IKK-beta inhibitors: an analysis of drug-receptor interaction by using molecular docking and pharmacophore 3D-QSAR approaches

Study of Pentacyclic Triterpenes from Lyophilised Aguaje: Anti-Inflammatory and Antioxidant Properties

Mauritia flexuosa (M. flexuosa), commonly known as Aguaje or Moriche palm, is traditionally recognised in South America for its medicinal properties, particularly for its anti-inflammatory and antioxidant effects. However, the bioactive compounds responsible for these effects have not been thoroughly investigated. This study aims to isolate and characterise pentacyclic triterpenoid compounds from M. flexuosa and to evaluate their therapeutic potential. Using various chromatographic and spectroscopic techniques including Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS), three pentacyclic triterpenoid compounds were successfully isolated. Among them, compound 1 (3,11-dioxours-12-en-28-oic acid) exhibited notable bioactivity, significantly inhibiting the activation of Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB) (IC50 = 7.39-8.11 μM) and of Nitric Oxide (NO) (IC50 = 4.75-6.59 μM), both of which are key processes in inflammation. Additionally, compound 1 demonstrated potent antioxidant properties by activating the antioxidant enzyme Superoxide Dismutase (SOD) (EC50 = 1.87 μM) and the transcription factor Nuclear factor erythroid 2-related factor 2 (Nrf2) (EC50 = 243-547.59 nM), thus showing its potential in combating oxidative stress. This study is the first to isolate and characterise the three compounds from M. flexuosa, suggesting that compound 1 could be a promising candidate for the development of safer and more effective therapies for inflammatory and oxidative stress-related diseases.

MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs

BACKGROUND

Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments but also expedites drug development process. However, achieving the desired level of computational accuracy for DTA identification methods remains a significant challenge.

RESULTS

We proposed a novel multi-view-based graph deep model known as MvGraphDTA for DTA prediction. MvGraphDTA employed a graph convolutional network (GCN) to extract the structural features from original graphs of drugs and targets, respectively. It went a step further by constructing line graphs with edges as vertices based on original graphs of drugs and targets. GCN was also used to extract the relationship features within their line graphs. To enhance the complementarity between the extracted features from original graphs and line graphs, MvGraphDTA fused the extracted multi-view features of drugs and targets, respectively. Finally, these fused features were concatenated and passed through a fully connected (FC) network to predict DTA.

CONCLUSIONS

During the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.

Elucidation and active ingredient identification of aqueous extract of Ficus exasperata Vahl leaf against bisphenol A-induced toxicity through in vivo and in silico assessments

Bisphenol A (BPA), an endocrine-disrupting chemical, poses significant health problems due to its induction of oxidative stress, inflammation, etc. Whereas Ficus exasperata Vahl leaf (FEVL) was reported for its ethnopharmacological properties against several ailments owing to its antioxidant, anti-inflammatory properties, etc. Here, we aim to elucidate and identify the bioactive compounds of aqueous extract of FEVL (AEFEVL) against BPA-induced toxicity using in vivo and in silico assessments. To determine the BPA toxicity mechanism and safe doses of AEFEVL, graded doses of BPA (0-400 μM) and AEFEVL (0-2.0 mg/10 g diets) were separately fed to flies to evaluate survival rates and specific biochemical markers. The mitigating effect of AEFEVL (0.5 and 1.0 mg/10 g diet) against BPA (100 and 200 μM)-induced toxicity in the flies after 7-day exposure was also carried out. Additionally, molecular docking analysis of BPA and BPA-o-quinone (BPAQ) against selected antioxidant targets, and HPLC-MS-revealed AEFEVL compounds against Keap-1 and IKKβ targets, followed by ADMET analysis, was conducted. Emergence rate, climbing ability, acetylcholinesterase, monoamine oxidase-B, and glutathione-S-transferase activities, and levels of total thiols, non-protein thiols, nitric oxide, protein carbonyl, malondialdehyde, and cell viability were evaluated. BPA-induced altered biochemical and behavioral parameters were significantly mitigated by AEFEVL in the flies (p < 0.05). BPAQ followed by BPA exhibited higher inhibitory activity, and epigallocatechin (EGC) showed the highest inhibitory activity among the AEFEVL compounds with desirable ADMET properties. Conclusively, our findings revealed that EGC might be responsible for the mitigative effect displayed by AEFEVL in BPA-induced toxicity in D. melanogaster.

Graphical abstract

ELIXIR-A: An Interactive Visualization Tool for Multi-Target Pharmacophore Refinement

Pharmacophore modeling is an important step in computer-aided drug design for identifying interaction points between the receptor and ligand complex. Pharmacophore-based models can be used for de novo drug design, lead identification, and optimization in virtual screening as well as for multi-target drug design. There is a need to develop a user-friendly interface to filter the pharmacophore points resulting from multiple ligand conformations. Here, we present ELIXIR-A, a Python-based pharmacophore refinement tool, to help refine the pharmacophores between multiple ligands from multiple receptors. Furthermore, the output can be easily used in virtual pharmacophore-based screening platforms, thereby contributing to the development of drug discovery.

An overview of kinase downregulators and recent advances in discovery approaches

Since the clinical approval of imatinib, the discovery of protein kinase downregulators entered a prosperous age. However, challenges still exist in the discovery of kinase downregulator drugs, such as the high failure rate during development, side effects, and drug-resistance problems. With the progress made through multidisciplinary efforts, an increasing number of new approaches have been applied to solve the above problems during the discovery process of kinase downregulators. In terms of in vitro and in vivo drug evaluation, progress was also made in cellular and animal model platforms for better and more clinically relevant drug assessment. Here, we review the advances in drug design strategies, drug property evaluation technologies, and efficacy evaluation models and technologies. Finally, we discuss the challenges and perspectives in the development of kinase downregulator drugs.

In silico drug discovery of IKK-β inhibitors from 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives based on QSAR, docking, molecular dynamics and drug-likeness evaluation studies

The Inhibitor of IKK-β (nuclear factor kappa B kinase subunit beta), a specific modulator of NF-κB (nuclear factor-κB), is considered a valid target to discover new active compounds for various cancers and rheumatoid arthritis treatment. In this study a series of thirty 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives was involved for a quantitative structure activity relationship model (QSAR) elaboration which allows the prediction of the pIC50 values of new designed compounds. The model can be used to predict the activity of new compounds within its applicability domain. Then a molecular docking study was carried out to identify the interactions between the compounds and the amino acids of the active site. After that, golden triangle, Veber's rule, and Lipinski's rule properties were calculated to identify the drug-likeness properties of the investigated compounds. Finally, in-silico-toxicity studies were performed to predict the toxicity of the new designed compounds. The analysis of the results of QSAR model and molecular docking succeeded to screen 21 interesting compounds with better inhibitory concentration having a good affinity to IKK-β. All compounds were within the range set by Veber's rule and Lipinski's rule. the analysis of golden triangle showed that the thirty 2-amino-3-cyano-4-alkyl-6-(2-hydroxyphenyl) pyridine derivatives would not have clearance and cell membrane permeability problems except comp6 comp12,comp20, comp21, and comp26.As for the new designed compounds, their properties may have these problems, except two compounds which are: A8m, A8p. The A1m, A1p, A3p and A11m compounds were predicted to be nontoxic. These findings indicate that the novel potent candidate drugs have promising potential to IKK-β enzyme inhibition and should motivate future experimental investigations.Communicated by Ramaswamy H. Sarma.

Targeting Nonsense: Optimization of 1,2,4-Oxadiazole TRIDs to Rescue CFTR Expression and Functionality in Cystic Fibrosis Cell Model Systems

Cystic fibrosis (CF) patients develop a severe form of the disease when the cystic fibrosis transmembrane conductance regulator (CFTR) gene is affected by nonsense mutations. Nonsense mutations are responsible for the presence of a premature termination codon (PTC) in the mRNA, creating a lack of functional protein. In this context, translational readthrough-inducing drugs (TRIDs) represent a promising approach to correct the basic defect caused by PTCs. By using computational optimization and biological screening, we identified three new small molecules showing high readthrough activity. The activity of these compounds has been verified by evaluating CFTR expression and functionality after treatment with the selected molecules in cells expressing nonsense–CFTR–mRNA. Additionally, the channel functionality was measured by the halide sensitive yellow fluorescent protein (YFP) quenching assay. All three of the new TRIDs displayed high readthrough activity and low toxicity and can be considered for further evaluation as a therapeutic approach toward the second major cause of CF.

Pan-Cancer Analysis and Drug Formulation for GPR139 and GPR142

GPR (G protein receptor) 139 and 142 are novel foundling GPCRs (G protein-coupled receptors) in the class "A" of the GPCRs family and are suitable targets for various biological conditions. To engage these targets, validated pharmacophores and 3D QSAR (Quantitative structure-activity relationship) models are widely used because of their direct fingerprinting capability of the target and an overall accuracy. The current work initially analyzes GPR139 and GPR142 for its genomic alteration via tumor samples. Next to that, the pharmacophore is developed to scan the 3D database for such compounds that can lead to potential agonists. As a result, several compounds have been considered, showing satisfactory performance and a strong association with the target. Additionally, it is gripping to know that the obtained compounds were observed to be responsible for triggering pan-cancer. This suggests the possible role of novel GPR139 and GPR142 as the substances for initiating a physiological response to handle the condition incurred as a result of cancer.

Rescuing the CFTR protein function: Introducing 1,3,4-oxadiazoles as translational readthrough inducing drugs

Nonsense mutations in the CFTR gene prematurely terminate translation of the CFTR mRNA leading to the production of a truncated protein that lacks normal function causing a more severe form of the cystic fibrosis (CF) disease. About 10% of patients affected by CF show a nonsense mutation. A potential treatment of this alteration is to promote translational readthrough of premature termination codons (PTCs) by Translational Readthrough Inducing Drugs (TRIDs) such as PTC124. In this context we aimed to compare the activity of PTC124 with analogues differing in the heteroatoms position in the central heterocyclic core. By a validated protocol consisting of computational screening, synthesis and biological tests we identified a new small molecule (NV2445) with 1,3,4-oxadiazole core showing a high readthrough activity. Moreover, we evaluated the CFTR functionality after NV2445 treatment in CF model systems and in cells expressing a nonsense-CFTR-mRNA. Finally, we studied the supramolecular interactions between TRIDs and CFTR-mRNA to assess the biological target/mechanism and compared the predicted ADME properties of NV2445 and PTC124.

Hyphenated 3D-QSAR statistical model-drug repurposing analysis for the identification of potent neuraminidase inhibitor

The Influenza A virus is one of the principle causes of respiratory illness in human. The surface glycoprotein of the influenza virus, neuraminidase (NA), has a vital role in the release of new viral particle and spreads infection in the respiratory tract. It has been long recognized as a valid drug target for influenza A virus infection. Oseltamivir is used as a standard drug of choice for the treatment of influenza. However, the emergence of mutants with novel mutations has increased the resistance to potent NA inhibitor. In the present investigation, we have employed computer-assisted combinatorial techniques in the screening of 8621 molecules from Drug Bank to find potent NA inhibitors. A three-dimensional pharmacophore model was generated from the previously reported 28 carbocylic influenza NA inhibitors along with oseltamivir using PHASE module of Schrödinger Suite. The model generated consists of one hydrogen bond acceptor (A), one hydrogen bond donors (D), one hydrophobic group (H), and one positively charged group (P), ADHP. The hypothesis was further validated for its integrity and significance using enrichment analysis. Subsequently, an atom-based 3D-QSAR model was built using the common pharmacophore hypothesis (CPH). The developed 3D-QSAR model was found to be statistically significant with R² value of 0.9866 and Q² value of 0.7629. Further screening was accomplished using three-stage docking process using the Glide algorithm. The resultant lead molecules were examined for its drug-like properties using the Qikprop algorithm. Finally, the calculated pIC₅₀ values of the lead compounds were validated by the AutoQSAR algorithm. Overall, the results from our analysis highlights that lisinopril (DB00722) is predicted to bind better with NA than currently approved drug. In addition, it has the best match in binding geometry conformations with the existing NA inhibitor. Note that the antiviral activity of lisinopril is reported in the literature. However, our paper is the first report on lisinopril activity against influenza A virus infection. These results are envisioned to help design the novel NA inhibitors with an increased antiviral efficacy.

A Molecular Dynamics-Shared Pharmacophore Approach to Boost Early-Enrichment Virtual Screening: A Case Study on Peroxisome Proliferator-Activated Receptor α

Molecular dynamics (MD) simulations can be used, prior to virtual screening, to add flexibility to proteins and study them in a dynamic way. Furthermore, the use of multiple crystal structures of the same protein containing different co-crystallized ligands can help elucidate the role of the ligand on a protein's active conformation, and then explore the most common interactions between small molecules and the receptor. In this work, we evaluated the contribution of the combined use of MD on crystal structures containing the same protein but different ligands to examine the crucial ligand-protein interactions within the complexes. The study was carried out on peroxisome proliferator-activated receptor α (PPARα). Findings derived from the dynamic analysis of interactions were then used as features for pharmacophore generation and constraints for generating the docking grid for use in virtual screening. We found that information derived from short multiple MD simulations using different molecules within the binding pocket of the target can improve the early enrichment of active ligands in the virtual screening process for this receptor. In the end we adopted a consensus scoring based on docking score and pharmacophore alignment to rank our dataset. Our results showed an improvement in virtual screening performance in early recognition when screening was performed with the Molecular dYnamics SHAred PharmacophorE (MYSHAPE) approach.

Conf-VLKA: A structure-based revisitation of the Virtual Lock-and-key Approach

In a previous work, we developed the in house Virtual Lock-and-Key Approach (VLKA) in order to evaluate target assignment starting from molecular descriptors calculated on known inhibitors used as an information source. This protocol was able to predict the correct biological target for the whole dataset with a good degree of reliability (80%), and proved experimentally, which was useful for the target fishing of unknown compounds. In this paper, we tried to remodel the previous in house developed VLKA in a more sophisticated one in order to evaluate the influence of 3D conformation of ligands on the accuracy of the prediction. We applied the same previous algorithm of scoring and ranking but, this time, combining it with a structure-based approach as docking. For this reason, we retrieved from the RCSB Protein Data Bank (PDB), the available 3D structures of the biological targets included into the previous work, and we used them to calculate poses of the 7352 dataset compounds in the VLKA biological targets. First, docking protocol has been used to retrieve docking scores, then, from the docked poses of each molecule, 3D-descriptors were calculated (Conf-VLKA), While the use of the simple docking scores proved to be inadequate to improve compounds classification, the Conf-VLKA showed some interesting variations compared to the original VLKA, especially for targets whose ligands present a high number of rotamers. This work represent a first preliminary study to be completed using other techniques such as induced fit docking or molecular dynamics structure clustering to take into account the protein side chains adaptation to ligands structures.

Design, synthesis and preliminary evaluation of dopamine-amino acid conjugates as potential D1 dopaminergic modulators

The dopamine-amino acid conjugate DA-Phen was firstly designed to obtain a useful prodrug for the therapy of Parkinson's disease, but experimental evidence shows that it effectively interacts with D₁ dopamine receptors (D₁DRs), leading to an enhancement in cognitive flexibility and to the development of adaptive strategies in aversive mazes, together with a decrease in despair-like behavior. In this paper, homology modelling, molecular dynamics, and site mapping of D1 receptor were carried out with the aim of further performing docking studies on other dopamine conjugates compared with D1 agonists, in the attempt to identify new compounds with potential dopaminergic activity. Two new conjugates (DA-Trp 2C, and DA-Leu 3C) have been identified as the most promising candidates, and consequently synthesized. Preliminary evaluation in terms of distribution coefficient (D^pH7.4), stability in rat brain homogenate, and in human plasma confirmed that DA-Trp (2C), and DA-Leu (3C) could be considered as very valuable candidates for further in vivo studies as new dopaminergic drugs.

Exploring the readthrough of nonsense mutations by non-acidic Ataluren analogues selected by ligand-based virtual screening

Ataluren, also known as PTC124, is a 5-(fluorophenyl)-1,2,4-oxadiazolyl-benzoic acid suggested to suppress nonsense mutations by readthrough of premature stop codons in the mRNA. Potential interaction of PTC124 with mRNA has been recently studied by molecular dynamics simulations highlighting the importance of H-bonding and stacking π-π interactions. A series of non-acidic analogues of PTC124 were selected from a large database via a ligand-based virtual screening approach. Eight of them were synthesized and tested for their readthrough activity using the Fluc reporter harboring the UGA premature stop codon. The most active compound was further tested for suppression of the UGA nonsense mutation in the bronchial epithelial IB3.1 cell line carrying the W1282X mutation in the CFTR gene.

New IKK inhibitors: Synthesis of new imidazo[1,2-a]quinoxaline derivatives using microwave assistance and biological evaluation as IKK inhibitors

The inhibition of the NF-κB-dependent pathways by IKK inhibitors plays an important role in immunity, inflammation, and cancer. New imidazoquinoxalines tricyclic derivatives are prepared using microwave assistance and their biological activities as IKK inhibitors are described. Compounds 6a present a potent inhibition activity and selectivity for IKK2. Docking studies in the IKK2 binding site allowed identification of residues most likely to interact with theses inhibitors and explain their potent IKK2 inhibition activity and selectivity.

Synthesis and Biological Screening of Silicon-Containing Ibuprofen Derivatives: A Study of Their NF-κβ Inhibitory Activity, Cytotoxicity, and Their Ability to Bind IKKβ

The synthesis and characterisation of new silicon-containing amides and esters derived from ibuprofen is reported. These compounds were tested against nuclear transcription factor κβ (NF-κβ). Higher inhibition values than those of ibuprofen were achieved by the new amides 10a–10d; ester derivatives did not show inhibitory activity. The cytotoxicity of these new derivatives was screened; none of them displayed significant toxicity at the screened doses. A molecular docking calculation on IKKβ (an enzyme related to NF-κβ activation) was carried out and the results showed that the amides interact better than ibuprofen with key residues, which are important to the inhibition of IKKβ.

The molecular events behind ferulic acid mediated modulation of IL-6 expression in LPS-activated Raw 264.7 cells

Identification of new antioxidant and anti-inflammatory bioactive molecules is an important tool for selecting effective formulations for the treatment of inflammation. The mouse macrophage cell line RAW 264.7, lipopolysaccharide (LPS)-activated, is associated with an inflammation response. Activated macrophages produce reactive oxygen species (ROS), nitric oxide (NO) and inflammatory cytokines such as IL-6, TNF-α and IL-10. In the present study we have showed that pre-treatment with Ferulic Acid (FA) reduces NO accumulation in the culture medium of LPS-induced macrophage cells. Moreover, real-time experiments have revealed that FA has an inhibitory effect at the transcriptional level on the expression of some inflammatory mediators such as IL-6, TNF-α and iNOS and an activation effect on the expression of some antioxidant molecules such as Metallothioneins (MT-1, MT-2). Importantly, we have found that FA reduced the translocation of NF-E2-related factor 2 (Nrf2) and nuclear transcription factor-κB (NF-κB) into the nuclei through a reduction of the expression of phosphorylated IKK and consequently inhibited IL-6 and NF-κB promoter activity in a luciferase assay. Our data clearly suggest that FA anti-inflammatory effects are mainly mediated through IKK/NF-κB signalling pathway. Therefore, FA could represent a new natural drug extremely useful to improve anti-inflammatory treatment.

Miltirone Induces G2/M Cell Cycle Arrest and Apoptosis in CCRF-CEM Acute Lymphoblastic Leukemia Cells

Miltirone (1) is a diterpene quinone extracted from a well-known Chinese traditional herb (Salvia miltiorrhiza). We investigated the cytotoxic effects of miltirone toward sensitive and multidrug-resistant acute lymphoblastic leukemia cell lines. Miltirone inhibited multidrug-resistant P-glycoprotein (P-gp)-overexpressing CEM/ADR5000 cells better than drug-sensitive CCRF-CEM wild-type cells, a phenomenon termed collateral sensitivity. Flow cytometric analyses revealed that miltirone induced G2/M arrest and apoptosis. Furthermore, miltirone stimulated reactive oxygen species (ROS) generation and mitochondrial membrane potential (MMP) disruption, which in turn induced DNA damage and activation of caspases and poly ADP-ribose polymerase (PARP). Downregulation of CCNB1 (cyclin B1) and CDC2 mRNA and upregulation of CDKN1A (p21) mRNA were in accord with miltirone-induced G2/M arrest. Moreover, miltirone decreased cell adherence to fibronectin. Molecular docking revealed that miltirone bound to the ATP-binding site of IKK-β. In conclusion, miltirone was collateral sensitive in multidrug-resistant P-gp-overexpressing cells, induced G2/M arrest, and triggered apoptosis via ROS-generated breakdown of MMP and DNA damage. Therefore, miltirone may be a promising candidate for cancer chemotherapy.

Accelerating Multiple Compound Comparison Using LINGO-Based Load-Balancing Strategies on Multi-GPUs

Compound comparison is an important task for the computational chemistry. By the comparison results, potential inhibitors can be found and then used for the pharmacy experiments. The time complexity of a pairwise compound comparison isO(n2), wherenis the maximal length of compounds. In general, the length of compounds is tens to hundreds, and the computation time is small. However, more and more compounds have been synthesized and extracted now, even more than tens of millions. Therefore, it still will be time-consuming when comparing with a large amount of compounds (seen as a multiple compound comparison problem, abbreviated to MCC). The intrinsic time complexity of MCC problem isO(k2n2)withkcompounds of maximal lengthn. In this paper, we propose a GPU-based algorithm for MCC problem, called CUDA-MCC, on single- and multi-GPUs. Four LINGO-based load-balancing strategies are considered in CUDA-MCC in order to accelerate the computation speed among thread blocks on GPUs. CUDA-MCC was implemented by C+OpenMP+CUDA. CUDA-MCC achieved 45 times and 391 times faster than its CPU version on a single NVIDIA Tesla K20m GPU card and a dual-NVIDIA Tesla K20m GPU card, respectively, under the experimental results.

New benzothieno[3,2-d]-1,2,3-triazines with antiproliferative activity: synthesis, spectroscopic studies, and biological activity

New benzothieno[3,2-d]-1,2,3-triazines, together with precursors triazenylbenzo[b]thiophenes, were designed, synthesized and screened as anticancer agents. The structural features of these compounds prompted us to investigate their DNA binding capability through UV-vis absorption titrations, circular dichroism, and viscometry, pointing out the occurrence of groove-binding. The derivative 3-(4-methoxy-phenyl)benzothieno[3,2-d]-1,2,3-triazin-4(3H)-one showed the highest antiproliferative effect against HeLa cells and was also tested in cell cycle perturbation experiments. The obtained results assessed for the first time the anticancer activity of benzothieno[3,2-d]-1,2,3-triazine nucleus, and we related it to its DNA-binding properties.

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

Design checkpoint kinase 2 inhibitors by pharmacophore modeling and virtual screening techniques

Damage to DNA is caused by ionizing radiation, genotoxic chemicals or collapsed replication forks. When DNA is damaged or cells fail to respond, a mutation that is associated with breast or ovarian cancer may occur. Mammalian cells control and stabilize the genome using a cell cycle checkpoint to prevent damage to DNA or to repair damaged DNA. Checkpoint kinase 2 (Chk2) is one of the important kinases, which strongly affects DNA-damage and plays an important role in the response to the breakage of DNA double-strands and related lesions. Therefore, this study concerns Chk2. Its purpose is to find potential inhibitors using the pharmacophore hypotheses (PhModels) and virtual screening techniques. PhModels can identify inhibitors with high biological activities and virtual screening techniques are used to screen the database of the National Cancer Institute (NCI) to retrieve compounds that exhibit all of the pharmacophoric features of potential inhibitors with high interaction energy. Ten PhModels were generated using the HypoGen best algorithm. The established PhModel, Hypo01, was evaluated by performing a cost function analysis of its correlation coefficient (r), root mean square deviation (RMSD), cost difference, and configuration cost, with the values 0.955, 1.28, 192.51, and 16.07, respectively. The result of Fischer's cross-validation test for the Hypo01 model yielded a 95% confidence level, and the correlation coefficient of the testing set (rtest) had a best value of 0.81. The potential inhibitors were then chosen from the NCI database by Hypo01 model screening and molecular docking using the cdocker docking program. Finally, the selected compounds exhibited the identified pharmacophoric features and had a high interaction energy between the ligand and the receptor. Eighty-three potential inhibitors for Chk2 are retrieved for further study.

Exploring the anticancer potential of pyrazolo[1,2-a]benzo[1,2,3,4]tetrazin-3-one derivatives: the effect on apoptosis induction, cell cycle and proliferation

In order to investigate their anticancer potential, four new pyrazolo[1,2-a]benzo[1,2,3,4]tetrazinone derivatives, designed through the chemometric protocol VLAK, and three of the most active compounds of the previous series have been evaluated on some cellular events including proliferation, apoptosis induction, and cell cycle. The NCI one dose (10 μM) screening revealed that the 8,9-di-methyl derivative showed activity against Leukemia (CCRF-CEM) and Colon cancer cell line (COLO 205), reaching 81% and 45% of growth inhibition (GI), respectively. Replacement of the two methyl groups with two chlorine atoms maintained the activity toward Leukemia cell (CCRF-CEM, GI 77%) and selectively enhanced the activity against COLO 205 attaining a LD50 in the μM range and against SW-620 a GI of 77%. Interestingly, an appreciable growth inhibition of 47% against therapeutically "refractory" Non-Small Cell Lung Cancer (NCI-H522) was observed. Moreover, the apoptosis induction, based on mitochondrial membrane depolarization, was found in the range EC50 3-5 μM on HeLa cell, evidencing a well defined relationship with the related in vitro cell growth inhibitory assays (MTT) performed against other selected tumor cell lines not included in the NCI tumor panel (HeLa, cervix; H292, lung; LAN-5, CNS; CaCo-2, colon; 16HBE, normal human cell lung) and against MCF-7 tumor cell line (breast). Only for the most active compounds, further cell cycle tests on HeLa displayed a cell arrest on S phase. Thus, a promising new class of anticancer candidates, acting as valuable apoptotic inductors, is proposed.

Synthesis and biological activities of a new class of heat shock protein 90 inhibitors, designed by energy-based pharmacophore virtual screening

The design through energy-based pharmacophore virtual screening has led to aminocyanopyridine derivatives as efficacious new inhibitors of Hsp90. The synthesized compounds showed a good affinity for the Hsp90 ATP binding site in the competitive binding assay. Moreover, they showed an excellent antiproliferative activity against a large number of human tumor cell lines. Further biological studies on the derivative with the higher EC50 confirmed its specific influence on the cellular pathways involving Hsp90.

Novel IKKβ inhibitors discovery based on the co-crystal structure by using binding-conformation-based and ligand-based method

IκB kinase β (IKKβ), an attractive anti-inflammation and anti-cancer target, plays a crucial role in the activation of NF-κB signalling pathway. To identify novel IKKβ inhibitors, we combined structure-based and ligand-based methods based on the co-crystal structure of IKKβ. According to the chemical similarity, 162 reported IKKβ inhibitors were divided into five classes. For each class, a 3D pharmacophore model was established based on the binding conformations of the compounds. The validated models were further used in virtual screening. Twelve drugable compounds were retained for biological test, resulting in two novel inhibitors with IC50 values lower than 10 μM. Compared to other models, our method considers the crystal structure of IKKβ for the first time.

Design of novel FLT-3 inhibitors based on dual-layer 3D-QSAR model and fragment-based compounds in silico

FMS-like tyrosine kinase 3 (FLT-3) is strongly correlated with acute myeloid leukemia, but no FLT-3-inhibitor cocomplex structure is available to assist the design of therapeutic inhibitors. Hence, we propose a dual-layer 3D-QSAR model for FLT-3 that integrates the pharmacophore, CoMFA, and CoMSIA. We then coupled the model with the fragment-based design strategy to identify novel FLT-3 inhibitors. In the first layer, the previously established model, Hypo02, was evaluated in terms of its correlation coefficient (r), RMS, cost difference, and configuration cost, with values of 0.930, 1.24, 106.45, and 16.44, respectively. Moreover, Fischer's cross-validation test of data generated by Hypo02 yielded a 98% confidence level, and the validation of the testing set yielded a best r value of 0.87. The features of Hypo02 were separated into two parts and then used to screen the MiniMaybridge fragment compound database. Nine novel FLT-3 inhibitors were generated in this layer. In the second layer, Hypo02 was subjected to an alignment rule to generate CoMFA- and CoMSIA-based models, for which the partial least-squares validation method was utilized. The values of q(2), r(2), and predictive r(2) were 0.58, 0.98, and 0.76, respectively, derived from the CoMFA model with steric and electrostatic fields. The CoMSIA model with five different fields yielded values of 0.54, 0.97, and 0.76 for q(2), r(2), and predictive r(2), respectively. The CoMFA and CoMSIA models were used to constrain 3D structures of the nine novel FLT-3 inhibitors. This dual-layer 3D-QSAR model constitutes a valuable tool to easily and quickly screen and optimize novel potential FLT-3 inhibitors for the treatment of acute myeloid leukemia.

In vitro and in silico studies of polycondensed diazine systems as anti-parasitic agents

Parasitic diseases caused by protozoarian agents are still relevant today more than ever. Recently, we synthesized several polycondensed diazine derivatives by means 1,3-dipolar cycloaddition reactions. A broad selection of these compounds were submitted to in vitro biological screening against Plasmodium falciparum, Leishmania infantum, Trypanosoma brucei, and Trypanosoma cruzi, resulting active at micromolar level. Induced Fit Docking/MM-GBSA studies were performed giving interesting indications about the probable mechanism of action of the most active compounds.

Structure and dynamics of the kinase IKK-β--A key regulator of the NF-kappa B transcription factor

The inhibitor κB kinase-β (IKK-β) phosphorylates the NF-κB inhibitor protein IκB leading to the translocation of the transcription factor NF-κB to the nucleus. The transcription factor NF-κB and consequently IKK-β are central to signal transduction pathways of mammalian cells. The purpose of this research was to develop a 3D structural model of the IKK-β kinase domain with its ATP cofactor and investigate its dynamics and ligand binding potential. Through a combination of comparative modelling and simulated heating/annealing molecular dynamics (SAMD) simulation in explicit water the model accuracy could be substantially improved compared to comparative modelling on its own as shown by model validation measures. The structure revealed the details of ATP/Mg(2+) binding indicating hydrophobic interactions with the adenine base and a significant contribution of Mg(2+) as a bridge between ATP phosphate groups and negatively charged side chains. The molecular dynamics trajectories of the ATP-bound and free enzyme showed two conformations in each case, which contributed to the majority of the trajectory. The ATP-free enzyme revealed a novel binding site distant from the ATP binding site that was not encountered in the ATP bound enzyme. Based on the overall structural flexibility, it is suggested that a truncated version of the kinase domain from Ala14 to Leu265 should be subjected to crystallisation trials. The 3D structure of this enzyme will enable rational design of new ligands and analysis of protein-protein interactions. Furthermore, our results may provide a new impetus for wet-lab based structural investigation focussing on a truncated kinase domain.

Structural and functional studies of a 50 kDa antigenic protein from Salmonella enterica serovar Typhi

The high typhoid incidence rate in developing and under-developed countries emphasizes the need for a rapid, affordable and accessible diagnostic test for effective therapy and disease management. TYPHIDOT®, a rapid dot enzyme immunoassay test for typhoid, was developed from the discovery of a ∼50 kDa protein specific for Salmonella enterica serovar Typhi. However, the structure of this antigen remains unknown till today. Studies on the structure of this antigen are important to elucidate its function, which will in turn increase the efficiency of the development and improvement of the typhoid detection test. This paper described the predictive structure and function of the antigenically specific protein. The homology modeling approach was employed to construct the three-dimensional structure of the antigen. The built structure possesses the features of TolC-like outer membrane protein. Molecular docking simulation was also performed to further probe the functionality of the antigen. Docking results showed that hexamminecobalt, Co(NH(3))(6)(3+), as an inhibitor of TolC protein, formed favorable hydrogen bonds with D368 and D371 of the antigen. The single point (D368A, D371A) and double point (D368A and D371A) mutations of the antigen showed a decrease (single point mutation) and loss (double point mutations) of binding affinity towards hexamminecobalt. The architecture features of the built model and the docking simulation reinforced and supported that this antigen is indeed the variant of outer membrane protein, TolC. As channel proteins are important for the virulence and survival of bacteria, therefore this ∼50 kDa channel protein is a good specific target for typhoid detection test.

Identification of human IKK-2 inhibitors of natural origin (part I): modeling of the IKK-2 kinase domain, virtual screening and activity assays

BACKGROUND

Their large scaffold diversity and properties, such as structural complexity and drug similarity, form the basis of claims that natural products are ideal starting points for drug design and development. Consequently, there has been great interest in determining whether such molecules show biological activity toward protein targets of pharmacological relevance. One target of particular interest is hIKK-2, a serine-threonine protein kinase belonging to the IKK complex that is the primary component responsible for activating NF-κB in response to various inflammatory stimuli. Indeed, this has led to the development of synthetic ATP-competitive inhibitors for hIKK-2. Therefore, the main goals of this study were (a) to use virtual screening to identify potential hIKK-2 inhibitors of natural origin that compete with ATP and (b) to evaluate the reliability of our virtual-screening protocol by experimentally testing the in vitro activity of selected natural-product hits.

METHODOLOGY/PRINCIPAL FINDINGS

We thus predicted that 1,061 out of the 89,425 natural products present in the studied database would inhibit hIKK-2 with good ADMET properties. Notably, when these 1,061 molecules were merged with the 98 synthetic hIKK-2 inhibitors used in this study and the resulting set was classified into ten clusters according to chemical similarity, there were three clusters that contained only natural products. Five molecules from these three clusters (for which no anti-inflammatory activity has been previously described) were then selected for in vitro activity testing, in which three out of the five molecules were shown to inhibit hIKK-2.

CONCLUSIONS/SIGNIFICANCE

We demonstrated that our virtual-screening protocol was successful in identifying lead compounds for developing new inhibitors for hIKK-2, a target of great interest in medicinal chemistry. Additionally, all the tools developed during the current study (i.e., the homology model for the hIKK-2 kinase domain and the pharmacophore) will be made available to interested readers upon request.

Discovery of a novel IKK-β inhibitor by ligand-based virtual screening techniques

Various inflammatory stimuli that activate the nuclear factor kappa B (NF-κB) signaling pathway converge on a serine/threonine kinase that displays a key role in the activation of NF-κB: the I kappa B kinase β (IKK-β). Therefore, IKK-β is considered an interesting target for combating inflammation and cancer. In our study, we developed a ligand-based pharmacophore model for IKK-β inhibitors. This model was employed to virtually screen commercial databases, giving a focused hit list of candidates. Subsequently, we scored by molecular shape to rank and further prioritized virtual hits by three-dimensional shape-based alignment. One out of ten acquired and biologically tested compounds showed inhibitory activity in the low micromolar range on IKK-β enzymatic activity in vitro and on NF-κB transactivation in intact cells. Compound 8 (2-(1-adamantyl)ethyl 4-[(2,5-dihydroxyphenyl)methylamino]benzoate) represents a novel chemical class of IKK-β inhibitors and shows that the presented model is a valid approach for identification and development of new IKK-β ligands.