Virtual Screening Docking Research Articles

3-aryl-indolinones derivatives as antiplasmodial agents: synthesis, biological activity and computational analysis

Malaria is an infectious illness, affecting vulnerable populations in Third World countries. Inspired by natural products, indole alkaloids have been used as a nucleus to design new antimalarial drugs. So, eighteen oxindole derivatives, aza analogues were obtained with moderate to excellent yields. Also, the saturated derivatives of oxindole and aza derivatives via H2/Pd/C reduction were obtained in good yields, leading to racemic mixtures of each compound. Next, the inhibitory activity against P. falciparum of 18 compounds were tested, founding six compounds with IC50 < 20 µM. The most active of these compounds was 8c; however, their unsaturated derivative 7c was inactive. Then, a structure-activity relationship analysis was done, founding that focused LUMO lobe on the specific molecular zone is related to inhibitory activity against P. falciparum. Finally, we found a potential inhibition of lactate dehydrogenase by oxindole derivatives, using molecular docking virtual screening.

Molecular Modeling and Computer-Designing for New Compounds Starting From Thiazolidinedione Molecule as Anti-Hyperglycemics

In the quest for novel PPAR-γ agonists as putative drugs for the treatment of type 2 diabetes, a new test set molecules were proposed as bioisosteric analogues to the anti-diabetic thiazolidine-2, 5-diones (TZDs). Virtual screening fitting study of these new molecules with the generated discovery studio (DS) common feature PPAR-γ agonist's hypothesis has predicted that most of these are active as PPAR-γ agonist and hence they are as antidiabetic-type 2 agents. Furthermore, molecular docking virtual screening for these active compounds, with the binding site of the PPAR-γ enzyme, revealed that the 2-pyrazolin-5-one and pyrazolidine-3,5-dione derivatives have higher or similar docking scores like that of the rosiglitazone. Also, the same docking study revealed that these compounds have the same binding site. This predicted that the designed proposed new molecules are considered PPAR-γ agonists active, and hence they are recommended to be synthesized as potential anti-diabetic type-2 agents.&#x0D;

Ensemble-based high-throughput virtual screening of natural ligands using the Super Natural-II database against cell-wall protein dTDP-4-dehydrorhamnose reductase (RmlD) in Mycobacterium tuberculosis

The disease Tuberculosis (TB) is caused by a bacterium called Mycobacterium tuberculosis (Mtb). The bacterial cell-wall consists of peptidoglycan layer maintains the cellular integrity and cell viability. The main problem resides in the cell cycle of Mycobacterium tuberculosis in its quiescent form which is not targeted by any drugs hence there is an immediate need for new antibiotics to target the cell wall. The current study deals with the dTDP-4-dehydrorahmnose reductase (RmlD) which is the final enzyme in the series of cell-wall proteins of Mtb. The RmlD is a part of Carbohydrate biosynthesis has been considered as a good drug target for the novel class of antibiotics. Our study begins with the protein structure prediction, Homology studies were conducted using the Phyre2 web server. The structure is then refined and subjected to molecular dynamics simulations for 50 ns using GROMACS. The clustering analysis has been carried out and generated 41 clusters with 2 Å as the cut-off. Blind docking virtual screening was performed against RmlD protein using the Super Natural-II database with AutoDock4.0. its results helped to screen top ligands based on best binding energies. In both dockings, there are some common residues in which the ligands are interacting and forming the Hydrogen bonds such as Asp-105, Val-158, Thr-160, Gly-161, Arg-224, Arg-256. The ligand-567 giving the best results by being in the top-3 of all the clusters in both blind docking as well as the active-site docking. Hence ligand-567 can be a potential inhibitor of RmlD which can further inhibit the cell-wall synthesis of Mycobacterium tuberculosis. Communicated by Ramaswamy H. Sarma

Quantitative structure-activity relationship, molecular docking, drug-likeness, and pharmacokinetic studies of some non-small cell lung cancer therapeutic agents

BackgroundLung cancer has been reported to be among the leading cancer cases in the world. It was also reported to have caused a lot of death every year and accounted for about one-third of the whole cancer deaths in the globe. The main subset of lung cancers that accounts for about 85% of the problems of lung cancer raised above was non-small cell lung cancer (NSCLC). The most common cause of NSCLCs that mostly affects women and cigarette smokers was recognized to be overexpression of epidermal growth factor receptor tyrosine kinase (EGFR TK).ResultsFive models on thirty five (35) NSCLC therapeutic agents were developed via quantitative structure-activity relationship (QSAR) technique. The best model among them was selected and reported due to its fitness statistically with the following validation parameters: R2 of 0.8764, R2adj of 0.8370, Qcv2 of 0.7655, R2test of 0.7024, and LOF of 0.3312. Molecular docking was used to elucidate the mode of binding interactions between the thirty five (35) NSCLC therapeutic agents and the binding pose of EGFR tyrosine kinase receptor (3IKA) in this research. Compound 29 was recognized to have the most excellent binding affinity of − 8.8 kcal/mol among others. The drug-likeness and pharmacokinetic properties of all the NSCLC therapeutic agents were predicted using SWISSADME, and none among the molecules under investigation violated more than the permissible limit of the conditions stated by Lipinski’s RO5 filters. Five hit compounds were identified using molecular docking virtual screening. The five (5) hit compounds were further screened and identified compound 16 and 27 as excellent among them using their pharmacokinetic profiles and drug-likeness properties.ConclusionQSAR technique was used to build five models on thirty five (35) NSCLC therapeutic agents. The best model among them was reported because it is statistically significant with good validation parameters. The molecular docking result has identified five (5) hit compounds. The most common amino acid residues to all hit compounds under investigation were Glu762, Leu718, Lys745, and Val726 which might be responsible for the higher inhibitory activities/binding affinities of the compounds under investigation. Furthermore, these five (5) hit compounds were further subjected to drug-likeness and pharmacokinetic properties prediction to determine which among them have the best pharmacokinetic profile. Compounds 16 and 27 among the hit compounds were observed to have high chance of passive absorption by the gastrointestinal tract while the other three have low tendency of passive absorption. More so, only compounds 16 and 27 have higher bioavailability scores, and none of the two have more than one violation of the RO5 criteria. The cause of efficiency of compounds 16 and 27 might be as a result of good pharmacokinetic profiles and drug-likeness properties possessed by the molecules when compared to other hit compounds.

Computational evaluation of potent 2-(1H-imidazol-2-yl) pyridine derivatives as potential V600E-BRAF inhibitors

BackgroundV600E-BRAF is a major protein target involved in various types of human cancers. However, the acquired resistance of the V600E-BRAF kinase to the vemurafenib and the side effects of other identified drugs initiate the search for efficient inhibitors. In the current paper, virtual docking screening combined with drug likeness and ADMET properties predictions were jointly applied to evaluate potent 2-(1H-imidazol-2-yl) pyridines as V600E-BRAF kinase inhibitors.ResultsMost of the studied compounds showed better docking scores and favorable interactions with theiV600E-BRAF target. Among the screened compounds, the two most potent (14 and 30) with good rerank scores (−124.079 and − 122.290) emerged as the most effective, and potent V600E-BRAF kinase inhibitors which performed better than vemurafenib (−116.174), an approved V600E-BRAF kinase inhibitor. Thus, the docking studies exhibited that these compounds have shown competing inhibition of V600E-BRAF kinase with vemurafenib at the active site and revealed better pharmacological properties based on Lipinski’s and Veber’s drug-likeness rules for oral bioavailability and ADMET properties.ConclusionThe docking result, drug-likeness rules, and ADMET parameters identified compounds (14 and 30) as the best hits against V600E-BRAF kinase with better pharmacological properties. This suggests that these compounds may be developed as potent V600E-BRAF inhibitors.

Structure-based design of some quinazoline derivatives as epidermal growth factor receptor inhibitors

BackgroundThe discovery of epidermal growth factor receptor (EGFR) inhibitors for the treatment of lung cancer, most especially non-small cell lung cancer (NSCLC), was one of the major challenges encountered by the medicinal chemist in the world. The treatment of EGFR tyrosine kinase to manage NSCLCs becomes an urgent therapeutic necessity. NSCLC was the foremost cause of cancer mortality worldwide. Therefore, there is a need to develop more EGFR inhibitors due to the development of drug resistance by the mutation. This research is aimed at designing new EGFR inhibitors using a structure-based design approach. Structure-based drug design comprises several steps such as protein structure retrieval and preparation, ligand library preparation, docking, and structural modification on the best hit compound to design new ones.ResultMolecular docking virtual screening on fifty sets of quinazoline derivatives/epidermal growth factor receptor inhibitors against their target protein (EGFR tyrosine kinase receptor PDB entry: 3IKA) and pharmacokinetic profile predictions were performed to identify hit compounds with promising affinities toward their target and good pharmacokinetic profiles. The hit compounds identified were compound 6 with a binding affinity of − 9.3 kcal/mol, compounds 5 and 8, each with a binding affinity of − 9.1 kcal/mol, respectively. The three hit compounds bound to EGFR tyrosine kinase receptor via four different types of interactions which include conventional hydrogen bond, carbon-hydrogen bond, electrostatic, and hydrophobic interactions, respectively. The best hit (compound 6) among the 3 hit compounds was retained as a template and used to design sixteen new EGFR inhibitors. The sixteen newly designed compounds were also docked into the active site of EGFR tyrosine kinase receptor to study their mode of interactions with the receptor. The binding affinities of these newly designed compounds range from − 9.5 kcal/mol to − 10.2 kcal/mol. The pharmacokinetic profile predictions of these newly designed compounds were further examined and found to be orally bioavailable with good absorption, low toxicity level, and permeable properties.ConclusionThe sixteen newly designed EGFR inhibitors were found to have better binding affinities than the template used in the designing process and afatinib the positive control (an FDA approved EGFR inhibitor). None of these designed compounds was found to violate more than the permissible limit set by RO5. More so, the newly designed compounds were found to have good synthetic accessibility which indicates that these newly designed compounds can be easily synthesized in the laboratory.

Structural Basis of Inhibition of the Pioneer Transcription Factor NF-Y by Suramin.

NF-Y is a transcription factor (TF) comprising three subunits (NF-YA, NF-YB, NF-YC) that binds with high specificity to the CCAAT sequence, a widespread regulatory element in gene promoters of prosurvival, cell-cycle-promoting, and metabolic genes. Tumor cells undergo “metabolic rewiring” through overexpression of genes involved in such pathways, many of which are under NF-Y control. In addition, NF-YA appears to be overexpressed in many tumor types. Thus, limiting NF-Y activity may represent a desirable anti-cancer strategy, which is an ongoing field of research. With virtual-screening docking simulations on a library of pharmacologically active compounds, we identified suramin as a potential NF-Y inhibitor. We focused on suramin given its high water-solubility that is an important factor for in vitro testing, since NF-Y is sensitive to DMSO. By electrophoretic mobility shift assays (EMSA), isothermal titration calorimetry (ITC), STD NMR, X-ray crystallography, and molecular dynamics (MD) simulations, we showed that suramin binds to the histone fold domains (HFDs) of NF-Y, preventing DNA-binding. Our analyses, provide atomic-level detail on the interaction between suramin and NF-Y and reveal a region of the protein, nearby the suramin-binding site and poorly conserved in other HFD-containing TFs, that may represent a promising starting point for rational design of more specific and potent inhibitors with potential therapeutic applications.

In silico evaluation of some 4-(quinolin-2-yl)pyrimidin-2-amine derivatives as potent V600E-BRAF inhibitors with pharmacokinetics ADMET and drug-likeness predictions

BackgroundThe resistance of V600E-BRAF to the vemurafenib and the side effects of the identified inhibitors trigger the research for a novel and more potent anti-melanoma agents. In this study, virtual docking screening along with pharmacokinetics ADMET and drug-likeness predictions were combined to evaluate some 4-(quinolin-2-yl)pyrimidin-2-amine derivatives as potent V600E-BRAF inhibitors.ResultsSome of the selected compounds exhibited better binding scores and favorable interaction with the V600E-BRAF enzyme. Out of the screened compounds, two most potent (5 and 9) having good Rerank scores (− 128.011 and − 126.258) emerged as effective and potent V600E-BRAF inhibitors that outperformed the FDA-approved V600E-BRAF inhibitor (vemurafenib, − 118.607). Thus, the molecular docking studies revealed that the studied compounds showed competing for inhibition of V600E-BRAF with vemurafenib at the binding site and possessed better pharmacological parameters based on the drug-likeness rules filters for the oral bioavailability, and ADMET risk parameters.ConclusionThe docking analysis, drug-likeness rules filters, and ADMET study identified compounds (5 and 9) as the best hits against V600E-BRAF kinase with enhanced pharmacological properties. This recommends that these compounds may be developed as potent anti-melanoma agents.

Potential Drugs Targeting Early Innate Immune Evasion of SARS-Coronavirus 2 via 2'-O-Methylation of Viral RNA.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing the COVID-19 respiratory disease pandemic utilizes unique 2′-O-methyltransferase (2′-O-MTase) capping machinery to camouflage its RNA from innate immune recognition. The nsp16 catalytic subunit of the 2′-O-MTase is unusual in its requirement for a stimulatory subunit (nsp10) to catalyze the ribose 2′-O-methylation of the viral RNA cap. Here we provide a computational basis for drug repositioning or de novo drug development based on three differential traits of the intermolecular interactions of the SARS-CoV-2-specific nsp16/nsp10 heterodimer, namely: (1) the S-adenosyl-l-methionine-binding pocket of nsp16, (2) the unique “activating surface” between nsp16 and nsp10, and (3) the RNA-binding groove of nsp16. We employed ≈9000 U.S. Food and Drug Administration (FDA)-approved investigational and experimental drugs from the DrugBank repository for docking virtual screening. After molecular dynamics calculations of the stability of the binding modes of high-scoring nsp16/nsp10–drug complexes, we considered their pharmacological overlapping with functional modules of the virus–host interactome that is relevant to the viral lifecycle, and to the clinical features of COVID-19. Some of the predicted drugs (e.g., tegobuvir, sonidegib, siramesine, antrafenine, bemcentinib, itacitinib, or phthalocyanine) might be suitable for repurposing to pharmacologically reactivate innate immune restriction and antagonism of SARS-CoV-2 RNAs lacking 2′-O-methylation.

Assessing the Performance of Mixed Strategies To Combine Lipophilic Molecular Similarity and Docking in Virtual Screening.

The accuracy of structure-based (SB) virtual screening (VS) is heavily affected by the scoring function used to rank a library of screened compounds. Even in cases where the docked pose agrees with the experimental binding mode of the ligand, the limitations of current scoring functions may lead to sensible inaccuracies in the ability to discriminate between actives and inactives. In this context, the combination of SB and ligand-based (LB) molecular similarity may be a promising strategy to increase the hit rates in VS. This study explores different strategies that aim to exploit the synergy between LB and SB methods in order to mitigate the limitations of these techniques, and to enhance the performance of VS studies by means of a balanced combination between docking scores and three-dimensional (3D) similarity. Particularly, attention is focused to the use of measurements of molecular similarity with PharmScreen, which exploits the 3D distribution of atomic lipophilicity determined from quantum mechanical-based continuum solvation calculations performed with the MST model, in conjunction with three docking programs: Glide, rDock, and GOLD. Different strategies have been explored to combine the information provided by docking and similarity measurements for re-ranking the screened ligands. For a benchmarking of 44 datasets, including 41 targets, the hybrid methods increase the identification of active compounds, according to the early (ROCe%) and total (AUC) enrichment metrics of VS, compared to pure LB and SB methods. Finally, the hybrid approaches are also more effective in enhancing the chemical diversity of active compounds. The datasets employed in this work are available in https://github.com/Pharmacelera/Molecular-Similarity-and-Docking.

Fast Identification of Possible Drug Treatment of Coronavirus Disease-19 (COVID-19) through Computational Drug Repurposing Study.

The recent outbreak of novel coronavirus disease-19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D structures of key viral proteins are resolved. The virus causing COVID-19 is SARS-CoV-2. Taking advantage of a recently released crystal structure of SARS-CoV-2 main protease in complex with a covalently bonded inhibitor, N3 (Liu et al., 10.2210/pdb6LU7/pdb), I conducted virtual docking screening of approved drugs and drug candidates in clinical trials. For the top docking hits, I then performed molecular dynamics simulations followed by binding free energy calculations using an end point method called MM-PBSA-WSAS (molecular mechanics/Poisson–Boltzmann surface area/weighted solvent-accessible surface area; Wang, Chem. Rev.2019, 119, 947831244000; Wang, Curr. Comput.-Aided Drug Des.2006, 2, 287; Wang; HouJ. Chem. Inf. Model., 2012, 52, 119922497310). Several promising known drugs stand out as potential inhibitors of SARS-CoV-2 main protease, including carfilzomib, eravacycline, valrubicin, lopinavir, and elbasvir. Carfilzomib, an approved anticancer drug acting as a proteasome inhibitor, has the best MM-PBSA-WSAS binding free energy, −13.8 kcal/mol. The second-best repurposing drug candidate, eravacycline, is synthetic halogenated tetracycline class antibiotic. Streptomycin, another antibiotic and a charged molecule, also demonstrates some inhibitory effect, even though the predicted binding free energy of the charged form (−3.8 kcal/mol) is not nearly as low as that of the neutral form (−7.9 kcal/mol). One bioactive, PubChem 23727975, has a binding free energy of −12.9 kcal/mol. Detailed receptor–ligand interactions were analyzed and hot spots for the receptor–ligand binding were identified. I found that one hot spot residue, His41, is a conserved residue across many viruses including SARS-CoV, SARS-CoV-2, MERS-CoV, and hepatitis C virus (HCV). The findings of this study can facilitate rational drug design targeting the SARS-CoV-2 main protease.

Anti-tubercular Modelling via QSAR Approach, In Silico Design and Virtual Docking Screening of Designed Hypothetical Inhibitors Against DNA gyrase Protein.

Mycobacterium tuberculosis has instigated a serious challenge toward the effective treatment of tuberculosis. The reoccurrence of the resistant strains of the disease to accessible drugs/medications has mandate for the development of more effective anti-tubercular agents with efficient activities. Time expended and costs in discovering and synthesizing new hypothetical drugs with improved biological activity have been a major challenge toward the treatment of multidrug resistance strain M. tuberculosis (TB). Meanwhile, to solve the stated problem, a new approach i.e. QSAR which establish connection between novel drugs with a better biological against M. tuberculosis is adopted. The anti-tubercular model established in this study to forecast the biological activities of some anti-tubercular compounds selected and to design new hypothetical drugs is subjective to the molecular descriptors; MATS7s, SM1_DzZ, SpMin4_Bhv, TDB3v and RDF70v. Ligand-receptor interactions between quinoline derivatives and the receptor (DNA gyrase) was carried out using molecular docking technique by employing the PyRx virtual screening software and discovery studio visualizer software. Furthermore, docking study indicates that compound 20 of the derivatives with promising biological activity has the utmost binding energy of -17.79 kcal/mol. Meanwhile, the interaction of the standard drug; isoniazid with the target enzyme was observed with the binding energy -14.6 kcal/mol which was significantly lesser than the binding energy of the ligand (compound 20). Therefore, compound 20 served as a template structure to design compounds with more efficient activities. Among the compounds designed; compounds 20p was observed with better anti-tubercular activities with more prominent binding affinities of - 24.3kcal/mol. The presumption of this research aid the medicinal chemists and pharmacist to design and synthesize a novel drug candidate against tuberculosis. Moreover, in-vitro and in-vivo test could be carried out to validate the computational results.

Study on Structure Activity Relationship of Natural Flavonoids against Thrombin by Molecular Docking Virtual Screening Combined with Activity Evaluation In Vitro.

Thrombin, a key enzyme of the serine protease superfamily, plays an integral role in the blood coagulation cascade and thrombotic diseases. In view of this, it is worthwhile to establish a method to screen thrombin inhibitors (such as natural flavonoid-type inhibitors) as well as investigate their structure activity relationships. Virtual screening using molecular docking technique was used to screen 103 flavonoids. Out of this number, 42 target compounds were selected, and their inhibitory effects on thrombin assayed by chromogenic substrate method. The results indicated that the carbon-carbon double bond group at the C2, C3 sites and the carbonyl group at the C4 sites of flavones were essential for thrombin inhibition, whereas the methoxy and O-glycosyl groups reduced thrombin inhibition. Noteworthy, introduction of OH groups at different positions on flavonoids either decreased or increased anti-thrombin potential. Myricetin exhibited the highest inhibitory potential against thrombin with an IC50 value of 56 μM. Purposively, the established molecular docking virtual screening method is not limited to exploring flavonoid structure activity relationships to anti-thrombin activity but also usefully discovering other natural active constituents.

Evaluation of consensus scoring methods for AutoDock Vina, smina and idock

We investigated the application of consensus scoring using the freely available and open source structure-based virtual screening docking programs AutoDock Vina, smina and idock. These individual programs and several simple consensus scoring methods were tested for their ability to identify hits against 20 DUD-E benchmark targets using the AUC and EF1 metrics. We found that all of the consensus scoring methods, however normalized, fared worse, on average, than simply using the output from a single program, smina. Additionally, the effect of a significant increase in the run time of all three programs was tested to find if a longer run time yielded improved results. Our results indicated that a longer run time than the default had little impact on the performance of these three programs or on consensus scoring methods based on their output. Thus, we have found that using the smina program alone at default settings is the best approach for researchers that do not have access to a suite of commercial docking software packages.

Virtual docking screening and QSAR studies to explore AKT and mTOR inhibitors acting on PI3K in cancers.

The phosphoinositide 3-kinase (PI3K) pathway is an important regulator of cell proliferation and metabolism. PI3K activation initiates a signal transduction cascade, of which the major effectors are the kinases AKT and mTOR. Aberrant activation of the PI3K/AKT/mTOR pathway is frequently observed in many human malignancies and the combination of compounds simultaneously targeting different related molecules in the PI3K/AKT/mTOR pathway leads to synergistic activity. To explore the competing common ATP inhibitors PI3K/AKT and PI3K/mTOR we developed a model PI3K-SAR 2D which made it possible to predict the bioactivity of inhibitors of AKT and mTOR towards PI3K; the interaction of the best inhibitors was evaluated by docking analysis and compared to that of dactolisib and pictilisib. A PI3K-SAR model with a correlation coefficient (R2) of 0.81706 and an RMSE of 0.16029 was obtained, which was validated and evaluated by a cross-validation method, LOO. The most predicted AKT and mTOR inhibitors present respectively pIC50 activities between 9.26–9.93 and 9.59–9.87.After docking and several comparisons, inhibitors with better predictions showed better affinity and interaction with PI3K compared to pictilisib and dactolisib, so we found that 4 inhibitors of AKT and 14 mTOR inhibitors met the criteria of Lipinski and Veber and could be future drugs.

Virtual Docking Screening and QSAR Studies to Explore PI3K and mTOR Inhibitors Acting on AKT in Cancers

The PI3K / AKT / mTOR pathway is an important regulator of a wide range of cellular processes including survival, proliferation, growth, metabolism, angiogenesis and metastasis. PI3K induces translocation of Ser / Thr Akt kinase, Akt is activated by PDK1 and mTOR2-dependent phosphorylations. Aberrant activation of the PI3K / AKT / mTOR pathway is frequently observed in many human malignancies and the combination of compounds simultaneously targeting different related molecules in the PI3K / AKT / mTOR pathway leads to synergistic activity. To explore the common AKT / mTOR and AKT / PI3K competitor ATP inhibitors we performed a 2D AKT-SAR model to predict the bioactivity of PI3K and mTOR inhibitors on AKT, the interaction of the best inhibitors was evaluated by docking analysis and compared to that of GSK690693 and Ipatasertib. An AKT-SAR model with a correlation coefficient (R2) of 0.85212 and an RMSE of 0.09266 was obtained, which was validated and evaluated by a cross-validation method LOO, the most predicted inhibitors of PI3K and mTOR respectively PIC50 activities between [9.30 - 8.54], and [9.79 - 8.91]. After docking and several comparisons, inhibitors with better predictions showed better affinity and interaction with AKT compared to GSK690693 and Ipatasertib. We therefore found that 8 PI3K inhibitors and 11 mTOR inhibitors met the Lipinski and Veber criteria and could be future drugs.

In silico analysis of a major allergen from Rattus norvegicus, Rat n 1, and cross-reactivity with domestic pets.

Background: Lipocalins play a role in the cellular trafficking of pheromones and are involved in allergic responses to domestic pets. However, the cross-reactivity among allergens of this group has been poorly explored, and the pheromone linking capacity is not well characterized. The aim of this study was to explore cross-reactive epitopes and pheromone linking capacity among Rat n 1 and homologues in domestic pets through an in silico approach. Methods: ElliPro and BepiPred in silico tools were used to predict B cell linear and cross-reactive epitopes. The pheromone linking capacity was explored by docking virtual screening with 2-ethylhexanol, 2,5-dimethylpyrazine, 2-sec-butyl-4,5-dihydrothiazole, and 2-heptanone ligands. Results: According to the analysis, Rat n 1 shares 52% identity with Equ c 1, Can f 6, Fel d 4, and Mus m 1 allergens. The overlapping structures analysis revealed high structural homology (root mean square deviation < 1). Four lineal and three discontinuous epitopes were predicted on Ra t n 1. A lineal epitope located between amino acids residues 24 and 36 was highly conserved on all allergens explored. A cross-reactive discontinuous epitope (T142, K143, D144, L145, S146, S147, D148, K152, L170, T171, T173, D174) was also found. Docking molecular simulations revealed the region involved in linking ligands, and we identified the properties of the binding of four pheromones and the binding potential of Rat n 1. Critical residues for interactions are reported in this study. Conclusions: We identified some possible allergens from Rattus norvegicus, and those allergens could have cross-reactivity with allergens from some animals. The results need to be confirmed with in vitro studies and could be utilized to contribute to immunotherapy and reduce allergic diseases related to lipocalins.

In silico analysis of a major allergen from Rattus norvegicus, Rat n 1, and cross-reactivity with domestic pets

Background: Lipocalins play a role in the cellular trafficking of pheromones and are involved in allergic responses to domestic pets. However, the cross-reactivity among allergens of this group has been poorly explored, and the pheromone linking capacity is not well characterized. The aim of this study was to explore cross-reactive epitopes and pheromone linking capacity among Rat n 1 and homologues in domestic pets through an in silico approach. Methods: ElliPro and BepiPred in silico tools were used to predict B cell linear and cross-reactive epitopes. The pheromone linking capacity was explored by docking virtual screening with 2-ethylhexanol, 2,5-dimethylpyrazine, 2-sec-butyl-4,5-dihydrothiazole, and 2-heptanone ligands. Results: According to the analysis, Rat n 1 shares 52% identity with Equ c 1, Can f 6, Fel d 4, and Mus m 1 allergens. The overlapping structures analysis revealed high structural homology (root mean square deviation < 1). Four lineal and three discontinuous epitopes were predicted on Ra t n 1. A lineal epitope located between amino acids residues 24 and 36 was highly conserved on all allergens explored. A cross-reactive discontinuous epitope (T142, K143, D144, L145, S146, S147, D148, K152, L170, T171, T173, D174) was also found. Docking molecular simulations revealed the region involved in linking ligands, and we identified the properties of the binding of four pheromones and the binding potential of Rat n 1. Critical residues for interactions are reported in this study. Conclusions: We identified some possible allergens from Rattus norvegicus, and those allergens could have cross-reactivity with allergens from some animals. The results need to be confirmed with in vitro studies and could be utilized to contribute to immunotherapy and reduce allergic diseases related to lipocalins.

In silico analysis of a major allergen from Rattus norvegicus, Rat n 1, and cross-reactivity with domestic pets

Background: Lipocalins play a role in the cellular trafficking of pheromones and are involved in allergic responses to domestic pets. However, the cross-reactivity among allergens of this group has been poorly explored, and the pheromone linking capacity is not well characterized. The aim of this study was to explore cross-reactive epitopes and pheromone linking capacity among Rat n 1 and homologues in domestic pets through an in silico approach. Methods: ElliPro and BepiPred in silico tools were used to predict B cell linear and cross-reactive epitopes. The pheromone linking capacity was explored by docking virtual screening with 2-ethylhexanol, 2,5-dimethylpyrazine, 2-sec-butyl-4,5-dihydrothiazole, and 2-heptanone ligands. Results: According to the analysis, Rat n 1 shares 52% identity with Equ c 1, Can f 6, Fel d 4, and Mus m 1 allergens. The overlapping structures assay revealed high structural homology (root mean square deviation < 1). Four lineal and three discontinuous epitopes were predicted on Ra t n 1. A lineal epitope located between amino acids residues 24 and 36 was highly conserved on all allergens explored. A cross-reactive discontinuous epitope (T142, K143, D144, L145, S146, S147, D148, K152, L170, T171, T173, D174) was also found. Docking molecular simulations revealed the active site, and we identified the properties of the binding of four pheromones and the binding potential of Rat n 1. Critical residues for interactions are reported in this study. Conclusions: We identified some possible allergens from Rattus norvegicus, and those allergens could have cross-reactivity with allergens from some animals. The results need to be confirmed with in vitro studies and could be utilized to contribute to immunotherapy and reduce allergic diseases related to lipocalins.

Identification of a novel potassium channel (GiK) as a potential drug target in Giardia lamblia: Computational descriptions of binding sites.

BackgroundThe protozoan Giardia lamblia is the causal agent of giardiasis, one of the main diarrheal infections worldwide. Drug resistance to common antigiardial agents and incidence of treatment failures have increased in recent years. Therefore, the search for new molecular targets for drugs against Giardia infection is essential. In protozoa, ionic channels have roles in their life cycle, growth, and stress response. Thus, they are promising targets for drug design. The strategy of ligand-protein docking has demonstrated a great potential in the discovery of new targets and structure-based drug design studies.MethodsIn this work, we identify and characterize a new potassium channel, GiK, in the genome of Giardia lamblia. Characterization was performed in silico. Because its crystallographic structure remains unresolved, homology modeling was used to construct the three-dimensional model for the pore domain of GiK. The docking virtual screening approach was employed to determine whether GiK is a good target for potassium channel blockers.ResultsThe GiK sequence showed 24–50% identity and 50–90% positivity with 21 different types of potassium channels. The quality assessment and validation parameters indicated the reliability of the modeled structure of GiK. We identified 110 potassium channel blockers exhibiting high affinity toward GiK. A total of 39 of these drugs bind in three specific regions.DiscussionThe GiK pore signature sequence is related to the small conductance calcium-activated potassium channels (SKCa). The predicted binding of 110 potassium blockers to GiK makes this protein an attractive target for biological testing to evaluate its role in the life cycle of Giardia lamblia and potential candidate for the design of novel antigiardial drugs.