Extra precision docking, free energy calculation and molecular dynamics simulation studies of CDK2 inhibitors

An integrative computational approach for the identification of dual inhibitors of isocitrate dehydrogenase 1 and 2 from phytocompounds of Phyllantus amarus

Genetic alterations of the genes encoding the isocitrate dehydrogenase (IDH) enzymes have been identified in about 20% of acute myeloid leukemia (AML) cases as well as many other forms of cancers. Notable among these alterations are the neomorphic IDH1_R132H and IDH2_R140Q mutations which lead to the production of an oncometabolite. Hence, their inhibition is widely considered a therapeutic strategy in the treatment of many cancers. While many inhibitors of the mutant enzymes have been developed, an inhibitor that is capable of co-inhibiting both enzymes are currently lacking while drug resistance has also limited the clinical usage of previously identified mono inhibitors. Consequently, this study employed molecular modeling approaches, such as molecular docking, molecular mechanics generalized Born Surface area (MM/GBSA), molecular dynamics (MD) simulation, and density functional theory (DFT) analysis to identify potential dual inhibitors of the previously mentioned mutant IDH1/2 from the phytocompounds of Phyllantus amarus. Of the 31 phytocompounds identified, 20 showed good binding affinities for both IDH1 _R132H and IDH2 _R140Q (ranging from -5.2 Kca/mol to -9.6 Kcal/mol) and had desirable pharmacokinetic properties. However, ellagic acid and pinoresinol possessed better pharmacokinetic properties, rendering suitable hits. Investigation of the behavior of the IDH1_R132H and IDH2_R140Q complexes with ellagic acid and pinoresinol via the RMSD, RMSF, and contact map analyses showed that all the complexes-maintained stability throughout the simulation time. Ultimately, ellagic acid and pinoresinol were identified as promising hits for the development of IDH1_R132H and IDH2_R140Q dual inhibitors. However, further experimental studies are needed to confirm their potential as therapies.Communicated by Ramaswamy H. Sarma.

Exploring the anti-protozoal mechanisms of Syzygium aromaticum phytochemicals targeting Cryptosporidium parvum lactate dehydrogenase through molecular dynamics simulations

Cryptosporidium parvum (C. parvum), a protozoan parasite, is known to induce significant gastrointestinal disease in humans. Lactate dehydrogenase (LDH), a protein of C. parvum, has been identified as a potential therapeutic target for developing effective drugs against infection. This study utilized a computational drug discovery approach to identify potential drug molecules against the LDH protein of C. parvum. In the present investigation, we conducted a structure-based virtual screening of 55 phytochemicals from the Syzygium aromaticum (S. aromaticum). This process identified four phytochemicals, including Gallotannin 23, Eugeniin, Strictinin, and Ellagitannin, that demonstrated significant binding affinity and dynamic stability with LDH protein. Interestingly, these four compounds have been documented to possess antibacterial, antiviral, anti-inflammatory, and antioxidant properties. The docked complexes were simulated for 100 ns using Desmond to check the dynamic stability. Finally, the free binding energy was computed from the last 10ns MD trajectories. Gallotannin 23 and Ellagitannin exhibited considerable binding affinity and stability with the target protein among all four phytochemicals. These findings suggest that these predicted phytochemicals from S. aromaticum could be further explored as potential hit candidates for developing effective drugs against C. parvum infection. The in vitro and in vivo experimental validation is still required to confirm their efficacy and safety as LDH inhibitors.

Metabolites profiling and cheminformatics bioprospection of selected medicinal plants against the main protease and RNA-dependent RNA polymerase of SARS-CoV-2

Despite the existence of some vaccines, SARS-CoV-2 (S-2) infections persist for various reasons relating to vaccine reluctance, rapid mutation rate, and an absence of specific treatments targeted to the infection. Due to their availability, low cost and low toxicity, research into potentially repurposing phytometabolites as therapeutic alternatives has gained attention. Therefore, this study explored the antiviral potential of metabolites of some medicinal plants [Spondias mombin, Macaranga barteri and Dicerocaryum eriocarpum (Sesame plant)] identified using liquid chromatography-mass spectrometry (LCMS) as possible inhibitory agents against the S-2 main protease (S-2 MP) and RNA-dependent RNA polymerase (RP) using computational approaches. Molecular docking was used to identify the compounds with the best affinities for the selected therapeutics targets. Afterwards, compounds with poor physicochemical characteristics, pharmacokinetics, and drug-likeness were screened out. The top-ranked compounds were further subjected to a 120-ns molecular dynamics (MD) simulation. Only quercetin 3-O-rhamnoside (-48.77 kcal/mol) had higher binding free energy than the reference standard (zafirlukast) (-44.99 kcal/mol) against S-2 MP. Conversely, all the top-ranked compounds (ellagic acid hexoside, spiraeoside, apigenin-4'-glucoside and chrysoeriol 7-glucuronide) except gnetin L (-24.24 kcal/mol) had higher binding free energy (-55.19 kcal/mol, -52.75 kcal/mol, -47.22 kcal/mol and -43.35 kcal/mol) respectively, against S-2 RP relative to the reference standard (-34.79 kcal/mol). The MD simulations study further revealed that the investigated inhibitors are thermodynamically stable and form structurally compatible complexes that impede the regular operation of the respective S-2 therapeutic targets. Although, these S-2 therapeutic candidates are promising, further in vitro and in vivo evaluation is required and highly recommended.Communicated by Ramaswamy H. Sarma.

Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation

GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibitors. In this study, multiclass classification-based QSAR models were developed using diverse machine learning algorithms. These models were built from curated compounds with experimentally derived GRK5 inhibitory activity. Additionally, a pharmacophore model was constructed using active compounds from the dataset. Among the models, the SVM-based approach proved most effective and was initially used to screen DrugBank compounds within the applicability domain. Compounds showing significant GRK5 inhibitory potential underwent evaluation for key pharmacophoric features. Prospective compounds were subjected to molecular docking to assess binding affinity towards GRK5's key active site amino acid residues. Stability at the binding site was analyzed through 200 ns molecular dynamics simulations. MM-GBSA analysis quantified individual free energy components contributing to the total binding energy with respect to binding site residues. Metadynamics analysis, including PCA, FEL, and PDF, provided crucial insights into conformational changes of both apo and holo forms of GRK5 at defined energy states. The study identifies DB02844 (S-Adenosyl-1,8-Diamino-3-Thiooctane) and DB13155 (Esculin) as promising GRK5 inhibitors, warranting further in vitro and in vivo validation studies.

Exploring new quinazolin-4(3H)-one derivatives as CDK2 inhibitors: Design, synthesis, and anticancer evaluation

In the present work, five series of new 2,3-disubstituted quinazolin-4(3H)-ones 4a-c, 5a-d, 6a-g, 7a,b, and 9a-c were designed, synthesized, and screened in vitro for their cytotoxic activity against 60 cancer cell lines by the National Cancer Institute, USA. Five candidates 4c, 6a, 6b, 6d, and 6g revealed promising cytotoxicity with significant percentage growth inhibition in the range of 81.98%-96.45% against the central nervous system (CNS) (SNB-19), melanoma (MDA-MB-435), and non-small cell lung cancer (HOP-62) cell lines. The in vitro cytotoxic half maximal inhibitory concentration (IC50 ) values for the most active compounds 4c, 6a, 6b, 6d, and 6g against the most sensitive cell lines were evaluated. Additionally, screening their cyclin-dependent kinase 2 (CDK2) inhibitory activity was performed. Ortho-chloro-benzylideneamino derivative 6b emerged as the most potent compound with IC50  = 0.67 µM compared to Roscovitine (IC50  = 0.64 µM). The most active candidates arrested the cell cycle at G1, S phases, or both, leading to cell death and inducing apoptosis against CNS (SNB-19), melanoma (MDA-MB-435), and non-small cell lung cancer (HOP-62) cell lines. The molecular docking study verified the resulting outcomes for the most active candidates in the CDK2-binding pocket. Finally, physicochemical, and pharmacokinetic properties deduced that compounds 4c, 6a, 6b, 6d, and 6g displayed significant drug-likeness properties. According to the obtained results, the newly targeted compounds are regarded as promising scaffolds for the continued development of novel CDK2 inhibitors.

Integrated Computational Approaches for Drug Design Targeting Cruzipain

Cruzipain inhibitors are required after medications to treat Chagas disease because of the need for safer, more effective treatments. Trypanosoma cruzi is the source of cruzipain, a crucial cysteine protease that has driven interest in using computational methods to create more effective inhibitors. We employed a 3D-QSAR model, using a dataset of 36 known inhibitors, and a pharmacophore model to identify potential inhibitors for cruzipain. We also built a deep learning model using the Deep purpose library, trained on 204 active compounds, and validated it with a specific test set. During a comprehensive screening of the Drug Bank database of 8533 molecules, pharmacophore and deep learning models identified 1012 and 340 drug-like molecules, respectively. These molecules were further evaluated through molecular docking, followed by induced-fit docking. Ultimately, molecular dynamics simulation was performed for the final potent inhibitors that exhibited strong binding interactions. These results present four novel cruzipain inhibitors that can inhibit the cruzipain protein of T. cruzi.

Comprehensive computational investigation for ligand recognition and binding dynamics of SdiA: a degenerate LuxR -type receptor in Klebsiella pneumoniae

SdiA is a LuxR-type receptor that controls the virulence of Klebsiella pneumoniae, a Gram-negative bacterium that causes various infections in humans. SdiA senses exogenous acyl-homoserine lactones (AHLs) and autoinducer-2 (AI-2), two types of quorum sensing signals produced by other bacterial species. However, the molecular details of how SdiA recognizes and binds to different ligands and how this affects its function and regulation in K. pneumoniae still need to be better understood. This study uses computational methods to explore the protein-ligand binding dynamics of SdiA with 11 AHLs and 2 AI-2 ligands. The 3D structure of SdiA was predicted through homology modeling, followed by molecular docking with AHLs and AI-2 ligands. Binding affinities were quantified using MM-GBSA, and complex stability was assessed via Molecular Dynamics (MD) simulations. Results demonstrated that SdiA in Klebsiella pneumoniae exhibits a degenerate binding nature, capable of interacting with multiple AHLs and AI-2. Specific ligands, namely C10-HSL, C8-HSL, 3-oxo-C8-HSL, and 3-oxo-C10-HSL, were found to have high binding affinities and formed critical hydrogen bonds with key amino acid residues of SdiA. This finding aligns with the observed preference of SdiA for AHLs having 8 to 10 carbon-length acyl chains and lacking hydroxyl groups. In contrast, THMF and HMF demonstrated poor binding properties. Furthermore, AI-2 exhibited a low affinity, corroborating the inference that SdiA is not the primary receptor for AI-2 in K. pneumoniae. These findings provide insights into the protein-ligand binding dynamics of SdiA and its role in quorum sensing and virulence of K. pneumoniae.

Bioactivity predictions and virtual screening using machine learning predictive model

Recently, there has been significant attention on machine learning algorithms for predictive modeling. Prediction models for enzyme inhibitors are limited, and it is essential to account for chemical biases while developing them. The lack of repeatability in available models and chemical bias issues constrain drug discovery and development. A new prediction model for enzyme inhibitors has been developed, and the model efficacy was checked using Dipeptidyl peptidase 4 (DPP-4) inhibitors. A Python script was prepared and can be provided for personal use upon request. Among various machine learning algorithms, it was found that Random Forest offers the best accuracy. Two models were compared, one with diverse training and test data and the other with a random split. It was concluded that machine learning predictive models based on the Murcko scaffold can address chemical bias concerns. In-silico screening of the Drug Bank database identified two molecules against DPP-4, which are previously proven hit molecules. The approach was further validated through molecular docking studies and molecular dynamics simulations, demonstrating the credibility and relevance of the developed model for future investigations and potential translation into clinical applications.Communicated by Ramaswamy H. Sarma.

Integrative analysis of potential diagnostic markers and therapeutic targets for glomerulus-associated diabetic nephropathy based on cellular senescence

Introduction

Diabetic nephropathy (DN), distinguished by detrimental changes in the renal glomeruli, is regarded as the leading cause of death from end-stage renal disease among diabetics. Cellular senescence plays a paramount role, profoundly affecting the onset and progression of chronic kidney disease (CKD) and acute kidney injuries. This study was designed to delve deeply into the pathological mechanisms between glomerulus-associated DN and cellular senescence.

Methods

Glomerulus-associated DN datasets and cellular senescence-related genes were acquired from the Gene Expression Omnibus (GEO) and CellAge database respectively. By integrating bioinformatics and machine learning methodologies including the LASSO regression analysis and Random Forest, we screened out four signature genes. The receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance of the selected genes. Rigorous experimental validations were subsequently conducted in the mouse model to corroborate the identification of three signature genes, namely LOX, FOXD1 and GJA1. Molecular docking with chlorogenic acids (CGA) was further established not only to validate LOX, FOXD1 and GJA1 as diagnostic markers but also reveal their potential therapeutic effects.

Results and discussion

In conclusion, our findings pinpointed three diagnostic markers of glomerulus-associated DN on the basis of cellular senescence. These markers could not only predict an increased risk of DN progression but also present promising therapeutic targets, potentially ushering in innovative treatments for DN in the elderly population.

Pinpointing top inhibitors for GSK3β from pool of indirubin derivatives using rigorous computational workflow and their validation using molecular dynamics (MD) simulations

Glycogen synthase kinase-3β (GSK3β) is a pivotal protein kinase implicated in a spectrum of debilitating diseases, encompassing cancer, diabetes, and neurodegenerative disorders. While the therapeutic potential of GSK3β inhibition is widely recognized, there remains an unmet need for a rigorous, systematic analysis probing the theoretical inhibition dynamics of a comprehensive library of indirubin derivatives against GSK3β using advanced computational methodologies. Addressing this gap, this study embarked on an ambitious endeavor, leveraging indirubin-a renowned scaffold-as a template to curate a vast library of 1000 indirubin derivatives from PubChem. These were enriched with varied substitutions and modifications, identified via a structure similarity search with a Tanimoto similarity threshold of 85%. Harnessing a robust virtual screening workflow, we meticulously identified the top 10 contenders based on XP docking scores. Delving deeper, we gauged the binding free energy differentials (ΔGBind) of these hits, spotlighting the top three compounds that showcased unparalleled binding prowess. A comparative pharmacophore feature mapping with the reference inhibitor OH8, co-crystallized with GSK3β (PDB ID: 6Y9R), was undertaken. The binding dynamics of these elite compounds were further corroborated with 100 ns molecular dynamics simulations, underlining their stable and potent interactions with GSK3β. Remarkably, our findings unveil that these indirubin derivatives not only match but, in certain scenarios, surpass the binding affinity and specificity of OH8. By bridging this research chasm, our study amplifies the therapeutic promise of indirubin derivatives, positioning them as frontrunners in the quest for groundbreaking GSK3β inhibitors, potentially revolutionizing treatments for a myriad of ailments.

Integrated computational approach identifies potential inhibitors of ASK1-(JNK/P38) interaction signaling: new insights into cancer therapeutics

Cancers are characterized by the aberrant expression of certain genes that trigger a cascade of molecular events that culminate in dysregulated cell division. Consequently, the inhibition of the products of these expressedgenes has emerged as a rational approach in cancer therapy. The apoptosis signal-regulating kinase 1 (ASK1) protein, encoded by the mitogen-activated protein kinase kinase kinase 5 (MAP3K5) gene, plays pertinent roles in the mediation of cell death induced by stress and inflammation, andis often found at elevated levels in cancer. Consequently, it has emerged as a molecular target for the development of potential chemotherapeutics through identification of selective inhibitors. However, there is still dearth of ASK1 inhibitors in clinical use. Hence, molecular modelling approaches were employed in this study to discover potential ASK1 inhibitors from phytochemicals. Twenty-five phytocompounds from four medicinal plants were tested for their inhibitory prowess via molecular docking. Interestingly, all the compounds exhibited promising inhibitory potentials for ASK1. However, further subjection to filtering procedures via different pipelines including drug-likeness evaluation, pharmacokinetics screening, toxicity profiling, and better affinities compared to the approved inhibitor resulted in three hit compounds namely ellagic acid, luteolin, and kaempferol with suitable properties. Profiling of the interactions formed between the hit\compounds and the targets revealed several interactions that were not present in that of the approved inhibitor, while molecular dynamics (MD) simulation revealed the complexes formed as stable. Conclusively, this study identified three compounds with ASK1 inhibitory potentials that are worthy of further exploration in in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

Modulatory properties of Thespesia garckeana (F. Hoffm.) Exell & Hillc. Aqueous fruit extract on female rats reproductive hormones and tissues histology and potential inhibitory activity of its constituents against SRD5α2

ETHNOPHARMACOLOGICAL RELEVANCE

Thespesia garckeana (F. Hoffm.) Exell & Hillc. is called Gorontula (Kola of Tula) in Nigeria, Morojwa in Bostwana, and Thespesia garckeana in South Africa and is widely distributed across Africa. Its parts reportedly possess multiple medicinal properties and are employed for treating various diseases. In Tula, Gombe State, Nigeria, the ripe fruit decoction is taken as remedy for female infertility as documented by Ochokwu and co in the Journal of Biology, Agriculture and Healthcare in 2015.

AIM OF THE STUDY

This research examined the effects of aqueous fruit extract of T. garckeana (F. Hoffm.) Exell & Hillc. (AFETG) on selected reproductive tissues and hormones in female rats and also evaluated the inhibitory potentials of its phytoconstituents against human 5-alpha reductase 2 (SRD5α2) using in silico approach.

METHODS

Twenty-five (25) sexually matured female rats were randomized into 5 groups (i.e. A - E). Oestrous in the rats was synchronized (subcutaneous oestradiol conjugate [10 μg/100 g BW]). Group A received distilled water (control). Group B received standard drug, clomiphene citrate (0.85 mg/kg BW), while groups C, D, and E received AFETG at 50, 100, and 200 mg/kg BW respectively. The animals were treated for five (5) days and sacrificed 24 h after. Their blood was collected and prepared for analysis of serum prolactin, oestradiol (E2), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) while ovaries, uteruses, and oviducts were studied for histological and histomorphometric changes. For the in silico study, the target protein, human steroid 5α-reductase 2 (SRD5α2) was prepared and its receptor grid was generated using Optimized Potential for Liquid Simulations-2005. The ligand 2D structures were prepared using LigPrep 2.4 software and docked using Glide. The binding energy of the ligands to the protein receptor was predicted using Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis.

RESULTS

AFETG significantly increased serum levels of E2 but did not alter serum levels of prolactin, LH and FSH when compared with distilled water and clomiphene citrate. AFETG also significantly increased ovarian tertiary follicular diameter, oviductal epithelial height and serosa thickness as well as uterine endometrial epithelial height, endometrial thickness, and myometrial thickness when compared with control. Ovarian secondary follicular diameter and oviductal submucosa thickness and muscular thickness were significantly decreased by AFETG when compared with control. Two compounds in T. garckeana (F. Hoffm.) Exell & Hillc.; D-Melezitose (-12.55 kcal/mol XP GScore) and 1, 3, 4-trihydroxy-5-oxo cyclohexane-1-carboxylic acid (-9.136 kcal/mol XP GScore) exhibited higher binding affinities for SRD5α2 than the reference ligand, epristeride (-8.096 kcal/mol XP GScore). In conclusion, the ability of AFETG to increase serum E2 level, thickness of uterine endometrium and ovarian tertiary follicles size can be explored for the treatment of female infertility caused by thinning of the uterine endometrium and reduced follicular size. Two compounds in AFETG (i.e. D-Melezitose and 1, 3, 4-trihydroxy-5-oxo cyclohexane-1-carboxylic acid are potential inhibitors of SRD5α2, thus aiding the biosynthesis of E2. Available evidence therefore corroborate the traditional use of T. garckeana (F. Hoffm.) Exell & Hillc fruit as a female fertility enhancer in Northern Nigeria.

Computational identification of potential inhibitors targeting cdk1 in colorectal cancer

Introduction: Despite improved treatment options, colorectal cancer (CRC) remains a huge public health concern with a significant impact on affected individuals. Cell cycle dysregulation and overexpression of certain regulators and checkpoint activators are important recurring events in the progression of cancer. Cyclin-dependent kinase 1 (CDK1), a key regulator of the cell cycle component central to the uncontrolled proliferation of malignant cells, has been reportedly implicated in CRC. This study aimed to identify CDK1 inhibitors with potential for clinical drug research in CRC. Methods: Ten thousand (10,000) naturally occurring compounds were evaluated for their inhibitory efficacies against CDK1 through molecular docking studies. The stability of the lead compounds in complex with CDK1 was evaluated using molecular dynamics simulation for one thousand (1,000) nanoseconds. The top-scoring candidates' ADME characteristics and drug-likeness were profiled using SwissADME. Results: Four hit compounds, namely, spiraeoside, robinetin, 6-hydroxyluteolin, and quercetagetin were identified from molecular docking analysis to possess the least binding scores. Molecular dynamics simulation revealed that robinetin and 6-hydroxyluteolin complexes were stable within the binding pocket of the CDK1 protein. Discussion: The findings from this study provide insight into novel candidates with specific inhibitory CDK1 activities that can be further investigated through animal testing, clinical trials, and drug development research for CRC treatment.

Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation

The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. Hence, we implemented parallel pharmacophore screening of 11,808 DrugBank compounds against RAF and MEK. ADHRR and DHHRR were modeled as a pharmacophore hypothesis for RAF and MEK respectively. Importantly, these hypotheses resulted an AUC value of > 0.90 with the external data set. As a result of phase screening, glide docking, and prime-MM/GBSA scoring, it is determined that DB08424 and DB08907 have the best chances of acting as multi-kinase inhibitors. The pi-cation interaction with key amino acid residues of both target receptors may responsible for the stronger binding with these kinases. Cumulative 600 ns MD simulation studies validate the binding ability of these compounds. Significantly, the hit compounds resulted higher number of stable conformational state with less atomic movements than the reference compound against both targets. The anti-cancer efficacy of the lead compounds was validated through machine learning-based approaches. These findings suggest that DB08424 and DB08907 might be novel molecules to be explored further experimentally to block the MAPK signaling in lung cancer patients.

Amphiphilic peptide Mastoparan-B induces conformational changes within the AdeB efflux pump, down-regulates adeB gene expression, and restores antibiotic susceptibility in an MDR strain of Acinetobacter baumannii

Mastoparan B (MP-B) is an amphiphilic peptide with a potent antimicrobial activity against most Gram-negative bacteria. However, there is little information available on the inhibition of the Acinetobacter baumannii resistance-nodulation-cell-division (RND) efflux pump using this antimicrobial peptide. Here, we carried out a series of in-silico experiments to find the mechanisms underlying the anti-efflux activity of MP-B using a multi-drug resistant (MDR) strain of A. baumannii (AB). According to our findings, MP-B demonstrated a potent antibacterial activity against an MDR-AB (minimum inhibitory concentration [MIC] = 1 μg/mL) followed by a 20-fold reduction in the adeB gene expression in the presence of sub-MIC of this peptide. Using Groningen Machine for Chemicals Simulation (GROMACS) via PyMOL Graphical User Interface (GUI), (we observed that, the AdeB transporter had conserved helix-turn-helix regions and a tight pore rich in Phe and Ala residues. To understand how inhibition of the AdeB is achieved, we generated 20 apo-MP-B poses using the InterPep and SiteMap tools. The high-quality model was created by homology modeling and used for docking via AutoDock/Vina to identify the MP-B binding sites. We established that the most apo-MP-B formed H-bonds to the backbone of five amino acids in the Helix-5. As a result, the dihedral angles of the involved amino acids shift by 9.0-9.6 Ǻ, causing a change in the conformation of the AdeB protein. This led to helix conformation stereoisomerization and block the AdeB activity. MP-B presumably has dual mechanisms. (1) It blocks the AdeB transporter by changing its conformation. (2) MP-B influences the adeB gene expression by binding to G-protein which laterally controls efflux regulators like MarA, RamA, SoxS, and Rob proteins.

Antioxidant evaluation and computational prediction of prospective drug-like compounds from polyphenolic-rich extract of Hibiscus cannabinus L. seed as antidiabetic and neuroprotective targets: assessment through in vitro and in silico studies

BACKGROUND

Reports have implicated diabetes mellitus (DM) and Alzheimer's disease (AD) as some of the global persistent health challenges with no lasting solutions, despite of significant inputs of modern-day pharmaceutical firms. This study therefore, aimed to appraise the in vitro antioxidant potential, enzymes inhibitory activities, and as well carry out in silico study on bioactive compounds from polyphenolic-rich extract of Hibiscus cannabinus seed (PEHc).

METHODS

In vitro antioxidant assays were performed on PEHc using standard methods while the identification of phytoconstituents was carried out with high performance liquid chromatography (HPLC). For the in silico molecular docking using Schrodinger's Grid-based ligand docking with energetics software, seven target proteins were retrieved from the database ( https://www.rcsb.org/ ).

RESULTS

HPLC technique identified twelve chemical compounds in PEHc, while antioxidant quantification revealed higher total phenolic contents (243.5 ± 0.71 mg GAE/g) than total flavonoid contents (54.06 ± 0.09 mg QE/g) with a significant (p < 0.05) inhibition of ABTS (IC₅₀ = 218.30 ± 0.87 µg/ml) and 1, 1-diphenyl-2-picrylhydrazyl free radicals (IC₅₀ = 227.79 ± 0.74 µg/ml). In a similar manner, the extract demonstrated a significant (p < 0.05) inhibitory activity against α-amylase (IC₅₀ = 256.88 ± 6.15 µg/ml) and α-glucosidase (IC₅₀ = 183.19 ± 0.23 µg/ml) as well as acetylcholinesterase (IC₅₀ = 262.95 ± 1.47 µg/ml) and butyrylcholinesterase (IC₅₀ = 189.97 ± 0.82 µg/ml), respectively. Furthermore, In silico study showed that hibiscetin (a lead) revealed a very strong binding affinity energies for DPP-4, (PDB ID: 1RWQ) and α-amylase (PDB ID: 1SMD), gamma-tocopherol ( for peptide-1 receptor; PDB ID: 3C59, AChE; PDB ID: 4EY7 and BChE; PDB ID: 7B04), cianidanol for α-glucosidase; PDB ID: 7KBJ and kaempferol for Poly [ADP-ribose] polymerase 1 (PARP-1); PDB ID: 6BHV, respectively. More so, ADMET scores revealed drug-like potentials of the lead compounds identified in PEHc.

CONCLUSION

As a result, the findings of this study point to potential drug-able compounds in PEHc that could be useful for the management of DM and AD.

Design, synthesis, molecular docking studies and biological evaluation of thiazole carboxamide derivatives as COX inhibitors

BACKGROUND

Nonsteroidal anti-inflammatory drugs (NSAIDs) have been the most commonly used class of medications worldwide for the last three decades.

OBJECTIVES

This study aimed to design and synthesize a novel series of methoxyphenyl thiazole carboxamide derivatives and evaluate their cyclooxygenase (COX) suppressant and cytotoxic properties.

METHODS

The synthesized compounds were characterized using ¹H, ¹³C-NMR, IR, and HRMS spectrum analysis and were evaluated for their selectivity towards COX-1 and COX-2 using an in vitro COX inhibition assay kit. Besides, their cytotoxicity was evaluated using the Sulforhodamine B (SRB) assay. Moreover, molecular docking studies were conducted to identify the possible binding patterns of these compounds within both COX-1 and COX-2 isozymes, utilizing human X-ray crystal structures. The density functional theory (DFT) analysis was used to evaluate compound chemical reactivity, which was determined by calculating the frontier orbital energy of both HOMO and LUMO orbitals, as well as the HOMO-LUMO energy gap. Finally, the QiKProp module was used for ADME-T analysis.

RESULTS

The results revealed that all synthesized molecules have potent inhibitory activities against COX enzymes. The percentage of inhibitory activities at 5 µM concentration against the COX2 enzyme was in the range of 53.9-81.5%, while the percentage against the COX-1 enzyme was 14.7-74.8%. That means almost all of our compounds have selective inhibition activities against the COX-2 enzyme, and the most selective compound was 2f, with selectivity ratio (SR) value of 3.67 at 5 µM concentration, which has a bulky group of trimethoxy on the phenyl ring that could not bind well with the COX-1 enzyme. Compound 2h was the most potent, with an inhibitory activity percentage at 5 µM concentration of 81.5 and 58.2% against COX-2 and COX-1, respectively. The cytotoxicity of these compounds was evaluated against three cancer cell lines: Huh7, MCF-7, and HCT116, and negligible or very weak activities were observed for all of these compounds except compound 2f, which showed moderate activities with IC₅₀ values of 17.47 and 14.57 µM against Huh7 and HCT116 cancer cell lines, respectively. Analysis of the molecular docking suggests 2d, 2e, 2f, and 2i molecules were bound to COX-2 isozyme favorably over COX-1 enzyme, and their interaction behaviors within COX-1 and COX-2 isozymes were comparable to celecoxib, as an ideal selective COX-2 drug, which explained their high potency and COX-2 selectivity. The molecular docking scores and expected affinity using the MM-GBSA approach were consistent with the recorded biological activity. The calculated global reactivity descriptors, such as HOMO and LUMO energies and the HOMO-LUMO gaps, confirmed the key structural features required to achieve favorable binding interactions and thus improve affinity. The in silico ADME-T studies asserted the druggability of molecules and have the potential to become lead molecules in the drug discovery process.

CONCLUSION

In general, the series of the synthesized compounds had a strong effect on both enzymes (COX-1 and COX-2) and the trimethoxy compound 2f was more selective than the other compounds.

Phytochemical Profiling, in Vitro Biological Activities and in Silico Molecular Docking Studies of the Crude Extract of Crambe orientalis, an Endemic Plant in Turkey

In this study, total phenolic and flavonoid analyses of flower, leaf, and stem aqueous extracts of C. orientalis were performed. Total phenolic contents of C. orientalis extracts ranged from 12.2±0.06 to 19.0±0.07 mg GAE/g extract. Total flavonoid values range between 2.0±0.11 and 6.6±0.19 mg CE/g extract. Urease, collagenase, tyrosinase, and α-glucosidase inhibition activities were determined in vitro and the relationship between them was examined. IC₅₀ results for all enzymes were obtained between 0.18 and 3.53 μg/mL. The aqueous extract of the plant C. orientalis showed potent cytotoxic effects against the human colon cancer cell lines DLD-1. As the extract concentration increases, cell death increases. The main fatty acid composition by GC/MS analysis is erucic acid (36.5 %). The potential binding modes of the fatty acids in the plant extract to the enzymes and possible inhibition mechanisms were determined by molecular docking calculation.

The inhibitory and anticancer properties of Annona squamosa L. seed extracts

Although Annona squamosa Linn. (Annonaceae) has been used in traditional medicine and is known to have several pharmacological properties, its impact on EGFR kinase has not been fully investigated. An assay (biochemical) was used to govern the potential of different A. squamosa seed extracts to scavenge free radicals in petroleum ether, acetone, ethanol, and methanol. We also tested A. squamosa leaf extracts for their ability to inhibit the growth of HEK 293, MCF7, and HepG2 cell lines. The PSE, ASE, ESE, and MSE all contained anti-cancer substances like anethole, cyclopentane, 1,1,3-trimethyl, and phosphonate oxide tributyl, according to phytochemical analysis. ESE extracts from A. squamosa seeds have been selected based on free radical generation probabilities, cytotoxicity studies, and phytochemical analysis. Subsequent insilico studies have been conducted, and the results have shown that interactions between compounds present in ESE extracts and the EGFR kinase are what give these compounds their inhibitory effects. Preliminary phytochemical and pharmacological activities were studied and reported. A. squamosa ESE extracts inhibited the growth of MCF7 cells, and a pharmacokinetic study showed that the compounds anethole, cyclopentane, 1,1,3-trimethyl, and phosphonium oxide tributyl had few undesirable side effects. These substances can be used to both prevent and treat cancer diseases.

Discovery and optimization of natural-based nanomolar c-Kit inhibitors via in silico and in vitro studies

c-Kit is a receptor tyrosine kinase which is involved in intracellular signaling and mutations of c-Kit have been associated with various types of cancers. Investigations have shown that inhibition of c-Kit, using tyrosine kinase inhibitors, yielded promising results in cancer treatment marking it as a promising target for cancer therapy. However, the emerging resistance for the current therapy necessitates the development of more potent inhibitors which are not affected by these mutations. Herein, virtual screening of a library of natural-based compounds yielded three hits (2, 5 and 6) which possessed nanomolar inhibitory (2.02, 4.33 and 2.80 nM, respectively) activity when tested in vitro against c-Kit. Single point mutation docking studies showed the hits to be unaffected by the most common resistance mutation in imatinib-resistant cells, mutation of Val654. Although, the top hits exhibited around 3000 higher inhibitory potency toward c-Kit when compared to imatinib (5.4 µM), previous studies have shown that they are metabolically unstable. Fragment-based drug design approaches were then employed to enhance binding affinity of the top hit and make it more metabolically stable. Screening of the generated fragments yielded a new derivative, F1, which demonstrated stronger binding affinity, stability and binding free energy when compared to the hit compound 2.Communicated by Ramaswamy H. Sarma.

Conformational changes in the AdeB transmembrane efflux pump by amphiphilic peptide Mastoparan-B, down-regulates expression of theadeB Gene and restores antibiotics Susceptibility.. [DOI: 10.1101/2023.01.03.522678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

No report exists on the role of Mastoparan B (MP-B) as an RND efflux pump inhibitor in multi-drug resistant (MDR)Acinetobacter baumannii. Here, we performed a series of in-silico experiments to predict the inhibition of the AdeB efflux pump by MP-B as a drug target agent. For this reason, an MDR strain ofA. baumanniiwas subjected to MICs against 12 antibiotics as well as MP-B. Expression of the adeB gene in the presence and absence of sub-MIC of MP-B was studied by qRT-PCR. It was found that MP-B had potent antimicrobial activity (MIC=1 μg/ml) associated with a 20-fold decrease in theadeB gene expression at the sub-MIC level. The stereochemical analysis using several automated servers confirmed that the AdeB protein is an inner membrane of the RND tripartite complex system with helix-turn-helix conformation and a pore rich in Phe, Ala, and Lys residue. Furthermore, 20 ligands were generated from the initial docked poses to create the correct protein-peptide complexes using the BioLiP pipeline. The pose showed high Z=1.2, C=1.41, TM=0.99, and RMSD=4.4 scores was selected for docking purposes. The molecular docking via AutoDock/Vina revealed that MP-B form H-bound with Val 499, Phe 454, Thr 474, Ser 461, Gly 465, and Tyr 468 residues of the AdeB helix-5 and caused a shift in the dihedral angle (Φ/Ψ) by distances of 9.0 Å, 9.3 Å, and 9.6 Å, respectively. This shift in folding was detected by AlphaFold 2 and influenced the overall druggability of the protein. From the above results, we concluded that MP-B can be a good candidate for bacterial efflux pump inhibition.

Synthesis of New Ester Derivatives of Salicylic Acid and Evaluation of Their COX Inhibitory Potential

Salicylic acid is an NSAID with serious side effects on the GIS. The side effects of salicylic acid on the GIS are slightly reduced by acetylating salicylic acid. 12 new ester analogs of salicylic acid were synthesized with high yields in this study. The chemical structures of the synthesized compounds were characterized by ¹ H-NMR, ¹³ C-NMR, and HRMS spectra. The inhibitory potential of the compounds was evaluated on COXs by in vitro and in silico studies. The COX2 inhibitory activity of the most potent inhibitor MEST1 (IC₅₀ : 0.048 μM) was found to be much higher than the COX2 inhibitory activity of aspirin (IC₅₀ : 2.60 μM). In docking studies, the strongest inhibitor among the compounds synthesized was predicted to be MEST1, with the lowest binding energy. Docking studies revealed that MEST1 extends from the hydrophobic channel to the top of the cyclooxygenase active site, forming various interactions with residues in the binding pocket.

Celecoxib, Glipizide, Lapatinib, and Sitagliptin as potential suspects of aggravating SARS-CoV-2 (COVID-19) infection: a computational approach

COVID-19 caused by SARS-CoV-2 has emerged as a potential threat to human life, especially to people suffering from chronic diseases. In this study, we investigated the ability of selected FDA-approved drugs to inhibit TACE (tumor necrosis factor α converting enzyme), which is responsible for the shedding of membrane-bound ACE2 (angiotensin-converting enzyme2) receptors into soluble ACE2. The inhibition of TACE would lead to an increased population of membrane-bound ACE2, which would facilitate ACE2-Spike protein interaction and viral entry. A total of 50 drugs prescribed in treating various chronic diseases in Saudi Arabia were screened by performing molecular docking using AutoDock4.2. Based on docking energy (≤ -9.00 kcal mol^-1), four drugs (Celecoxib, Glipizide, Lapatinib, and Sitagliptin) were identified as potential inhibitors of TACE, with binding affinities up to 10⁶-10⁷ M^-1. Analysis of the molecular docking suggests that these drugs were bound to TACE's catalytic domain and interact with the key residues such as His405, Glu406, and His415, which are involved in active site Zn²⁺ ion chelation. Molecular dynamics simulation was performed to confirm the stability of TACE-drugs complexes. RMSD (root mean square deviation), RMSF (root mean square fluctuation), Rg (radius of gyration), and SASA (solvent accessible surface area) were within the acceptable limits. Free energy calculations using Prime-MM/GBSA suggest that Celecoxib formed the most stable complex with TACE, followed by Glipizide, Sitagliptin, and Lapatinib. The finding of this study suggests a mechanism for drugs to aggravate SARS-CoV-2 infection and hence high mortality in patients suffering from chronic diseases.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.

Exploring novel and potent molecules for disrupting DEPTOR-mTOR interaction through structure-steered screening, extra-exactitude molecular docking, prime binding free energy estimation and voguish molecular dynamics

Dep domain containing mTOR interacting protein (DEPTOR) has critical implications in the development and progression of human malignancies. Increased expression of DEPTOR promotes the growth of tumor cells by inhibiting the mTORC1, which alleviates the negative feedback inhibition by mTORC1 downstream target S6Ks on PI3K/AKT pathway thereby promotes cell survival and prevents apoptosis. This clearly suggests that targetting DEPTOR-mTOR interactions through small molecules may prove as an effective strategy for circumventing distinct cancers. In this study, we employed a top-down approach for finding three novel molecules which may prove effective in disrupting Deptor-mTOR interaction. Following DEPTOR modelling and validation we performed grid-directed structure-based screening by specifying the residues of DEPTOR known to interact with mTOR. A library of 10,000 protein-protein disrupting molecules was screened against the defined region of DEPTOR. From the screened molecules, 30 molecules with highest binding affinity were chosen for molecular docking. Thirty (30) extra-precision molecular docking experiments and 30 molecular mechanics generalized born surface area (MMGBSA) assays were performed. Following this top 10 molecules in terms of binding affinity were selected and the interaction profile of their corresponding docked files was generated. The top three molecules were finally selected after taking all the three parameters including docking score, binding energy value and interaction profile into consideration. For atomistic insights regarding DEPTOR-topmost hit interactions, molecular dynamics was performed for 100 ns. This molecule after further evaluation may prove as promising candidate for anticancer therapy.Communicated by Ramaswamy H. Sarma.

Experimental, and theoretical investigations on the structure and vibrational spectral analysis of oxalate complex of nicotinamide and computational scrutiny against prostate cancer

This investigation involved oxalate salt of B vitamin experimental and theoretical spectra analysis. Docking studies and molecular dynamic simulation analysis were also carried out against the target protein involved in prostate cancer. At room temperature, the infra-red and Raman spectra results were chronicled in at range 4000-400 cm^-1. In the crystalline environment along with the shifting of some spectral bands, the effect of hydrogen bonding force is detected. HF and DFT/B3LYP were employed to estimate the optimized geometry with the basis set of 6-311++G (d,p). Hypothetical wavenumbers presented a respectable agreement with the investigational values. The various genuine modes are observed and some of them are perceived in the experimentally observed spectra. Hyperconjugative interaction and intramolecular charge transfer (ICT) values were calculated with the help of the natural bond orbital (NBO) study. HOMO-LUMO plot technique was employed to examine the compound's hardness of chemical, chemical potential, and electro-negativity. The molecules' bioactivity and therapeutic efficacy were estimated through the lower band gap value of the frontier orbitals. In silico analysis was performed, to analyse the therapeutic efficacy of oxalate complex of Nicotinamide against Prostate cancer through Molecular docking and dynamics study. ADME/T analysis revealed the pharmaceutical efficacy of the oxalate complex of Nicotinamide by satisfying Lipinski's Rule of Five, BBB, HOA, etc.Highlights of the workComparative studies of theoretical and experimental vibrational spectra of the B vitaminTheoretical wavenumber numbers were showed good agreement with the experimental valuesTheoretical bond lengths and bond angles were slightly deviated from the experimental valuesTheoretical calculations shows that B vitamin exists in a CocrystalNumber of modes calculated from the factor group method is match with the theoretical method.

Molecular mechanisms of Baihedihuang decoction as a treatment for breast cancer related anxiety: A network pharmacology and molecular docking study

BACKGROUND

The therapeutic effects of a combination of Chinese medicines called Baihedihuang decoction (BD) have been clinically verified, although its molecular targets in breast cancer related anxiety remain unknown.

AIM

To explore the molecular mechanisms of BD for breast cancer related anxiety treatment.

METHODS

We used the Traditional Chinese Medicine Systems Pharmacology database to screen the active ingredients and potential targets of BD, and constructed the "drug-ingredient-target" network map with the help of Cytoscape 3.8 software. Also, we used the Online Mendelian Inheritance in Man, DrugBank, and Gencards databases to collect the disease targets of breast cancer related anxiety, and used the STRING platform to perform protein interaction analysis and construct the protein-protein interaction network. Metascape platform was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of key targets. Molecular docking technology was used to verify the drug component/target disease network.

RESULTS

We screened 16 active ingredients of BD for breast cancer related anxiety, with 113 target proteins. There are 931 disease targets of breast cancer related anxiety, and finally, 43 key targets and 305 Kyoto Encyclopedia of Genes and Genomes pathways were generated. The main active ingredients of BD for breast cancer related anxiety are verbascoside, β-sitosterol, stigmasterol, catalpol, etc. CDK2, TP53, HTR2A, ESR1, etc. are its key targets, and the main involved signaling pathways may include neuroactive ligand-receptor interaction pathway, 5-hydroxytryptaminergic synapse, P53 signaling pathway, cGMP-PKG signaling pathway, the cAMP signaling pathway, etc. Finally, molecular docking was performed with Vina software to validate the key active ingredients in BD with the selected key action targets. The molecular docking results showed that verbascoside, β-sitosterol, stigmasterol and CDK2 could stably bind and interact through amino acid residues SER249, ARG260, PRO228, ALA282, SER276, LYS273, ASN272, etc.

CONCLUSION

The therapeutic effect of BD for breast cancer related anxiety is multi-level, multi-target, and multi-pathway. The findings of this study provide ideas and basis for further research.

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

SARS-CoV-2 triggered a worldwide medical crisis, affecting the world’s social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19’s threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski’s rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein–ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein–ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein–ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation.

Identification of 1H-purine-2,6-dione derivative as a potential SARS-CoV-2 main protease inhibitor: molecular docking, dynamic simulations, and energy calculations

The rapid spread of the coronavirus since its first appearance in 2019 has taken the world by surprise, challenging the global economy, and putting pressure on healthcare systems across the world. The introduction of preventive vaccines only managed to slow the rising death rates worldwide, illuminating the pressing need for developing effective antiviral therapeutics. The traditional route of drug discovery has been known to require years which the world does not currently have. In silico approaches in drug design have shown promising results over the last decade, helping to decrease the required time for drug development. One of the vital non-structural proteins that are essential to viral replication and transcription is the SARS-CoV-2 main protease (Mpro). Herein, using a test set of recently identified COVID-19 inhibitors, a pharmacophore was developed to screen 20 million drug-like compounds obtained from a freely accessible Zinc database. The generated hits were ranked using a structure based virtual screening technique (SBVS), and the top hits were subjected to in-depth molecular docking studies and MM-GBSA calculations over SARS-COV-2 Mpro. Finally, the most promising hit, compound (1), and the potent standard (III) were subjected to 100 ns molecular dynamics (MD) simulations and in silico ADME study. The result of the MD analysis as well as the in silico pharmacokinetic study reveal compound 1 to be a promising SARS-Cov-2 MPro inhibitor suitable for further development.

Investigation of effective natural inhibitors for starch hydrolysing enzymes from Simaroubaceae plants by molecular docking analysis and comparison with in-vitro studies

The present study aims to find the effective natural enzyme inhibitors against alpha-amylase and alpha-glucosidase from the array of compounds identified in plants of the Simaroubaceae family using molecular docking and ADME/Toxicity studies. Among the 218 compounds docked against seven enzymes, buddlenol-A and citrusin-B showed the best binding energies (kcal/mol) of -7.830 and -7.383 against human salivary alpha-amylase and pancreatic alpha-amylase respectively. The other two compounds 9-hydroxycanthin-6-one and bruceolline-B had the best binding energy of -6.461 and -7.576 against N-terminal and C-terminal maltase glucoamylase respectively. Whereas the binding energy of prosopine (-6.499) and fisetinidol (-7.575) was considered as the best against N-terminal and C-terminal sucrase-isomaltase respectively. Picrasidine-X showed the best binding energy (-7.592) against yeast alpha-glucosidase. The study revealed that the seven compounds which showed the best binding energy against respective enzymes are considered as the 'lead hit compounds'. Even though the 'lead hit compounds' are not obeying all the laws of ADMET, the drug-likeness properties of 9-hydroxycanthin-6-one, fisetinidol, picrasidine-X, and prosopine were considerable. Also, kaempferol-3-O-pentoside was the recent compound identified from the Simarouba glauca plant extract found to be one among the top five lead hit compounds against four enzymes. This study provides valuable insight into the direction of developing natural compounds as potential starch hydrolysing enzyme inhibitors for managing type 2 diabetes.

Exploring the Activity of Fungal Phenalenone Derivatives as Potential CK2 Inhibitors Using Computational Methods

Cancer represents one of the most prevalent causes of global death. CK2 (casein kinase 2) activation boosted cancer proliferation and progression. Therefore, CK2 inhibition can have a crucial role in prohibiting cancer progression and enhancing apoptosis. Fungi have gained vast interest as a wealthy pool of anticancer metabolites that could particularly target various cancer progression-linked signaling pathways. Phenalenones are a unique class of secondary metabolites that possess diverse bioactivities. In the current work, the CK2 inhibitory capacity of 33 fungal phenalenones was explored using computational studies. After evaluating the usefulness of the compounds as enzyme inhibitors by ADMET prediction, the compounds were prepared for molecular docking in the CK2-α1 crystal structure (PDB: 7BU4). Molecular dynamic simulation was performed on the top two scoring compounds to evaluate their binding affinity and protein stability through a simulated physiological environment. Compound 19 had a superior binding affinity to the co-crystallized ligand (Y49). The improved affinity can be attributed to the fact that the aliphatic chain makes additional contact with Asp120 in a pocket distant from the active site.

Risedronate and Methotrexate Are High-Affinity Inhibitors of New Delhi Metallo-β-Lactamase-1 (NDM-1): A Drug Repurposing Approach

Bacteria expressing New Delhi metallo-β-lactamase-1 (NDM-1) can hydrolyze β-lactam antibiotics (penicillins, cephalosporins, and carbapenems) and, thus, mediate multidrug resistance. The worldwide dissemination of NDM-1 poses a serious threat to public health, imposing a huge economic burden in the development of new antibiotics. Thus, there is an urgent need for the identification of novel NDM-1 inhibitors from a pool of already-known drug molecules. Here, we screened a library of FDA-approved drugs to identify novel non-β-lactam ring-containing inhibitors of NDM-1 by applying computational as well as in vitro experimental approaches. Different steps of high-throughput virtual screening, molecular docking, molecular dynamics simulation, and enzyme kinetics were performed to identify risedronate and methotrexate as the inhibitors with the most potential. The molecular mechanics/generalized Born surface area (MM/GBSA) and molecular dynamics (MD) simulations showed that both of the compounds (risedronate and methotrexate) formed a stable complex with NDM-1. Furthermore, analyses of the binding pose revealed that risedronate formed two hydrogen bonds and three electrostatic interactions with the catalytic residues of NDM-1. Similarly, methotrexate formed four hydrogen bonds and one electrostatic interaction with NDM-1's active site residues. The docking scores of risedronate and methotrexate for NDM-1 were -10.543 kcal mol-1 and -10.189 kcal mol-1, respectively. Steady-state enzyme kinetics in the presence of risedronate and methotrexate showed a decreased catalytic efficiency (i.e., kcat/Km) of NDM-1 on various antibiotics, owing to poor catalytic proficiency and affinity. The results were further validated by determining the MICs of imipenem and meropenem in the presence of risedronate and methotrexate. The IC50 values of the identified inhibitors were in the micromolar range. The findings of this study should be helpful in further characterizing the potential of risedronate and methotrexate to treat bacterial infections.

Identification of a novel peptide that activates alcohol dehydrogenase from crucian carp swim bladder and how it protects against acute alcohol-induced liver injury in mice

Alcoholism is a severe threat to public health, and there are no adequate treatments for alcoholic liver disease. The aim of this study was to identify bioactive peptides derived from natural proteins that prevent acute alcohol-induced liver injury. We identified a peptide with the sequence Gly-Leu-hydroxyproline-Gly-Glu-Arg (GLpGER) from the hydrolysate of crucian carp swim bladder using size-exclusion chromatography and reversed-phase chromatography. The in vitro EC₅₀ value of GLpGER to activate alcohol dehydrogenase (ADH) was 137.9 ± 9 µM. Molecular docking experiments indicated that the mechanism by which GLpGER activates ADH may be related to the formation of stable complexes with ADH active pockets through hydrogen bonding, and electrostatic and hydrophobic interactions. Oral administration of GLpGER one hour before acute alcohol ingestion significantly increased alcohol metabolism, manifesting as reduced incidence of the loss of righting reflex, increased alcohol tolerance time, shortened sobering time, and decreased blood alcohol concentration level. GLpGER restored liver ADH activity, maintained the typical morphology of hepatocytes, and reduced serum levels of alanine aminotransferase and aspartate aminotransferase. These findings suggest that GLpGER might reduce acute alcohol-induced liver injury and may have the potential to be developed as an anti-inebriation ingredient.

Combining in silico and in vitro approaches to identify endogenous hypoglycemic peptides from human milk

Potential endogenous hypoglycemic peptides derived from breast milk were screened by in silico approaches against intestinal glucose absorption- and metabolism-related membrane proteins (i.e., SGLT1, ATPase, and GPR40), and their inhibitory...

In Silico Screening of Available Drugs Targeting Non-Small Cell Lung Cancer Targets: A Drug Repurposing Approach

The RAS-RAF-MEK-ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper for the many malignant effects of its downstream effector. Even though MEK inhibitors are under investigation in many cancers, drug resistance continues to be the principal limiting factor to achieving cures in patients with cancer. Hence, we accomplished a high-throughput virtual screening to overcome this bottleneck by the discovery of dual-targeting therapy in cancer treatment. Here, a total of 11,808 DrugBank molecules were assessed through high-throughput virtual screening for their activity against MEK. Further, the Glide docking, MLSF and prime-MM/GBSA methods were implemented to extract the potential lead compounds from the database. Two compounds, DB012661 and DB07642, were outperformed in all the screening analyses. Further, the study results reveal that the lead compounds also have a significant binding capability with the co-target PIM1. Finally, the SIE-based free energy calculation reveals that the binding of compounds was majorly affected by the van der Waals interactions with MEK receptor. Overall, the in silico binding efficacy of these lead compounds against both MEK and PIM1 could be of significant therapeutic interest to overcome drug resistance in the near future.

Structure-based discovery of selective CYP17A1 inhibitors for Castration-resistant prostate cancer treatment

Prostate cancer (PCa) is the most common malignancy found in men and the second leading cause of cancer-related death worldwide. Castration-resistant PCa (CRPC) is defined by PCa cells that stop responding to hormone therapy. Cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17A1) plays a critical role in the biosynthesis of androgens in humans. Androgen signaling cascade is a principal survival pathway for PCa cells and androgen-deprivation therapy (ADT) remains the key treatment for patients marked with locally advanced and metastatic PCa cells. Available synthetic drugs have been reported for toxicity, drug resistance, and decreasing efficacy. Thus, the design of novel selective inhibitors of CYP17A1 lyase would help circumvent associated side effects and improve pharmacological activities. Therefore, we employed structural bioinformatics techniques via molecular docking; molecular mechanics generalized born surface area (MM-GBSA), molecular dynamics (MD) simulation, and pharmacokinetic study to identify putative CYP17A1 lyase inhibitors. The results of the computational investigation showed that the Prunus dulcis compounds exhibited higher binding energy than the clinically approved abiraterone acetate. The stability of the ligand with the highest binding affinity (quercetin-3-o-rutinoside) was observed during MD simulation for 10 ns. Quercetin-3-o-rutinoside was observed to be stable within the active site of CYP17A1Lyase throughout the simulation period. The result of the pharmacokinetic study revealed that these compounds are promising therapeutic agents. Collectively, this study proposed that bioactive compounds from P. dulcis may be potential selective inhibitors of CYP17A1Lyase in CRPC treatments.

QSAR and deep learning model for virtual screening of potential inhibitors against Inosine 5' Monophosphate dehydrogenase (IMPDH) of Cryptosporidium parvum

Cryptosporidium parvum (Cp) causes a gastro-intestinal disease called Cryptosporidiosis. C. parvum Inosine 5' monophosphate dehydrogenase (CpIMPDH) is responsible for the production of guanine nucleotides. In the present study, 37 known urea-based congeneric compounds were used to build a 2D and 3D QSAR model against CpIMPDH. The built models were validated based on OECD principles. A deep learning model was adopted from a framework called Deep Purpose. The model was trained with 288 known active compounds and validated using a test set. From the training set of the 3D QSAR, a pharmacophore model was built and the best pharmacophore hypotheses were scored and sorted using a phase-hypo score. A phytochemical database was screened using both the pharmacophore model and a deep learning model. The screened compounds were considered for glide XP docking, followed by quantum polarized ligand docking. Finally, the best compound among them was considered for molecular dynamics simulation study.

In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: an approach to prevent virus assembly

Currently, there is no specific treatment to cure COVID-19. Many medicinal plants have antiviral, antioxidant, antibacterial, antifungal, anticancer, wound healing etc. Therefore, the aim of the current study was to screen for potent inhibitors of N-terminal domain (NTD) of nucleocapsid phosphoprotein of SARS-CoV-2. The structure of NTD of RNA binding domain of nucleocapsid phosphoprotein of SARS coronavirus 2 was retrieved from the Protein Data Bank (PDB 6VYO) and the structures of 100 different phytocompounds were retrieved from Pubchem. The receptor protein and ligands were prepared using Schrodinger's Protein Preparation Wizard. Molecular docking was done by using the Schrodinger's maestro 12.0 software. Drug likeness and toxicity of active phytocompounds was predicted by using Swiss adme, admetSAR and protox II online servers. Molecular dynamic simulation of the best three protein- ligand complexes (alizarin, aloe-emodin and anthrarufin) was performed to study the interaction stability. We have identified three potential active sites (named as A, B, C) on receptor protein for efficient binding of the phytocompounds. We found that, among 100 phytocompounds, emodin, aloe-emodin, anthrarufin, alizarine, and dantron of Rheum emodi showed good binding affinity at all the three active sites of RNA binding domain of nucleocapsid phosphoprotein of COVID-19.The binding energies of emodin, aloe-emodin, anthrarufin, alizarine, and dantron were -8.299, -8.508, -8.456, -8.441, and -8.322 Kcal mol^-1 respectively (site A), -7.714, -6.433, -6.354, -6.598, and -6.99 Kcal mol^-1 respectively (site B), and -8.299, 8.508, 8.538, 8.841, and 8.322 Kcal mol^-1 respectively (site C). All the active phytocompounds follows the drug likeness properties, non-carcinogenic, and non-toxic. Theses phytocompounds (alone or in combination) could be developed into effective therapy against COVID-19. From MD simulation data, we found that all three complexes of 6VYO with alizarin, aloe-emodin and anthrarufin were stable up to 50 ns. These phytocompounds can be tested further for in vitro or in vivo and used as a potential drug to cure SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: an approach to prevent virus assembly

Currently, there is no specific treatment to cure COVID-19. Many medicinal plants have antiviral, antioxidant, antibacterial, antifungal, anticancer, wound healing etc. Therefore, the aim of the current study was to screen for potent inhibitors of N-terminal domain (NTD) of nucleocapsid phosphoprotein of SARS-CoV-2. The structure of NTD of RNA binding domain of nucleocapsid phosphoprotein of SARS coronavirus 2 was retrieved from the Protein Data Bank (PDB 6VYO) and the structures of 100 different phytocompounds were retrieved from Pubchem. The receptor protein and ligands were prepared using Schrodinger's Protein Preparation Wizard. Molecular docking was done by using the Schrodinger's maestro 12.0 software. Drug likeness and toxicity of active phytocompounds was predicted by using Swiss adme, admetSAR and protox II online servers. Molecular dynamic simulation of the best three protein- ligand complexes (alizarin, aloe-emodin and anthrarufin) was performed to study the interaction stability. We have identified three potential active sites (named as A, B, C) on receptor protein for efficient binding of the phytocompounds. We found that, among 100 phytocompounds, emodin, aloe-emodin, anthrarufin, alizarine, and dantron of Rheum emodi showed good binding affinity at all the three active sites of RNA binding domain of nucleocapsid phosphoprotein of COVID-19.The binding energies of emodin, aloe-emodin, anthrarufin, alizarine, and dantron were -8.299, -8.508, -8.456, -8.441, and -8.322 Kcal mol^-1 respectively (site A), -7.714, -6.433, -6.354, -6.598, and -6.99 Kcal mol^-1 respectively (site B), and -8.299, 8.508, 8.538, 8.841, and 8.322 Kcal mol^-1 respectively (site C). All the active phytocompounds follows the drug likeness properties, non-carcinogenic, and non-toxic. Theses phytocompounds (alone or in combination) could be developed into effective therapy against COVID-19. From MD simulation data, we found that all three complexes of 6VYO with alizarin, aloe-emodin and anthrarufin were stable up to 50 ns. These phytocompounds can be tested further for in vitro or in vivo and used as a potential drug to cure SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

Computational Evaluation of Bioactive Compounds from Colocasia affinis Schott as a Novel EGFR Inhibitor for Cancer Treatment

INTRODUCTION

Epidermal growth factor receptor (EGFR) is a transmembrane protein that belongs to the ErbB/HER-family of tyrosine kinase receptors. Somatic mutations and overexpression of EGFR have been reported to play a vital role in cancer cell development and progression, including cell proliferation, differentiation, angiogenesis, apoptosis, and metastatic spread. Hence, EGFR is an important therapeutic target for the treatment of various types of epithelial cancers. Somatic mutations have led to resistance to clinically approved synthetic EGFR inhibitors. Furthermore, synthetic EGFR inhibitors have been associated with several side effects. Thus, there is a need to develop novel EGFR inhibitors with an acceptable biosafety profile and high efficacy.

METHODS

Herein, we employed structural bioinformatics and theoretical chemistry techniques via molecular docking, molecular mechanics generalized Born surface area (MM-GBSA) calculation, density functional theory analysis (DFT), and pharmacokinetic study to identify novel EGFR inhibitors.

RESULTS

The stringent molecular docking and MM-GBSA calculations identified MET 793, LYS 745, PHE 723, ASP 855, ARG 411, and THR 854 as principal amino acid residues for EGFR-ligands interactions. Furthermore, Colocasia affinis Schott compounds exhibited higher binding energy and more stable interactions than the reference compound (gefitinib). DFT analysis also ascertains better bioactivity and chemical reactivity of C. affinis Schott with favorable intramolecular charge transfer between electron-donor and electron acceptor groups. The pharmacokinetic profile of C. affinis Schott bioactive compounds satisfies Lipinski's rule of five assessment.

CONCLUSION

Collectively, C. affinis Schott compounds demonstrated higher inhibitory potentials against EGFR and better pharmacological properties when compared with gefitinib. C. affinis Schott compounds are therefore suggested as promising therapeutic EGFR inhibitors for cancer treatment.

Combined 4D-QSAR and target-based approaches for the determination of bioactive Isatin derivatives

The hybrid method of the Electron-Conformational Genetic Algorithm (EC-GA) was used to determine the pharmacophore groups and to estimate anticancer activity in isatin derivatives using a robust 4D-QSAR software (EMRE). To build the model, each compound is represented by a set of conformers rather than a single conformation. The Electron Conformational Matrix of Congruity (ECMC) is composed via EMRE software. Electron Conformational Submatrix of Activity (ECSA) was calculated by the comparison of these matrices. Genetic algorithm was used to select important variables to predict theoretical activity. The model with the best seven parameters produced satisfactory results. The E statistics technique was applied to the generated EC-GA model to evaluate the individual contribution of each of the descriptors on biological activity. The r² and q² values of the training set compounds were found to be 0.95 and 0.93, respectively. Because no previous 4D-QSAR studies on isatin derivatives have been conducted, this study is important in the development of new isatin derivatives. In this study, 27 isatin derivatives whose activities were estimated using the hybrid EC-GA method were also investigated through molecular docking and molecular dynamics simulations for their BCL-2 inhibitory activity.

High-Throughput Screening and Molecular Dynamics Simulation of Natural Product-like Compounds against Alzheimer's Disease through Multitarget Approach

Alzheimer’s disease (AD) is a progressive neurological disorder that affects 50 million people. Despite this, only two classes of medication have been approved by the FDA. Therefore, we have planned to develop therapeutics by multitarget approach. We have explored the library of 2029 natural product-like compounds for their multi-targeting potential against AD by inhibiting AChE, BChE (cholinergic pathway) MAO-A, and MOA-B (oxidative stress pathway) through in silico high-throughput screening and molecular dynamics simulation. Based on the binding energy of these target enzymes, approximately 189 compounds exhibited a score of less than −10 kcal/mol against all targets. However, none of the control inhibitors exhibited a binding affinity of less than −10 kcal/mol. Among these, the top 10 hits of compounds against all four targets were selected for ADME-T analysis. As a result, only F0850-4777 exhibited an acceptable range of physicochemical properties, drug-likeness, pharmacokinetics, and suitability for BBB permeation with high GI-A and non-toxic effects. The molecular dynamics study confirmed that F0850-4777 remained inside the binding cavity of targets in a stable conformation throughout the simulation and Prime-MM/GBSA study revealed that van der Waals’ energy (ΔG_vdW) and non-polar solvation or lipophilic energy (ΔG_{Sol_Lipo}) contribute favorably towards the formation of a stable protein–ligand complex. Thus, F0850-4777 could be a potential candidate against multiple targets of two pathophysiological pathways of AD and opens the doors for further confirmation through in vitro and in vivo systems.

Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations

The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits-ZINC20392430, SN00112175, SN00004718, and SN00262261-having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.

Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review

Computer-aided drug design (CADD) is one of the pivotal approaches to contemporary pre-clinical drug discovery, and various computational techniques and software programs are typically used in combination, in a bid to achieve the desired outcome. Several approved drugs have been developed with the aid of CADD. On SciFinder®, we evaluated more than 600 publications through systematic searching and refining, using the terms, virtual screening; software methods; computational studies and publication year, in order to obtain data concerning particular aspects of CADD. The primary focus of this review was on the databases screened, virtual screening and/or molecular docking software program used. Furthermore, we evaluated the studies that subsequently performed molecular dynamics (MD) simulations and we reviewed the software programs applied, the application of density functional theory (DFT) calculations and experimental assays. To represent the latest trends, the most recent data obtained was between 2015 and 2020, consequently the most frequently employed techniques and software programs were recorded. Among these, the ZINC database was the most widely preferred with an average use of 31.2%. Structure-based virtual screening (SBVS) was the most prominently used type of virtual screening and it accounted for an average of 57.6%, with AutoDock being the preferred virtual screening/molecular docking program with 41.8% usage. Following the screening process, 38.5% of the studies performed MD simulations to complement the virtual screening and GROMACS with 39.3% usage, was the popular MD software program. Among the computational techniques, DFT was the least applied whereby it only accounts for 0.02% average use. An average of 36.5% of the studies included reports on experimental evaluations following virtual screening. Ultimately, since the inception and application of CADD in pre-clinical drug discovery, more than 70 approved drugs have been discovered, and this number is steadily increasing over time.