Isomeric Activity Cliffs-A Case Study for Fluorine Substitution of Aminergic G Protein-Coupled Receptor Ligands.

Currently, G protein-coupled receptors (GPCRs) constitute a significant group of membrane-bound receptors representing more than 30% of therapeutic targets. Fluorine is commonly used in designing highly active biological compounds, as evidenced by the steadily increasing number of drugs by the Food and Drug Administration (FDA). Herein, we identified and analyzed 898 target-based F-containing isomeric analog sets for SAR analysis in the ChEMBL database-FiSAR sets active against 33 different aminergic GPCRs comprising a total of 2163 fluorinated (1201 unique) compounds. We found 30 FiSAR sets contain activity cliffs (ACs), defined as pairs of structurally similar compounds showing significant differences in affinity (≥50-fold change), where the change of fluorine position may lead up to a 1300-fold change in potency. The analysis of matched molecular pair (MMP) networks indicated that the fluorination of aromatic rings showed no clear trend toward a positive or negative effect on affinity. Additionally, we propose an in silico workflow (including induced-fit docking, molecular dynamics, quantum polarized ligand docking, and binding free energy calculations based on the Generalized-Born Surface-Area (GBSA) model) to score the fluorine positions in the molecule.

Molecularly Imprinted Hydrogels Selective to Ribavirin as New Drug Delivery Systems to Improve Efficiency of Antiviral Nucleoside Analogue: A Proof-of-Concept Study with Influenza A Virus.

This study describes the synthesis and evaluation of different imprinted hydrogels using ribavirin as template molecule. Ribavirin serves as a model molecule because it possesses a broad-spectrum antiviral effect against RNA viruses, which are expected as emerging viruses. The choice of monomers enables to stabilize the pre-polymerization complex and to synthesize biocompatible polymers. Predictive studies as well as experimental works conclude similar results on best ribavirin:monomers ratios. Thus, materials exhibit high selective cavities toward ribavirin. These affinities allow to show release profiles drastically different from the non-imprinted ones at two temperatures. The imprinted materials show a sustained profile able to release antiviral for more than 24 h. The hydrogels obtained are biocompatible with model cells retained, human lung epithelial BEAS-2B cells. Cell viability is excellent and pro-inflammatory response is insignificant when imprinted polymers are incubated with cells. Finally, viral tests carried out on Influenza A infected lung cells show that imprinted delivery systems delivering 1 to 3 µg of antiviral have the same efficiency as a medium containing 30 µg mL-1 of active agent. As a very interesting result, the molecularly imprinted polymers as drug delivery systems allow to increase the local concentration of antiviral, to improve their delivery when its bioavailability is low.

Pharmacoprint: A Combination of a Pharmacophore Fingerprint and Artificial Intelligence as a Tool for Computer-Aided Drug Design.

Structural fingerprints and pharmacophore modeling are methodologies that have been used for at least 2 decades in various fields of cheminformatics, from similarity searching to machine learning (ML). Advances in in silico techniques consequently led to combining both these methodologies into a new approach known as the pharmacophore fingerprint. Herein, we propose a high-resolution, pharmacophore fingerprint called Pharmacoprint that encodes the presence, types, and relationships between pharmacophore features of a molecule. Pharmacoprint was evaluated in classification experiments by using ML algorithms (logistic regression, support vector machines, linear support vector machines, and neural networks) and outperformed other popular molecular fingerprints (i.e., ECFP4, Estate, MACCS, PubChem, Substructure, Klekota-Roth, CDK, Extended, and GraphOnly) and the ChemAxon pharmacophoric features fingerprint. Pharmacoprint consisted of 39 973 bits; several methods were applied for dimensionality reduction, and the best algorithm not only reduced the length of the bit string but also improved the efficiency of the ML tests. Further optimization allowed us to define the best parameter settings for using Pharmacoprint in discrimination tests and for maximizing statistical parameters. Finally, Pharmacoprint generated for three-dimensional (3D) structures with defined hydrogens as input data was applied to neural networks with a supervised autoencoder for selecting the most important bits and allowed us to maximize the Matthews correlation coefficient up to 0.962. The results show the potential of Pharmacoprint as a new, perspective tool for computer-aided drug design.

Improved HDAC Inhibition, Stronger Cytotoxic Effect and Higher Selectivity against Leukemias and Lymphomas of Novel, Tricyclic Vorinostat Analogues.

Histone deacetylase (HDAC) inhibitors are a class of drugs used in the cancer treatment. Here, we developed a library of 19 analogues of Vorinostat, an HDAC inhibitor used in lymphomas treatment. In Vorinostat, we replaced the hydrophobic phenyl group with various tricyclic 'caps' possessing a central, eight-membered, heterocyclic ring, and investigated the HDAC activity and cytotoxic effect on the cancer and normal cell lines. We found that 3 out of the 19 compounds, based on dibenzo[b,f]azocin-6(5H)-one, 11,12-dihydrodibenzo[b,f]azocin-6(5H)-one, and benzo[b]naphtho[2,3-f][1,5]diazocine-6,14(5H,13H)-dione scaffolds, showed better HDACs inhibition than the referenced Vorinostat. In leukemic cell line MV4-11 and in the lymphoma cell line Daudi, three compounds showed lower IC50 values than Vorinostat. These compounds had higher activity and selectivity against MV4-11 and Daudi cell lines than reference Vorinostat. We also observed a strong correlation between HDACs inhibition and the cytotoxic effect. Cell lines derived from solid tumours: A549 (lung carcinoma) and MCF-7 (breast adenocarcinoma) as well as reference BALB/3T3 (normal murine fibroblasts) were less susceptible to compounds tested. Developed derivatives show improved properties than Vorinostat, thus they could be considered as possible agents for leukemia and lymphoma treatment.

Tuning the activity of known drugs via the introduction of halogen atoms, a case study of SERT ligands - Fluoxetine and fluvoxamine.

The selective serotonin reuptake inhibitors (SSRIs), acting at the serotonin transporter (SERT), are one of the most widely prescribed antidepressant medications. All five approved SSRIs possess either fluorine or chlorine atoms, and there is a limited number of reports describing their analogs with heavier halogens, i.e., bromine and iodine. To elucidate the role of halogen atoms in the binding of SSRIs to SERT, we designed a series of 22 fluoxetine and fluvoxamine analogs substituted with fluorine, chlorine, bromine, and iodine atoms, differently arranged on the phenyl ring. The obtained biological activity data, supported by a thorough in silico binding mode analysis, allowed the identification of two partners for halogen bond interactions: the backbone carbonyl oxygen atoms of E493 and T497. Additionally, compounds with heavier halogen atoms were found to bind with the SERT via a distinctly different binding mode, a result not presented elsewhere. The subsequent analysis of the prepared XSAR sets showed that E493 and T497 participated in the largest number of formed halogen bonds. The XSAR library analysis led to the synthesis of two of the most active compounds (3,4-diCl-fluoxetine 42, SERT Ki = 5 nM and 3,4-diCl-fluvoxamine 46, SERT Ki = 9 nM, fluoxetine SERT Ki = 31 nM, fluvoxamine SERT Ki = 458 nM). We present an example of the successful use of a rational methodology to analyze binding and design more active compounds by halogen atom introduction. 'XSAR library analysis', a new tool in medicinal chemistry, was instrumental in identifying optimal halogen atom substitution.

Design, synthesis and biological evaluation of 2-substituted-6-[(4-substituted-1-piperidyl)methyl]-1H-benzimidazoles as inhibitors of ebola virus infection.

Novel 2-substituted-6-[(4-substituted-1-piperidyl)methyl]-1H-benzimidazoles were designed and synthesized as Ebola virus inhibitors. The proposed structures of the new prepared benzimidazole-piperidine hybrids were confirmed based on their spectral data and CHN analyses. The target compounds were screened in vitro for their anti-Ebola activity. Among tested molecules, compounds 26a (EC50=0.93 µM, SI = 10) and 25a (EC50=0.64 µM, SI = 20) were as potent as and more selective than Toremifene reference drug (EC50 = 0.38 µM, SI = 7) against cell line. Data suggests that the mechanism by which 25a and 26a block EBOV infection is through the inhibition of viral entry at the level of NPC1. Furthermore, a docking study revealed that several of the NPC1 amino acids that participate in binding to GP are involved in the binding of the most active compounds 25a and 26a. Finally, in silico ADME prediction indicates that 26a is an idealy drug-like candidate. Our results could enable the development of small molecule drug capable of inhibiting Ebola virus, especially at the viral entry step.

Rationally designed N-phenylsulfonylindoles as a tool for the analysis of the non-basic 5-HT6R ligands binding mode.

Among all of the monoaminergic receptors, the 5-HT6R has the highest number of non-basic ligands (approximately 5% of compounds stored in 25th version of ChEMBL database have the strongest basic pKa below 5, calculated using the Instant JChem calculator plugin). These compounds, when devoid of a basic nitrogen, exhibit high affinity and remarkable selectivity. Despite a decade of research, no clues have been given for explanation of such an intriguing phenomenon. Here, a series of analogs of four known 5-HT6R ligands, has been rationally designed to approach this issue. For each of the synthesized 42 compounds, a binding affinity for 5-HT6R has been measured, together with a selectivity profile against 5-HT1AR, 5-HT2AR, 5-HT7R and D2R. Performed induced fit docking and molecular dynamics experiments revealed that no particular interaction was responsible for the activity of non-basic compounds. In fact, a plain N-phenylsulfonylindole (1e) was found to possess a moderate (5-HT6R, Ki = 159 nM) affinity. No other monoaminergic receptor has as simple and selective ligand as this one. Thus, it is stated that it binds to the receptor solely based on its conformation and as such, possesses a minimum amount of features, required for binding. Also, any functional group able to form an additional interaction with the receptor increase the binding affinity, like in the case of two highly active non-basic compounds 3e and 5g (5-HT6R, Ki = 65 nM and 38 nM, respectively).

Virtual screening-driven discovery of dual 5-HT6/5-HT2A receptor ligands with pro-cognitive properties.

A virtual screening campaign aimed at finding structurally new compounds active at 5-HT6R provided a set of candidates. Among those, one structure, 4-(5-{[(2-{5-fluoro-1H-pyrrolo[2,3-b]pyridin-3-yl}ethyl)amino]methyl}furan-2-yl)phenol (1, 5-HT6R Ki = 91 nM), was selected as a hit for further optimization. As expected, the chemical scaffold of selected compound was significantly different from all the serotonin receptor ligands published to date. Synthetic efforts, supported by molecular modelling, provided 43 compounds representing different substitution patterns. The derivative 42, 4-(5-{[(2-{5-fluoro-1H-pyrrolo[2,3-b]pyridin-3-yl}ethyl)amino]methyl}furan-2-yl)phenol (5-HT6R Ki = 25, 5-HT2AR Ki = 32 nM), was selected as a lead and showed a good brain/plasma concentration profile, and it reversed phencyclidine-induced memory impairment. Considering the unique activity profile, the obtained series might be a good starting point for the development of a novel antipsychotic or antidepressant with pro-cognitive properties.

In Silico Methods for the Discovery of Orthosteric GABAB Receptor Compounds.

The GABAB receptor (GABAB-R) is a heterodimeric class C G protein-coupled receptor comprised of the GABAB1a/b and GABAB2 subunits. The endogenous orthosteric agonist γ-amino-butyric acid (GABA) binds within the extracellular Venus flytrap (VFT) domain of the GABAB1a/b subunit. The receptor is associated with numerous neurological and neuropsychiatric disorders including learning and memory deficits, depression and anxiety, addiction and epilepsy, and is an interesting target for new drug development. Ligand- and structure-based virtual screening (VS) are used to identify hits in preclinical drug discovery. In the present study, we have evaluated classical ligand-based in silico methods, fingerprinting and pharmacophore mapping and structure-based in silico methods, structure-based pharmacophores, docking and scoring, and linear interaction approximation (LIA) for their aptitude to identify orthosteric GABAB-R compounds. Our results show that the limited number of active compounds and their high structural similarity complicate the use of ligand-based methods. However, by combining ligand-based methods with different structure-based methods active compounds were identified in front of DUDE-E decoys and the number of false positives was reduced, indicating that novel orthosteric GABAB-R compounds may be identified by a combination of ligand-based and structure-based in silico methods.

Selective inhibition of human cathepsin S by 2,4,6-trisubstituted 1,3,5-triazine analogs.

We report herein the synthesis and biological evaluation of a new series of 2,4,6-trisubstituted 1,3,5-triazines as reversible inhibitors of human cysteine cathepsins. The desired products bearing morpholine and N-Boc piperidine, respectively, were obtained in three to four steps from commercially available trichlorotriazine. Seventeen hitherto unknown compounds were evaluated in vitro against various cathepsins for their inhibitory properties. Among them, compound 7c (4-(morpholin-4-yl)-6-[4-(trifluoromethoxy)anilino]-1,3,5-triazine-2-carbonitrile) was identified as the most potent and selective inhibitor of cathepsin S (Ki  =  2  ±â€¯â€¯0.3 nM). Also 7c impaired the autocatalytic maturation of procathepsin S. Molecular docking studies support that 7c bound within the active site of cathepsin S, by interacting with Gly23, Cys25 and Trp26 (S1 subsite), with Asn67, Gly69 and Phe70 (S2 subsite) and with Gln19 (S1' pocket).

The effect of the intramolecular C-H⋯O interactions on the conformational preferences of bis-arylsulfones - 5-HT6 receptor antagonists and beyond.

The development of compounds with enhanced activity and selectivity by a conserved spatial orientation of the pharmacophore elements has a long history in medicinal chemistry. Rigidified compounds are an example of this concept. However, the intramolecular interactions were seldom used as a basis for conformational restraints. Here, we show the weak intramolecular interactions that contribute to the relatively well-conserved geometry of N1-arylsulfonyl indole derivatives. The structure analysis along with quantum mechanics calculations revealed a crucial impact of the sulfonyl group on the compound geometry. The weak intramolecular C-H⋯O interaction stabilizes the mutual "facing" orientation of two aromatic fragments. These findings extend the pharmacological interpretation of the sulfonyl group role from the double hydrogen bond acceptor to the conformational scaffold based on intramolecular forces. This feature has, to date, been omitted in in silico drug discovery. Our results should increase the awareness of researchers to consider the conformational preference when designing new compounds or improving computational methods.

Soloxolone methyl inhibits influenza virus replication and reduces virus-induced lung inflammation.

Highly pathogenic influenza viruses pose a serious public health threat to humans. Although vaccines are available, new antivirals are needed to efficiently control disease progression and virus transmission due to the emergence of drug-resistant viral strains. In this study, we describe the anti-viral properties of Soloxolone methyl (SM) (methyl 2-cyano-3,12-dioxo-18ßH-olean-9(11),1(2)-dien-30-oate, a chemical derivative of glycyrrhetinic acid) against the flu virus. Anti-flu efficacy studies revealed that SM exhibits antiviral activity against the H1N1 influenza A virus in a dose-dependent manner causing a more than 10-fold decrease in virus titer and a reduction in the expression of NP and M2 viral proteins. In a time-of-addition study, SM was found to act at an early stage of infection to exhibit an inhibitory effect on both the attachment step and virus uptake into cells. Also, in infected cells SM downregulates the expression of the inflammatory cytokines IL-6 and TNF-α. In infected mice, SM administered intranasally prior to and after infection significantly decreases virus titers in the lung and prevents post-challenge pneumonia. Together, these results suggest that Soloxolone methyl might serve as an effective therapeutic agent to manage influenza outbreaks and virus-associated complications, and further preclinical and clinical investigation may be warranted.

Pyrano[2,3,4-cd]indole as a Scaffold for Selective Nonbasic 5-HT6R Ligands.

In this letter, we report the synthesis of a pyrano[2,3,4-cd]indole chemical scaffold designed through a tandem bioisostere generation/virtual screening protocol in search of 5-HT6R ligands. The discovered chemical scaffold resulted in the design of highly active basic and nonbasic 5-HT6R ligands (5-HT6R Ki = 1 nM for basic compound 6b and 5-HT6R Ki = 4 nM for its neutral analog 7b). Additionally, molecular modeling suggested that the hydroxyl group of nonbasic ligands 7a-7d forms hydrogen bonds with aspartic acid D3×32 or D7.36×35.

Ligand-guided homology modelling of the GABAB2 subunit of the GABAB receptor.

γ-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the central nervous system, and disturbances in the GABAergic system have been implicated in numerous neurological and neuropsychiatric diseases. The GABAB receptor is a heterodimeric class C G protein-coupled receptor (GPCR) consisting of GABAB1a/b and GABAB2 subunits. Two GABAB receptor ligand binding sites have been described, namely the orthosteric GABA binding site located in the extracellular GABAB1 Venus fly trap domain and the allosteric binding site found in the GABAB2 transmembrane domain. To date, the only experimentally solved three-dimensional structures of the GABAB receptor are of the Venus fly trap domain. GABAB receptor allosteric modulators, however, show great therapeutic potential, and elucidating the structure of the GABAB2 transmembrane domain may lead to development of novel drugs and increased understanding of the allosteric mechanism of action. Despite the lack of x-ray crystal structures of the GABAB2 transmembrane domain, multiple crystal structures belonging to other classes of GPCRs than class A have been released within the last years. More closely related template structures are now available for homology modelling of the GABAB receptor. Here, multiple homology models of the GABAB2 subunit of the GABAB receptor have been constructed using templates from class A, B and C GPCRs, and docking of five clusters of positive allosteric modulators and decoys has been undertaken to select models that enrich the active compounds. Using this ligand-guided approach, eight GABAB2 homology models have been chosen as possible structural representatives of the transmembrane domain of the GABAB2 subunit. To the best of our knowledge, the present study is the first to describe homology modelling of the transmembrane domain of the GABAB2 subunit and the docking of positive allosteric modulators in the receptor.

Practical application of the Average Information Content Maximization (AIC-MAX) algorithm: selection of the most important structural features for serotonin receptor ligands.

The Average Information Content Maximization algorithm (AIC-MAX) based on mutual information maximization was recently introduced to select the most discriminatory features. Here, this methodology was applied to select the most significant bits from the Klekota-Roth fingerprint for serotonin receptors ligands as well as to select the most important features for distinguishing ligands with activity for one receptor versus another. The interpretation of selected bits and machine-learning experiments performed using the reduced interpretations outperformed the raw fingerprints and indicated the most important structural features of the analyzed ligands in terms of activity and selectivity. Moreover, the AIC-MAX methodology applied here for serotonin receptor ligands can also be applied to other target classes.

From Homology Models to a Set of Predictive Binding Pockets-a 5-HT1A Receptor Case Study.

Despite its remarkable importance in the arena of drug design, serotonin 1A receptor (5-HT1A) has been elusive to the X-ray crystallography community. This lack of direct structural information not only hampers our knowledge regarding the binding modes of many popular ligands (including the endogenous neurotransmitter-serotonin), but also limits the search for more potent compounds. In this paper we shed new light on the 3D pharmacological properties of the 5-HT1A receptor by using a ligand-guided approach (ALiBERO) grounded in the Internal Coordinate Mechanics (ICM) docking platform. Starting from a homology template and set of known actives, the method introduces receptor flexibility via Normal Mode Analysis and Monte Carlo sampling, to generate a subset of pockets that display enriched discrimination of actives from inactives in retrospective docking. Here, we thoroughly investigated the repercussions of using different protein templates and the effect of compound selection on screening performance. Finally, the best resulting protein models were applied prospectively in a large virtual screening campaign, in which two new active compounds were identified that were chemically distinct from those described in the literature.

Straightforward synthesis of 2,4,6-trisubstituted 1,3,5-triazine compounds targeting cysteine cathepsins K and S.

The synthesis and evaluation against various cysteine cathepsins with endopeptidase activity, of two new families of hitherto unknown 1,3,5-triazines, substituted by a nitrile function and either a cyclohexylamine moiety (5-like) or a piperazine moiety (9-like) are described. The structure-activity relationship was discussed; from 16 synthesized novel compounds, 9h was the most active and selectively inhibitor of Cat K (IC50 = 28 nM) and Cat S (IC50 = 23 nM). Molecular docking of 9h to X-ray crystal structure of cathepsins K and S confirmed a common binding mode with a crucial covalent bond with Cys25. We observed for 9h that p-trifluorophenyl group is located in S2 pocket and possess hydrophobic interactions with Tyr67 and Met68. Triazine and piperazine moieties are located in S'1 pocket and interact with Gly23, Cys63, Gly64 and Gly65. Altogether, these results indicate that the new analogs can make them effective agents against some viruses for which the glycoprotein cleavage is mediated by an array of proteases.

Rational design in search for 5-phenylhydantoin selective 5-HT7R antagonists. Molecular modeling, synthesis and biological evaluation.

A series of novel arylpiperazine 5-(4-fluorophenyl)-5-methylhydantoins with 2-hydroxypropyl linker (2-15) was synthesized and evaluated on their affinity towards serotonin 5-HT7 receptor (5-HT7R) in comparison to other closely related GPCRs: serotonin 5-HT1A, and dopamine D2 receptors. The functional activity studied through the measurement of 5-HT7R-mediated cyclic AMP production in Human Embryonic Kidney 293 cells (HEK293) stably expressing human 5-HT7 proved their antagonistic properties. The lead structure was also examined in the preliminary metabolic stability study using human liver microsomes (HMLs). The process of selection of candidates for synthesis was supported by a special molecular modeling workflow including combinatorial library generation, docking, and machine learning-based assessment. Additionally, in silico predictions of selectivity over 5-HT1AR and D2R, as well as functional activity were carried out. The newly synthesized compounds were proved to possess a potent affinity for 5-HT7R, similar to that of the lead structure of 5-(4-fluorophenyl)-3-(3-(4-(2-methoxyphenyl)piperazin-1-yl)-2-hydroxypropyl)-5-methylimidazolidine-2,4-dione (1). For several derivatives, significant selectivity both over 5-HT1AR and D2R was found.

Average Information Content Maximization--A New Approach for Fingerprint Hybridization and Reduction.

Fingerprints, bit representations of compound chemical structure, have been widely used in cheminformatics for many years. Although fingerprints with the highest resolution display satisfactory performance in virtual screening campaigns, the presence of a relatively high number of irrelevant bits introduces noise into data and makes their application more time-consuming. In this study, we present a new method of hybrid reduced fingerprint construction, the Average Information Content Maximization algorithm (AIC-Max algorithm), which selects the most informative bits from a collection of fingerprints. This methodology, applied to the ligands of five cognate serotonin receptors (5-HT2A, 5-HT2B, 5-HT2C, 5-HT5A, 5-HT6), proved that 100 bits selected from four non-hashed fingerprints reflect almost all structural information required for a successful in silico discrimination test. A classification experiment indicated that a reduced representation is able to achieve even slightly better performance than the state-of-the-art 10-times-longer fingerprints and in a significantly shorter time.

Ligand-Based Virtual Screening in a Search for Novel Anti-HIV-1 Chemotypes.

In a search for new anti-HIV-1 chemotypes, we developed a multistep ligand-based virtual screening (VS) protocol combining machine learning (ML) methods with the privileged structures (PS) concept. In its learning step, the VS protocol was based on HIV integrase (IN) inhibitors fetched from the ChEMBL database. The performances of various ML methods and PS weighting scheme were evaluated and applied as VS filtering criteria. Finally, a database of 1.5 million commercially available compounds was virtually screened using a multistep ligand-based cascade, and 13 selected unique structures were tested by measuring the inhibition of HIV replication in infected cells. This approach resulted in the discovery of two novel chemotypes with moderate antiretroviral activity, that, together with their topological diversity, make them good candidates as lead structures for future optimization.