Drug discovery beyond the 'rule-of-five'

Novel imidazo[2,1-b]thiazoles and imidazo[1,2-a]pyridines tethered with indolinone motif as VEGFR-2 inhibitors and apoptotic inducers: Design, synthesis and biological evaluations

The current study investigates the anticancer and VEGFR-2 inhibitory activities of 16 novel indolinone-grafted imidazo[2,1-b]thiazole and imidazo[1,2-a]pyridine derivatives (6a-h and 10a-h). The structures of these target compounds were confirmed using elemental and spectral analyses. All compounds were evaluated for their VEGFR-2 inhibitory activity in vitro, with eight compounds demonstrating promising results, exhibiting IC50 values in the sub-micromolar range (0.22 μM - 0.95 μM). Additionally, the anticancer potential of these compounds was assessed using an MTT assay against two breast cancer cell lines, MCF-7 and MDA-MB-231. Compounds 6a, 6f, 6 h, and 10f showed superior performance (IC50 = 9.79, 8.78, 8.35, and 10.88 µM, respectively) compared to the reference drug cisplatin (IC50 = 11.50 µM) against MDA-MB-231 cells. Based on their consistent VEGFR-2 inhibitory activity, compounds 6a, 6 h, and 10f were selected for further analysis. Molecular docking studies with VEGFR-2 (PDB ID: 4AGD) revealed binding behaviors similar to the co-crystallized ligand sunitinib. Among the reported target molecules, compound 10f exhibited the most desirable characteristics in terms of efficacy and safety and was further analyzed using density-functional theory (DFT) simulations to better understand its physical properties.

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.

Functional analysis, virtual screening, and molecular dynamics revealed potential novel drug targets and their inhibitors against cardiovascular disease in human

Cardiovascular disease (CVD) is a group of diseases, affecting the human heart and accounting for 30% of deaths worldwide. Major CVDs include heart failure, hypertension, stroke, etc. Various therapeutics are available against CVD, still there is a dire need to find out potential protein drug targets to reduce economic burden and mortality rate. Goal of the current study was to utilize sequential computational techniques to find the best cardiovascular drug targets and their inhibitors. Common human cardiovascular targets of both databases (GeneCards and Uniprot) were subjected to bioinformatics analyses. Purpose was to validate putative therapeutic targets employing the structure-based bioinformatics methods to determine their physiochemical properties and biological processes. Three stable proteins, that have 0 transmembrane helices, and possess biological processes were screened as potential protein-based therapeutic targets: Hemoglobin subunit beta (HBB), Gamma-enolase (ENO2), and Cholesteryl ester transfer protein (CETP). Tertiary structures of target proteins were retrieved from PDB, and molecular docking technique was utilized to evaluate a library of 5000 phytochemicals against the interacting residues of the target protein as well as their respective standard drugs through MOE and Pyrx software. Top five phytochemicals (d-Sesamin, 1,3-benzodioxole, Sativanone, Thiamine, and Cajanol) were identified based on their RMSD and docking scores as compared to their standard drugs. The docking studies were also validated by MM-GBSA binding free energy and molecular dynamics simulations. According to the study's findings, these phytochemicals may eventually be used as drugs to treat CVD. Further in vitro testing is required to confirm their efficacy and drug potency.Communicated by Ramaswamy H. Sarma.

Drug-likeness analysis, in silico ADMET profiling of compounds in Kedrostis foetidissima (Jacq.) Cogn, and antibacterial activity of the plant extract

Plants are a treasure trove of bioactive compounds. Kedrostis foetidissima (Jacq.) Cogn. has many important phytoconstituents like cucurbitacins, rutin, and quercitin compounds. Among these compounds, Quercetin-3-O- Rhamnoside (1) has antioxidant, anti-inflammatory, anticancer properties. Rutin (2) has anti-inflammatory, antioxidant, anti-diabetic, anti-microbial, antiviral properties, 7, 10-Hexa decadienoic acid methyl ester (3) has anti-inflammatory, antioxidant, hypocholesterolemia and anticancer activities. Docosanoic acid (4) has antioxidant, α-Glucosidase inhibitory activity. 3,7,11,15-Tetra methyl hexa decan-1-ol (5) has antiviral properties. Cucurbitacin-B (6) has antipyretic, analgesic, anti-inflammatory, antimicrobial, and antitumor activities. Performance of experimental studies on phytochemicals become more difficult as the availability of compounds in small quantities, hence the computational methods becomes important for drug discovery. Based on their biological activity, compounds 1-6 were tested for in silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling and drug-likeness properties using the Swiss ADME online web server and the pkCSM server. All the studied compounds obey Lipinski's rule of five except compounds 1 and 2 with two and three violations each. The entire selected compounds have a good bioavailability score in the recommended range of 0 to 1. Compound 4 has high (0.85) and compounds 1 and 2 have low (0.17) oral bioavailability scores. All the selected compounds from Kedrostis foetidissima have strong pharmacological activities. Supporting this, the selected plant methanol extracts of leaf, stem callus, and tuber have shown well in vitro antibacterial activity against Bacillus subtilis, Escherichia coli, and Proteus vulgaris. Therefore, these compounds may be developed into drug molecules with additional clinical research.

In-silico screening and identification of potential drug-like compounds for dengue-associated thrombocytopenia from Carica papaya leaf extracts

Dengue virus is a mosquito-borne pathogen that causes a variety of illnesses ranging from mild fever to severe and fatal dengue haemorrhagic fever or dengue shock syndrome. One of the major clinical manifestations of severe dengue infection is thrombocytopenia. The dengue non-structural protein 1 (NS1) is the primary protein that stimulates immune cells via toll-like receptor 4 (TLR4), induces platelets, and promotes aggregation, which could result in thrombocytopenia. The leaf extracts of Carica papaya seem to have therapeutic benefits in managing thrombocytopenia associated with dengue. The present study focuses on understanding the underlying mechanism of the use of papaya leaf extracts in treating thrombocytopenia. We have identified 124 phytocompounds that are present in the papaya leaf extract. The pharmacokinetics, molecular docking, binding free energy calculations, and molecular dynamic simulations were performed to investigate the drug-like properties, binding affinities, and interaction of phytocompounds with NS1 protein as well as the interactions of NS1 with TLR4. Three phytocompounds were found to bind with the ASN130, a crucial amino acid residue in the active site of the NS1 protein. Thus, we conclude that Rutin, Myricetin 3-rhamnoside, or Kaempferol 3-(2''-rhamnosylrutinoside) may serve as promising molecules by ameliorating thrombocytopenia in dengue-infected patients by interfering the interaction of NS1 with TLR4. These molecules can serve as drugs in the management of dengue-associated thrombocytopenia after verifying their effectiveness and assessing the drug potency, through additional in-vitro assays.Communicated by Ramaswamy H. Sarma.

Fenamates and ibuprofen as foundational components in the synthesis of innovative, targeted COX-2 anti-inflammatory drugs, undergoing thorough biopharmacological assessments and in-silico computational studies

Cyclooxygenase-2 plays a vital role in inflammation by catalyzing arachidonic acid conversion toward prostaglandins, making it a prime therapeutic objective. Selective COX-2 inhibitors represent significant progress in anti-inflammatory therapy, offering improved efficacy and fewer side effects. This study describes the synthesis of novel anti-inflammatory compounds from established pharmaceutically marketed agents like fenamates III-V and ibuprofen VI. Through rigorous in vitro testing, compounds 7b-c, and 12a-b demonstrated substantial in vitro selective inhibition, with IC50 values of 0.07 to 0.09 μM, indicating potent pharmacological activity. In vivo assessment, particularly focusing on compound 7c, revealed significant anti-inflammatory effects. Markedly, it demonstrated the highest inhibition of paw thickness (58.62 %) at the 5-hr mark compared to the carrageenan group, indicating its potency in mitigating inflammation. Furthermore, it exhibited a rapid onset of action, with a 54.88 % inhibition observed at the 1-hr mark. Subsequent comprehensive evaluations encompassing analgesic efficacy, histological characteristics, and toxicological properties indicated that compound 7c did not induce gastric ulcers, in contrast to the ulcerogenic tendency associated with mefenamic acid. Moreover, compound 7c underwent additional investigations through in silico methodologies such as molecular modelling, field alignment, and density functional theory. These analyses underscored the therapeutic potential and safety profile of this novel compound, warranting further exploration and development in the realm of pharmaceutical research.

Computational Applications: Beauvericin from a Mycotoxin into a Humanized Drug

Drug discovery was initially attributed to coincidence or experimental research. Historically, the traditional approaches were complex, lengthy, and expensive, entailing costly random screening of synthesized compounds or natural products coupled with in vivo validation largely depending on the availability of appropriate animal models. Currently, in silico modeling has become a vital tool for drug discovery and repurposing. Molecular docking and dynamic simulations are being used to find the best match between a ligand and a molecule, an approach that could help predict the biomolecular interactions between the drug and the target host. Beauvericin (BEA) is an emerging mycotoxin produced by the entomopathogenic fungus Beauveria bassiana, being originally studied for its potential use as a pesticide. BEA is now considered a molecule of interest for its possible use in diverse biotechnological applications in the pharmaceutical industry and medicine. In this manuscript, we provide an overview of the repurposing of BEA as a potential therapeutic agent for multiple diseases. Furthermore, considerable emphasis is given to the fundamental role of in silico techniques to (i) further investigate the activity spectrum of BEA, a secondary metabolite, and (ii) elucidate its mode of action.

In silico identification and in vitro validation of alpha-hederin as a potent inhibitor of Wnt/β-catenin signaling pathway in breast cancer stem cells

Cancer stem cells (CSCs) play a vital role in metastasis, recurrence and chemoresistance in breast cancer. β-catenin, which is a frequently over activated protein in CSCs, binds to T-cell factor/lymphoid enhancer factor (Tcf/Lef) family transcription factors leading to ectopic expression of Wnt pathway responsive genes necessary for the maintenance and action of CSCs. With the aim of identifying a small molecules that can effectively eliminate CSCs, molecular docking studies were performed against the Tcf/Lef binding hotspot on β-catenin using a library of 100 natural or synthetic small molecules. Small molecule ligands giving docking energy better than - 7 kcal/mol were further investigated by binding interactions analysis and molecular dynamics (MD) simulations. These compounds were then investigated in vitro, for cytotoxicity against CSCs isolated from MDA-MB-231 triple negative breast cancer cells. Alpha-hederin (AH) was identified as the only compound in the selected library that has cytotoxicity against breast CSCs. AH was further investigated for it's ability to regulate Wnt pathway target genes (Cyclin D1 and CD44)and the tumor suppressor p53by real-time quantitative PCR. Absorption, distribution, metabolism, excretion and toxicity properties of the AH was predicted in silico. AH significantly down regulated the transcription of Cyclin D1 and CD44 while up-regulating the transcription of p53. AH was predicted to have acceptable drug likeness. Although AH is currently known to inhibit the growth of various cancer cells in vitro, present study demonstrated for the first time that it is a potent inhibitor of Wnt/β-catenin signaling pathway and induce apoptosis in breast CSCs.

Variolin B from sea sponge against lung cancer: a multitargeted molecular docking with fingerprinting and molecular dynamics simulation study

Lung Cancer is the one that causes more fatalities in the world compared to other cancers, and its uniqueness is that it can be found in both males and females. However, recent data has shown that males are more affected due to lifestyle habits like smoking, tobacco consumption and inhaling polluted air. The World Health Organization has kept lung cancer on its priority list as it causes 1.8 million deaths worldwide each year, and the predictions show that the cases are going to increase year by year, and by 2050, there can be 3.8 million new cases and 3.2 million deaths, and the global health system is not prepared for it. Also, finding drug candidates that can help shrink cancerous cells and lead to their death is essential to reduce global mortality. The system needs drug compounds that can inhibit multiple paths together not to enter drug resistance quickly and to reduce costs. Our study identified a compound named Variolin B (DB08694) that belongs to the organic compounds class of pyrrolopyridines. The identified compound can inhibit multiple proteins, drastically reducing the global burden. Variolin B was identified as a potential candidate against lung cancer using the multisampling algorithm such as HTVS, SP, and XP, followed by MM\GBSA calculations showing the docking score of -9.245 Kcal/mol to -5.92 Kcal/mol. Also, we have validated it with ADMET predictions and molecular fingerprinting to analyse the interaction patterns. Further, the study was extended to molecular dynamics simulations for 100 ns to understand the complex stability and simulative interactions. The complex's overall molecular dynamics simulation helped us understand that the identified candidate is stable with the lowest deviation and fluctuations.Communicated by Ramaswamy H. Sarma.

Modification of ibuprofen to improve the medicinal effect; structural, biological, and toxicological study

Ibuprofen is classified as a non-steroidal anti-inflammatory drug (NSAID) that is employed as an initial treatment option for its non-steroidal anti-inflammatory, pain-relieving, and antipyretic properties. However, Ibuprofen is linked to specific well-known gastrointestinal adverse effects like ulceration and gastrointestinal bleeding. It has been linked to harmful effects on the liver, kidney, and heart. The purpose of the study is to create novel and potential IBU analogue with reduced side effects with the enhancement of their medicinal effects, so as to advance the overall safety profile of the drug. The addition of some novel functional groups including CH3, F, CF3, OCF3, Cl, and OH at various locations in its core structure suggestively boost the chemical as well as biological action. The properties of these newly designed structures were analyzed through chemical, physical, and spectral calculations using Density Functional Theory (DFT) and time-dependent DFT through B3LYP/6-31 g (d,p) basis set for geometry optimization. Molecular docking and non-bonding interaction studies were conducted by means of the human prostaglandin synthase protein (PDB ID: 5F19) to predict binding affinity, interaction patterns, and the stability of the protein-drug complex. Additionally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and PASS (Prediction of Activity Spectra for Substances) predictions were employed to evaluate the pharmacokinetic and toxicological properties of these structures. Importantly, most of the analogues displayed reduced hepatotoxicity, nephrotoxicity, and carcinogenicity in comparison to the original drug. Moreover, molecular docking analyses indicated improved medicinal outcomes, which were further supported by pharmacokinetic calculations. Together, these findings suggest that the modified structures have reduced adverse effects along with improved therapeutic action compared to the parent drug.

Navigating the Chemical Space of ENR Inhibitors: A Comprehensive Analysis

Antimicrobial resistance is a global health threat that requires innovative strategies against drug-resistant bacteria. Our study focuses on enoyl-acyl carrier protein reductases (ENRs), in particular FabI, FabK, FabV, and InhA, as potential antimicrobial agents. Despite their promising potential, the lack of clinical approvals for inhibitors such as triclosan and isoniazid underscores the challenges in achieving preclinical success. In our study, we curated and analyzed a dataset of 1412 small molecules recognized as ENR inhibitors, investigating different structural variants. Using advanced cheminformatic tools, we mapped the physicochemical landscape and identified specific structural features as key determinants of bioactivity. Furthermore, we investigated whether the compounds conform to Lipinski rules, PAINS, and Brenk filters, which are crucial for the advancement of compounds in development pipelines. Furthermore, we investigated structural diversity using four different representations: Chemotype diversity, molecular similarity, t-SNE visualization, molecular complexity, and cluster analysis. By using advanced bioinformatics tools such as matched molecular pairs (MMP) analysis, machine learning, and SHAP analysis, we were able to improve our understanding of the activity cliques and the precise effects of the functional groups. In summary, this chemoinformatic investigation has unraveled the FAB inhibitors and provided insights into rational antimicrobial design, seamlessly integrating computation into the discovery of new antimicrobial agents.

Chemico-pharmacological evaluation of the methanolic leaf extract of Catharanthus ovalis: GC-MS/MS, in vivo, in vitro, and in silico approaches

Introduction: Natural plant-based medicines have gained popularity recently as a major source of inventive, risk-free, and more potent secondary bioactive compounds with medicinal potential. Catharanthus ovalis is a perennial shrub containing various indole alkaloids cultivated extensively for local medical purposes. Methods: This research is conducted to identify the phytocompounds present in the leaves of C. ovalis and its central and peripheral analgesic, thrombolytic, and membrane-stabilizing activities through tail immersion, acetic acid-induced writhing, human blood clot lysis, and erythrocyte lysis by heat and hypotonic solution methods, respectively. Results and discussion: A total of 39 compounds were identified using GC-MS/MS techniques, including hexadecanoic acid, methyl ester (56.749%), methyl stearate (29.782%), carvacrol and its TBDMS derivative (12.586%), and 9-octadecenoic acid, methyl ester, (E)-] (9.297%) presented in high quantity. The highest tail immersion latency was observed for the 600 mg/kg extract of C. ovalis crude extract. Both 400 and 600 mg/kg doses of C. ovalis crude extract exhibited prominent peripheral analgesic activity. The maximum thrombolytic effect was observed by DCM soluble fraction extract by inhibiting 54.87% of the clot. However, the aqueous-soluble fraction of this extract manifested an excellent membrane-stabilizing effect by showing 73.98% and 87.51% hemolysis against heat- and hypotonic-induced hemolysis, respectively. Some of the compounds were identified as active agents against different receptors related to these diseases, which supported the findings of in vitro and in vivo tests. Conclusion: Further investigation needs to be conducted to specify and identify the exact mechanism of action of these compounds.

Neuroprotective effect of the traditional decoction Tian-Si-Yin against Alzheimer's disease via suppression of neuroinflammation

ETHNOPHARMACOLOGICAL RELEVANCE

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease among old adults. As a traditional Chinese medicine, the herbal decoction Tian-Si-Yin consists of Morinda officinalis How. and Cuscuta chinensis Lam., which has been widely used to nourish kidney. Interestingly, Tian-Si-Yin has also been used to treat dementia, depression and other neurological conditions. However, its therapeutic potential for neurodegenerative diseases such as AD and the underlying mechanisms remain unclear.

AIM OF THE STUDY

To evaluate the therapeutic effect of the herbal formula Tian-Si-Yin against AD and to explore the underlying mechanisms.

MATERIALS AND METHODS

The N2a cells treated with amyloid β (Aβ) peptide or overexpressing amyloid precursor protein (APP) were used to establish cellular models of AD. The in vivo anti-AD effects were evaluated by using Caenorhabditis elegans and 3 × Tg-AD mouse models. Tian-Si-Yin was orally administered to the mice for 8 weeks at a dose of 10, 15 or 20 mg/kg/day, respectively. Its protective role on memory deficits of mice was examined using the Morris water maze and fear conditioning tests. Network pharmacology, proteomic analysis and ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry (UHPLC-MS/MS) were used to explore the underlying molecular mechanisms, which were further investigated by Western blotting and immunohistochemistry.

RESULTS

Tian-Si-Yin was shown to improve cell viability of Aβ-treated N2a cells and APP-expressing N2a-APP cells. Tian-Si-Yin was also found to reduce ROS level and extend lifespan of transgenic AD-like C. elegans model. Oral administration of Tian-Si-Yin at medium dose was able to effectively rescue memory impairment in 3 × Tg mice. Tian-Si-Yin was further shown to suppress neuroinflammation by inhibition of glia cell activation and downregulation of inflammatory cytokines, diminishing tau phosphoralytion and Aβ deposition in the mice. Using UHPLC-MS/MS and network pharmacology technologies, 17 phytochemicals from 68 components of Tian-Si-Yin were identified as potential anti-AD components. MAPK1, BRAF, TTR and Fyn were identified as anti-AD targets of Tian-Si-Yin from network pharmacology and mass spectrum.

CONCLUSIONS

This study has established the protective effect of Tian-Si-Yin against AD and demonstrates that Tian-Si-Yin is capable of improving Aβ level, tau pathology and synaptic disorder by regulating inflammatory response.

In silico evaluation of pharmacokinetics properties of withanolides and simulation of their biological activities against Alzheimer's disease

The withanolides are naturally occurring steroidal lactones found mainly in plants of the Solanaceae family. The subtribe Withaninae includes species like Withania sominifera, which are a source of many bioactive withanolides. In this work, we selected and evaluate the ADMET-related properties of 91 withanolides found in species of the subtribe Withaninae computationally, to predict the relationship between their structures and their pharmacokinetic profiles. We also evaluated the interaction of these withanolides with known targets of Alzheimer's disease (AD) through molecular docking and molecular dynamics. Withanolides presented favorable pharmacokinetic properties, like high gastrointestinal absorption, lipophilicity (logP ≤ 5), good distribution and excretion parameters, and a favorable toxicity profile. The specie Withania aristata stood out as an interesting source of the promising withanolides classified as 5-ene with 16-ene or 17-ene. These withanolides presented a favourable pharmacokinetic profile and were also highlighted as the best candidates for inhibition of AD-related targets. Our results also suggest that withanolides are likely to act as cholinesterase inhibitors by interacting with the catalytic pocket in an energy favorable and stable way.Communicated by Ramaswamy H. Sarma.

Alzheimer's disease: In silico study of rosemary diterpenes activities

The global surge in Alzheimer's disease poses a significant public health concern. In response, we study the efficacy of carnosic acid and related abietane-type diterpenes extracted from rosemary as acetylcholinesterase (AChE) inhibitors. Our analyses, using in silico techniques, encompassed all the compounds within this extract. Through molecular docking, we explored how these compounds interact with the active site of the AChE protein. The docking scores, ranging from -5.560 Kcal/mol to -7.270 Kcal/mol, indicate robust binding affinities. Assessment of the ADME/T (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) properties and pharmacokinetics of these compounds reveal favorable profiles for all the tested substances. These encouraging results suggest the potential of these compounds as candidates for further development to prevent and/or treat Alzheimer's disease. Among these compounds, we find rosmanol as the most likely candidate for further research and clinical trials to validate their efficacy.

Isolation of bioactive phytochemicals from Crinum asiaticum L. along with their cytotoxic and TRAIL-resistance abrogating prospect assessment

Crinum asiaticum L. (Amaryllidaceae) is a perennial bulbous herb, locally utilized for possessing multifaceted pharmacological properties including anticancer, immune-stimulating, analgesic, antiviral, antimalarial, antibacterial and antifungal, in addition to its popularity as an aesthetic plant. Separation of MeOH extract of C. asiaticum leaves yielded three known compounds as cycloneolitsol (1), hippeastrine (2) and β-sitosterol (3). Among these, compounds 1 and 2 were subjected to the cytotoxic assay and found that they induced mild effect against HCT116, Huh7 and DU145 cell lines with the IC50 values from 73.76 to 132.53 μM. When tested for TRAIL-resistance abrogating activity, 1 (100 μM) along with TRAIL (100 ng/mL) showed moderate activity in AGS cells producing 25 % more inhibition than the agent alone. Whereas 2 (20 and 30 μM) in combination with TRAIL (100 ng/mL) exhibited strong activity in abrogating TRAIL-resistance and caused 34 % and 36 % more inhibition in AGS cells, respectively. The in-silico studies of compound 2 revealed high docking hits with the TRAIL-associated anti-apoptotic proteins which give a justification for the regulatory interactions to induce such abrogating activity. It is still recommended to conduct further investigations to understand their exact molecular mechanism.

Identification of new pharmacophore against SARS-CoV-2 spike protein by multi-fold computational and biochemical techniques

COVID-19 appeared as a highly contagious disease after its outbreak in December 2019 by the virus, named SARS-CoV-2. The threat, which originated in Wuhan, China, swiftly became an international emergency. Among different genomic products, spike protein of virus plays a crucial role in the initiation of the infection by binding to the human lung cells, therefore, SARS-CoV-2's spike protein is a promising therapeutic target. Using a combination of a structure-based virtual screening and biochemical assay, this study seeks possible therapeutic candidates that specifically target the viral spike protein. A database of ~ 850 naturally derived compounds was screened against SARS-CoV-2 spike protein to find natural inhibitors. Using virtual screening and inhibitory experiments, we identified acetyl 11-keto-boswellic acid (AKBA) as a promising molecule for spike protein, which encouraged us to scan the rest of AKBA derivatives in our in-house database via 2D-similarity searching. Later 19 compounds with > 85% similarity with AKBA were selected and docked with receptor binding domain (RBD) of spike protein. Those hits declared significant interactions at the RBD interface, best possess and excellent drug-likeness and pharmacokinetics properties with high gastrointestinal absorption (GIA) without toxicity and allergenicity. Our in-silico observations were eventually validated by in vitro bioassay, interestingly, 10 compounds (A3, A4, C3, C6A, C6B, C6C, C6E, C6H, C6I, and C6J) displayed significant inhibitory ability with good percent inhibition (range: > 72-90). The compounds C3 (90.00%), C6E (91.00%), C6C (87.20%), and C6D (86.23%) demonstrated excellent anti-SARS CoV-2 spike protein activities. The docking interaction of high percent inhibition of inhibitor compounds C3 and C6E was confirmed by MD Simulation. In the molecular dynamics simulation, we observed the stable dynamics of spike protein inhibitor complexes and the influence of inhibitor binding on the protein's conformational arrangements. The binding free energy ΔGTOTAL of C3 (-38.0 ± 0.08 kcal/mol) and C6E (-41.98 ± 0.08 kcal/mol) respectively indicate a strong binding affinity to Spike protein active pocket. These findings demonstrate that these molecules particularly inhibit the function of spike protein and, therefore have the potential to be evaluated as drug candidates against SARS-CoV-2.

Anti-diabetic drug discovery using the bioactive compounds of Momordica charantia by molecular docking and molecular dynamics analysis

Diabetes mellitus (DM) is a multifactorial life-threatening endocrine disease characterized by abnormalities in glucose metabolism. It is a chronic metabolic disease that involves multiple enzymes such as α-amylase and α-glucosidases. Inhibition of these enzymes has been identified as a promising method for managing diabetes, and researchers are currently focusing on discovering novel α-amylase and α-glucosidase inhibitors for diabetes therapy. Hence, we have selected 12 bioactive compounds from the Momordica charantia (MC) plant and performed a virtual screening and molecular dynamics investigation to identify natural inhibitors of α-amylase and α-glucosidases. Our in silico result revealed that phytocompound Rutin showed the highest binding affinity against α-amylase (1HNY) enzymes at (-11.68 kcal/mol), followed by Karaviloside II (-9.39), Momordicoside F (-9.19), Campesterol (-9.11. While docking against α-glucosidases (4J5T), Rutin again showed the greatest binding affinity (-11.93 kcal/mol), followed by Momordicine (-9.89), and Campesterol (-8.99). Molecular dynamics (MD) simulation research is currently the gold standard for drug design and discovery. Consequently, we conducted simulations of 100 nanoseconds (ns) to assess the stability of protein-ligand complexes based on parameters like RMSD, RMSF, RG, PCA, and FEL. The significance of our findings indicates that rutin from MC might serve as an effective natural therapeutic agent for diabetes management due to its strongest binding affinities with α-amylase and α-glucosidase enzymes. Further research in animals and humans is essential to validate the efficacy of these drug molecules.Communicated by Ramaswamy H. Sarma.

Evaluating physiochemical properties of FDA-approved orally administered drugs

INTRODUCTION

Analyses of orally administered FDA-approved drugs from 1990 to 1993 enabled the identification of a set of physiochemical properties known as Lipinski's Rule of Five (Ro5). The original Ro5 and extended versions still remain the reference criteria for drug development programs. Since many bioactive compounds do not conform to the Ro5, we validated the relevance of and adherence to these rulesets in a contemporary cohort of FDA-approved drugs.

AREAS COVERED

The authors noted that a significant proportion of FDA-approved orally administered parent compounds from 2011 to 2022 deviate from the original Ro5 criteria (~38%) or the Ro5 with extensions (~53%). They then evaluated if a contemporary Ro5 criteria (cRo5) could be devised to better predict oral bioavailability. Furthermore, they discuss many case studies showcasing the need for and benefit of increasing the size of certain compounds and cover several evolving strategies for improving oral bioavailability.

EXPERT OPINION

Despite many revisions to the Ro5, the authors find that no single proposed physiochemical rule has universal concordance with absolute oral bioavailability. Innovations in drug delivery and formulation have dramatically expanded the range of physicochemical properties and the chemical diversity for oral administration.

Computational drug discovery on human immunodeficiency virus with a customized long short-term memory variational autoencoder deep-learning architecture

Despite attempts to control the spread of human immunodeficiency virus (HIV) through the use of anti-HIV medications, the absence of an effective vaccine continues to present a significant obstacle. In addition, the development of drug resistance by HIV underscores the necessity for computational drug discovery methods to identify novel therapies. This investigation specifically focused on employing a long short-term memory (LSTM) variational autoencoder deep-learning architecture for computational drug discovery in relation to HIV. Our data set comprised simplified molecular input line entry system (SMILES)-encoded compounds, which were used to train the LSTM autoencoder. Remarkably, our model achieved a training accuracy of 91%, with a data set containing 1377 compounds. Leveraging the generative model derived from the training phase, we generated potential new drugs for combating HIV and assessed their interaction with the virus using a previously developed artificial intelligence model. Lastly, we verified the drug likeliness of our computationally generated compounds in accordance with Lipinski's rule of five. Overall, our study presents a promising approach to computational drug discovery in the ongoing battle against HIV.

Guiding the Way: Traditional Medicinal Chemistry Inspiration for Rational Gram-Negative Drug Design

The discovery and development of small-molecule therapeutics effective against Gram-negative pathogens are highly challenging tasks. Most compounds that are active in biochemical settings fail to exhibit whole-cell activity. The major reason for this lack of activity is the effectiveness of bacterial cell envelopes as permeability barriers. These barriers originate from the nutrient-selective outer membranes, which act synergistically with polyspecific efflux pumps. Guiding principles to enable rational optimization of small molecules for efficient penetration and intracellular accumulation in Gram-negative bacteria would have a transformative impact on the discovery and design of chemical probes and therapeutics. In this Perspective, we draw on inspiration from traditional medicinal chemistry approaches for eukaryotic drug design to present a broader call for action in developing comparable approaches for Gram-negative bacteria.

In silico simulation of hyperoside, isoquercetin, quercetin, and quercitrin as potential antivirals against the pNP868R protein of African swine fever virus

Background and Aim

African swine fever (ASF) causes disease in pigs with up to 100% mortality rates. There is no effective vaccine to protect against it. This study aimed to perform in silico docking of ASF virus (ASFV) pNP868R protein with potential flavonoid ligands to identify ligands that interfere with mRNA cap formation.

Materials and Methods

The ASFV pNP868R protein was tested with hyperoside, isoquercetin, quercetin, and quercitrin in this in silico simulation. ASFV pNP868R protein was extracted from the Research Collaboration for Structural Bioinformatics Protein Data Bank (RCSB PDB) database with PDB ID 7D8U (https://www.rcsb.org/structure/7D8U). Standard ligands were separated from proteins using UCSF Chimera 1.13. The standard ligand was redocked to protein using AutoDockTools 1.5.6 with the AutoDock4 method for validation. In the docking process, the grid box size was 40 × 40 × 40 Å3 with x, y, and z coordinates of 16.433, -43.826, and -9.496, respectively. The molecular docking process of the proposed ligand-protein complex can proceed if the standard ligand position is not significantly different from its original position in the viral protein's pocket. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (RoG) of the hyperoside with the lowest energy binding need to be analyzed with molecular dynamics using Groningen machine for chemical simulation 5.1.1.

Results

Molecular docking and dynamic simulation revealed that hyperoside had the most stable and compact binding to the pNP868R protein. Hyperoside binds to the protein at the minimum energy of -9.07 KJ/mol. The RMSD, RMSF, and RoG values of 0.281 nm, 0.2 nm, and 2.175 nm, respectively, indicate the stability and compactness of this binding.

Conclusion

Hyperoside is the most likely antiviral candidate to bind to the pNP868R protein in silico. Therefore, it is necessary to test whether this flavonoid can inhibit mRNA capping in vitro and elicit the host immune response against uncapped viral mRNA.

Identification of potential inhibitors against Escherichia coli Mur D enzyme to combat rising drug resistance: an in-silico approach

Indiscriminate use of anti-microbial agents has resulted in the inception, frequency, and spread of antibiotic resistance among targeted bacterial pathogens and the commensal flora. Mur enzymes, playing a crucial role in cell-wall synthesis, are one of the most appropriate targets for developing novel inhibitors against antibiotic-resistant bacterial pathogens. In the present study, in-silico high-throughput virtual (HTVS) and Standard-Precision (SP) screening was carried out with 0.3 million compounds from several small-molecule libraries against the E. coli Mur D enzyme (PDB ID 2UUP). The docked complexes were further subjected to extra-precision (XP) docking calculations, and highest Glide-score compound was further subjected to molecular simulation studies. The top six virtual hits (S1-S6) displayed a glide score (G-score) within the range of -9.013 to -7.126 kcal/mol and compound S1 was found to have the highest stable interactions with the Mur D enzyme (2UUP) of E. coli. The stability of compound S1 with the Mur D (2UUP) complex was validated by a 100-ns molecular dynamics simulation. Binding free energy calculation by the MM-GBSA strategy of the S1-2UUP (Mur D) complex established van der Waals, hydrogen bonding, lipophilic, and Coulomb energy terms as significant favorable contributors for ligand binding. The final lead molecules were subjected to ADMET predictions to study their pharmacokinetic properties and displayed promising results, except for certain modifications required to improve QPlogHERG values. So, the compounds screened against the Mur D enzyme can be further studied as preparatory points for in-vivo studies to develop potential drugs. HIGHLIGHTSE.coli is a common cause of urinary tract infections.E.coli MurD enzyme is a suitable target for drug development.Novel inhibitors against E.coli MurD enzyme were identified.Molecular dynamics studies identified in-silico potential of identified compound.ADMET predictions and Lipinski's rule of five studies showed promising results.Communicated by Ramaswamy H. Sarma.

Biochemical and molecular docking-based strategies of Acalypha indica and Boerhavia diffusa extract by targeting bacterial strains and cancer proteins

Antibiotic-resistant microbes have emerged around the world, presenting a risk to health. Plant-derived drugs have become a potential source for the production of antibiotic-resistant drugs and cancer therapies. In this study, we investigated the antibacterial, cytotoxic and antioxidant properties of Acalypha indica and Boerhavia diffusa, and conducted in silico molecular docking experiments against EGFR and VEGFR-2 proteins. The metabolic extract of A. indica inhibited Streptococcus iniae and Staphylococcus sciuri with inhibition zones of 21.66 ± 0.57 mm and 20.33 ± 0.57 mm, respectively. The B. diffusa leaf extract produced inhibition zones of 20.3333 ± 0.5773 mm and 20.33 ± 0.57 mm against Streptococcus iniae and Edwardsiella anguillarum, respectively. A. indica and B. diffusa extracts had toxicities of 162.01 μg/ml and 175.6 μg/ml, respectively. Moreover, B. diffusa (IC50 =154.42 µg/ml) leaf extract exhibited moderately higher antioxidant activity compared with the A. indica (IC50 = 218.97 µg/ml) leaf extract. Multiple interactions were observed at Leu694, Met769 and Leu820 sites for EGFR and at Asp1046 and Cys1045 sites for VEGFR during the molecular docking study. CID-235030, CID-70825 and CID-156619353 had binding energies of -7.6 kJ/mol, -7.5 kJ/mol and -7.6 kJ/mol, respectively, with EGFR protein. VEGFR-2 protein had docking energies of -7.5 kJ/mol, -7.6 kJ/mol and -7.3 kJ/mol, respectively, for CID-6420353, CID-156619353 and CID-70825 compounds. The MD simulation trajectories revealed the hit compound; CID-235030 and EGFR complex, CID-6420353 and VEGFR-2 exhibit stable profile in the root mean square deviation (RMSD), radius of gyration (Rg), solvent accessible surface area (SASA), hydrogen bond and root mean square fluctuation (RMSF) and the binding free energy by MM-PBSA method. This study indicates that methanol extracts of A. indica and B. diffusa may play a crucial role in developing antibiotic-resistant and cancer drugs.Communicated by Ramaswamy H. Sarma.

Computational analysis of potential drug-like compounds from Solanum torvum - A promising phytotherapeutics approach for the treatment of diabetes

Diabetes mellitus (DM) is a global pandemic that is characterized by high blood glucose levels. Conventional treatments have limitations, leading to the search for natural alternatives. This study focused on Solanum torvum (STV), a medicinal plant, to identify potential anti-diabetic compounds using molecular docking and molecular dynamics simulations. We focused on identifying natural inhibitors of two key enzymes involved in glucose metabolism: α-amylase (1HNY) and α-glucosidase (4J5T). In our preliminary docking study, rutin showed the highest binding affinity (-11.58 kcal/mol) to α-amylase, followed by chlorogenin (-7.58 kcal/mol) and myricetin (-5.82 kcal/mol). For α-glucosidase, rutin had the highest binding affinity (-11.78 kcal/mol), followed by chlorogenin (-7.11 kcal/mol) and fisetin (-6.44 kcal/mol). Hence, chlorogenin and rutin were selected for further analysis and compared with acarbose, an FDA-approved antidiabetic drug. Comparative docking revealed that chlorogenin had the highest binding affinity of (-9.9 kcal/mol) > rutin (-8.7 kcal/mol) and > acarbose (-7.7 kcal/mol) for α-amylase. While docking with α-glucosidase, chlorogenin again had the highest binding affinity of (-9.8 kcal/mol) > compared to rutin (-9.5 kcal/mol) and acarbose (-7.9 kcal/mol). Molecular dynamics (MD) simulations were conducted to assess their stability. We simulated 100 nanoseconds (ns) trajectories to analyze their stability on various parameters, including RMSD, RMSF, RG, SASA, H-bond analysis, PCA, FEL, and MM-PBSA on the six docked proteins. In conclusion, our study suggests that chlorogenin and rutin derived from STV may be effective natural therapeutic agents for diabetes management because of their strong binding affinities for the α-amylase and α-glucosidase enzymes.Communicated by Ramaswamy H. Sarma.

Natural product-derived therapies for treating drug-resistant epilepsies: From ethnopharmacology to evidence-based medicine

ETHNOPHARMACOLOGICAL RELEVANCE

Epilepsy is one of the most prevalent neurological human diseases, affecting 1% of the population in all age groups. Despite the availability of over 25 anti-seizure medications (ASMs), which are approved in most industrialized countries, approximately 30% of epilepsy patients still experience seizures that are resistant to these drugs. Since ASMs target only limited number of neurochemical mechanisms, drug-resistant epilepsy (DRE) is not only an unmet medical need, but also a formidable challenge in drug discovery.

AIM

In this review, we examine recently approved epilepsy drugs based on natural product (NP) such as cannabidiol (CBD) and rapamycin, as well as NP-based epilepsy drug candidates still in clinical development, such as huperzine A. We also critically evaluate the therapeutic potential of botanical drugs as polytherapy or adjunct therapy specifically for DRE.

METHODS

Articles related to ethnopharmacological anti-epileptic medicines and NPs in treating all forms of epilepsy were collected from PubMed and Scopus using keywords related to epilepsy, DRE, herbal medicines, and NPs. The database clinicaltrials.gov was used to find ongoing, terminated and planned clinical trials using herbal medicines or NPs in epilepsy treatment.

RESULTS

A comprehensive review on anti-epileptic herbal drugs and natural products from the ethnomedical literature is provided. We discuss the ethnomedical context of recently approved drugs and drug candidates derived from NPs, including CBD, rapamycin, and huperzine A. Recently published studies on natural products with preclinical efficacy in animal models of DRE are summarized. Moreover, we highlight that natural products capable of pharmacologically activating the vagus nerve (VN), such as CBD, may be therapeutically useful to treat DRE.

CONCLUSIONS

The review highlights that herbal drugs utilized in traditional medicine offer a valuable source of potential anti-epileptic drug candidates with novel mechanisms of action, and with clinical promise for the treatment of drug-resistant epilepsy (DRE). Moreover, recently developed NP-based anti-seizure medications (ASMs) indicate the translational potential of metabolites of plant, microbial, fungal and animal origin.

Graph Attention Network based mapping of knowledge relations between chemical spaces of Nuclear factor kappa B and Centella asiatica

The confounding nature of the innate immunity target Nuclear Factor kappa B (NF-κB) and its interaction with Centella asiatica (CA) molecules necessitate the intervention of advanced technologies, such as deep learning methods. The integration of chemical space concepts with deep learning technologies is a new way of knowledge mapping used to explore drug-target interactions, especially in molecular libraries derived from traditional medicine based molecular sources. The current constraint of virtual screening for mechanistic target hunting is the use of a binary classification model that includes active and inactive molecules from in vitro experiments to explore drug-target interaction. This study aims to explore the regulatory nature of the molecules from the inhibition and activation of the NF-κB bioassay data set and map this information for a knowledge-based analysis against the molecules of CA, a low-growing tropical plant. This finding has led to a new direction in the field, transitioning from the conventional active-inactive framework to a more comprehensive active-inactive-regulatory model. This approach can be thoroughly explored by leveraging a graph-based deep learning system. The study presents an innovative approach using a Graph Attention Network (GAT) to rank CA molecules in chemical space based on their similarity with NF-κB bioassay molecules, enabling the efficient analysis of complex relationships between molecules and their regulatory function. Graph Attention Network (GAT) overcomes the limitations of traditional deep learning models such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in handling non-Euclidean graph data and allows for a more precise understanding of similarity ranking by utilizing molecular graphs and attention behavior. By measuring similarity and arranging a matrix of similarity ranking based on GAT, deep neural ranking-based algorithms confirmed the regulatory behaviour of an innate immunity target NF-κB with the support of underlying inverse mapping in the surjective chemical spaces of NF-κB bioassays and CA molecular spaces. Overall, the study introduces new techniques for exploring the regulatory behaviour of complex targets like NF-κB. We then used t-SNE for clustering in chemical space and scaffold hunting for scaffold property analysis and identified nine CA molecules that exhibit regulatory behavior of NF-κB target and are recommended for further investigation.

Structure-Based High-Throughput Virtual Screening and Molecular Dynamics Simulation for the Discovery of Novel SARS-CoV-2 NSP3 Mac1 Domain Inhibitors

Since the emergence of SARS-CoV-2, many genetic variations within its genome have been identified, but only a few mutations have been found in nonstructural proteins (NSPs). Among this class of viral proteins, NSP3 is a multidomain protein with 16 different domains, and its largest domain is known as the macrodomain or Mac1 domain. In this study, we present a virtual screening campaign in which we computationally evaluated the NCI anticancer library against the NSP3 Mac1 domain, using Molegro Virtual Docker. The top hits with the best MolDock and Re-Rank scores were selected. The physicochemical analysis and drug-like potential of the top hits were analyzed using the SwissADME data server. The binding stability and affinity of the top NSC compounds against the NSP3 Mac1 domain were analyzed using molecular dynamics (MD) simulation, using Desmond software, and their interaction energies were analyzed using the MM/GBSA method. In particular, by applying subsequent computational filters, we identified 10 compounds as possible NSP3 Mac1 domain inhibitors. Among them, after the assessment of binding energies (ΔGbind) on the whole MD trajectories, we identified the four most interesting compounds that acted as strong binders of the NSP3 Mac1 domain (NSC-358078, NSC-287067, NSC-123472, and NSC-142843), and, remarkably, it could be further characterized for developing innovative antivirals against SARS-CoV-2.

Identification of new potent agonists for toll-like receptor 8 by virtual screening methods, molecular dynamics simulation, and MM-GBSA

Toll-like receptor 8 (TLR8), as an endosomal transmembrane receptor, plays a crucial role in the innate immune response to neoplasia and viruses. Previous studies have shown that TLR8 agonists e.g. Motolimod can be used to treat patients with last-stage cancer. In this study, in order to find new suitable ligands for TLR8, 16 PBD codes related to TLR8 complexes were collected to design the pharmacophore models using the Pharmit server. Then the PubChem, and ZINC databases were screened by them. Subsequently, the ADME-Tox features of the compounds were detected using FAF-Drugs4 and the selected compounds were docked to TLR8 (PDB: 3w3j). Molecular dynamics simulation was used to compare compounds with the best docking scores, with Motolimod in complex with TLR8. Finally, two compounds were identified, PubChem: 124126919 (A) and PubChem: 18559540 (B), each with advantages over Motolimod. As the RMSD results showed that compound A has very good flexibility, in terms of energy calculated using the MM-GBSA method, complex B and TLR8 showed the lowest energy level compared to the rest of the complexes. These observations suggest that these two compounds could be used as TLR8 agonists with the desired pharmacological features in future experimental studies.Communicated by Ramaswamy H. Sarma.

New Hybrid Compound Candidate as Photothermal Agent Based on DPP Derivatives and Toluidine Blue: A Theoretical Perspective

In this article, the synthesis of a new hybrid compound, candidate as photothermal agent, is proposed, based on TDPP (3,6-di(thiophene-2-yl)-2,5-dihydropyrrolo[3,4-c]pyrrole-1,4-dione) and toluidine blue. Electronic structure calculations at the DFT, TD-DFT and CCSD level of theories were performed to obtain ground and excited states molecular structures, photophysical properties and absorption spectrum of the hybrid and the starting compounds. Additionally, ADMET calculations were performed to predict the pharmacokinetic, metabolic and toxicity properties of the proposed compound. The results showed that the proposed compound is a strong candidate for photothermal agent since (1) it absorbs close to the near-infrared region, (2) it has low fluorescence and intersystem crossing rate constants, (3) it has accessible conical intersection with low energy barrier, (4) the compound shows lower toxicity than the well know compound toluidine blue, which is used in photodynamic therapy, (5) the compound does not show carcinogenic potential, and (6) it obeys the Lipinski's rule of five, used as a reference for the design of new pharmaceuticals.

Fragment merging approach for the design of thiazole/thiazolidine clubbed pyrazoline derivatives as anti-inflammatory agents: Synthesis, biopharmacological evaluation and molecular modeling studies

Fragment merging approach was applied for the design of thiazole/thiazolidinone clubbed pyrazoline derivatives 5a-e, 6a-c, 7 and 10a-d as dual COX-2 and 5-LOX inhibitors. Compounds 5a, 6a, and 6b were the most potent and COX-2 selective inhibitors (IC50= 0.03-0.06 μM, SI = 282.7-472.9) with high activity against 5-LOX (IC50 = 4.36-4.86 μM), while compounds 5b and 10a were active and selective 5-LOX inhibitors with IC50 = 2.43 and 1.58 μM, respectively. In vivo assay and histopathological examination for most active candidate 6a revealed significant decrease in inflammation with higher safety profile in comparison to standard drugs. Compound 6a exhibited the same orientation and binding interactions as the reference COX-2 and 5-LOX inhibitors (celecoxib and quercetin, respectively). Consequently, compound 6a has been identified as a potential lead for further optimization and the development of safe and effective anti-inflammatory drugs.

Structure-based virtual screening of natural compounds against wild and mutant (R1155K, A1156T and D1168A) NS3-4A protease of Hepatitis C virus

NS3-4A, a serine protease, is a primary target for drug development against Hepatitis C Virus (HCV). However, the effectiveness of potent next-generation protease inhibitors is limited by the emergence of mutations and resulting drug resistance. To address this, in this study a structure-based drug design approach is employed to screen a large library of 7320 natural compounds against both wild-type and mutant variants of NS3-4A protease. Telaprevir, a widely used protease inhibitor, was recruited as the control drug. The top 10 compounds with favorable binding affinities underwent drug-likeness evaluation. Based on ADMET studies, complexes of NP_024762 and NP_006776 were selected for molecular dynamic simulations. Principal component analysis (PCA) was employed to explore the conformational space and protein dynamics of the protein-ligand complex using a Free Energy Landscape (FEL) approach. The cosine values obtained from FEL analysis ranged from 0 to 1, and eigenvectors with cosine values below 0.2 were chosen for further analysis. To forecast binding free energies and evaluate energy contributions per residue, the MM-PBSA method was employed. The results highlighted the crucial role of amino acids in the catalytic domain for the binding of the protease with phytochemicals. Stable associations between the top compounds and the target protease were confirmed by the formation of hydrogen bonds in the binding pocket involving residues: His1057, Gly1137, Ser1139, and Ala1157. These findings suggest the potential of these compounds for further validation through biological evaluation.Communicated by Ramaswamy H. Sarma.

Molecular simulations required to target novel and potent inhibitors of cancer invasion

INTRODUCTION

Computer-aided drug design (CADD) is a computational approach used to discover, develop, and analyze drugs and active molecules with similar biochemical properties. Molecular simulation technology has significantly accelerated drug research and reduced manufacturing costs. It is an optimized drug discovery method that greatly improves the efficiency of novel drug development processes.

AREASCOVERED

This review discusses the development of molecular simulations of effective cancer inhibitors and traces the main outcomes of in silico studies by introducing representative categories of six important anticancer targets. The authors provide views on this topic from the perspective of both medicinal chemistry and artificial intelligence, indicating the major challenges and predicting trends.

EXPERT OPINION

The goal of introducing CADD into cancer treatment is to realize a highly efficient, accurate, and desired approach with a high success rate for identifying potent drug candidates. However, the major challenge is the lack of a sophisticated data-filtering mechanism to verify bottom data from mixed-quality references. Consequently, despite the continuous development of algorithms, computer power, and interface optimization, specific data filtering mechanisms will become an urgent and crucial issue in the future.

An interrupted Corey-Chaykovsky reaction of designed azaarenium salts: synthesis of complex polycyclic spiro- and fused cyclopropanoids

Simultaneous dearomatizing spirannulation of pyridinium salts is still in its infancy. Here, we present an organized skeletal remodeling of designed pyridinium salts by utilizing an interrupted Corey-Chaykovsky reaction to access unprecedented and structurally intriguing molecular architectures such as the vicinal bis-spirocyclic indanones and spirannulated benzocycloheptanones. This hybrid strategy rationally merges the nucleophilic features of sulfur ylides with the electrophilic pyridinium salts to achieve the regio- and stereoselective synthesis of new classes of cyclopropanoids. The plausible mechanistic pathways were derived from experimental results and control experiments.

Design and Development of COX-II Inhibitors: Current Scenario and Future Perspective

Innate inflammation beyond a threshold is a significant problem involved in cardiovascular diseases, cancer, and many other chronic conditions. Cyclooxygenase (COX) enzymes are key inflammatory markers as they catalyze prostaglandins production and are crucial for inflammation processes. While COX-I is constitutively expressed and is generally involved in "housekeeping" roles, the expression of the COX-II isoform is induced by the stimulation of different inflammatory cytokines and also promotes the further generation of pro-inflammatory cytokines and chemokines, which affect the prognosis of various diseases. Hence, COX-II is considered an important therapeutic target for drug development against inflammation-related illnesses. Several selective COX-II inhibitors with safe gastric safety profiles features that do not cause gastrointestinal complications associated with classic anti-inflammatory drugs have been developed. Nevertheless, there is mounting evidence of cardiovascular side effects from COX-II inhibitors that resulted in the withdrawal of market-approved anti-COX-II drugs. This necessitates the development of COX-II inhibitors that not only exhibit inhibit potency but also are free of side effects. Probing the scaffold diversity of known inhibitors is vital to achieving this goal. A systematic review and discussion on the scaffold diversity of COX inhibitors are still limited. To address this gap, herein we present an overview of chemical structures and inhibitory activity of different scaffolds of known COX-II inhibitors. The insights from this article could be helpful in seeding the development of next-generation COX-II inhibitors.

In-silico studies on wild orange (Citrus macroptera Mont.) compounds against COVID-19 pro-inflammation targets

One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an in silico approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of Citrus macroptera against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski's rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our in silico results suggest that all the natural phyto-compounds derived from C. macroptera could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation.Communicated by Ramaswamy H. Sarma.

Selective vitamins as potential options for dietary therapeutic interventions: In silico and In vitro insights from mutant C terminal fragment of FGA

We have used an integrated computational approach to explore the role of vitamin C and vitamin D in preventing aggregation of Fibrinogen A alpha-chain (FGA^cter) protein responsible for renal amyloidosis. We modelled structures of E524K / E526K mutants of FGA^cter protein and examined the potential interactions of these mutants with vitamin C and vitamin D3. Interaction of these vitamins at the amyloidogenic site may prevent the intermolecular interaction required for amyloid formation. The binding free energy values of vitamin C and vitamin D3 for E524K FGA^cter and E526K FGA^cter are - 67.12 ± 30.46 kJ/mole and - 79.45 ± 26.12 kJ/mol, respectively. Experimental studies using Congo red absorption, aggregation index studies and AFM imaging show encouraging results. The AFM images of E526K FGA^cter contained more extensive and higher protofibril aggregates, whereas, in the presence of vitamin D3, small monomeric and oligomeric aggregates were observed. Overall, the works provide interesting results about vitamin C and D role in preventing renal amyloidosis.

Inhibiting Leishmania donovani Sterol Methyltransferase to Identify Lead Compounds Using Molecular Modelling

The recent outlook of leishmaniasis as a global public health concern coupled with the reportage of resistance and lack of efficacy of most antileishmanial drugs calls for a concerted effort to find new leads. The study combined In silico and in vitro approaches to identify novel potential synthetic small-molecule inhibitors targeting the Leishmania donovani sterol methyltransferase (LdSMT). The LdSMT enzyme in the ergosterol biosynthetic pathway is required for the parasite’s membrane fluidity, distribution of membrane proteins, and control of the cell cycle. The lack of LdSMT homologue in the human host and its conserved nature among all Leishmania parasites makes it a viable target for future antileishmanial drugs. Initially, six known inhibitors of LdSMT with IC50 < 10 μM were used to generate a pharmacophore model with a score of 0.9144 using LigandScout. The validated model was used to screen a synthetic library of 95,630 compounds obtained from InterBioScreen limited. Twenty compounds with pharmacophore fit scores above 50 were docked against the modelled three-dimensional structure of LdSMT using AutoDock Vina. Consequently, nine compounds with binding energies ranging from −7.5 to −8.7 kcal/mol were identified as potential hit molecules. Three compounds comprising STOCK6S-06707, STOCK6S-84928, and STOCK6S-65920 with respective binding energies of −8.7, −8.2, and −8.0 kcal/mol, lower than 22,26-azasterol (−7.6 kcal/mol), a known LdSMT inhibitor, were selected as plausible lead molecules. Molecular dynamics simulation studies and molecular mechanics Poisson–Boltzmann surface area calculations showed that the residues Asp25 and Trp208 were critical for ligand binding. The compounds were also predicted to have antileishmanial activity with reasonable pharmacological and toxicity profiles. When the antileishmanial activity of the three hits was evaluated in vitro against the promastigotes of L. donovani, mean half-maximal inhibitory concentrations (IC50) of 21.9 ± 1.5 μM (STOCK6S-06707), 23.5 ± 1.1 μM (STOCK6S-84928), and 118.3 ± 5.8 μM (STOCK6S-65920) were obtained. Furthermore, STOCK6S-84928 and STOCK6S-65920 inhibited the growth of Trypanosoma brucei, with IC50 of 14.3 ± 2.0 μM and 18.1 ± 1.4 μM, respectively. The identified compounds could be optimised to develop potent antileishmanial therapeutic agents.

Synthesis of isochromanone containing natural products from myxobacteria

This review details the biological activity, biosynthesis and synthesis of isochromanone metabolites isolated from myxobacteria. Strategies towards the synthesis of the isochomanone and oxazole fragments of these natural products are highlighted.

Computational Approaches to Enzyme Inhibition by Marine Natural Products in the Search for New Drugs

The exploration of biologically relevant chemical space for the discovery of small bioactive molecules present in marine organisms has led not only to important advances in certain therapeutic areas, but also to a better understanding of many life processes. The still largely untapped reservoir of countless metabolites that play biological roles in marine invertebrates and microorganisms opens new avenues and poses new challenges for research. Computational technologies provide the means to (i) organize chemical and biological information in easily searchable and hyperlinked databases and knowledgebases; (ii) carry out cheminformatic analyses on natural products; (iii) mine microbial genomes for known and cryptic biosynthetic pathways; (iv) explore global networks that connect active compounds to their targets (often including enzymes); (v) solve structures of ligands, targets, and their respective complexes using X-ray crystallography and NMR techniques, thus enabling virtual screening and structure-based drug design; and (vi) build molecular models to simulate ligand binding and understand mechanisms of action in atomic detail. Marine natural products are viewed today not only as potential drugs, but also as an invaluable source of chemical inspiration for the development of novel chemotypes to be used in chemical biology and medicinal chemistry research.

CSM-Toxin: A Web-Server for Predicting Protein Toxicity

Biologics are one of the most rapidly expanding classes of therapeutics, but can be associated with a range of toxic properties. In small-molecule drug development, early identification of potential toxicity led to a significant reduction in clinical trial failures, however we currently lack robust qualitative rules or predictive tools for peptide- and protein-based biologics. To address this, we have manually curated the largest set of high-quality experimental data on peptide and protein toxicities, and developed CSM-Toxin, a novel in-silico protein toxicity classifier, which relies solely on the protein primary sequence. Our approach encodes the protein sequence information using a deep learning natural languages model to understand "biological" language, where residues are treated as words and protein sequences as sentences. The CSM-Toxin was able to accurately identify peptides and proteins with potential toxicity, achieving an MCC of up to 0.66 across both cross-validation and multiple non-redundant blind tests, outperforming other methods and highlighting the robust and generalisable performance of our model. We strongly believe the CSM-Toxin will serve as a valuable platform to minimise potential toxicity in the biologic development pipeline. Our method is freely available as an easy-to-use webserver.

Design of novel anti-cancer drugs targeting TRKs inhibitors based 3D QSAR, molecular docking and molecular dynamics simulation

Tropomyosin receptor kinase (TRK) enzymes are responsible for different types of tumors caused by neurotrophic tyrosine receptor kinase gene fusion and have been identified as an effective target for anticancer therapy. The study of the mechanism between polo-like kinase (PLKs) and pyrazol inhibitors was performed using 3D-QSAR modeling, molecular docking, and MD simulations in order to design high-activity inhibitors. The HQSAR (Q2 = 0.793, R2 = 0.917, R2ext = 0.961), CoMFA (Q2 = 0.582, R2 = 0.722, R2ext = 0.951), CoMSIA/SE (Q2 = 0.603, R2 = 0.801, R2ext = 0.849), and Topomer CoMFA (Q2 = 0.726, R2 = 0.992, R2ext = 0.717) showed good reliability and predictability. All models have been successfully tested by external validation, so all five established models are reliable. The analysis of the different contour maps of different models gives structural information to improve the inhibitory function. Molecular docking results show that the amino acids Met 592, GLU 590, LEU 657, VAL 524, and PHE 589 are the active sites of the tropomyosin receptor TRKs. The results obtained by MD showed that compound 19i could form a more stable complex protein (PDB id: 5KVT). Based on these results, we developed new compounds and their expected inhibitory activities. The results of physicochemical and ADME-Tox properties showed that the four proposed molecules are orally bioavailable, and they are not toxic in the Ames test. Thus, these results would provide modeling information that could help experimental researchers find TRK type I inhibitors more efficiently.Communicated by Ramaswamy H. Sarma.

3D-QSAR Studies, Molecular Docking, Molecular Dynamic Simulation, and ADMET Proprieties of Novel Pteridinone Derivatives as PLK1 Inhibitors for the Treatment of Prostate Cancer

Overexpression of polo-like kinase 1 (PLK1) has been found in many different types of cancers. With its essential role in cell proliferation, PLK1 has been determined to be a broad-spectrum anti-cancer target. In this study, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations were applied on a series of novel pteridinone derivatives as PLK1 inhibitors to discover anti-cancer drug candidates. In this work, three models—CoMFA (Q² = 0.67, R² = 0.992), CoMSIA/SHE (Q² = 0.69, R² = 0.974), and CoMSIA/SEAH (Q² = 0.66, R² = 0.975)—of pteridinone derivatives were established. The three models that were established gave Rpred2 = 0.683, Rpred 2= 0.758, and Rpred 2= 0.767, respectively. Thus, the predictive abilities of the three proposed models were successfully evaluated. The relations between the different champs and activities were well-demonstrated by the contour chart of the CoMFA and CoMSIA/SEAH models. The results of molecular docking indicated that residues R136, R57, Y133, L69, L82, and Y139 were the active sites of the PLK1 protein (PDB code: 2RKU), in which the more active ligands can inhibit the enzyme of PLK1. The results of the molecular dynamic MD simulation diagram were obtained to reinforce the previous molecular docking results, which showed that both inhibitors remained stable in the active sites of the PLK1 protein (PDB code: 2RKU) for 50 ns. Finally, a check of the ADME-Tox properties of the two most active molecules showed that molecular N° 28 could represent a good drug candidate for the therapy of prostate cancer diseases.

In-silico screening and identification of phytochemicals from Centella asiatica as potential inhibitors of sodium-glucose co-transporter 2 for treating diabetes

Sodium-glucose co-transporter 2 (SGLT-2) is a major transport protein responsible for reabsorption of glucose from the kidney back to the bloodstream. Inhibiting this protein effectively lowers the glucose level of diabetic patients; however, the use of synthetic SGLT-2 inhibitors has been linked to some serious adverse effects. There is a need to identify safer alternatives that are equally or more effective as the current inhibitor drugs. Phytochemicals are known for their efficacy as herbal remedies, but these molecules remain underexplored as source of therapeutic agents. In this study, we performed in silico screening to identify potential SGLT-2 inhibitors from the 21 phytochemicals from Centella asiatica. Docking results identified eleven compounds with estimated binding energies comparable to that of known inhibitors drugs. The stability of the complexes was then elucidated using 100 ns MD simulations. From our dynamic binding free energy calculations using MM/PBSA, asiaticoside, betulinic acid, centellasapogenol, methyl brahmate, and rutin exceeded at least one of the binding energies of the reference compounds, which highlights their strong affinity towards SGLT-2. Among the five, betulinic acid, centellasapogenol, and methyl brahmate maintained their structural stability to the same extent as the references and exhibited better oral bioavailability and excellent drug-like properties. Because of these results, it is recommended to prioritize betulinic acid, centellasapogenol, and methyl brahmate in future in vitro and in vivo studies to verify their potential as inhibitor drugs for diabetes therapies. Communicated by Ramaswamy H. Sarma.

Polypharmacology of some medicinal plant metabolites against SARS-CoV-2 and host targets: Molecular dynamics evaluation of NSP9 RNA binding protein

Medicinal plants as rich sources of bioactive compounds are now being explored for drug development against COVID-19. 19 medicinal plants known to exhibit antiviral and anti-inflammatory effects were manually curated, procuring a library of 521 metabolites; this was virtually screened against NSP9, including some other viral and host targets and were evaluated for polypharmacological indications. Leads were identified via rigorous scoring thresholds and ADMET filtering. MM-GBSA calculation was deployed to select NSP9-Lead complexes and the complexes were evaluated for their stability and protein-ligand communication via MD simulation. We identified 5 phytochemical leads for NSP9, 23 for Furin, 18 for ORF3a, and 19 for IL-6. Ochnaflavone and Licoflavone B, obtained from Lonicera japonica (Japanese Honeysuckle) and Glycyrrhiza glabra (Licorice), respectively, were identified to have the highest potential polypharmacological properties for the aforementioned targets and may act on multiple pathways simultaneously to inhibit viral entry, replication, and disease progression. Additionally, MD simulation supports the robust stability of Ochnaflavone and Licoflavone B against NSP9 at the active sites via hydrophobic interactions, H-bonding, and H-bonding facilitated by water. This study promotes the initiation of further experimental analysis of natural product-based anti-COVID-19 therapeutics.

Antispasmodic activity of the ethanol extract of Citrullus lanatus seeds: Justifying ethnomedicinal use in Pakistan to treat asthma and diarrhea

ETHNOPHARMACOLOGICAL RELEVANCE

Citrullus lanatus (Thunb.) belongs to the ground family, Cucurbitaceae, known for edible fruit. Besides nutritional benefits, the traditional herbal practitioners in Pakistan and India used their seeds to treat gastrointestinal, respiratory, and urinary disorders. In Northern Sudan, its seeds are often used as a laxative. Its root is laxative and emetic at a high dose. Its seeds are also used to treat bedwetting and urinary tract obstruction.

AIM OF THE STUDY

This study aimed to elucidate the multi-target mechanisms of Citrullus lanatus seeds to treat asthma and diarrhea. The pharmacological experiments were designed and conducted, along with the pharmacology network and molecular docking predictions, to verify the seeds biopotency for antispasmodic and bronchodilator properties.

METHODS

LC ESI-MS/MS were performed to identify the potentially active compounds in hydroethanolic extract of Citrullus lanatus seeds, then to quantify them by HPLC. The quantified bioactive compounds of Citrullus lanatus, i.e., stigmasterol, quinic acid, malic acid, epicatechin, caffeic acid, rutin, p-coumaric acid, quercetin, ferulic acid, scopoletin, apigenin, and kaempferol were subjected to in silico studies for molecular docking. The hydroethanolic extract of Citrullus lanatus seeds was examined on isolated rabbit tissue, i.e., jejunum, trachea, and urinary bladder. The antiperistalsis, antidiarrheal and antisecretory studies were also performed in animal models.

RESULTS

In silico studies revealed that bioactive compounds of C. lanatus seeds interfere with asthma and diarrhea-associated target genes, which are a member of calcium mediate signaling, regulation of cytosolic calcium concentration, smooth muscle contraction, and inflammatory responses. It was also found that rutin, quercetin, kaempferol, and scopoletin were stronger binding to voltage-gated calcium channels, calcium/calmodulin-dependent protein kinase, myosin light chain kinase, and phosphoinositide phospholipase C, thus, exerting calcium channel blocker activity. The hydroethanolic extract of C. lanatus seeds exerted a concentration-dependent relaxant response for the spasmolytic response on isolated jejunum and trachea preparations and caused relaxation of spastic contraction of K⁺ (80 mM). Furthermore, it caused a non-parallel rightward shift with suppression of calcium concentration-response curves. In animal models, the Cl.EtOH showed antiperistalsis, antidiarrheal and antisecretory response.

CONCLUSION

Thus, we confirm Citrullus lanatus seeds have some medicinal effects by regulating the contractile response through target proteins of calcium mediates signaling and can be a promising component in the medical treatment for asthma and diarrhea.

In Silico Evaluation of Sesquiterpenes and Benzoxazinoids Phytotoxins against Mpro, RNA Replicase and Spike Protein of SARS-CoV-2 by Molecular Dynamics. Inspired by Nature

In the work described here, a number of sesquiterpenes and benzoxazinoids from natural sources, along with their easily accessible derivatives, were evaluated against the main protease, RNA replicase and spike glycoprotein of SARS-CoV-2 by molecular docking. These natural products and their derivatives have previously shown remarkable antiviral activities. The most relevant compounds were the 4-fluoro derivatives of santamarine, reynosin and 2-amino-3H-phenoxazin-3-one in terms of the docking score. Those compounds fulfill the Lipinski’s rule, so they were selected for the analysis by molecular dynamics, and the kinetic stabilities of the complexes were assessed. The addition of the 4-fluorobenzoate fragment to the natural products enhances their potential against all of the proteins tested, and the complex stability after 50 ns validates the inhibition calculated. The derivatives prepared from reynosin and 2-amino-3H-phenoxazin-3-one are able to generate more hydrogen bonds with the M^pro, thus enhancing the stability of the protein–ligand and generating a long-term complex for inhibition. The 4-fluoro derivate of santamarine and reynosin shows to be really active against the spike protein, with the RMSD site fluctuation lower than 1.5 Å. Stabilization is mainly achieved by the hydrogen-bond interactions, and the stabilization is improved by the 4-fluorobenzoate fragment being added. Those compounds tested in silico reach as candidates from natural sources to fight this virus, and the results concluded that the addition of the 4-fluorobenzoate fragment to the natural products enhances their inhibition potential against the main protease, RNA replicase and spike protein of SARS-CoV-2.