Searching for the most effective screening system to identify cell-active inhibitors of beta-secretase

The beta-secretase BACE1 is an attractive drug target for reducing the level of the Alzheimer's disease-promoting Abeta peptide in the brain. Whereas potent peptidomimetic in vitro inhibitors of BACE1 have been designed, screening approaches to identify cell-permeable small molecule inhibitors have had limited success so far. In the present minireview we summarize existing screening methods, discuss their scope of application in the drug discovery process and compare them to a novel cell-based screening system to identify BACE1 inhibitors by a positive yeast growth selection.     

Identification of novel fragment compounds targeted against the pY pocket of v-Src SH2 by computational and NMR screening and thermodynamic evaluation

Discovery of small molecule inhibitors of protein-protein interactions is a major challenge to pharmaceutical development. Fragment-based approaches have begun to be widely adopted as an effective way of exploring chemical space on a protein surface with reduced library size. On completion of a fragment screen, the subsequent selection of appropriate "hit" molecules for development is a key decision point. Thermodynamic parameters can be used in this decision process. In this work, a fragment identification protocol based on a virtual fragment analysis and selection followed by 19F NMR screening was directed at the phosphotyrosine binding site of the Src SH2 domain. Three new ligands were identified. Isothermal titration calorimetry was used to provide thermodynamic parameters for the physiologically relevant ligand and the selected fragments. One of these fragments possesses a highly favorable enthalpic contribution to complex formation compared to other fragments and to the physiologically relevant ligand suggesting that it would make a good candidate for compound development.     

Tripeptidic BACE1 inhibitors devised by in-silico conformational structure-based design

Previously reported pentapeptidic BACE1 inhibitors, designed using a substrate-based approach, were used as lead compounds for the further design of non-peptidic BACE1 inhibitors. Although these peptidic and non-peptidic inhibitors, with a hydroxymethylcarbonyl isostere as a substrate transition-state mimic, exhibited potent BACE1 inhibitory activities, their molecular-sizes appeared a little too big (molecular weight of >600daltons) for developing practical anti-Alzheimer's disease drugs. To develop lower weight BACE1 inhibitors, a series of tripeptidic BACE1 inhibitors were devised using a design approach based on the conformation of a virtual inhibitor bound to the BACE1 active site, also called 'in-silico conformational structure-based design'. Although these tripeptidic BACE1 inhibitors contained some natural amino acid residues, they are expected to be useful as lead compounds for developing the next generation BACE1 inhibitors, due to their low molecular size and unique structural features compared with previously reported inhibitors.     

Identification of novel leads applying in silico studies for Mycobacterium multidrug resistant (MMR) protein

Multidrug efflux mechanism is the main cause of intrinsic drug resistance in bacteria. Mycobacterium multidrug resistant (MMR) protein belongs to small multidrug resistant family proteins (SMR), causing multidrug resistance to proton (H⁺)-linked lipophilic cationic drug efflux across the cell membrane. In the present work, MMR is treated as a novel target to identify new molecular entities as inhibitors for drug resistance in Mycobacterium tuberculosis. In silico techniques are applied to evaluate the 3D structure of MMR protein. The putative amino acid residues present in the active site of MMR protein are predicted. Protein–ligand interactions are studied by docking cationic ligands transported by MMR protein. Virtual screening is carried out with an in-house library of small molecules against the grid created at the predicted active site residues in the MMR protein. Absorption distribution metabolism and elimination (ADME) properties of the molecules with best docking scores are predicted. The studies with cationic ligands and those of virtual screening are analysed for identification of new lead molecules as inhibitors for drug resistance caused by the MMR protein.     

Structure based virtual screening to identify inhibitors against MurE Enzyme of Mycobacterium tuberculosis using AutoDock Vina

The Mur E enzyme of Mur pathway of Mycobacterium tuberculosis is an attractive drug target as it is unique to bacteria and is absent in mammalian cells. The virtual screening of large libraries of drug like molecules against a protein target is a common strategy used to identify novel inhibitors. However, the method has a large number of pitfalls, with large variations in accuracy caused in part by inaccurate protocols, use of improper standards and libraries, and system dependencies such as the potential for nonspecific docking from large active-site cavities. The screening of drug-like small molecules from diversity sets can, however, be used to short-list potential fragments as building blocks to generate leads with improved specificity. We describe a protocol to implement this strategy, which involves an analysis of the active site and known inhibitors to identify orthospecific determinants, virtual screening of a drug-like diversity library to identify potential drug primitives, and inspection of the potential docked fragments for both binding potential and toxicity. The protocol is implemented on the M.tb Mur E protein which has a large active site with poor enrichment of known positives and a set of drug-like molecules that meets this criteria is presented for further analysis.

Abbreviations

MTB - Mycobacterium tuberculosis, NCI - National Cancer Institute, PDB - Protein Databank.     

Triazolyl tryptoline derivatives as β-secretase inhibitors

Tryptoline, a core structure of ochrolifuanine E, which is a hit compound from virtual screening of the Thai herbal database against BACE1 was used as a scaffold for the design of BACE1 inhibitors. The tryptoline was linked with different side chains by 1,2,3-triazole ring readily synthesized by catalytic azide-alkyne cycloaddition reactions. Twenty two triazolyl tryptoline derivatives were synthesized and screened for the inhibitory action against BACE1. JJCA-140 was the most potent inhibitor (IC(50)=1.49 μM) and was 100 times more selective for BACE1 than for Cat-D.     

Structure- and Ligand-Based Virtual Screening Identifies New Scaffolds for Inhibitors of the Oncoprotein MDM2

A major challenge in the field of ligand discovery is to identify chemically useful fragments that can be developed into inhibitors of specific protein-protein interactions. Low molecular weight fragments (with molecular weight less than 250 Da) are likely to bind weakly to a protein’s surface. Here we use a new virtual screening procedure which uses a combination of similarity searching and docking to identify chemically tractable scaffolds that bind to the p53-interaction site of MDM2. The binding has been verified using capillary electrophoresis which has proven to be an excellent screening method for such small, weakly binding ligands.     

Discovery of Fragment Molecules That Bind the Human Peroxiredoxin 5 Active Site

The search for protein ligands is a crucial step in the inhibitor design process. Fragment screening represents an interesting method to rapidly find lead molecules, as it enables the exploration of a larger portion of the chemical space with a smaller number of compounds as compared to screening based on drug-sized molecules. Moreover, fragment screening usually leads to hit molecules that form few but optimal interactions with the target, thus displaying high ligand efficiencies. Here we report the screening of a homemade library composed of 200 highly diverse fragments against the human Peroxiredoxin 5 protein. Peroxiredoxins compose a family of peroxidases that share the ability to reduce peroxides through a conserved cysteine. The three-dimensional structures of these enzymes ubiquitously found throughout evolution have been extensively studied, however, their biological functions are still not well understood and to date few inhibitors have been discovered against these enzymes. Six fragments from the library were shown to bind to the Peroxiredoxin 5 active site and ligand-induced chemical shift changes were used to drive the docking of these small molecules into the protein structure. The orientation of the fragments in the binding pocket was confirmed by the study of fragment homologues, highlighting the role of hydroxyl functions that hang the ligands to the Peroxiredoxin 5 protein. Among the hit fragments, the small catechol molecule was shown to significantly inhibit Peroxiredoxin 5 activity in a thioredoxin peroxidase assay. This study reports novel data about the ligand-Peroxiredoxin interactions that will help considerably the development of potential Peroxiredoxin inhibitors.     

Dynamic and Multi-Pharmacophore Modeling for Designing Polo-Box Domain Inhibitors

The polo-like kinase 1 (Plk1) is a critical regulator of cell division that is overexpressed in many types of tumors. Thus, a strategy in the treatment of cancer has been to target the kinase activity (ATPase domain) or substrate-binding domain (Polo-box Domain, PBD) of Plk1. However, only few synthetic small molecules have been identified that target the Plk1-PBD. Here, we have applied an integrative approach that combines pharmacophore modeling, molecular docking, virtual screening, and in vitro testing to discover novel Plk1-PBD inhibitors. Nine Plk1-PBD crystal structures were used to generate structure-based hypotheses. A common pharmacophore model (Hypo1) composed of five chemical features was selected from the 9 structure-based hypotheses and used for virtual screening of a drug-like database consisting of 159,757 compounds to identify novel Plk1-PBD inhibitors. The virtual screening technique revealed 9,327 compounds with a maximum fit value of 3 or greater, which were selected and subjected to molecular docking analyses. This approach yielded 93 compounds that made good interactions with critical residues within the Plk1-PBD active site. The testing of these 93 compounds in vitro for their ability to inhibit the Plk1-PBD, showed that many of these compounds had Plk1-PBD inhibitory activity and that compound Chemistry_28272 was the most potent Plk1-PBD inhibitor. Thus Chemistry_28272 and the other top compounds are novel Plk1-PBD inhibitors and could be used for the development of cancer therapeutics.     

Ligand based virtual screening to find novel inhibitors against plant toxin Ricin by using the ZINC database

Ricin is known as a potent toxin against animals. It consists of two chains, Ricin Toxin A (RTA) and Ricin Toxin B (RTB). The toxic effect is known to be caused by RTA. Inhibitors for RTA with less efficiency have been reported. Hence, it is of interest to identify new inhibitors. Virtual screening methods (computer aided drug designing) to find similar molecules in drug database were used for screening new inhibitors against RTA. We used the structure of RTA in complex with Pteroic acid (PDB code: 1BR6) as target molecule. Ligand based virtual screening approach was used in which the known inhibitory molecule Pteroic acid (PTA) served as a template to identify similar ligands from the ZINC database. These ligands were docked inside the binding pocket of RTA by using the MVD (Molegro Virtual Docker). This approach successfully identified six novel compounds. These docked ligands interacted with Asn78, Ala79, Val81, Gly121 and Ser176 amino acids, which are key residues of the RTA active site. Three compounds in particular, ZINC05156321 (6, 7 diphenylpteridin-4-ol), ZINC05156324 (6, 7-bis (3-fluorophenyl) pteridin-4-ol) and ZINC08555900 (6, 7-bis (4-fluorophenyl)-1H-pteridin-4-one), showed higher binding affinity in comparison to PTA, with high interaction energy, better space fitting and electrostatic interactions. These molecules should be tested for in vitro and in vivo activities in future for consideration as effective inhibitors.     

Receptor-based virtual screening evaluation for the identification of estrogen receptor β ligands

Abstract

In this paper, a receptor-based virtual screening study for the identification of estrogen receptor β (ERβ) ligands was developed. Starting from a commercial database of 400?000 molecules, only six compounds resulted to be potential active ligands of ERβ. Interestingly, all the six molecules possess scaffolds that had already been reported in known ERβ ligands. Therefore, the results obtained herein confirm the reliability of our virtual screening procedure, thus encouraging the application of this protocol to larger commercial databases in order to identify new ERβ ligands.     

An unbiased cell morphology-based screen for new, biologically active small molecules

We have implemented an unbiased cell morphology-based screen to identify small-molecule modulators of cellular processes using the Cytometrix (TM) automated imaging and analysis system. This assay format provides unbiased analysis of morphological effects induced by small molecules by capturing phenotypic readouts of most known classes of pharmacological agents and has the potential to read out pathways for which little is known. Four human-cancer cell lines and one noncancerous primary cell type were treated with 107 small molecules comprising four different protein kinase-inhibitor scaffolds. Cellular phenotypes induced by each compound were quantified by multivariate statistical analysis of the morphology, staining intensity, and spatial attributes of the cellular nuclei, microtubules, and Golgi compartments. Principal component analysis was used to identify inhibitors of cellular components not targeted by known protein kinase inhibitors. Here we focus on a hydroxyl-substituted analog (hydroxy-PP) of the known Src-family kinase inhibitor PP2 because it induced cell-specific morphological features distinct from all known kinase inhibitors in the collection. We used affinity purification to identify a target of hydroxy-PP, carbonyl reductase 1 (CBR1), a short-chain dehydrogenase-reductase. We solved the X-ray crystal structure of the CBR1/hydroxy-PP complex to 1.24 A resolution. Structure-based design of more potent and selective CBR1 inhibitors provided probes for analyzing the biological function of CBR1 in A549 cells. These studies revealed a previously unknown function for CBR1 in serum-withdrawal-induced apoptosis. Further studies indicate CBR1 inhibitors may enhance the effectiveness of anticancer anthracyclines. Morphology-based screening of diverse cancer cell types has provided a method for discovering potent new small-molecule probes for cell biological studies and anticancer drug candidates.     

Hit clustering can improve virtual fragment screening: CDK2 and PARP1 case studies

Virtual fragment screening could be a promising alternative to existing experimental screening techniques. However, reliable methods of in silico fragment screening are yet to be established and validated. In order to develop such an approach we first checked how successful the existing molecular docking methods can be in predicting fragment binding affinities and poses. Using our Lead Finder docking software the RMSD of the binding energy prediction was observed to be 1.35 kcal/mol(-1) on a set of 26 experimentally characterized fragment inhibitors, and the RMSD of the predicted binding pose from the experimental one was <1.5 ?. Then, we explored docking of 68 fragments obtained from 39 drug molecules for which co-crystal structures were available from the PDB. It appeared that fragments that participate in oriented non-covalent interactions, such as hydrogen bonds and metal coordination, could be correctly docked in 70-80% of cases suggesting the potential success of rediscovering of corresponding drugs by in silico fragment approach. Based on these findings we've developed a virtual fragment screening technique which involved structural filtration of protein-ligand complexes for specific interactions and subsequent clustering in order to minimize the number of preferable starting fragment candidates. Application of this method led to 2 millimolar-scale fragment PARP1 inhibitors with a new scaffold.     

Identification of InhA inhibitors: A combination of virtual screening,molecular dynamics simulations and quantum chemical studies

In the present work, multiple pharmacophore-based virtual screening of the SPECS natural product database was carried out to identify novel inhibitors of the validated biological target, InhA. The pharmacophore models were built from the five different groups of the co-crystallized ligands present within the active site. The generated models with the same features from each group were pooled and subjected to the test set validation, receiver–operator characteristic analysis and Güner–Henry studies. A set of five hypotheses with sensitivity > 0.5, specificity > 0.5, area under curve (AUC) > 0.7, and goodness of hit score > 0.7 were retrieved and exploited for the virtual screening. The common hits (87 molecules) obtained from these hypotheses were processed via drug-likeness filters. The filtered molecules (27 molecules) were compared for the binding modes and the top scored molecules (12 molecules) along with the reference (triclosan (TCL), docking score = ?11.65 kcal/mol) were rescored and reprioritized via molecular mechanics-generalized Born surface area approach. Eventually, the stability of reprioritized (10 molecules) docked complexes was scrutinized via molecular dynamics simulations. Moreover, the quantum chemical studies of the dynamically stable compounds (9 molecules) were performed to understand structural features essential for the activity. Overall, the protocol resulted in the recognition of nine lead compounds that can be targeted against InhA.     

Robust and Systematic Drug Screening Method Using Chemical Arrays and the Protein Library: Identification of Novel Inhibitors of Carbonic Anhydrase II

The identification of specific interactions between small molecules and human proteins of interest is a fundamental step in chemical biology and drug development. Here we describe an efficient method to obtain novel binding ligands of human proteins by a chemical array approach. Our method includes large-scale ligand screening with two libraries, proteins and chemicals, the use of cell lysates that express proteins of interest fused with red fluorescent protein, and high-throughput screening by merged display analysis, which removes false positive signals from array experiments. Using our systematic platform, we detected novel inhibitors of carbonic anhydrase II. It is suggested that our systematic platform is a rapid and robust approach to screen novel ligands for human proteins of interest.     

Robust and systematic drug screening method using chemical arrays and the protein library: identification of novel inhibitors of carbonic anhydrase II

The identification of specific interactions between small molecules and human proteins of interest is a fundamental step in chemical biology and drug development. Here we describe an efficient method to obtain novel binding ligands of human proteins by a chemical array approach. Our method includes large-scale ligand screening with two libraries, proteins and chemicals, the use of cell lysates that express proteins of interest fused with red fluorescent protein, and high-throughput screening by merged display analysis, which removes false positive signals from array experiments. Using our systematic platform, we detected novel inhibitors of carbonic anhydrase II. It is suggested that our systematic platform is a rapid and robust approach to screen novel ligands for human proteins of interest.     

A minimalist approach to fragment-based ligand design using common rings and linkers: application to kinase inhibitors

We present a novel method for stepwise scaffold assembly that integrates fragment-by-fragment ligand design approaches with high-throughput virtual library screening (COREGEN). As an extension of our earlier studies of common features present in drug molecules, we investigate the hypothesis that most pharmaceutically interesting ligands can be expressed in terms of the ring-linker frameworks that comprise them. Analysis of 119 published kinase inhibitors from at least 18 different targets illustrates that a basis set of 4 rings and 8 linkers is sufficient to describe approximately 90% of ring and linker occurrences, respectively. A similar result was derived from a larger set of approximately 40,000 kinase inhibitors from curated patents. A method for ring-linker-based assembly of scaffold libraries that uses experimental information to guide the placement of anchor fragments is validated using a set of reported kinase inhibitors of Bcr-Abl, Cdk2, and Src. In every case, the predominant structural motif of reported ligand cores is reproduced and variations are suggested. To underscore generality of this approach, a novel scaffold for a cyclooxygenase-2 (COX-2) selective ligand is proposed.     

Identification of chemically diverse Chk1 inhibitors by receptor-based virtual screening

Inhibition of the Chk1 kinase by small molecules is of great therapeutic interest for oncology and in understanding the cellular regulation of the G2/M checkpoint. We report how computational docking of a large electronic catalogue of compounds to an X-ray structure of the Chk1 ATP-binding site allowed prioritisation of a small subset of these compounds for assay. This led to the discovery of 10 novel Chk1 inhibitors, distributed among nine new and clearly different chemical scaffolds. Several of these scaffolds have promising lead-like properties. All these ligands act by competitive binding to the targeted ATP site. The crystal structures of four of these compounds bound to this site are presented, and reasonable modelled docking modes are suggested for the 5 other scaffolds. This structural context is used to assess the potential of these scaffolds for further medicinal chemistry efforts, suggesting that several of them could be elaborated to make additional interactions with the buried part of the ATP site. Some unusual interactions with the conserved kinase backbone motif are pointed out. The ligand-binding modes are also used to discuss their medicinal chemistry potential with respect to undesirable chemical functionalities, whether these functionalities bind directly to the protein or not. Overall, this work illustrates how virtual screening can identify a diverse set of ligands which bind to the targeted site. The structural models for these ligands in the Chk1 ATP-binding site will facilitate further medicinal chemistry efforts targeting this kinase.     

A neural network based virtual screening of cytochrome P450 3A4 inhibitors

A virtual screening test to identify potential CP450 3A4 inhibitors has been developed. Molecular structures of inhibitors and non-inhibitors available in the Genetest database were represented using 2D Unity fingerprints and a feedforward neural network was trained to classify molecules regarding their inhibitory activity. Validation tests revealed that our neural net recognizes at least 89% of 3A4 inhibitors and suggest using this methodology in our virtual screening protocol.