Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators.

Molecular docking is a key method used in virtual screening (VS) campaigns to identify small-molecule ligands for drug discovery targets. While docking provides a tangible way to understand and predict the protein-ligand complex formation, the docking algorithms are often unable to separate active ligands from inactive molecules in practical VS usage. Here, a novel docking and shape-focused pharmacophore VS protocol is demonstrated for facilitating effective hit discovery using retinoic acid receptor-related orphan receptor gamma t (RORγt) as a case study. RORγt is a prospective target for treating inflammatory diseases such as psoriasis and multiple sclerosis. First, a commercial molecular database was flexibly docked. Second, the alternative docking poses were rescored against the shape/electrostatic potential of negative image-based (NIB) models that mirror the target's binding cavity. The compositions of the NIB models were optimized via iterative trimming and benchmarking using a greedy search-driven algorithm or brute force NIB optimization. Third, a pharmacophore point-based filtering was performed to focus the hit identification on the known RORγt activity hotspots. Fourth, free energy binding affinity evaluation was performed on the remaining molecules. Finally, twenty-eight compounds were selected for in vitro testing and eight compounds were determined to be low µM range RORγt inhibitors, thereby showing that the introduced VS protocol generated an effective hit rate of ~29%.

Rational design, optimization, and biological evaluation of novel α-Phosphonopropionic acids as covalent inhibitors of Rab geranylgeranyl transferase.

Rab geranylgeranyltransferase (GGTase-II, RGGT) catalyses the post-translational modification of eukaryotic Rab GTPases, proteins implicated in several pathologies, including cancer, diabetes, neurodegenerative, and infectious diseases. Thus, RGGT inhibitors are believed to be a potential platform for the development of drugs and tools for studying processes related to the abnormal activity of Rab GTPases. Here, a series of new α-phosphonocarboxylates have been prepared in the first attempt of rational design of covalent inhibitors of RGGT derived from non-covalent inhibitors. These compounds were equipped with electrophilic groups capable of binding cysteines, which are present in the catalytic cavity of RGGT. A few of these analogues have shown micromolar activity against RGGT, which correlated with their ability to inhibit the proliferation of the HeLa cancer cell line. The proposed mechanism of this inhibitory activity was rationalised by molecular docking and mass spectrometric measurements, supported by stability and reactivity studies.

Sdfconf: A Novel, Flexible, and Robust Molecular Data Management Tool.

Projects in chemo- and bioinformatics often consist of scattered data in various types and are difficult to access in a meaningful way for efficient data analysis. Data is usually too diverse to be even manipulated effectively. Sdfconf is data manipulation and analysis software to address this problem in a logical and robust manner. Other software commonly used for such tasks are either not designed with molecular and/or conformational data in mind or provide only a narrow set of tasks to be accomplished. Furthermore, many tools are only available within commercial software packages. Sdfconf is a flexible, robust, and free-of-charge tool for linking data from various sources for meaningful and efficient manipulation and analysis of molecule data sets. Sdfconf packages molecular structures and metadata into a complete ensemble, from which one can access both the whole data set and individual molecules and/or conformations. In this software note, we offer some practical examples of the utilization of sdfconf.

Coumarins as Tool Compounds to Aid the Discovery of Selective Function Modulators of Steroid Hormone Binding Proteins.

Steroid hormones play an essential role in a wide variety of actions in the body, such as in metabolism, inflammation, initiating and maintaining sexual differentiation and reproduction, immune functions, and stress response. Androgen, aromatase, and sulfatase pathway enzymes and nuclear receptors are responsible for steroid biosynthesis and sensing steroid hormones. Changes in steroid homeostasis are associated with many endocrine diseases. Thus, the discovery and development of novel drug candidates require a detailed understanding of the small molecule structure-activity relationship with enzymes and receptors participating in steroid hormone synthesis, signaling, and metabolism. Here, we show that simple coumarin derivatives can be employed to build cost-efficiently a set of molecules that derive essential features that enable easy discovery of selective and high-affinity molecules to target proteins. In addition, these compounds are also potent tool molecules to study the metabolism of any small molecule.

Fragment- and negative image-based screening of phosphodiesterase 10A inhibitors.

A novel virtual screening methodology called fragment- and negative image-based (F-NiB) screening is introduced and tested experimentally using phosphodiesterase 10A (PDE10A) as a case study. Potent PDE10A-specific small-molecule inhibitors are actively sought after for their antipsychotic and neuroprotective effects. The F-NiB combines features from both fragment-based drug discovery and negative image-based (NIB) screening methodologies to facilitate rational drug discovery. The selected structural parts of protein-bound ligand(s) are seamlessly combined with the negative image of the target's ligand-binding cavity. This cavity- and fragment-based hybrid model, namely its shape and electrostatics, is used directly in the rigid docking of ab initio generated ligand 3D conformers. In total, 14 compounds were acquired using the F-NiB methodology, 3D quantitative structure-activity relationship modeling, and pharmacophore modeling. Three of the small molecules inhibited PDE10A at ~27 to ~67 µM range in a radiometric assay. In a larger context, the study shows that the F-NiB provides a flexible way to incorporate small-molecule fragments into the drug discovery.

A Practical Perspective: The Effect of Ligand Conformers on the Negative Image-Based Screening.

Negative image-based (NIB) screening is a rigid molecular docking methodology that can also be employed in docking rescoring. During the NIB screening, a negative image is generated based on the target protein's ligand-binding cavity by inverting its shape and electrostatics. The resulting NIB model is a drug-like entity or pseudo-ligand that is compared directly against ligand 3D conformers, as is done with a template compound in the ligand-based screening. This cavity-based rigid docking has been demonstrated to work with genuine drug targets in both benchmark testing and drug candidate/lead discovery. Firstly, the study explores in-depth the applicability of different ligand 3D conformer generation software for acquiring the best NIB screening results using cyclooxygenase-2 (COX-2) as the example system. Secondly, the entire NIB workflow from the protein structure preparation, model build-up, and ligand conformer generation to the similarity comparison is performed for COX-2. Accordingly, hands-on instructions are provided on how to employ the NIB methodology from start to finish, both with the rigid docking and docking rescoring using noncommercial software. The practical aspects of the NIB methodology, especially the effect of ligand conformers, are discussed thoroughly, thus, making the methodology accessible for new users.

Suitability of MMGBSA for the selection of correct ligand binding modes from docking results.

The estimation of the correct binding mode and affinity of a ligand into a target protein using computational methods is challenging. However, docking can introduce poses from which the correct binding mode could be identified using other methods. Here, we analyzed the reliability of binding energy estimation using the molecular mechanics-generalized Born surface area (MMGBSA) method without and with energy minimization to identify the likely ligand binding modes within docking results. MMGBSA workflow (a) outperformed docking in recognizing the correct binding modes of androgen receptor ligands and (b) improved the correlation coefficient of computational and experimental results of rescored docking poses to phosphodiesterase 4B. Combined with stability and atomic distance analysis, MMGBSA helped to (c) identify the binding modes and sites of metabolism of cytochrome P450 2A6 substrates. The standard deviation of estimated binding energy within one simulation was lowered by minimization in all three example cases. Minimization improved the identification of the correct binding modes of androgen receptor ligands. Although only three case studies are shown, the results are analogous and indicate that these behaviors could be generalized. Such identified binding modes could be further used, for example, with free energy perturbation methods to understand binding energetics more accurately.

Discovery of Retinoic Acid-Related Orphan Receptor γt Inverse Agonists via Docking and Negative Image-Based Screening.

Retinoic acid-related orphan receptor γt (RORγt) has a vital role in the differentiation of T-helper 17 (TH17) cells. Potent and specific RORγt inverse agonists are sought for treating TH17-related diseases such as psoriasis, rheumatoid arthritis, and type 1 diabetes. Here, the aim was to discover novel RORγt ligands using both standard molecular docking and negative image-based screening. Interestingly, both of these in silico techniques put forward mostly the same compounds for experimental testing. In total, 11 of the 34 molecules purchased for testing were verified as RORγt inverse agonists, thus making the effective hit rate 32%. The pIC50 values for the compounds varied from 4.9 (11 µM) to 6.2 (590 nM). Importantly, the fact that the verified hits represent four different cores highlights the structural diversity of the RORγt inverse agonism and the ability of the applied screening methodologies to facilitate much-desired scaffold hopping for drug design.

Improving Docking Performance Using Negative Image-Based Rescoring.

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.

Blocking oestradiol synthesis pathways with potent and selective coumarin derivatives.

A comprehensive set of 3-phenylcoumarin analogues with polar substituents was synthesised for blocking oestradiol synthesis by 17-ß-hydroxysteroid dehydrogenase 1 (HSD1) in the latter part of the sulphatase pathway. Five analogues produced ≥62% HSD1 inhibition at 5 µM and, furthermore, three of them produced ≥68% inhibition at 1 µM. A docking-based structure-activity relationship analysis was done to determine the molecular basis of the inhibition and the cross-reactivity of the analogues was tested against oestrogen receptor, aromatase, cytochrome P450 1A2, and monoamine oxidases. Most of the analogues are only modestly active with 17-ß-hydroxysteroid dehydrogenase 2 - a requirement for lowering effective oestradiol levels in vivo. Moreover, the analysis led to the synthesis and discovery of 3-imidazolecoumarin as a potent aromatase inhibitor. In short, coumarin core can be tailored with specific ring and polar moiety substitutions to block either the sulphatase pathway or the aromatase pathway for treating breast cancer and endometriosis.

Structure-Activity Relationship Analysis of 3-Phenylcoumarin-Based Monoamine Oxidase B Inhibitors.

Monoamine oxidase B (MAO-B) catalyzes deamination of monoamines such as neurotransmitters dopamine and norepinephrine. Accordingly, small-molecule MAO-B inhibitors potentially alleviate the symptoms of dopamine-linked neuropathologies such as depression or Parkinson's disease. Coumarin with a functionalized 3-phenyl ring system is a promising scaffold for building potent MAO-B inhibitors. Here, a vast set of 3-phenylcoumarin derivatives was designed using virtual combinatorial chemistry or rationally de novo and synthesized using microwave chemistry. The derivatives inhibited the MAO-B at 100 nM-1 µM. The IC50 value of the most potent derivative 1 was 56 nM. A docking-based structure-activity relationship analysis summarizes the atom-level determinants of the MAO-B inhibition by the derivatives. Finally, the cross-reactivity of the derivatives was tested against monoamine oxidase A and a specific subset of enzymes linked to estradiol metabolism, known to have coumarin-based inhibitors. Overall, the results indicate that the 3-phenylcoumarins, especially derivative 1, present unique pharmacological features worth considering in future drug development.

Molecular Docking-Based Design and Development of a Highly Selective Probe Substrate for UDP-glucuronosyltransferase 1A10.

Intestinal and hepatic glucuronidation by the UDP-glucuronosyltransferases (UGTs) greatly affect the bioavailability of phenolic compounds. UGT1A10 catalyzes glucuronidation reactions in the intestine, but not in the liver. Here, our aim was to develop selective, fluorescent substrates to easily elucidate UGT1A10 function. To this end, homology models were constructed and used to design new substrates, and subsequently, six novel C3-substituted (4-fluorophenyl, 4-hydroxyphenyl, 4-methoxyphenyl, 4-(dimethylamino)phenyl, 4-methylphenyl, or triazole) 7-hydroxycoumarin derivatives were synthesized from inexpensive starting materials. All tested compounds could be glucuronidated to nonfluorescent glucuronides by UGT1A10, four of them highly selectively by this enzyme. A new UGT1A10 mutant, 1A10-H210M, was prepared on the basis of the newly constructed model. Glucuronidation kinetics of the new compounds, in both wild-type and mutant UGT1A10 enzymes, revealed variable effects of the mutation. All six new C3-substituted 7-hydroxycoumarins were glucuronidated faster by human intestine than by liver microsomes, supporting the results obtained with recombinant UGTs. The most selective 4-(dimethylamino)phenyl and triazole C3-substituted 7-hydroxycoumarins could be very useful substrates in studying the function and expression of the human UGT1A10.

Identification of the Privileged Position in the Imidazo[1,2-a]pyridine Ring of Phosphonocarboxylates for Development of Rab Geranylgeranyl Transferase (RGGT) Inhibitors.

Members of the Rab GTPase family are master regulators of vesicle trafficking. When disregulated, they are associated with a number of pathological states. The inhibition of RGGT, an enzyme responsible for post-translational geranylgeranylation of Rab GTPases represents one way to control the activity of these proteins. Because the number of molecules modulating RGGT is limited, we combined molecular modeling with biological assays to ascertain how modifications of phosphonocarboxylates, the first reported RGGT inhibitors, rationally improve understanding of their structure-activity relationship. We have identified the privileged position in the core scaffold of the imidazo[1,2-a]pyridine ring, which can be modified without compromising compounds' potency. Thus modified compounds are micromolar inhibitors of Rab11A prenylation, simultaneously being inactive against Rap1A/Rap1B modification, with the ability to inhibit proliferation of the HeLa cancer cell line. These findings were rationalized by molecular docking, which recognized interaction of phosphonic and carboxylic groups as decisive in phosphonocarboxylate localization in the RGGT binding site.

Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization.

ABSTRACT: Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also includes an automatic calculation of the AUC for the ROC curve and Boltzmann-enhanced discrimination of ROC (BEDROC). Furthermore, in virtual screening campaigns it is often important to understand the early enrichment of active ligand identification, for this Rocker offers automated calculation routine. To enable further development of Rocker, it is freely available (MIT-GPL license) for use and modifications from our web-site (http://www.jyu.fi/rocker).

Identification of estrogen receptor α ligands with virtual screening techniques.

Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example, structure-based methods identified an already known active ligand from the widely-used bechmarking decoy molecule set. Although prospective VS against one commercially available database with around 100,000 drug-like molecules did not retrieve many testworthy hits, one novel hit molecule with pIC50 value of 6.6, was identified. Furthermore, our small in-house compound collection of easy-to-synthesize molecules was virtually screened against ERα, yielding to five hit candidates, which were found to be active in vitro having pIC50 values from 5.5 to 6.5.

Case-specific performance of MM-PBSA, MM-GBSA, and SIE in virtual screening.

In drug discovery the reliable prediction of binding free energies is of crucial importance. Methods that combine molecular mechanics force fields with continuum solvent models have become popular because of their high accuracy and relatively good computational efficiency. In this research we studied the performance of molecular mechanics generalized Born surface area (MM-GBSA), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), and solvated interaction energy (SIE) both in their virtual screening efficiency and their ability to predict experimentally determined binding affinities for five different protein targets. The protein-ligand complexes were derived with two different approaches important in virtual screening: molecular docking and ligand-based similarity search methods. The results show significant differences between the different binding energy calculation methods. However, the length of the molecular dynamics simulation was not of crucial importance for accuracy of results.

Ultrafast protein structure-based virtual screening with Panther.

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Reliability of Virtual Screening Methods in Prediction of PDE4B-inhibitor Activity.

Identification of active ligands using computational methods is a challenging task. For example, molecular docking, pharmacophore modeling, and three dimensional quantitative structure-activity relationship models (3D-QSAR) are widely used methods to identify novel small molecules. However, all these methods have, in addition to advantages, also significant pitfalls. The aim of this study was to compare some commonly used computational methods to estimate their ability to separate highly active PDE4B-inhibitors from less active and inactive ones. Here, 152 molecules with pIC50-range of 3.4-10.5, originating from six original studies were used. High correlation coefficients by using docking, docking with postprocessing with molecular mechanics-generalized Born-surface area -method (MMGBSA), pharmacophore modeling, and 3D-QSAR were obtained. These results are well in line with earlier studies done with similar methods, and suggest that computational methods could be successfully used to identify novel PDE4B-inhibitors, especially if using multiple methods together.

Molecular mechanism of T-cell protein tyrosine phosphatase (TCPTP) activation by mitoxantrone.

T-cell protein tyrosine phosphatase (TCPTP) is a ubiquitously expressed non-receptor protein tyrosine phosphatase. It is involved in the negative regulation of many cellular signaling pathways. Thus, activation of TCPTP could have important therapeutic applications in diseases such as cancer and inflammation. We have previously shown that the α-cytoplasmic tail of integrin α1ß1 directly binds and activates TCPTP. In addition, we have identified in a large-scale high-throughput screen six small molecules that activate TCPTP. These small molecule activators include mitoxantrone and spermidine. In this study, we have investigated the molecular mechanism behind agonist-induced TCPTP activation. By combining several molecular modeling and biochemical techniques, we demonstrate that α1-peptide and mitoxantrone activate TCPTP via direct binding to the catalytic domain, whereas spermidine does not interact with the catalytic domain of TCPTP in vitro. Furthermore, we have identified a hydrophobic groove surrounded by negatively charged residues on the surface of TCPTP as a putative binding site for the α1-peptide and mitoxantrone. Importantly, these data have allowed us to identify a new molecule that binds to TCPTP, but interestingly cannot activate its phosphatase activity. Accordingly, we describe here mechanism of TCPTP activation by mitoxantrone, the cytoplasmic tail of α1-integrin, and a mitoxantrone-like molecule at the atomic level. These data provide invaluable insight into the development of novel TCPTP activators, and may facilitate the rational discovery of small-molecule cancer therapeutics.

2NH and 3OH are crucial structural requirements in sphingomyelin for sticholysin II binding and pore formation in bilayer membranes.

Sticholysin II (StnII) is a pore-forming toxin from the sea anemone Stichodactyla heliantus which belongs to the large actinoporin family. The toxin binds to sphingomyelin (SM) containing membranes, and shows high binding specificity for this lipid. In this study, we have examined the role of the hydrogen bonding groups of the SM long-chain base (i.e., the 2NH and the 3OH) for StnII recognition. We prepared methylated SM-analogs which had reduced hydrogen bonding capability from 2NH and 3OH. Both surface plasmon resonance experiments, and isothermal titration calorimetry measurements indicated that StnII failed to bind to bilayers containing methylated SM-analogs, whereas clear binding was seen to SM-containing bilayers. StnII also failed to induce calcein release (i.e., pore formation) from vesicles made to contain methylated SM-analogs, but readily induced calcein release from SM-containing vesicles. Molecular modeling of SM docked to the phosphocholine binding site of StnII indicated that the 2NH and 3OH groups were likely to form a hydrogen bond with Tyr135. In addition, it appeared that Tyr111 and Tyr136 could donate hydrogen bonds to phosphate oxygen, thus stabilizing SM binding to the toxin. We conclude that the interfacial hydrogen bonding properties of SM, in addition to the phosphocholine head group, are crucial for high-affinity SM/StnII-interaction.