacological strategy to alleviate Aβ aggregate-induced neurotoxicity in Alzheimer's disease (AD). Maity et al. shortlisted ADH-353 from a small library of positively charged N-substituted oligopyrrolamides for its notable ability to inhibit Aβ fibrillation, disintegrate intracellular cytotoxic Aβ oligomers, and alleviate Aβ-induced cytotoxicity in the SH-SY5Y and N2a cells. However, the molecular mechanism through which ADH-353 interacts with the Aβ42 fibrils, leading to their disruption and subsequent clearance, remains unclear. Thus, a detailed molecular mechanism underlying the disruption of neurotoxic Aβ42 fibrils (PDB ID 2NAO) by ADH-353 has been illuminated in this work using molecular dynamics simulations. Interestingly, conformational snapshots during simulation depicted the shortening and disappearance of β-strands and the emergence of a helix conformation, indicating a loss of the well-organized β-sheet-rich structure of the disease-relevant Aβ42 fibril on the incorporation of ADH-353. ADH-353 binds strongly to the Aβ42 fibril (ΔGbinding= -142.91 ± 1.61 kcal/mol) with a notable contribution from the electrostatic interactions between positively charged N-propylamine side chains of ADH-353 with the glutamic (Glu3, Glu11, and Glu22) and aspartic (Asp7 and Asp23) acid residues of the Aβ42 fibril. This aligns well with heteronuclear single quantum coherence NMR studies, which depict that the binding of ADH-353 with the Aβ peptide is driven by electrostatic and hydrophobic contacts. Furthermore, a noteworthy decrease in the binding affinity of Aβ42 fibril chains on the incorporation of ADH-353 indicates the weakening of interchain interactions leading to the disruption of the double-horseshoe conformation of the Aβ42 fibril. The illumination of key interactions responsible for the destabilization of the Aβ42 fibril by ADH-353 in this work will greatly aid in designing new chemical scaffolds with enhanced efficacy for the clearance of Aβ aggregates in AD.

Innovative virtual screening of PD-L1 inhibitors: the synergy of molecular similarity, neural networks and GNINA docking

Aims: Immune checkpoint inhibitors targeting PD-L1 are crucial in cancer research for preventing cancer cells from evading the immune system.Materials & methods: This study developed a screening model combining ANN, molecular similarity, and GNINA 1.0 docking to target PD-L1. A database of 2044 substances was compiled from patents.Results: For molecular similarity, the AVALON emerged as the most effective fingerprint, demonstrating an AUC-ROC of 0.963. The ANN model outperformed the Random Forest and Support Vector Classifier in cross-validation and external validation, achieving an average precision of 0.851 and an F1 score of 0.790. GNINA 1.0 was validated through redocking and retrospective control, achieving an AUC of 0.975.Conclusions: From 15235 DrugBank compounds, 22 candidates were shortlisted. Among which (3S)-1-(4-acetylphenyl)-5-oxopyrrolidine-3-carboxylic acid emerged as the most promising.

A Near-Explicit Reaction Mechanism of Chlorine-Initiated Limonene: Implications for Health Risks Associated with the Concurrent Use of Cleaning Agents and Disinfectants

Limonene, a key volatile chemical product (VCP) commonly found in personal care and cleaning agents, is emerging as a major indoor air pollutant. Recently, elevated levels of reactive chlorine species during bleach cleaning and disinfection have been reported to increase indoor oxidative capacity. However, incomplete knowledge of the indoor transformation of limonene, especially the missing chlorine chemistry, poses a barrier to evaluating the environmental implications associated with the concurrent use of cleaning agents and disinfectants. Here, we investigated the reaction mechanisms of chlorinated limonene peroxy radicals (Cl-lim-RO2•), key intermediates in determining the chlorine chemistry of limonene, and toxicity of transformation products (TPs) using quantum chemical calculations and toxicology modeling. The results indicate that Cl-lim-RO2• undergoes a concerted autoxidation process modulated by RO2• and alkoxy radicals (RO•), particularly emphasizing the importance of RO• isomerization. Following this generalized autoxidation mechanism, Cl-lim-RO2• can produce low-volatility precursors of secondary organic aerosols. Toxicological findings further indicate that the majority of TPs exhibit increased respiratory toxicity, mutagenicity, and eye/skin irritation compared to limonene, presenting an occupational hazard for indoor occupants. The proposed near-explicit reaction mechanism of chlorine-initiated limonene significantly enhances our current understanding of both RO2• and RO• chemistry while also highlighting the health risks associated with the concurrent use of cleaning agents and disinfectants.

A comprehensive review of artificial intelligence for pharmacology research

With the innovation and advancement of artificial intelligence, more and more artificial intelligence techniques are employed in drug research, biomedical frontier research, and clinical medicine practice, especially, in the field of pharmacology research. Thus, this review focuses on the applications of artificial intelligence in drug discovery, compound pharmacokinetic prediction, and clinical pharmacology. We briefly introduced the basic knowledge and development of artificial intelligence, presented a comprehensive review, and then summarized the latest studies and discussed the strengths and limitations of artificial intelligence models. Additionally, we highlighted several important studies and pointed out possible research directions.

Unraveling the molecular basis for effective regulation of integrin α5β1 for enhanced therapeutic interventions

Cell attachment to the extracellular matrix significantly impacts the integrity of tissues and human health. The integrin α5β1 is a heterodimer of α5 and β1 subunits and has been identified as a crucial modulator in several human carcinomas. Integrin α5β1 significantly regulates cell proliferation, angiogenesis, inflammation, tumor metastasis, and invasion. This regulatory role of integrin α5β1 in tumor metastasis makes it an appealing target for cancer therapy. The majority of the drugs targeting integrin α5β1 are limited only to clinical trials. In our study, we have performed 94287 compounds screening to determine potential drugs against α5β1 integrin. We have used ATN-161 as a reference and employed combined bioinformatic methodologies, including molecular modelling, virtual screening, MM-GBSA, cell-line cytotoxicity prediction, ADMET, Density Functional Theory (DFT), Non-covalent Interactions (NCI) and molecular simulation, to identify putative integrin α5β1 inhibitors. We found Taxifolin, PD133053, and Acebutolol that possess inhibitory activity against α5β1 integrin and could act as effective drug for the cancer treatment. Taxifolin, PD133053, and Acebutolol exhibited excellent binding to the druggable pocket of integrin α5β1, and also maintained a unique binding mechanism with extra hydrophobic contacts at molecular level. Overall, our study gives new pharmacological candidates that may act as a potential drug against integrin α5β1.

MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning

Predicting compound-induced inhibition of cardiac ion channels is crucial and challenging, significantly impacting cardiac drug efficacy and safety assessments. Despite the development of various computational methods for compound-induced inhibition prediction in cardiac ion channels, their performance remains limited. Most methods struggle to fuse multi-source data, relying solely on specific dataset training, leading to poor accuracy and generalization. We introduce MultiCBlo, a model that fuses multimodal information through a progressive learning approach, designed to predict compound-induced inhibition of cardiac ion channels with high accuracy. MultiCBlo employs progressive multimodal information fusion technology to integrate the compound's SMILES sequence, graph structure, and fingerprint, enhancing its representation. This is the first application of progressive multimodal learning for predicting compound-induced inhibition of cardiac ion channels, to our knowledge. The objective of this study was to predict the compound-induced inhibition of three major cardiac ion channels: hERG, Cav1.2, and Nav1.5. The results indicate that MultiCBlo significantly outperforms current models in predicting compound-induced inhibition of cardiac ion channels. We hope that MultiCBlo will facilitate cardiac drug development and reduce compound toxicity risks. Code and data are accessible at: https://github.com/taowang11/MultiCBlo. The online prediction platform is freely accessible at: https://huggingface.co/spaces/wtttt/PCICB.

Exploring the chemical space for potential inhibitors against cell surface binding protein of Mpox virus using molecular fingerprint based screening approach

Mpox virus is the latest member of the Poxviridae family of which small pox virus is a member. Monekypox virus has led to thousands of infections across the globe. Poxvirus gains entry into the cell making use of glycosaminoglycans like chondroitin sulphate and heparan sulphate. The interaction of the Mpox virus protein E8L also called cell surface binding protein is crucial for host cell attachment, membrane fusion and viral entry into the host cell leading to establishment of infection thus making this protein a very attractive therapeutic target. In this study we have tried to utilize the chondroitin sulphate binding groove present in the protein and identify molecules which are structurally similar to chondroitin sulphate. These molecules can thus occupy the same pocket but with a better binding affinity than chondroitin sulphate in order to outcompete the latter molecule from binding to the E8L protein and thus prevent it from performing its function. This study may pave the way for development of highly efficient therapeutics against the Mpox virus and further curb its infective potential.Communicated by Ramaswamy H. Sarma.

Targeting COVID-19 and varicocele by blocking inflammasome: Ligand-based virtual screening

COVID-19 is a new generation of outbreaks that invade not only local emerging region, continental but also the whole globe. Varicocele on the other hand, is a testicular vascular disease that underlies 40 % of male infertility cases. Fortunately, the two diseases can be blocked through targeting one common target, NLRP3 inflammasome. Upon searching for similar drugs that gained FDA-approval in ChEMBL library along with examining their potential blockade of the receptor through docking using CB-DOCK-2, three potential approved drugs can be repurposed, ChEMBL 4297185, ChEMBL 1201749, ChEMBL 1200545 which had binding energy of -9.8 and -9.7 kcal/mol (stronger than the reference inhibitor, -9.3 kcal/mol). Also, ADME profile of the top 3 drugs showed better attributes. Also, the simulated proteins exhibited stable pattern with strong free binding energies. Among the potential inhibitor drugs ChEMBL 4297185 was found to remain inside the binding site of the protein during the 200 ns simulation time. Hence, it is anticipated to have the highest binding and thus inhibition potential against the protein. The suggested drugs, especially ChEMBL 4297185, are potentially repurposable toward treating COVID-19 and varicocele which deserve further experimental validation.

Synthesis, biological evaluation, theoretical calculations, QSAR and molecular docking studies of novel arylaminonaphthols as potent antioxidants and BChE inhibitors

A completely green protocol was developed for the synthesis of a series of arylaminonaphthol derivatives in the presence of N-ethylethanolamine (NEEA) as a catalyst under ultrasonic irradiation and solventless conditions. The major assets of this methodology were the use of non-toxic organic medium, available catalyst, mild reaction condition, and good to excellent yield of desired products. All of the synthesized products were screened for their in vitro antioxidant activity using DPPH, ABTS, and Ferric-phenanthroline assays and it was found that most of them are potent antioxidant agents. Also, their butyrylcholinesterase inhibitory activity has been investigated in vitro. All tested compounds exhibited potential inhibitory activity toward BuChE when compared to standard reference drug galantamine, however, compounds 4r, 4u, 4 g and 4x gave higher butyrylcholinesterase inhibitory with IC50 values of 14.78 ± 0.65 µM, 16.18 ± 0.50 µM, 20.00 ± 0.50 µM, and 20.28 ± 0.08 µM respectively. On the other hand, we employed density functional theory (DFT), calculations to analyze molecular geometry and global reactivity descriptors, and MESP analysis to predict electrophilic and nucleophilic attacks. A quantitative structure-activity relationship (QSAR) investigation was conducted on the antioxidant and butyrylcholinesterase properties of 25 arylaminonaphthol derivatives, resulting in robust and satisfactory models. To evaluate their anti-Alzheimer's activity, compounds 4 g, 4q, 4r, 4u, and 4x underwent docking simulations at the active site of the acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), revealing why these compounds displayed superior activity, consistent with the biological findings.

An In Silico-Guided Approach for Assessing Herb-Drug Interaction Potential: A Case Study with Cudrania tricuspidata Leaf Extracts

Cudrania tricuspidata leaf extracts have long been utilized as traditional oriental medicines across Asian countries like Korea, China, and Japan. These extracts are renowned for their therapeutic benefits in addressing inflammation, tumors, obesity, and diabetes, maintaining their status as a pivotal folk remedy. Given the rising trend of combining medicinal herbs with conventional medications, it is imperative to explore the potential herb-drug interactions. However, there is a dearth of research on evaluating the herb-drug interactions of C. tricuspidata leaf extracts. Also, the intricate chemical composition of medicinal herbs presents methodological hurdles in establishing causal relationships between their constituents and herb-drug interactions. To overcome these challenges, a combined in silico and in vitro workflow was developed and effectively applied to evaluate the potential herb-drug interaction of C. tricuspidata leaf extracts along with the associated chemical factors. In in vitro CYP inhibition assays, C. tricuspidata leaf extracts exhibited potent inhibition of CYP1A2 and CYP2C8, with quercetin, kaempferol, and their glycosides identified as the major constituents. In silico analysis based on the prediction tools (ADMETlab 2.0 and pkCSM) identified key contributors to CYP inhibition, quercetin and kaempferol. Additionally, molecular docking analysis validated the binding of ligands (quercetin and kaempferol) to proteins (CYP1A2 and CYP2C8). These findings suggest that C. tricuspidata leaf extracts could inhibit CYP1A2 and CYP2C8, aiding in understanding the herb-drug interaction potential of C. tricuspidata leaf extracts for safe clinical application. Furthermore, this approach can be broadly applied to study herb-drug interactions of various medicinal herbs, enhancing their therapeutic benefits and reducing adverse reactions by considering chemical profiles relevant to herb-drug interaction potential in herbal preparations.

Exploration of selected monoterpenes as potential TRPC channel family modulator in lung cancer, an in-silico upshot

Lung cancer is still the most frequent cause of cancer-related death, accounting for nearly two million cases yearly. As cancer is a multifactorial disease, developing novel molecular therapeutics that can simultaneously target multiple associated cellular processes has become necessary. Ion channels are diverse regulators of cancer-related processes such as abnormal proliferation, invasion, migration, tumor progression, inhibition of apoptosis, and chemoresistance. Among the various families of ion channels, the transient receptor potential canonical channel family steps out in the context of lung cancer, as several members have been postulated as prognostic markers for lung cancer. Phytochemicals have been found to have health benefits in the treatment of a variety of diseases and disorders. Among phytochemicals, monoterpenes are effective in treating both the early and late stages of cancer. The molecular docking interaction analysis was conducted to evaluate the binding potential of selected monoterpenes with TRPC3, TRPC4, TRPC5, and TRPC6 involved in different phases of carcinogenesis. Amongst the selected monoterpenes, thymoquinone exhibited the highest binding energy of -6.7 kcal/mol against the TRPC4 channel, and all amino acid binding residues were similar to those of the known inhibitor for TRPC4. In addition, molecular-dynamic simulation results parameters, such as RMSD, RMSF, and Rg, indicated that thymoquinone did not impact the protein compactness and exhibited stability during the interaction. The average interaction energy between thymoquinone and TRPC4 protein was -26.85 kJ/mol. In-silico Drug-likeness and ADMET profiling indicated that thymoquinone is a druggable candidate with minimal toxicity. We propose further investigation and evaluation of thymoquinone for lead optimization and drug development.Communicated by Ramaswamy H. Sarma.

Identification of potential inhibitors of Mtb InhA: a pharmacoinformatics approach

The emergence of superbugs of multi-drug resistant (MDR/RR) and extensively drug-resistant (XDR) Mycobacterium tuberculosis (Mtb) strains at a faster rate is posing a serious threat to Tuberculosis (TB) control worldwide. Mtb enoyl-acyl carrier protein reductase (InhA) is a well-established target of the front-line anti-TB prodrug Isoniazid (INH), which requires activation by Catalase-peroxidase enzyme (KatG) in order to inhibit InhA enzyme, that is crucial for the biosynthesis of the mycobacterial cell wall. Currently, due to widespread resistance to this drug, it is necessary to identify new clinical candidates that directly inhibit InhA enzyme and do not require activation by KatG, thereby circumventing most of the resistance mechanisms. In the present study, high-throughput virtual screening of ASINEX database was carried out to identify potential direct inhibitors of Mtb InhA. Best twenty compounds with good binding energies ranging between -12.36 and -9.27 kcal/mol were selected as promising virtual screening hits. These molecules were subjected to ADME study followed by toxicity prediction. Finally, four top-ranked molecules which are structurally diverse and possess best binding affinity than the co-crystalized ligand have been chosen for MD simulation studies followed by MM-GBSA analysis to validate and ensure the stability of hits in the active site of the enzyme. Based on the 100 ns MD simulation studies and binding free energy estimates, three hit molecules B244, B369, and B310 could be considered as potential inhibitors for Mtb InhA, which are likely to be potent against INH-resistant Mtb strains after successful experimental validation.Communicated by Ramaswamy H. Sarma.

Molecular modeling strategy for detailing the primary mechanism of action of copanlisib to PI3K: combined ligand-based and target-based approach

Since dysregulation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway is associated with the pathogenesis of cancer, inflammation, and autoimmunity, PI3K has emerged as an attractive target for drug development. Although copanlisib is the first pan-PI3K inhibitor to be approved for clinical use, the precise mechanism by which it acts on PI3K has not been fully elucidated. To reveal the binding mechanisms and structure-activity relationship between PI3K and copanlisib, a comprehensive modeling approach that combines 3D-quantitative structure-activity relationship (3D-QSAR), pharmacophore model, and molecular dynamics (MD) simulation was utilized. Initially, the structure-activity relationship of copanlisib and its derivatives were explored by constructing a 3D-QSAR. Then, the key chemical characteristics were identified by building common feature pharmacophore models. Finally, MD simulations were performed to elucidate the important interactions between copanlisib and different PI3K subtypes, and highlight the key residues for tight-binding inhibitors. The present study uncovered the principal mechanism of copanlisib's action on PI3K at the theoretical level, and these findings might provide guidance for the rational design of pan-PI3K inhibitors.Communicated by Ramaswamy H. Sarma.

AI-Powered Mining of Highly Customized and Superior ESIPT-Based Fluorescent Probes

Excited-state intramolecular proton transfer (ESIPT) has attracted great attention in fluorescent sensors and luminescent materials due to its unique photobiological and photochemical features. However, the current structures are far from meeting the specific demands for ESIPT molecules in different scenarios; the try-and-error development method is labor-intensive and costly. Therefore, it is imperative to devise novel approaches for the exploration of promising ESIPT fluorophores. This research proposes an artificial intelligence approach aiming at exploring ESIPT molecules efficiently. The first high-quality ESIPT dataset and a multi-level prediction system are constructed that realized accurate identification of ESIPT molecules from a large number of compounds under a stepwise distinguishing from conventional molecules to fluorescent molecules and then to ESIPT molecules. Furthermore, key structural features that contributed to ESIPT are revealed by using the SHapley Additive exPlanations (SHAP) method. Then three strategies are proposed to ensure the ESIPT process while keeping good safety, pharmacokinetic properties, and novel structures. With these strategies, >700 previously unreported ESIPT molecules are screened from a large pool of 570 000 compounds. The ESIPT process and biosafety of optimal molecules are successfully validated by quantitative calculation and experiment. This novel approach is expected to bring a new paradigm for exploring ideal ESIPT molecules.

Exploring the therapeutic potential of prolinamides as multi-targeted agents for Alzheimer's disease treatment: molecular docking and molecular dynamic simulation studies

Alzheimer's disease (AD) presents a significant global health challenge, with its prevalence expected to rise sharply in the coming years. Despite extensive research, effective treatments addressing the multifaceted pathophysiology of AD remain elusive. This study investigates the therapeutic potential of twenty-seven prolinamides (P1 - P27), with the focus on their interactions with key proteins implicated in AD pathogenesis. Four of the compounds, namely; 10-((4-nitrophenyl)prolyl)-10 H-phenothiazine (P14), 2-((4-nitrophenyl)prolyl)isoindoline (P19), 1-(4-formylphenyl)-N-(p-tolyl)pyrrolidine-2-carboxamide (P22), and N,1-bis(4-nitrophenyl)pyrrolidine-2-carboxamide (P27) showed promising potential as Alzheimer's drug. In-silico approaches including molecular docking, molecular dynamic (MD) simulation, post md study, physicochemical and drug-likeness parameters were employed to ascertain the potential of these compounds as inhibitors of certain proteins implicated in the pathophysiology of Alzheimer's disease. Molecular docking and dynamics simulations demonstrated that P14, P19, P22 and P27 exhibited promising binding affinities towards crucial AD-associated proteins, including Beta-Secretase 1 (BACE1), Butyrylcholinesterase (BuChE), and Tau-tubulin kinase 2 (TTBK2). Structural stability analyses revealed that prolinamides, particularly P22 and P27 for BACE1 and P14 and P19 for BuChE, exhibited greater stability than their reference ligands, indicated by lower RMSD, RoG, and RMSF values. For BuChE, Rivastigmine had a docking score of -7.0 kcal/mol, a binding free energy (ΔGbind) of -22.19 ± 2.44 kcal/mol, RMSD of 1.361 ± 0.162 Å, RMSF of 9.357 ± 3.212 Å, and RoG of 22.919 ± 0.064 Å, whereas P19 exhibited a superior docking score of -10.3 kcal/mol, a significantly better ΔGbind of -33.74 ± 2.84 kcal/mol, RMSD of 1.347 ± 0.132 Å, RMSF of 8.164 ± 2.748 Å, and RoG of 22.868 ± 0.070 Å. Physicochemical and pharmacokinetic assessments affirmed the drug-likeness and bioavailability of P19 notably capable of penetrating the blood-brain barrier. Compounds P19 and P22, emerged as multi-targeted ligands, offering the potential for simultaneous modulation of multiple AD-related pathways. These findings highlight the possibilities of these compounds to be explored as novel therapeutic agents for AD. They also highlight the need for further experimental validation to confirm their efficacy and safety profiles, advancing them toward clinical application in AD management.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00250-z.

In silico, in vitro, and in vivo acute and sub-acute toxicity profiling of whole plant methanol extract of Equisetum diffusum D. Don from the sub-Himalayan West Bengal, India, having ethnobotanical uses

BACKGROUND

Equisetum diffusum D. Don commonly known as 'Himalayan horsetail', has been traditionally used in the treatment of back pain, bone fracture and dislocation, and arthritis by various tribal communities of India. Our previous study confirmed the anti-inflammatory efficacy of the plant through in silico, in vitro, and in vivo model studies. Therefore, the current research is focused on safety dose evaluation for the first-time of the whole-plant methanol extract (EDME) of E. diffusum through appropriate in silico, in vitro, and in vivo approaches.

METHOD

The whole plant, along with its rhizomes, was collected, and the methanol extract was prepared. The in silico ADMET study was performed to predict the pharmacokinetics profile and toxicity of all the identified phyto-compounds of EDME previously screened by GC-MS study. In vitro cytotoxicity study of EDME was performed using two cell lines: kidney (HEK293) and liver (Huh7) cell lines. The in vivo toxicity study of EDME was validated by the acute toxicity (OECD 423, 2002) and sub-acute toxicity assays (OECD 407, 2008) in the Wistar Albino rat model.

RESULTS

The in silico ADMET study of all 47 bioactives predicted good pharmacokinetic and low toxicity profiles. In vitro cytotoxicity showed higher IC50 values of EDME viz., 672 ± 15.7 μg/mL and 1698 ± 6.54 μg/mL for both kidney (HEK293) and liver (Huh7) cell lines, respectively, which were considered as low-toxic. Based on acute oral toxicity, the LD50 value of the extract was considered "non-toxic" up to a feeding range of 2000 mg/kg of body weight. The regular consumption of the extract for an extended period (28 days) was also qualified as safe based on the body and organ weight, hematological, biochemical, and histoarchitecture results in the sub-acute toxicity assay.

CONCLUSION

The detailed in silico, in vitro, in vivo (acute and sub-acute oral toxicity) studies gave us a new insight to the safety dose evaluation of Equisetum diffusum, which may serve as a reliable documentation for undertaking the experimental validation of the ethnobotanical uses of the plant which would help in the field of drug development for the treatment of inflammation related complications.

Combination of ligand‑based and structure‑based virtual screening for the discovery of novel Janus kinase 2 inhibitors against philadelphia-negative myeloproliferative neoplasms

The activating V617F mutation in Janus kinase 2 (JAK2) has been shown to be the major cause for classic Philadelphia-negative myeloproliferative neoplasms (MPNs). Thus, the development of pharmacologic JAK2 inhibitors is an essential move in combating MPNs. In this study, screening methods examining both ligands and their structures were developed to discover novel JAK2 inhibitors from the ChemDiv database with virtual screening identifying 886 candidate inhibitors. Next, these compounds were further filtered using ADMET, drug likeliness, and PAINS filtering, which reduced the compound number even further. This consolidated list of candidate compounds (n = 49) was then evaluated biologically at molecular level and the highest performing inhibitor with a novel scaffold was selected for further examination. This candidate inhibitor, CD4, was then subjected to molecular dynamics studies, with complex stability, root-mean-square deviation, radius of gyration, binding free energy, and binding properties all examined. The result suggested that CD4 interacts with JAK2 and that the CD4-JAK2 complex is stable. This study was able to identify a candidate inhibitor that warrants further examination and optimization and may potentially serve as a future MPN treatment.