Investigating the potassium interactions with the palytoxin induced channels in Na+/K+ pump

K(+) has been appointed as the main physiological inhibitor of the palytoxin (PTX) effect on the Na(+)/K(+) pump. This toxin acts opening monovalent cationic channels through the Na(+)/K(+) pump. We investigate, by means of computational modeling, the kinetic mechanisms related with K(+) interacting with the complex PTX-Na(+)/K(+) pump. First, a reaction model, with structure similar to Albers-Post model, describing the functional cycle of the pump, was proposed for describing K(+) interference on the complex PTX-Na(+)/K(+) pump in the presence of intracellular ATP. A mathematic model was derived from the reaction model and it was possible to solve numerically the associated differential equations and to simulate experimental maneuvers about the PTX induced currents in the presence of K(+) in the intra- and extracellular space as well as ATP in the intracellular. After the model adjusting to the experimental data, a Monte Carlo method for sensitivity analysis was used to analyze how each reaction parameter acts during each experimental maneuver involving PTX. For ATP and K(+) concentrations conditions, the simulations suggest that the enzyme substate with ATP bound to its high-affinity sites is the main substate for the PTX binding. The activation rate of the induced current is limited by the K(+) deocclusion from the PTX-Na(+)/K(+) pump complex. The K(+) occlusion in the PTX induced channels in the enzymes with ATP bound to its low-affinity sites is the main mechanism responsible for the reduction of the enzyme affinity to PTX.     

Identification of Novel TRPC5 Inhibitors by Pharmacophore-Based and Structure-Based Approaches

Canonical transient receptor potential-5 (TRPC5), which belongs to the subfamily of transient receptor potential (TRP) channels, is a non-selective cation channel mainly expressed in the central nervous system and shows more restricted expression in the periphery. TRPC5 plays a crucial role in human physiology and pathology, for instance, anxiety, depression, epilepsy, pain, memory and chronic kidney disease (CKD). However, due to lack of the effective and selective inhibitors, its physiological and pathological mechanism remains so far unknown. It is therefore pivotal to identify potential TRPC5 inhibitors. We have applied ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) methods. The pharmacophore models of TRPC5 antagonists generated by using the HypoGen and HipHop algorithms were used as a query model for the screening of potential inhibitors against the Specs database. The resultant hits from LBVS were further screened by SBVS. SBVS was carried out based on the homology model generation of human TRPC5, binding site identification, molecular dynamics optimization and molecular docking studies. In our systematic screening approaches, we have identified 7 hits compounds with comparable dock score after Lipinski and Veber rules, ADMET, PAINS analysis, cluster analysis, and similarity analysis. In conclusion, the current research provides novel backbones for the new-generation of TRPC5 inhibitors.     

Kv1.2 potassium channel inhibitors from Chukrasia tabularis

Eighteen new limonoids, chubularisins A-R (1-18), along with eleven known analogues, were isolated from the stem bark of Chukrasia tabularis. The structures of 1-18 were elucidated on the basis of spectroscopic data and chemical evidence. Compound 1 represented the first example of 8,9,12-orthoester of phragmalin limonoids. Interestingly, compounds 4, 8, and 22 exhibited potent and selective inhibition against the delayed rectifier (I(K)) K(+) current with IC(50) values of 0.61, 2.03, and 2.15 μM, respectively.     

Design and synthesis of skeletal analogues of gambierol: attenuation of amyloid-β and tau pathology with voltage-gated potassium channel and N-methyl-D-aspartate receptor implications

Gambierol is a potent neurotoxin that belongs to the family of marine polycyclic ether natural products and primarily targets voltage-gated potassium channels (K(v) channels) in excitable membranes. Previous work in the chemistry of marine polycyclic ethers has suggested the critical importance of the full length of polycyclic ether skeleton for potent biological activity. Although we have previously investigated structure-activity relationships (SARs) of the peripheral functionalities of gambierol, it remained unclear whether the whole polycyclic ether skeleton is needed for its cellular activity. In this work, we designed and synthesized two truncated skeletal analogues of gambierol comprising the EFGH- and BCDEFGH-rings of the parent compound, both of which surprisingly showed similar potency to gambierol on voltage-gated potassium channels (K(v)) inhibition. Moreover, we examined the effect of these compounds in an in vitro model of Alzheimer's disease (AD) obtained from triple transgenic (3xTg-AD) mice, which expresses amyloid beta (Aβ) accumulation and tau hyperphosphorylation. In vitro preincubation of the cells with the compounds resulted in significant inhibition of K(+) currents, a reduction in the extra- and intracellular levels of Aβ, and a decrease in the levels of hyperphosphorylated tau. In addition, pretreatment with these compounds reduced the steady-state level of the N-methyl-D-aspartate (NMDA) receptor subunit 2A without affecting the 2B subunit. The involvement of glutamate receptors was further suggested by the blockage of the effect of gambierol on tau hyperphosphorylation by glutamate receptor antagonists. The present study constitutes the first discovery of skeletally simplified, designed polycyclic ethers with potent cellular activity and demonstrates the utility of gambierol and its synthetic analogues as chemical probes for understanding the function of K(v) channels as well as the molecular mechanism of Aβ metabolism modulated by NMDA receptors.     

翼梗五味子的研究 V: 五脂素A1, A2, 表五脂A1和epischisandrone的结构

从四川宜宾产翼梗五味子的果实中分得七个四氢萘木脂素, 其中三个鉴定为: 恩施辛enshicine, 表恩施辛epienshicine和schisandrone, 其余四个均属新化合物, 命名为五脂素wnlignan A1, 五脂素A2, 表五脂素epiwnlignan A1和epischisandrone. 它们的结构(包括绝对构型)由光谱分析和化学转化为(+)-dimethylguaiacine和(-)-dimethylisoguaiacine而阐明. 四个新化合物皆有不同程度的体外抗癌活性.     

Novel inhibitor discovery through virtual screening against multiple protein conformations generated via ligand-directed modeling: a maternal embryonic leucine zipper kinase example

Kinase targets have been demonstrated to undergo major conformational reorganization upon ligand binding. Such protein conformational plasticity remains a significant challenge in structure-based virtual screening methodology and may be approximated by screening against an ensemble of diverse protein conformations. Maternal embryonic leucine zipper kinase (MELK), a member of serine-threonine kinase family, has been recently found to be involved in the tumerogenic state of glioblastoma, breast, ovarian, and colon cancers. We therefore modeled several conformers of MELK utilizing the available chemogenomic and crystallographic data of homologous kinases. We carried out docking pose prediction and virtual screening enrichment studies with these conformers. The performances of the ensembles were evaluated by their ability to reproduce known inhibitor bioactive conformations and to efficiently recover known active compounds early in the virtual screen when seeded with decoy sets. A few of the individual MELK conformers performed satisfactorily in reproducing the native protein-ligand pharmacophoric interactions up to 50% of the cases. By selecting an ensemble of a few representative conformational states, most of the known inhibitor binding poses could be rationalized. For example, a four conformer ensemble is able to recover 95% of the studied actives, especially with imperfect scoring function(s). The virtual screening enrichment varied considerably among different MELK conformers. Enrichment appears to improve by selection of a proper protein conformation. For example, several holo and unliganded active conformations are better to accommodate diverse chemotypes than ATP-bound conformer. These results prove that using an ensemble of diverse conformations could give a better performance. Applying this approach, we were able to screen a commercially available library of half a million compounds against three conformers to discover three novel inhibitors of MELK, one from each template. Among the three compounds validated via experimental enzyme inhibition assays, one is relatively potent (15; K(d) = 0.37 μM), one moderately active (12; K(d) = 3.2 μM), and one weak but very selective (9; K(d) = 18 μM). These novel hits may be utilized to assist in the development of small molecule therapeutic agents useful in diseases caused by deregulated MELK, and perhaps more importantly, the approach demonstrates the advantages of choosing an appropriate ensemble of a few conformers in pursuing compound potency, selectivity, and novel chemotypes over using single target conformation for structure-based drug design in general.     

Moving pieces in a proteomic puzzle: mass fingerprinting of toxic fractions from the venom of Tityus serrulatus (Scorpiones, Buthidae).

Scorpion venoms are very complex mixtures of molecules, most of which are peptides that display different kinds of biological activity. These venoms have been studied in the light of their pharmacological targets and their constituents are able to bind specifically to a variety of ionic channels located in prey tissues, resulting in neurotoxic effects. Toxins that modulate Na(+), K(+), Ca(++) and Cl(-) currents have been described in scorpion venoms. Mass spectrometry was employed to analyze toxic fractions from the venom of the Brazilian scorpion Tityus serrulatus in order to shed light on the molecular composition of this venom and to facilitate the search for novel pharmacologically active compounds. T. serrulatus venom was first subjected to gel filtration to separate its constituents according to their molecular size. The resultant fractions II and III, which account for 90 and 10% respectively of the whole venom toxic effect, were further analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS), on-line liquid chromatography/electrospray mass spectrometry (LC/ESMS) and off-line LC/MALDI-TOFMS in order to establish their mass fingerprints. The molecular masses in fraction II were predominantly between 6500 and 7500 Da. This corresponds to long-chain toxins that mainly act on voltage-gated Na(+) channels. Fraction III is more complex and predominantly contained molecules with masses between 2500 and 5000 Da. This corresponds to the short-chain toxin family, most of which act on K(+) channels, and other unknown peptides. Finally, we were able to measure the molecular masses of 380 different compounds present in the two fractions investigated. To our knowledge, this is the largest number of components ever detected in the venom of a single animal species. Some of the toxins described previously from T. serrulatus venom could be detected by virtue of their molecular masses. The interpretation of this large set of data has provided us with useful proteomic information on the venom, and the implications of these findings are discussed.     

Homology model-based virtual screening for GPCR ligands using docking and target-biased scoring

The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS). Our approach was evaluated in retrospective virtual screening experiments for antagonists of the metabotropic glutamate receptor (mGluR) subtype 5. The results of our approach were compared to the results obtained by conventional scoring functions (Dock-Score, PMF-Score, Gold-Score, ChemScore, and FlexX-Score). The IFS lead to significantly higher enrichment rates, relative to the competing scoring functions. Though using a target-biased scoring approach, the results were not biased toward the chemical classes of the reference structures. Our results indicate that the presented approach has the potential to serve as a general setup for successful structure-based GPCR virtual screening.     

Identification of Novel β3-Adrenoceptor Agonists Using Energetic Analysis, Structure Based Pharmacophores and Virtual Screening

β3 Adrenergic receptor (β3-AR), is a potential therapeutic target for the treatment of type II diabetes and obesity. We report the identification of novel compounds as β3-AR agonists by integrating different approaches of energetic analysis, structure based pharmacophore designing and virtual screening. In a step wise filtering protocol, structure based virtual screening of 2,33,450 compounds was done. These molecules were docked into the active site of the receptor utilizing three levels of accuracy; ligands passing the HTVS (high throughput virtual screening) step were subsequently analyzed in Glide SP (Standard Precision) and finally in Glide XP (Extra Precision) to estimate the receptor ligand binding affinities. In the second step a total of 300 pharmacophore hypotheses were generated from a set of known and diverse β3-AR agonists. The best hypothesis showed six features: three hydrogen bond acceptors, one positively charged group, and two aromatic rings. To cross validate, pharmacophore filtering was done on the set of shortlisted compounds from structure based VS (virtual screening). The different screening techniques employed were validated using enrichment factor calculations. The energetic based Pharmacophore performed fairly well at distinguishing active from the inactive compounds and yielded a greater diversity of active molecules whereas the number of actives retrieved in the case of structure based screening was the highest.     

Pores Formed by Bis-macrocyclic Bola-amphiphiles in Vesicle and Planar Bilayer Membranes

A new series of bis-macrocyclic bola-amphiphiles were prepared, and their transport activities in vesicle and planar bilayer membranes were evaluated. From vesicle experiments, the apparent kinetic order in transporter indicates that aggregates are the kinetically active species. Step-conductance changes observed in planar bilayer membranes indicate that the compounds act as channels. Multiple copies of the same channel form in which the conductance is controlled by the macrocyclic portions of the structures. The pores are ion-selective in the sequence Cs(+) > K(+) > Na(+) > Cl(-), controlled by the polar head-groups of the structures. The data are consistent with a model involving the formation of active dimers.     

Validation studies of the site-directed docking program LibDock

The performance of the site-features docking algorithm LibDock has been evaluated across eight GlaxoSmithKline targets as a follow-up to a broad validation study of docking and scoring software (Warren, G. L.; Andrews, W. C.; Capelli, A.; Clarke, B.; Lalonde, J.; Lambert, M. H.; Lindvall, M.; Nevins, N.; Semus, S. F.; Senger, S.; Tedesco, G.; Walls, I. D.; Woolven, J. M.; Peishoff, C. E.; Head, M. S. J. Med. Chem. 2006, 49, 5912-5931). Docking experiments were performed to assess both the accuracy in reproducing the binding mode of the ligand and the retrieval of active compounds in a virtual screening protocol using both the DJD (Diller, D. J.; Merz, K. M., Jr. Proteins 2001, 43, 113-124) and LigScore2 (Krammer, A. K.; Kirchoff, P. D.; Jiang, X.; Venkatachalam, C. M.; Waldman, M. J. Mol. Graphics Modell. 2005, 23, 395-407) scoring functions. This study was conducted using DJD scoring, and poses were rescored using all available scoring functions in the Accelrys LigandFit module, including LigScore2. For six out of eight targets at least 30% of the ligands were docked within a root-mean-square difference (RMSD) of 2.0 A for the crystallographic poses when the LigScore2 scoring function was used. LibDock retrieved at least 20% of active compounds in the top 10% of screened ligands for four of the eight targets in the virtual screening protocol. In both studies the LigScore2 scoring function enhanced the retrieval of crystallographic poses or active compounds in comparison with the results obtained using the DJD scoring function. The results for LibDock accuracy and ligand retrieval in virtual screening are compared to 10 other docking and scoring programs. These studies demonstrate the utility of the LigScore2 scoring function and that LibDock as a feature directed docking method performs as well as docking programs that use genetic/growing and Monte Carlo driven algorithms.     

Transmembrane ion channels constructed of cholic acid derivatives.

A new class of supramolecular transmembrane ion channels was prepared by linking two amphiphilic cholic acid methyl ethers through biscarbamate bonds to afford bis(7,12-dimethyl-24-carboxy-3-cholanyl)-N,N'-xylylene dicarbamate 2 and bis[7,12-dimethyl-24-(N,N,N-trimethylethanaminium-2-carboxylate)-3-cholanyl]-N,N'-xylylene dicarbamate dichloride 3. When incorporated into a planar bilayer membrane, both compounds showed stable (lasting 10 ms to 10 s) single ion channel currents. Only limited numbers of relatively small conductances were characterized for these channels (5-20 pS for 2 and 5-10 pS for 3, 10 and 17 pS for 2, and 9 pS for 3 in particular). Both channels were cation selective, and permeability ratios of potassium cation to chloride anion were 17 and 7.9 for 2 and 3, respectively, reflecting the difference in ionic species of the headgroup. Both channels 2 and 3 showed significant potassium selectivity over sodium by a factor of 3.1 and 3.2, respectively. No Li(+) currents were observed for 2, showing sharp discrimination between Na(+) or K(+).     

Hampering the early aggregation of PrP-E200K protein by charge-based inhibitors: a computational study

A multilayered computational workflow was designed to identify a druggable binding site on the surface of the E200K pathogenic mutant of the human prion protein, and to investigate the effect of the binding of small molecules in the inhibition of the early aggregation of this protein. At this purpose, we developed an efficient computational tool to scan the molecular interaction properties of a whole MD trajectory, thus leading to the characterization of plausible binding regions on the surface of PrP-E200K. These structural data were then employed to drive structure-based virtual screening and fragment-based approaches to the seeking of small molecular binders of the PrP-E200K. Six promising compounds were identified, and their binding stabilities were assessed by MD simulations. Therefore, analyses of the molecular electrostatic potential similarity between the bound complexes and unbound protein evidenced their potential activity as charged-based inhibitors of the PrP-E200K early aggregation.

     

The identification of new ATAD2 bromodomain inhibitors: the application of combined ligand and structure-based virtual screening

Ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches were used to identify new inhibitors for ATAD2 bromodomain. The LBVS approach was used to search 23,129,083 clean compounds to identify compounds similar to an active compound with reported pIC₅₀ equal to 7.2. Based on LBVS results, 19 compounds were selected. To perform SBVS, by applying nine filters on 23,129,083 clean compounds, 1,057,060 compounds were selected. After performing SBVS on these selected compounds with idock software, 16 compounds with the lowest binding energies were selected. More accurate molecular docking analysis was performed on these 35 selected compounds by using iGEMDOCK software and six of them with the lowest binding energies were selected as hit compounds. These compounds were zinc36647229, zinc77969074, zinc13637358, zinc77971540, zinc12991296 and zinc19374204.     

Hot-spots-guided receptor-based pharmacophores (HS-Pharm): a knowledge-based approach to identify ligand-anchoring atoms in protein cavities and prioritize structure-based pharmacophores

The design of biologically active compounds from ligand-free protein structures using a structure-based approach is still a major challenge. In this paper, we present a fast knowledge-based approach (HS-Pharm) that allows the prioritization of cavity atoms that should be targeted for ligand binding, by training machine learning algorithms with atom-based fingerprints of known ligand-binding pockets. The knowledge of hot spots for ligand binding is here used for focusing structure-based pharmacophore models. Three targets of pharmacological interest (neuraminidase, beta2 adrenergic receptor, and cyclooxygenase-2) were used to test the evaluated methodology, and the derived structure-based pharmacophores were used in retrospective virtual screening studies. The current study shows that structure-based pharmacophore screening is a powerful technique for the fast identification of potential hits in a chemical library, and that it is a valid alternative to virtual screening by molecular docking.     

SHAFTS: a hybrid approach for 3D molecular similarity calculation. 1. Method and assessment of virtual screening

We developed a novel approach called SHAFTS (SHApe-FeaTure Similarity) for 3D molecular similarity calculation and ligand-based virtual screening. SHAFTS adopts a hybrid similarity metric combined with molecular shape and colored (labeled) chemistry groups annotated by pharmacophore features for 3D similarity calculation and ranking, which is designed to integrate the strength of pharmacophore matching and volumetric overlay approaches. A feature triplet hashing method is used for fast molecular alignment poses enumeration, and the optimal superposition between the target and the query molecules can be prioritized by calculating corresponding "hybrid similarities". SHAFTS is suitable for large-scale virtual screening with single or multiple bioactive compounds as the query "templates" regardless of whether corresponding experimentally determined conformations are available. Two public test sets (DUD and Jain's sets) including active and decoy molecules from a panel of useful drug targets were adopted to evaluate the virtual screening performance. SHAFTS outperformed several other widely used virtual screening methods in terms of enrichment of known active compounds as well as novel chemotypes, thereby indicating its robustness in hit compounds identification and potential of scaffold hopping in virtual screening.     

Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer

NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in the genetic makeup of NEK7 leads to the development of cancer malignancies and fatal inflammatory disease, i.e., breast cancer, non-small cell lung cancer, gout, rheumatoid arthritis, and liver cirrhosis. Therefore, NEK7 is a promising target for drug development against various cancer malignancies. The combination of drug repurposing and structure-based virtual screening of large libraries of compounds has dramatically improved the development of anticancer drugs. The current study focused on the virtual screening of 1200 benzene sulphonamide derivatives retrieved from the PubChem database by selecting and docking validation of the crystal structure of NEK7 protein (PDB ID: 2WQN). The compounds library was subjected to virtual screening using Auto Dock Vina. The binding energies of screened compounds were compared to standard Dabrafenib. In particular, compound 762 exhibited excellent binding energy of −42.67 kJ/mol, better than Dabrafenib (−33.89 kJ/mol). Selected drug candidates showed a reactive profile that was comparable to standard Dabrafenib. To characterize the stability of protein–ligand complexes, molecular dynamic simulations were performed, providing insight into the molecular interactions. The NEK7–Dabrafenib complex showed stability throughout the simulated trajectory. In addition, binding affinities, pIC50, and ADMET profiles of drug candidates were predicted using deep learning models. Deep learning models predicted the binding affinity of compound 762 best among all derivatives, which supports the findings of virtual screening. These findings suggest that top hits can serve as potential inhibitors of NEK7. Moreover, it is recommended to explore the inhibitory potential of identified hits compounds through in-vitro and in-vivo approaches.     

Virtual Screening of Human O-GlcNAc Transferase Inhibitors

O-GlcNAc transferase (OGT) is one of essential mammalian enzymes, which catalyze the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine (UDP-GlcNAc) to hydroxyl groups of serines and threonines (Ser/Thr) in proteins. Dysregulations of cellular O-GlcNAc have been implicated in diabetes, neurodegenerative disease, and cancer, which brings great interest in developing potent and speci c small-molecular OGT inhibitors. In this work, we performed virtual screening on OGT catalytic site to identify potential inhibitors. 7134792 drug-like compounds from ZINC (a free database of commercially available compounds for virtual screening) and 4287550 compounds generated by FOG (fragment optimized growth program) were screened and the top 116 compounds ranked by docking score were analyzed. By comparing the screening results, we found FOG program can generate more compounds with better docking scores than ZINC. The top ZINC compounds ranked by docking score were grouped into two classes, which held the binding positions of UDP and GlcNAc of UDPGlcNAc. Combined with individual fragments in binding pocket, de novo compounds were designed and proved to have better docking score. The screened and designed compounds may become a starting point for developing new drugs.