A Computational Study on Thiourea Analogs as Potent MK-2 Inhibitors

Mitogen-activated protein kinase-activated protein kinase 2 (MK-2) has been identified as a drug target for the treatment of inflammatory diseases. Currently, a series of thiourea analogs as potent MK-2 inhibitors were studied using comprehensive computational methods by 3D-QSAR, molecular docking and molecular dynamics simulations for a further improvement in activities. The optimal 3D models exhibit high statistical significance of the results, especially for the CoMFA results with r(2) (ncv), q(2) values of 0.974, 0.536 for the internal validation, and r(2) (pred), r(2) (m) values of 0.910, 0.723 for the external validation and Roy's index, respectively. In addition, more rigorous validation criteria suggested by Tropsha were also employed to check the built models. Graphic representation of the results, as contoured 3D coefficient plots, also provides a clue to the reasonable modification of molecules: (i) The substituent with a bulky size and electron-rich group at the C5 position of the pyrazine ring is required to enhance the potency; (ii) The H-bond acceptor group in the C3 position of the pyrazine ring is likely to be helpful to increase MK-2 inhibition; (iii) The small and electropositive substituent as a hydrogen bond donor of the C2 position in the oxazolone ring is favored; In addition, several important amino acid residues were also identified as playing an important role in MK-2 inhibition. The agreement between 3D-QSAR, molecular docking and molecular dynamics simulations also proves the rationality of the developed models. These results, we hope, may be helpful in designing novel and potential MK-2 inhibitors.     

A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ

Fragment-Based Drug Discovery (FBDD) has become, in recent years, a consolidated approach in the drug discovery process, leading to several drug candidates under investigation in clinical trials and some approved drugs. Among these successful applications of the FBDD approach, kinases represent a class of targets where this strategy has demonstrated its real potential with the approved kinase inhibitor Vemurafenib. In the Kinase family, protein kinase CK1 isoform δ (CK1δ) has become a promising target in the treatment of different neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. In the present work, we set up and applied a computational workflow for the identification of putative fragment binders in large virtual databases. To validate the method, the selected compounds were tested in vitro to assess the CK1δ inhibition.     

Exploration of N-Arylsulfonyl-indole-2-carboxamide Derivatives as Novel Fructose-1,6-bisphosphatase Inhibitors by Molecular Simulation

A series of N-arylsulfonyl-indole-2-carboxamide derivatives have been identified as potent fructose-1,6-bisphosphatase (FBPase) inhibitors (FBPIs) with excellent selectivity for the potential therapy of type II diabetes mellitus. To explore the structure–activity relationships (SARs) and the mechanisms of action of these FBPIs, a systematic computational study was performed in the present study, including three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, pharmacophore modeling, molecular dynamics (MD), and virtual screening. The constructed 3D-QSAR models exhibited good predictive ability with reasonable parameters using comparative molecular field analysis (q² = 0.709, R² = 0.979, r_pre² = 0.932) and comparative molecular similarity indices analysis (q² = 0.716, R² = 0.978, r_pre² = 0.890). Twelve hit compounds were obtained by virtual screening using the best pharmacophore model in combination with molecular dockings. Three compounds with relatively higher docking scores and better ADME properties were then selected for further studies by docking and MD analyses. The docking results revealed that the amino acid residues Met18, Gly21, Gly26, Leu30, and Thr31 at the binding site were of great importance for the effective bindings of these FBPIs. The MD results indicated that the screened compounds VS01 and VS02 could bind with FBPase stably as its cognate ligand in dynamic conditions. This work identified several potential FBPIs by modeling studies and might provide important insights into developing novel FBPIs.     

A Combination of 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation Studies of Benzimidazole-Quinolinone Derivatives as iNOS Inhibitors

Inducible Nitric Oxide Synthase (iNOS) has been involved in a variety of diseases, and thus it is interesting to discover and optimize new iNOS inhibitors. In previous studies, a series of benzimidazole-quinolinone derivatives with high inhibitory activity against human iNOS were discovered. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking and molecular dynamics (MD) simulation approaches were applied to investigate the functionalities of active molecular interaction between these active ligands and iNOS. A QSAR model with R² of 0.9356, Q² of 0.8373 and Pearson-R value of 0.9406 was constructed, which presents a good predictive ability in both internal and external validation. Furthermore, a combined analysis incorporating the obtained model and the MD results indicates: (1) compounds with the proper-size hydrophobic substituents at position 3 in ring-C (R₃ substituent), hydrophilic substituents near the X₆ of ring-D and hydrophilic or H-bond acceptor groups at position 2 in ring-B show enhanced biological activities; (2) Met368, Trp366, Gly365, Tyr367, Phe363, Pro344, Gln257, Val346, Asn364, Met349, Thr370, Glu371 and Tyr485 are key amino acids in the active pocket, and activities of iNOS inhibitors are consistent with their capability to alter the position of these important residues, especially Glu371 and Thr370. The results provide a set of useful guidelines for the rational design of novel iNOS inhibitors.     

Synthesis and SAR of Tetracyclic Inhibitors of Protein Kinase CK2 Derived from Furocarbazole W16

The serine/threonine kinase CK2 modulates the activity of more than 300 proteins and thus plays a crucial role in various physiological and pathophysiological processes including neurodegenerative disorders of the central nervous system and cancer. The enzymatic activity of CK2 is controlled by the equilibrium between the heterotetrameric holoenzyme CK2α₂β₂ and its monomeric subunits CK2α and CK2β. A series of analogues of W16 ((3aR,4S,10S,10aS)-4-{[(S)-4-benzyl-2-oxo-1,3-oxazolidin-3-yl]carbonyl}-10-(3,4,5-trimethoxyphenyl)-4,5,10,10a-tetrahydrofuro[3,4-b]carbazole-1,3(3aH)-dione ((+)- 3 a )) was prepared in an one-pot, three-component Levy reaction. The stereochemistry of the tetracyclic compounds was analyzed. Additionally, the chemically labile anhydride structure of the furocarbazoles 3 was replaced by a more stable imide ( 9 ) and N-methylimide ( 10 ) substructure. The enantiomer (−)- 3 a (K_i=4.9 μM) of the lead compound (+)- 3 a (K_i=31 μM) showed a more than sixfold increased inhibition of the CK2α/CK2β interaction (protein-protein interaction inhibition, PPII) in a microscale thermophoresis (MST) assay. However, (−)- 3 a did not show an increased enzyme inhibition of the CK2α₂β₂ holoenzyme, the CK2α subunit or the mutated CK2α′ ^C336S subunit in the capillary electrophoresis assay. In the pyrrolocarbazole series, the imide (−)- 9 a (K_i=3.6 μM) and the N-methylimide (+)- 10 a (K_i=2.8 μM) represent the most promising inhibitors of the CK2α/CK2β interaction. However, neither compound could inhibit enzymatic activity. Unexpectedly, the racemic tetracyclic pyrrolocarbazole (±)- 12 , with a carboxy moiety in the 4-position, displays the highest CK2α/CK2β interaction inhibition (K_i=1.8 μM) of this series of compounds.     

Synthesis of Dihydrobenzofuro[3,2-b]chromenes as Potential 3CLpro Inhibitors of SARS-CoV-2: A Molecular Docking and Molecular Dynamics Study

The recent emergence of pandemic of coronavirus (COVID-19) caused by SARS-CoV-2 has raised significant global health concerns. More importantly, there is no specific therapeutics currently available to combat against this deadly infection. The enzyme 3-chymotrypsin-like cysteine protease (3CLpro) is known to be essential for viral life cycle as it controls the coronavirus replication. 3CLpro could be a potential drug target as established before in the case of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). In the current study, we wanted to explore the potential of fused flavonoids as 3CLpro inhibitors. Fused flavonoids (5a,10a-dihydro-11H-benzofuro[3,2-b]chromene) are unexplored for their potential bioactivities due to their low natural occurrences. Their synthetic congeners are also rare due to unavailability of general synthetic methodology. Here we designed a simple strategy to synthesize 5a,10a-dihydro-11H-benzofuro[3,2-b]chromene skeleton and it's four novel derivatives. Our structural bioinformatics study clearly shows excellent potential of the synthesized compounds in comparison to experimentally validated inhibitor N3. Moreover, in-silico ADMET study displays excellent druggability and extremely low level of toxicity of the synthesized molecules. Further, for better understanding, the molecular dynamic approach was implemented to study the change in dynamicity after the compounds bind to the protein. A detailed investigation through clustering analysis and distance calculation gave us sound comprehensive data about their molecular interaction. In summary, we anticipate that the currently synthesized molecules could not only be a potential set of inhibitors against 3CLpro but also the insights acquired from the current study would be instrumental in further developing novel natural flavonoid based anti-COVID therapeutic spectrums.     

In Silico Evaluation of Hexamethylene Amiloride Derivatives as Potential Luminal Inhibitors of SARS-CoV-2 E Protein

The coronavirus E proteins are small membrane proteins found in the virus envelope of alpha and beta coronaviruses that have a high degree of overlap in their biochemical and functional properties despite minor sequence variations. The SARS-CoV-2 E is a 75-amino acid transmembrane protein capable of acting as an ion channel when assembled in a pentameric fashion. Various studies have found that hexamethylene amiloride (HMA) can inhibit the ion channel activity of the E protein in bilayers and also inhibit viral replication in cultured cells. Here, we use the available structural data in conjunction with homology modelling to build a comprehensive model of the E protein to assess potential binding sites and molecular interactions of HMA derivatives. Furthermore, we employed an iterative cycle of molecular modelling, extensive docking simulations, molecular dynamics and leveraging steered molecular dynamics to better understand the pore characteristics and quantify the affinity of the bound ligands. Results from this work highlight the potential of acylguanidines as blockers of the E protein and guide the development of subsequent small molecule inhibitors.     

Structural Determination of Three Different Series of Compounds as Hsp90 Inhibitors Using 3D-QSAR Modeling, Molecular Docking and Molecular Dynamics Methods

Hsp90 is involved in correcting, folding, maturation and activation of a diverse array of client proteins; it has also been implicated in the treatment of cancer in recent years. In this work, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), molecular docking and molecular dynamics were performed on three different series of Hsp90 inhibitors to build 3D-QSAR models, which were based on the ligand-based or receptor-based methods. The optimum 3D-QSAR models exhibited reasonable statistical characteristics with averaging internal q(2) > 0.60 and external r(2) (pred) > 0.66 for Benzamide tetrahydro-4H-carbazol-4-one analogs (BT), AT13387 derivatives (AT) and Dihydroxylphenyl amides (DA). The results revealed that steric effects contributed the most to the BT model, whereas H-bonding was more important to AT, and electrostatic, hydrophobic, H-bond donor almost contributed equally to the DA model. The docking analysis showed that Asp93, Tyr139 and Thr184 in Hsp90 are important for the three series of inhibitors. Molecular dynamics simulation (MD) further indicated that the conformation derived from docking is basically consistent with the average structure extracted from MD simulation. These results not only lead to a better understanding of interactions between these inhibitors and Hsp90 receptor but also provide useful information for the design of new inhibitors with a specific activity.     

Anti-adipogenic and Pro-lipolytic Effects on 3T3-L1 Preadipocytes by CX-4945, an Inhibitor of Casein Kinase 2

Casein kinase 2 (CK2) is a ubiquitously expressed serine/threonine kinase and is upregulated in human obesity. CX-4945 (Silmitasertib) is a CK2 inhibitor with anti-cancerous and anti-adipogenic activities. However, the anti-adipogenic and pro-lipolytic effects and the mode of action of CX-4945 in (pre)adipocytes remain elusive. Here, we explored the effects of CX-4945 on adipogenesis and lipolysis in differentiating and differentiated 3T3-L1 cells, a murine preadipocyte cell line. CX-4945 at 15 μM strongly reduced lipid droplet (LD) accumulation and triglyceride (TG) content in differentiating 3T3-L1 cells, indicating the drug’s anti-adipogenic effect. Mechanistically, CX-4945 reduced the expression levels of CCAAT/enhancer-binding protein-α (C/EBP-α), peroxisome proliferator-activated receptor-γ (PPAR-γ), fatty acid synthase (FAS), acetyl-CoA carboxylase (ACC), and perilipin A in differentiating 3T3-L1 cells. Strikingly, CX-4945 further increased the phosphorylation levels of cAMP-activated protein kinase (AMPK) and liver kinase B-1 (LKB-1) while decreasing the intracellular ATP content in differentiating 3T3-L1 cells. In differentiated 3T3-L1 cells, CX-4945 had abilities to stimulate glycerol release and elevate the phosphorylation levels of hormone-sensitive lipase (HSL), pointing to the drug’s pro-lipolytic effect. In addition, CX-4945 induced the activation of extracellular signal-regulated kinase-1/2 (ERK-1/2), and PD98059, an inhibitor of ERK-1/2, attenuated the CX4945-induced glycerol release and HSL phosphorylation in differentiated 3T3-L1 cells, indicating the drug’s ERK-1/2-dependent lipolysis. In summary, this investigation shows that CX-4945 has strong anti-adipogenic and pro-lipolytic effects on differentiating and differentiated 3T3-L1 cells, mediated by control of the expression and phosphorylation levels of CK2, C/EBP-α, PPAR-γ, FAS, ACC, perilipin A, AMPK, LKB-1, ERK-1/2, and HSL.     

Computational Design of Miniproteins as SARS-CoV-2 Therapeutic Inhibitors

A rational therapeutic strategy is urgently needed for combating SARS-CoV-2 infection. Viral infection initiates when the SARS-CoV-2 receptor-binding domain (RBD) binds to the ACE2 receptor, and thus, inhibiting RBD is a promising therapeutic for blocking viral entry. In this study, the structure of lead antiviral candidate binder (LCB1), which has three alpha-helices (H1, H2, and H3), is used as a template to design and simulate several miniprotein RBD inhibitors. LCB1 undergoes two modifications: structural modification by truncation of the H3 to reduce its size, followed by single and double amino acid substitutions to enhance its binding with RBD. We use molecular dynamics (MD) simulations supported by ab initio density functional theory (DFT) calculations. Complete binding profiles of all miniproteins with RBD have been determined. The MD investigations reveal that the H3 truncation results in a small inhibitor with a −1.5 kcal/mol tighter binding to RBD than original LCB1, while the best miniprotein with higher binding affinity involves D17R or E11V + D17R mutation. DFT calculations provide atomic-scale details on the role of hydrogen bonding and partial charge distribution in stabilizing the minibinder:RBD complex. This study provides insights into general principles for designing potential therapeutics for SARS-CoV-2.     

Analysis of Binding Determinants for Different Classes of Competitive and Noncompetitive Inhibitors of Glycine Transporters

Glycine transporters are interesting therapeutic targets as they play significant roles in glycinergic and glutamatergic systems. The search for new selective inhibitors of particular types of glycine transporters (GlyT-1 and GlyT-2) with beneficial kinetics is hampered by limited knowledge about the spatial structure of these proteins. In this study, a pool of homology models of GlyT-1 and GlyT-2 in different conformational states was constructed using the crystal structures of related transporters from the SLC6 family and the recently revealed structure of GlyT-1 in the inward-open state, in order to investigate their binding sites. The binding mode of the known GlyT-1 and GlyT-2 inhibitors was determined using molecular docking studies, molecular dynamics simulations, and MM-GBSA free energy calculations. The results of this study indicate that two amino acids, Gly373 and Leu476 in GlyT-1 and the corresponding Ser479 and Thr582 in GlyT-2, are mainly responsible for the selective binding of ligands within the S1 site. Apart from these, one pocket of the S2 site, which lies between TM3 and TM10, may also be important. Moreover, selective binding of noncompetitive GlyT-1 inhibitors in the intracellular release pathway is affected by hydrophobic interactions with Ile399, Met382, and Leu158. These results can be useful in the rational design of new glycine transporter inhibitors with desired selectivity and properties in the future.     

3D-QSAR and Molecular Docking Studies on Derivatives of MK-0457, GSK1070916 and SNS-314 as Inhibitors against Aurora B Kinase

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.     

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.     

Pharmacophore and Molecular Docking Guided 3D-QSAR Study of Bacterial Enoyl-ACP Reductase (FabI) Inhibitors

Enoyl acyl carrier protein (ACP) reductase (FabI) is a potential target for the development of antibacterial agents. Three-dimensional quantitative structure-activity relationships (3D-QSAR) for substituted formamides series of FabI inhibitors were investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Pharmacophore and molecular docking methods were used for construction of the molecular alignments. A training set of 36 compounds was performed to create the 3D-QSAR models and their external predictivity was proven using a test set of 11 compounds. Graphical interpretation of the results revealed important structural features of the formamides related to the active site of FabI. The results may be exploited for further optimization of the design of new potent FabI inhibitors.     

Structural requirements of N-substituted spiropiperidine analogues as agonists of nociceptin/orphanin FQ receptor

The nociceptin/orphanin FQ (NOP) receptor is involved in a wide range of biological functions, including pain, anxiety, depression and drug abuse. Especially, its agonists have great potential to be developed into anxiolytics. In this work, both the ligand- and receptor-based three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques on 103 N-substituted spiropiperidine analogues as NOP agonists. The resultant optimal ligand-based CoMSIA model exhibited Q(2) of 0.501, R(2) (ncv) of 0.912 and its predictive ability was validated by using an independent test set of 26 compounds which gave R(2) (pred) value of 0.818. In addition, docking analysis and molecular dynamics simulation (MD) were also applied to elucidate the probable binding modes of these agonists. Interpretation of the 3D contour maps, in the context of the topology of the active site of NOP, provided insight into the NOP-agonist interactions. The information obtained from this work can be used to accurately predict the binding affinity of related agonists and also facilitate the future rational design of novel agonists with improved activity.     

Combined 3D-QSAR and Docking Modelling Study on Indolocarbazole Series Compounds as Tie-2 Inhibitors

Tie-2, a kind of endothelial cell tyrosine kinase receptor, is required for embryonic blood vessel development and tumor angiogenesis. Several compounds that showed potent activity toward this attractive anticancer drug target in the assay have been reported. In order to investigate the structure-activity correlation of indolocarbazole series compounds and modify them to improve their selectivity and activity, 3D-QSAR models were built using CoMFA and CoMSIA methods and molecular docking was used to check the results. Based on the common sketch align, two good QSAR models with high predictabilities (CoMFA model: q(2) = 0.823, r(2) = 0.979; CoMSIA model: q(2) = 0.804, r(2) = 0.967) were obtained and the contour maps obtained from both models were applied to identify the influence on the biological activity. Molecular docking was then used to confirm the results. Combined with the molecular docking results, the detail binding mode between the ligands and Tie-2 was elucidated, which enabled us to interpret the structure-activity relationship. These satisf actory results not only offered help to comprehend the action mechanism of indolocarbazole series compounds, but also provide new information for the design of new potent inhibitors.     

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.     

3D-QSAR Studies on Barbituric Acid Derivatives as Urease Inhibitors and the Effect of Charges on the Quality of a Model

Urease enzyme (EC 3.5.1.5) has been determined as a virulence factor in pathogenic microorganisms that are accountable for the development of different diseases in humans and animals. In continuance of our earlier study on the helicobacter pylori urease inhibition by barbituric acid derivatives, 3D-QSAR (three dimensional quantitative structural activity relationship) advance studies were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. Different partial charges were calculated to examine their consequences on the predictive ability of the developed models. The finest developed model for CoMFA and CoMSIA were achieved by using MMFF94 charges. The developed CoMFA model gives significant results with cross-validation (q²) value of 0.597 and correlation coefficients (r²) of 0.897. Moreover, five different fields i.e., steric, electrostatic, and hydrophobic, H-bond acceptor and H-bond donors were used to produce a CoMSIA model, with q² and r² of 0.602 and 0.98, respectively. The generated models were further validated by using an external test set. Both models display good predictive power with r²_pred ≥ 0.8. The analysis of obtained CoMFA and CoMSIA contour maps provided detailed insight for the promising modification of the barbituric acid derivatives with an enhanced biological activity.