New method for the assessment of all drug-like pockets across a structural genome

Bioefficacy, chromatographic profiling and drug-likeness analysis of flavonoids and terpenoids as potential inhibitors of H1N1 influenza viral proteins

Considering medicinal plants, natural products present in these plants are the best sources of medications for combating viral infection. The possible drug target against viral H1N1 influenza proteins lead to identification of selected secondary metabolites from potential plants Tinospora cordifolia, Ocimum sanctum, and Piper nigrum. On analysis of in vitro cell based antiviral activity of the selected plant extracts, an indication for a possible lead compound against neuraminidase activity was evident. Potent ligands were selected using drug docking and ADMET analysis, and the screened lead metabolites were ultimately identified as terpenoid (Columbin) and, flavonoid (Cubebin, and Apigenin). Among the selected ligands, the drug binding activity of Cubebin with all the 6 proteins of H1N1 influenza type A virus, HA (4r8w), NA (4qn7), M2 (3lbw), PA (4wsb), PB1 (2znl) and PB2 (3wil), was pronounced. In addition, physicochemical and pharmacokinetic parameters linked to absorption, distribution, metabolism, excretion and toxicity (ADMET) have been evaluated and corroborate with our in vitro results. Molecular dynamics modelling indicated Cubebin can be a potential phytochemical in a drug discovery pipeline for the development of neuraminidase inhibitors. Further studies can provide a possibility for an alternative therapy against Influenza viruses.

PEARL-seq: A Photoaffinity Platform for the Analysis of Small Molecule-RNA Interactions

RNA is emerging as a valuable target for the development of novel therapeutic agents. The rational design of RNA-targeting small molecules, however, has been hampered by the relative lack of methods for the analysis of small molecule-RNA interactions. Here, we present our efforts to develop such a platform using photoaffinity labeling. This technique, termed Photoaffinity Evaluation of RNA Ligation-Sequencing (PEARL-seq), enables the rapid identification of small molecule binding locations within their RNA targets and can provide information on ligand selectivity across multiple different RNAs. These data, when supplemented with small molecule SAR data and RNA probing data enable the construction of a computational model of the RNA-ligand structure, thereby enabling the rational design of novel RNA-targeted ligands.

Druggable exosites of the human kino-pocketome

Small molecules binding at any of the multiple regulatory sites on the molecular surface of a protein kinase may stabilize or disrupt the corresponding interaction, leading to consequent modulation of the kinase cellular activity. As such, each of these sites represents a potential drug target. Even targeting sites outside the immediate ATP site, the so-called exosites, may cause desirable biological effects through an allosteric mechanism. Targeting exosites can alleviate adverse effects and toxicity that is common when ATP-site compounds bind promiscuously to many other types of kinases. In this study we have identified, catalogued, and annotated all potentially druggable exosites on the protein kinase domains within the existing structural human kinome. We then priority-ranked these exosites by those most amenable to drug design. In order to identify pockets that are either consistent across the kinome, or unique and specific to a particular structure, we have also implemented a normalized representation of all pockets, and displayed these graphically. Finally, we have built a database and designed a web-based interface for users interested in accessing the 3-dimensional representations of these pockets. We envision this information will assist drug discovery efforts searching for untargeted binding pockets in the human kinome.

Molecular modelling and docking analysis of pleurocidin (an antimicrobial peptide) like peptides with enterotoxin H from Klebsilla pneumonia

Enterotoxin H is a key molecular target for replication and establishment of Klebsilla pneumonia in the host. Therefore, it is of interest to study the interaction of enterotoxin H with pleurocidin like peptides using molecular modelling (template PDB ID: 1YCE), Lig-Plot (ligand construction) and docking tools for therapeutic consideration. The hydrophobic pocket and the active site residues (Val 13, Met 16, Gly 25, Ala 25, and Ile 28) were identified using Cast P, Molegro and Sitehound tools. Docking results show that the pleurocidin like peptides interacts with the active sites of enterotoxin H with 300.96 docking score with optimal binding features.

Synthesis, Antitumor Activity, and Docking Analysis of New Pyrido[3',2':4,5]furo(thieno)[3,2-d]pyrimidin-8-amines

Continuing our research in the field of new heterocyclic compounds, herein we report on the synthesis and antitumor activity of new amino derivatives of pyrido[3',2':4,5](furo)thieno[3,2-d]pyrimidines as well as of two new heterocyclic systems: furo[2-e]imidazo[1,2-c]pyrimidine and furo[2,3-e]pyrimido[1,2-c]pyrimidine. Thus, by refluxing the 8-chloro derivatives of pyrido[3',2':4,5]thieno(furo)[3,2-d]pyrimidines with various amines, the relevant pyrido[3',2':4,5]thieno(furo)[3,2-d]pyrimidin-8-amines were obtained. Further, the cyclization of some amines under the action of phosphorus oxychloride led to the formation of new heterorings: imidazo[1,2-c]pyrimidine and pyrimido[1,2-c]pyrimidine. The possible antitumor activity of the newly synthesized compounds was evaluated in vitro. The biological tests evidenced that some of them showed pronounced antitumor activity. A study of the structure-activity relationships revealed that the compound activity depended mostly on the nature of the amine fragments. A docking analysis was also performed for the most active compounds.

Apoptosome activation, an important molecular instigator in 6-mercaptopurine induced Leydig cell death

Leydig cells are crucial to the production of testosterone in males. It is unknown if the cancer chemotherapeutic drug, 6-mercaptopurine (6 MP), produces Leydig cell failure among adult survivors of childhood acute lymphoblastic leukemia. Moreover, it is not known whether Leydig cell failure is due to either a loss of cells or an impairment in their function. Herein, we show, in a subset of childhood cancer survivors, that Leydig cell failure is related to the dose of 6 MP. This was extended, in a murine model, to demonstrate that 6 MP exposure induced caspase 3 activation, and the loss of Leydig cells was independent of Bak and Bax activation. The death of these non-proliferating cells was triggered by 6 MP metabolism, requiring formation of both cytosolic reactive oxygen species and thiopurine nucleotide triphosphates. The thiopurine nucleotide triphosphates (with physiological amounts of dATP) uniquely activated the apoptosome. An ABC transporter (Abcc4/Mrp4) reduced the amount of thiopurines, thereby providing protection for Leydig cells. The studies reported here demonstrate that the apoptosome is uniquely activated by thiopurine nucleotides and suggest that 6 MP induced Leydig cell death is likely a cause of Leydig cell failure in some survivors of childhood cancer.

In silico docking, molecular dynamics and binding energy insights into the bolinaquinone-clathrin terminal domain binding site

Clathrin-mediated endocytosis (CME) is a process that regulates selective internalization of important cellular cargo using clathrin-coated vesicles. Perturbation of this process has been linked to many diseases including cancer and neurodegenerative conditions. Chemical proteomics identified the marine metabolite, 2-hydroxy-5-methoxy-3-(((1S,4aS,8aS)-1,4a,5-trimethyl-1,2,3,4,4a,7,8,8a-octahydronaphthalen-2-yl)methyl)cyclohexa-2,5-diene-1,4-dione (bolinaquinone) as a clathrin inhibitor. While being an attractive medicinal chemistry target, the lack of data about bolinaquinone’s mode of binding to the clathrin enzyme represents a major limitation for its structural optimization. We have used a molecular modeling approach to rationalize the observed activity of bolinaquinone and to predict its mode of binding with the clathrin terminal domain (CTD). The applied protocol started by global rigid-protein docking followed by flexible docking, molecular dynamics and linear interaction energy calculations. The results revealed the potential of bolinaquinone to interact with various pockets within the CTD, including the clathrin-box binding site. The results also highlight the importance of electrostatic contacts over van der Waals interactions for proper binding between bolinaquinone and its possible binding sites. This study provides a novel model that has the potential to allow rapid elaboration of bolinaquinone analogues as a new class of clathrin inhibitors.

Rational design of berberine-based FtsZ inhibitors with broad-spectrum antibacterial activity

Inhibition of the functional activity of Filamenting temperature-sensitive mutant Z (FtsZ) protein, an essential and highly conserved bacterial cytokinesis protein, is a promising approach for the development of a new class of antibacterial agents. Berberine, a benzylisoquinoline alkaloid widely used in traditional Chinese and native American medicines for its antimicrobial properties, has been recently reported to inhibit FtsZ. Using a combination of in silico structure-based design and in vitro biological assays, 9-phenoxyalkyl berberine derivatives were identified as potent FtsZ inhibitors. Compared to the parent compound berberine, the derivatives showed a significant enhancement of antibacterial activity against clinically relevant bacteria, and an improved potency against the GTPase activity and polymerization of FtsZ. The most potent compound 2 strongly inhibited the proliferation of Gram-positive bacteria, including methicillin-resistant S. aureus and vancomycin-resistant E. faecium, with MIC values between 2 and 4 µg/mL, and was active against the Gram-negative E. coli and K. pneumoniae, with MIC values of 32 and 64 µg/mL respectively. The compound perturbed the formation of cytokinetic Z-ring in E. coli. Also, the compound interfered with in vitro polymerization of S. aureus FtsZ. Taken together, the chemical modification of berberine with 9-phenoxyalkyl substituent groups greatly improved the antibacterial activity via targeting FtsZ.

Structure-based design of small-molecule protein–protein interaction modulators: the story so far

As the pivotal role of protein–protein interactions in cell growth, transcriptional activity, intracellular trafficking, signal transduction and pathological conditions has been assessed, experimental and in silico strategies have been developed to design protein–protein interaction modulators. State-of-the-art structure-based design methods, mainly pharmacophore modeling and docking, which have succeeded in the identification of enzyme inhibitors, receptor agonists and antagonists, and new tools specifically conceived to target protein–protein interfaces (e.g., hot-spot and druggable pocket prediction methods) have been applied in the search for small-molecule protein–protein interaction modulators. Many successful applications of structure-based design approaches that, despite the challenge of targeting protein–protein interfaces with small molecules, have led to the identification of micromolar and submicromolar hits are reviewed here.

In Silico screening on the three-dimensional model of the Plasmodium vivax SUB1 protease leads to the validation of a novel anti-parasite compound

Widespread drug resistance calls for the urgent development of new antimalarials that target novel steps in the life cycle of Plasmodium falciparum and Plasmodium vivax. The essential subtilisin-like serine protease SUB1 of Plasmodium merozoites plays a dual role in egress from and invasion into host erythrocytes. It belongs to a new generation of attractive drug targets against which specific potent inhibitors are actively searched. We characterize here the P. vivax SUB1 enzyme and show that it displays a typical auto-processing pattern and apical localization in P. vivax merozoites. To search for small PvSUB1 inhibitors, we took advantage of the similarity of SUB1 with bacterial subtilisins and generated P. vivax SUB1 three-dimensional models. The structure-based virtual screening of a large commercial chemical compounds library identified 306 virtual best hits, of which 37 were experimentally confirmed inhibitors and 5 had Ki values of <50 μM for PvSUB1. Interestingly, they belong to different chemical families. The most promising competitive inhibitor of PvSUB1 (compound 2) was equally active on PfSUB1 and displayed anti-P. falciparum and Plasmodium berghei activity in vitro and in vivo, respectively. Compound 2 inhibited the endogenous PfSUB1 as illustrated by the inhibited maturation of its natural substrate PfSERA5 and inhibited parasite egress and subsequent erythrocyte invasion. These data indicate that the strategy of in silico screening of three-dimensional models to select for virtual inhibitors combined with stringent biological validation successfully identified several inhibitors of the PvSUB1 enzyme. The most promising hit proved to be a potent cross-inhibitor of PlasmodiumSUB1, laying the groundwork for the development of a globally active small compound antimalarial.

Drug-like density: a method of quantifying the "bindability" of a protein target based on a very large set of pockets and drug-like ligands from the Protein Data Bank

One approach to estimating the "chemical tractability" of a candidate protein target where we know the atomic resolution structure is to examine the physical properties of potential binding sites. A number of other workers have addressed this issue. We characterize ~290,000 "pockets" from ~42,000 protein crystal structures in terms of a three parameter "pocket space": volume, buriedness, and hydrophobicity. A metric DLID (drug-like density) measures how likely a pocket is to bind a drug-like molecule. This is calculated from the count of other pockets in its local neighborhood in pocket space that contain drug-like cocrystallized ligands and the count of total pockets in the neighborhood. Surprisingly, despite being defined locally, a global trend in DLID can be predicted by a simple linear regression on log(volume), buriedness, and hydrophobicity. Two levels of simplification are necessary to relate the DLID of individual pockets to "targets": taking the best DLID per Protein Data Bank (PDB) entry (because any given crystal structure can have many pockets), and taking the median DLID over all PDB entries for the same target (because different crystal structures of the same protein can vary because of artifacts and real conformational changes). We can show that median DLIDs for targets that are detectably homologous in sequence are reasonably similar and that median DLIDs correlate with the "druggability" estimate of Cheng et al. (Nature Biotechnology 2007, 25, 71-75).

Assessing the structural conservation of protein pockets to study functional and allosteric sites: implications for drug discovery

Background

With the classical, active-site oriented drug-development approach reaching its limits, protein ligand-binding sites in general and allosteric sites in particular are increasingly attracting the interest of medicinal chemists in the search for new types of targets and strategies to drug development. Given that allostery represents one of the most common and powerful means to regulate protein function, the traditional drug discovery approach of targeting active sites can be extended by targeting allosteric or regulatory protein pockets that may allow the discovery of not only novel drug-like inhibitors, but activators as well. The wealth of available protein structural data can be exploited to further increase our understanding of allosterism, which in turn may have therapeutic applications. A first step in this direction is to identify and characterize putative effector sites that may be present in already available structural data.

Results

We performed a large-scale study of protein cavities as potential allosteric and functional sites, by integrating publicly available information on protein sequences, structures and active sites for more than a thousand protein families. By identifying common pockets across different structures of the same protein family we developed a method to measure the pocket's structural conservation. The method was first parameterized using known active sites. We characterized the predicted pockets in terms of sequence and structural conservation, backbone flexibility and electrostatic potential. Although these different measures do not tend to correlate, their combination is useful in selecting functional and regulatory sites, as a detailed analysis of a handful of protein families shows. We finally estimated the numbers of potential allosteric or regulatory pockets that may be present in the data set, finding that pockets with putative functional and effector characteristics are widespread across protein families.

Conclusions

Our results show that structurally conserved pockets are a common feature of protein families. The structural conservation of protein pockets, combined with other characteristics, can be exploited in drug discovery procedures, in particular for the selection of the most appropriate target protein and pocket for the design of drugs against entire protein families or subfamilies (e.g. for the development of broad-spectrum antimicrobials) or against a specific protein (e.g. in attempting to reduce side effects).

Prediction of 3D metal binding sites from translated gene sequences based on remote-homology templates

Database-scale analysis was performed to determine whether structural models, based on remote homologues, are effective in predicting 3D transition metal binding sites in proteins directly from translated gene sequences. The extent by which side chain modeling alone reduces sensitivity and selectivity is shown to be <10%. Surprisingly, selectivity was not dependent on the level of sequence homology between template and target, or on the presence of a metal ion in the structural template. Applying a modification of the CHED algorithm (Babor et al., Proteins 2008;70:208-217) and machine learning filters, a selectivity of approximately 90% was achieved for protein sequences using unrelated structural templates over a sequence identity range of 18-100%. Below approximately 18% identity, the number of analyzable target-template pairs and predictability of metal binding sites falls off sharply. A full third of structural templates were found to have target partners only in the remote homology range of 18-30%. In this range, nonmetal-binding templates are calculated to be the majority and serve to predict with 50% sensitivity at the geometric level. Overall, sensitivity at the geometric level for targets having templates in the 18-30% sequence identity range is 73%, with an average of one false positive site per true site. Protein sequences described as "unknown" in the UniProt database and composed largely of unidentified genome project sequences were studied and metal binding sites predicted. A web server for prediction of metal binding sites from protein sequence is provided.

Structure-based approaches to antibiotic drug discovery

The development of antimicrobials has advanced tremendously over the past century. However, as our production capacity increases, the threat of resistance is ever-present. To combat this resistance, two main avenues of drug discovery are being pursued: identifying new microbial proteins for which to direct drug discovery efforts, and designing innovative drugs that target existing proteins. The advent of structural genomics research has advanced to the point of rapidly discovering novel microbial protein targets. In addition, modern tools of computational biology greatly enhance the speed and reliability of antimicrobial discovery. The various steps of this process are outlined and discussed, including virtual ligand screening, pocket identification, and compound optimization.