Comparison of Structure‐ and Ligand‐Based Virtual Screening Protocols Considering Hit List Complementarity and Enrichment Factors

Structure‐ and ligand‐based virtual‐screening methods (docking, 2D‐ and 3D‐similarity searching) were analysed for their effectiveness in virtual screening against four different targets: angiotensin‐converting enzyme (ACE), cyclooxygenase 2 (COX‐2), thrombin and human immunodeficiency virus 1 (HIV‐1) protease. The relative performance of the tools was compared by examining their ability to recognise known active compounds from a set of actives and nonactives. Furthermore, we investigated whether the application of different virtual‐screening methods in parallel provides complementary or redundant hit lists. Docking was performed with GOLD, Glide, FlexX and Surflex. The obtained docking poses were rescored by using nine different scoring functions in addition to the scoring functions implemented as objective functions in the docking algorithms. Ligand‐based virtual screening was done with ROCS (3D‐similarity searching), Feature Trees and Scitegic Functional Fingerprints (2D‐similarity searching). The results show that structure‐ and ligand‐based virtual‐screening methods provide comparable enrichments in detecting active compounds. Interestingly, the hit lists that are obtained from different virtual‐screening methods are generally highly complementary. These results suggest that a parallel application of different structure‐ and ligand‐based virtual‐screening methods increases the chance of identifying more (and more diverse) active compounds from a virtual‐screening campaign.     

Prospective Virtual Screening in a Sparse Data Scenario: Design of Small‐Molecule TLR2 Antagonists

Toll‐like receptors (TLRs) are critical signaling molecules with roles in various severe clinical conditions such as sepsis and rheumatoid arthritis, and have therefore been advocated as promising drug targets for the treatment of these diseases. The aim of this study was to discover small‐molecule antagonists of TLR2 by computer‐aided drug design. This goal poses several challenges due to the lack of available data on TLR2 modulators. To overcome these hurdles we developed a combined structure‐ and ligand‐based virtual screening approach. First, we calculated molecular interaction fields of the TLR2 binding site to derive a structure‐based 3D pharmacophore, which was then used for virtual screening. We then performed a two‐step shape‐ and feature‐based similarity search using known TLR2 ligands as query structures. A selection of virtual screening hits was biologically tested in a cell‐based assay for TLR2 signaling inhibition, leading to the identification of several compounds with antagonistic activity (IC₅₀ values) in the low‐micromolar range.     

Structure‐Based Virtual Screening and Electrophysiological Evaluation of New Chemotypes of Kv1.5 Channel Blockers

Atrial fibrillation (AF) is the most prevalent nonfatal cardiac rhythm disorder associated with an increased risk of heart failure and stroke. Considering the ventricular side effects induced by anti‐arrhythmic agents in current use, K_v1.5 channel blockers have attracted a great deal of deliberation owing to their selective actions on atrial electrophysiology. Herein we report new chemotypes of K_v1.5 channel blockers that were identified through a combination of structure‐based virtual screening and in silico druglike property prediction including six scoring functions, as well as electrophysiological evaluation. Among them, five of the 18 compounds exhibited >50 % blockade ratio at 10 μM , and have structural features different from conventional K_v1.5 channel blockers. These novel scaffolds could serve as hits for further optimization and SAR studies for the discovery of selective agents to treat AF.     

A Series of 18F‐Labelled Pyridinylphenyl Amides as Subtype‐Selective Radioligands for the Dopamine D3 Receptor

Synthesis, biological activity, and structure–selectivity relationship (SSR) studies of a novel series of potential dopamine D3 receptor radioligands as imaging agents for positron emission tomography (PET) are reported. Considering a structurally diverse library of D3 ligands, SSR studies were performed for a new series of fluorinated pyridinylphenyl amides using CoMFA and CoMSIA methods. The in vitro D3 affinities of the predicted series of biphenyl amide ligands 9 a – d revealed single‐digit to sub‐nanomolar potencies (K_i=0.52–1.6 nM ), displaying excellent D3 selectivity over the D2 subtype of 110‐ to 210‐fold for the test compounds 9 a – c . Radiofluorination by nucleophilic substitution of Br or NO₂ by ¹⁸F led to radiochemical yields of 66–92 % for [¹⁸F] 9 a – d . However, the specific activities of [¹⁸F] 9 b and [¹⁸F] 9 d were insufficient, rendering their use for in vivo studies impossible. Biodistribution studies of [¹⁸F] 9 a and [¹⁸F] 9 c using rat brain autoradiography revealed accumulation in the ventricles, thus indicating insufficient biokinetic properties of [¹⁸F] 9 a and [¹⁸F] 9 c for D3 receptor imaging in vivo.     

A Structure‐Based Virtual Screening Approach toward the Discovery of Histone Deacetylase Inhibitors: Identification of Promising Zinc‐Chelating Groups

The inhibitors of histone deacetylases (HDACs) have drawn a great deal of attention due to their promising potential as small‐molecule therapeutics for the treatment of cancer. By means of virtual screening with docking simulations under consideration of the effects of ligand solvation, we were able to identify six novel HDAC inhibitors with IC₅₀ values ranging from 1 to 100 μM . These newly identified inhibitors are structurally diverse and have various chelating groups for the active site zinc ion, including N‐[1,3,4]thiadiazol‐2‐yl sulfonamide, N‐thiazol‐2‐yl sulfonamide, and hydroxamic acid moieties. The former two groups are included in many drugs in current clinical use and have not yet been reported as HDAC inhibitors. Therefore, they can be considered as new inhibitor scaffolds for the development of anticancer drugs by structure–activity relationship studies to improve the inhibitory activities against HDACs. Interactions with the HDAC1 active site residues responsible for stabilizing these new inhibitors are addressed in detail.     

Synthesis, 3D‐QSAR,and Structural Modeling of Benzolactam Derivatives with Binding Affinity for the D2 and D3 Receptors

A series of 37 benzolactam derivatives were synthesized, and their respective affinities for the dopamine D₂ and D₃ receptors evaluated. The relationships between structures and binding affinities were investigated using both ligand‐based (3D‐QSAR) and receptor‐based methods. The results revealed the importance of diverse structural features in explaining the differences in the observed affinities, such as the location of the benzolactam carbonyl oxygen, or the overall length of the compounds. The optimal values for such ligand properties are slightly different for the D₂ and D₃ receptors, even though the binding sites present a very high degree of homology. We explain these differences by the presence of a hydrogen bond network in the D₂ receptor which is absent in the D₃ receptor and limits the dimensions of the binding pocket, causing residues in helix 7 to become less accessible. The implications of these results for the design of more potent and selective benzolactam derivatives are presented and discussed.     

Scaffold Hopping with Virtual Screening from IP3 to a Drug‐Like Partial Agonist of the Inositol Trisphosphate Receptor

Inositol 1,4,5‐trisphosphate (IP₃) is a universal signalling molecule that releases calcium from stores within cells by activating the IP₃ receptor. Although chemical tools that modulate the IP₃ receptor exist, none is ideal due to trade offs between potency, selectivity and cell permeability, and their chemical properties make them challenging starting points for optimisation. Therefore, to find new leads, we used virtual screening to scaffold hop from IP₃ by using the program ROCS to perform a 3D ligand‐based screen of the ZINC database of purchasable compounds. We then used the program FRED to dock the top‐ranking hits into the IP₃ binding pocket of the receptor. We tested the 12 highest‐scoring hits in a calcium‐release bioassay and identified SI‐9 as a partial agonist. SI‐9 competed with [³H]IP₃ binding, and reduced histamine‐induced calcium signalling in HeLa cells. SI‐9 has a novel 2D scaffold that represents a tractable lead for designing improved IP₃ receptor modulators.     

Similarity‐Based Virtual Screening with a Bayesian Inference Network

An inference network model for molecular similarity searching: The similarity search problem is modeled using inference or evidential reasoning under uncertainty. The inference network model treats similarity searching as an evidential reasoning process in which multiple sources of evidence about compounds and reference structures are combined to estimate resemblance probabilities.

     

The Azulene Framework as a Novel Arene Bioisostere: Design of Potent Dopamine D4 Receptor Ligands Inducing Penile Erection

Blue makes it happen : The non‐uniform charge distribution of the blue colored azulene framework is highly suitable for the bioisosteric replacement of bicyclic heteroarene moieties. Showing an analogous binding mode as heterocyclic dopamine D4 receptor‐selective lead compounds, the induction of penile erection in rats over a greater range of doses indicates a putative advantage of the rationally developed azulene derivative 2 b over apomorphine.

     

Discovery of Ligands for the Human Intestinal Di‐/Tripeptide Transporter (hPEPT1) Using a QSAR‐Assisted Virtual Screening Strategy

The discovery of novel ligands for the hPEPT1 transporter is reported. By exploiting a fast and rigorously validated QSAR model in combination with the distance in activity‐centered chemical space (DACCS) approach, a database of commercially available compounds (Sigma–Aldrich) was screened for virtual hits. Twelve compounds were then purchased and characterized in an apical [¹⁴C]Gly‐Sar uptake competition assay. Four compounds displayed affinity in the medium‐to‐high range. A simple benzophenone derivative displayed high affinity with a sub‐millimolar binding constant (K_i=0.24 mM ). The results of this study will serve as starting points for future projects, including the design and synthesis of compound libraries that seek to systematically explore the fundamental requirements for binding and transport by hPEPT1.     

Combined Ligand‐ and Receptor‐Based Virtual Screening Methodology to Identify Structurally Diverse Protein Tyrosine Phosphatase 1B Inhibitors

Protein tyrosine phosphatase 1B (PTP1B) is a potential drug target for diabetes and obesity. However, the design of PTP1B inhibitors that combine potency and bioavailability is a great challenge, and new leads are needed to circumvent this problem. Virtual screening (VS) workflows can be used to find new PTP1B inhibitors with little chemical similarity to existing inhibitors. Unfortunately, previous VS workflows for the identification of PTP1B inhibitors have several limitations, such as a small number of experimentally tested compounds and the low bioactivity of those compounds. We developed a VS workflow capable of identifying 15 structurally diverse PTP1B inhibitors from 20 compounds, the bioactivity of which was tested in vitro. Moreover, we identified two PTP1B inhibitors with the highest bioactivity reported by any VS campaign (i.e., IC₅₀ values of 1.4 and 2.1 μm ), which could be used as new lead compounds.     

Studies of New Fused Benzazepine as Selective Dopamine D3 Receptor Antagonists Using 3D-QSAR, Molecular Docking and Molecular Dynamics

In recent years, great interest has been paid to the development of compounds with high selectivity for central dopamine (DA) D3 receptors, an interesting therapeutic target in the treatment of different neurological disorders. In the present work, based on a dataset of 110 collected benzazepine (BAZ) DA D3 antagonists with diverse kinds of structures, a variety of in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), homology modeling, molecular docking and molecular dynamics (MD) were carried out to reveal the requisite 3D structural features for activity. Our results show that both the receptor-based (Q(2) = 0.603, R(2) (ncv) = 0.829, R(2) (pre) = 0.690, SEE = 0.316, SEP = 0.406) and ligand-based 3D-QSAR models (Q(2) = 0.506, R(2) (ncv) =0.838, R(2) (pre) = 0.794, SEE = 0.316, SEP = 0.296) are reliable with proper predictive capacity. In addition, a combined analysis between the CoMFA, CoMSIA contour maps and MD results with a homology DA receptor model shows that: (1) ring-A, position-2 and R(3) substituent in ring-D are crucial in the design of antagonists with higher activity; (2) more bulky R(1) substituents (at position-2 of ring-A) of antagonists may well fit in the binding pocket; (3) hydrophobicity represented by MlogP is important for building satisfactory QSAR models; (4) key amino acids of the binding pocket are CYS101, ILE105, LEU106, VAL151, PHE175, PHE184, PRO254 and ALA251. To our best knowledge, this work is the first report on 3D-QSAR modeling of the new fused BAZs as DA D3 antagonists. These results might provide information for a better understanding of the mechanism of antagonism and thus be helpful in designing new potent DA D3 antagonists.     

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q² = 0.621, r²_pred = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.     

Predicted Ligands for the Human Urotensin‐II G Protein‐Coupled Receptor with Some Experimental Validation

Human Urotensin‐II (U‐II) is the most potent mammalian vasoconstrictor known. 1 Thus, a U‐II antagonist would be of therapeutic value in a number of cardiovascular disorders. 2 Here, we describe our work on the prediction of the structure of the human U‐II receptor (hUT₂R) using GEnSeMBLE (GPCR Ensemble of Structures in Membrane BiLayer Environment) complete sampling Monte Carlo method. With the validation of our predicted structures, we designed a series of new potential antagonists predicted to bind more strongly than known ligands. Next, we carried out R‐group screening to suggest a new ligand predicted to bind with 7 kcal mol^?1 better energy than 1‐{2‐[4‐(2‐bromobenzyl)‐4‐hydroxypiperidin‐1‐yl]ethyl}‐3‐(thieno[3,2‐b]pyridin‐7‐yl)urea, the designed antagonist predicted to have the highest affinity for the receptor. Some of these predictions were tested experimentally, validating the computational results. Using the pharmacophore generated from the predicted structure for hUT₂R bound to ACT‐058362, we carried out virtual screening based on this binding site. The most potent hit compounds identified contained 2‐(phenoxymethyl)‐1,3,4‐thiadiazole core, with the best derivative exhibiting an IC₅₀ value of 0.581 μM against hUT₂R when tested in vitro. Our efforts identified a new scaffold as a potential new lead structure for the development of novel hUT₂R antagonists, and the computational methods used could find more general applicability to other GPCRs.     

Development of Benzophenone‐Alkyne Bifunctional Sigma Receptor Ligands

Sigma (σ) receptors are unique non‐opioid binding sites that are associated with a broad range of disease states. Sigma‐2 receptors provide a promising target for diagnostic imaging and pharmacological interventions to curb tumor progression. Most recently, the progesterone receptor (PGRMC1, 25 kDa) has been shown to have σ2 receptor‐like binding properties, thus highlighting the need to understand the biological function of an 18 kDa protein that exhibits σ2‐like photoaffinity labeling (denoted here as σ2‐18k) but the amino acid sequence of which is not known. In order to provide new tools for the study of the σ2‐18k protein, we have developed bifunctional σ receptor ligands each bearing a benzophenone photo‐crosslinking moiety and an alkyne group to which an azide‐containing biotin affinity tag can be covalently attached through click chemistry after photo‐crosslinking. Although several compounds showed favorable σ2 binding properties, the highest affinity (2 nM ) and the greatest potency in blocking photolabeling of σ2‐18k by a radioactive photoaffinity ligand was shown by compound 22 . These benzophenone‐alkyne σ receptor ligands might therefore be amenable for studying the σ2‐18k protein through chemical biology approaches. To the best of our knowledge, these compounds represent the first reported benzophenone‐containing clickable σ receptor ligands, which might potentially have broad applications based on the “plugging in” of various tags.