Gaucher Disease: A Glance from a Medicinal Chemistry Perspective

Rare diseases are particular pathological conditions affecting a limited number of people and few drugs are known to be effective as therapeutic treatment. Gaucher disease, caused by a deficiency of the lysosomal enzyme glucocerebrosidase, belongs to this class of disorders, and it is considered the most common among the Lysosomal Storage Diseases. The two main therapeutic approaches are the Enzyme Replacement Therapy (ERT) and the Substrate Reduction Therapy (SRT). ERT, consisting in replacing the defective enzyme by administering a recombinant enzyme, is effective in alleviating the visceral symptoms, hallmarks of the most common subtype of the disease whereas it has no effects when symptoms involve CNS, since the recombinant protein is unable to significantly cross the Blood Brain Barrier. The SRT strategy involves inhibiting glucosylceramide synthase (GCS), the enzyme responsible for the production of the associated storage molecule. The rational design of new inhibitors of GCS has been hampered by the lack of either the crystal structure of the enzyme or an in-silico model of the active site which could provide important information regarding the interactions of potential inhibitors with the target, but, despite this, interesting results have been obtained and are herein reviewed.

Enzymatic Synthesis and Structural Modeling of Bio-Based Oligoesters as an Approach for the Fast Screening of Marine Biodegradation and Ecotoxicity

Given the widespread use of esters and polyesters in products like cosmetics, fishing nets, lubricants and adhesives, whose specific application(s) may cause their dispersion in open environments, there is a critical need for stringent eco-design criteria based on biodegradability and ecotoxicity evidence. Our approach integrates experimental and computational methods based on short oligomers, offering a screening tool for the rapid identification of sustainable monomers and oligomers, with a special focus on bio-based alternates. We provide insights into the relationships between the chemical structure and properties of bio-based oligomers in terms of biodegradability in marine environments and toxicity in benchmark organisms. The experimental results reveal that the considered aromatic monomers (terephthalic acid and 2,5-furandicarboxylic acid) accumulate under the tested conditions (OECD 306), although some slight biodegradation is observable when the inoculum derives from sites affected by industrial and urban pollution, which suggests that ecosystems adapt to non-natural chemical pollutants. While clean seas are more susceptible to toxic chemical buildup, biotic catalytic activities offer promise for plastic pollution mitigation. Without prejudice to the fact that biodegradability inherently signifies a desirable trait in plastic products, nor that it automatically grants them a sustainable "license", this study is intended to facilitate the rational design of new polymers and materials on the basis of specific uses and applications.

MOViDA: Multi-Omics Visible Drug Activity Prediction with a Biologically Informed Neural Network Model

MOTIVATION

The process of drug development is inherently complex, marked by extended intervals from the inception of a pharmaceutical agent to its eventual launch in the market. Additionally, each phase in this process is associated with a significant failure rate, amplifying the inherent challenges of this task. Computational virtual screening powered by machine learning algorithms has emerged as a promising approach for predicting therapeutic efficacy. However, the complex relationships between the features learned by these algorithms can be challenging to decipher.

RESULTS

We have engineered an artificial neural network model designed specifically for predicting drug sensitivity. This model utilizes a biologically informed Visible Neural Network (VNN), thereby enhancing its interpretability. The trained model allows for an in-depth exploration of the biological pathways integral to prediction and the chemical attributes of drugs that impact sensitivity. Our model harnesses multi-omics data derived from an different tumor tissue sources, as well as molecular descriptors that encapsulate the properties of drugs. We extended the model to predict drug synergy, resulting in favorable outcomes while retaining interpretability. Given the imbalanced nature of publicly available drug screening datasets, our model demonstrated superior performance to state-of-the-art visible machine learning algorithms.

Destabilizers of the thymidylate synthase homodimer accelerate its proteasomal degradation and inhibit cancer growth

Drugs that target human thymidylate synthase (hTS), a dimeric enzyme, are widely used in anticancer therapy. However, treatment with classical substrate-site-directed TS inhibitors induces over-expression of this protein and development of drug resistance. We thus pursued an alternative strategy that led us to the discovery of TS-dimer destabilizers. These compounds bind at the monomer-monomer interface and shift the dimerization equilibrium of both the recombinant and the intracellular protein toward the inactive monomers. A structural, spectroscopic, and kinetic investigation has provided evidence and quantitative information on the effects of the interaction of these small molecules with hTS. Focusing on the best among them, E7, we have shown that it inhibits hTS in cancer cells and accelerates its proteasomal degradation, thus causing a decrease in the enzyme intracellular level. E7 also showed a superior anticancer profile to fluorouracil in a mouse model of human pancreatic and ovarian cancer. Thus, over sixty years after the discovery of the first TS prodrug inhibitor, fluorouracil, E7 breaks the link between TS inhibition and enhanced expression in response, providing a strategy to fight drug-resistant cancers.

Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications

Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly desirable for in silico drug discovery and medicinal chemistry applications. In this work, we revised a well‐established molecular mechanics' force field and applied a hybrid quantum mechanics and machine learning approach to parametrize the hydrogen‐bonding (HB) potentials of small molecules, improving this aspect of the molecular description. Approximately 66,000 molecules were chosen from available drug databases and subjected to density functional theory calculations (DFT). For each atom, the molecular electrostatic potential (EP) was extracted and used to derive new HB energy contributions; this was subsequently combined with a fingerprint‐based description of the structural environment via partial least squares modeling, enabling the new potentials to be used for molecules outside of the training set. We demonstrate that parameter prediction for molecules outside of the training set correlates with their DFT‐derived EP, and that there is correlation of the new potentials with hydrogen‐bond acidity and basicity scales. We show the newly derived MIFs vary in strength for various ring substitution in accordance with chemical intuition. Finally, we report that this derived parameter, when extended to non‐HB atoms, can also be used to estimate sites of reaction.

Side-Chain Modified Ergosterol and Stigmasterol Derivatives as Liver X Receptor Agonists

A series of stigmasterol and ergosterol derivatives, characterized by the presence of oxygenated functions at C-22 and/or C-23 positions, were designed as potential liver X receptor (LXR) agonists. The absolute configuration of the newly created chiral centers was definitively assigned for all the corresponding compounds. Among the 16 synthesized compounds, 21, 27, and 28 were found to be selective LXRα agonists, whereas 20, 22, and 25 showed good selectivity for the LXRβ isoform. In particular, 25 showed the same degree of potency as 22R-HC (3) at LXRβ, while it was virtually inactive at LXRα (EC₅₀ = 14.51 μM). Interestingly, 13, 19, 20, and 25 showed to be LXR target gene-selective modulators, by strongly inducing the expression of ABCA1, while poorly or not activating the lipogenic genes SREBP1 and SCD1 or FASN, respectively.

Understanding Oxadiazolothiazinone Biological Properties: Negative Inotropic Activity versus Cytochrome P450-Mediated Metabolism

We present a series of oxadiazolothiazinones, selective inotropic agents on isolated cardiac tissues, devoid of chronotropy and vasorelaxant activity. Functional and binding data for the precursor of the series (compound 1) let us hypothesize LTCC blocking activity and the existence of a recognition site specific for this scaffold. We synthesized and tested 22 new derivatives: introducing a para-methoxyphenyl at C-8 led to compound 12 (EC50 = 0.022 μM), twice as potent as its para-bromo analogue (1). For 10 analogues, we extended the characterization of the biological properties by including the assessment of metabolic stability in human liver microsomes and cytochrome P450 inhibition potential. We observed that the methoxy group led to active compounds with low metabolic stability and high CYP inhibition, whereas the protective effect of bromine resulted in enhanced metabolic stability and reduced CYP inhibition. Thus, we identified two para-bromo benzothiazino-analogues as candidates for further studies.

Discovery of Novel, Potent, and Specific Cell-Death Inducers in the Jurkat Acute Lymphoblastic Leukemia Cell Line

The limited clinical efficacy of many cancer therapeutics has initiated intense research efforts toward the discovery of novel chemical entities in this field. In this study, 31 hit candidates were selected from nearly 800,000 database compounds in a ligand-based virtual screening campaign. In turn, three of these hits were found to have (sub)micromolar potencies in proliferation assays with the Jurkat acute lymphatic leukemic cell line. In this assay, the three hits were found to exhibit higher potency than clinically tested cell-death inducers (GDC-0152, AT-406, and birinapant). Importantly, antiproliferative activity toward non-cancer peripheral blood mononuclear cells (PBMCs) was found to be marginal. Further biological characterization demonstrated the cell-death-inducing properties of these compounds. Biological testing of hit congeners excluded a nonspecific, toxic effect of the novel structures. Altogether, these findings may have profound relevance for the development of clinical candidates in tumor therapy.

Synthesis and L-type calcium channel blocking activity of new chiral oxadiazolothiazinones

Oxadiazolo[3,4-c][1,4]thiazin-3-ones are cardiovascular agents that block L-type calcium channels. Previous data of cardiac and vasorelaxant activity on guinea-pig for several derivatives indicated the two positions ortho to the thiazine's sulphur as crucial for modulating the activity; but these positions are likely susceptible to metabolic biotransformations, as indicated by in silico predictions. We designed new derivatives, and obtained three negative inotropic agents with EC50 in the low nanomolar range, more potent than all the precursors published so far. In particular, benzocondensation at the thiazine ring led to 3a (EC50 = 0.013 μM) and 3b (EC50 = 0.006 μM). Besides negative inotropy, we also observed relaxant activity on nonvascular muscle in the micromolar range. We resolved the new derivatives by chiral chromatography, and determined their absolute configuration by comparing experimental and calculated chiroptical properties (VCD, ECD and ORD): they hold the same absolute configuration-optical rotation relationship, (S)-(+)/(R)-(-). Both cardiac and nonvascular activity are majorly or mostly retained in the R-form for all the compounds, but for the nonvascular activity we observed a strong stereoselectivity for 3a, with the R-form in the nanomolar range (IC50 = 0.020 μM) and 259-fold more potent than the S-one.

Playing with opening and closing of heterocycles: using the cusmano-ruccia reaction to develop a novel class of oxadiazolothiazinones, active as calcium channel modulators and P-glycoprotein inhibitors

As a result of the ring-into-ring conversion of nitrosoimidazole derivatives, we obtained a molecular scaffold that, when properly decorated, is able to decrease inotropy by blocking L-type calcium channels. Previously, we used this scaffold to develop a quantitative structure-activity relationship (QSAR) model, and we used the most potent oxadiazolothiazinone as a template for ligand-based virtual screening. Here, we enlarge the diversity of chemical decorations, present the synthesis and in vitro data for 11 new derivatives, and develop a new 3D-QSAR model with recent in silico techniques. We observed a key role played by the oxadiazolone moiety: given the presence of positively charged calcium ions in the transmembrane channel protein, we hypothesize the formation of a ternary complex between the oxadiazolothiazinone, the Ca2+ ion and the protein. We have supported this hypothesis by means of pharmacophore generation and through the docking of the pharmacophore into a homology model of the protein. We also studied with docking experiments the interaction with a homology model of P-glycoprotein, which is inhibited by this series of molecules, and provided further evidence toward the relevance of this scaffold in biological interactions.

Modelling cytochromes P450 binding modes to predict P450 inhibition, metabolic stability and isoform selectivity

The cytochromes P450 (P450) superfamily is a diverse group of enzymes involved in the metabolism of xenobiotics, whose orientations within the catalytic site can lead to different binding modes, namely productive, nonproductive, and inhibitory. This article collects the most recent approaches that individually study P450- ligand interactions, including a novel in silico technology, developed in the framework of the Human Cytochrome P450 Consortium initiative, that provides reliable in silico predictions of P450 inhibition, metabolic stability and isoform selectivity.

Targeting cystalysin, a virulence factor of treponema denticola-supported periodontitis

Cystalysin from Treponema denticola is a pyridoxal 5'-phosphate dependent lyase that catalyzes the formation of pyruvate, ammonia, and sulfide from cysteine. It is a virulence factor in adult periodontitis because its reaction contributes to hemolysis, which sustains the pathogen. Therefore, it was proposed as a potential antimicrobial target. To identify specific inhibitors by structure-based in silico methods, we first validated the crystal structure of cystalysin as a reliable starting point for the design of ligands. By using single-crystal absorption microspectrophotometry, we found that the enzyme in the crystalline state, with respect to that in solution, exhibits: 1) the same absorption spectra for the catalytic intermediates, 2) a close pKa value for the residue controlling the keto enamine ionization, and 3) similar reactivity with glycine, L-serine, L-methionine, and the nonspecific irreversible inhibitor aminoethoxyvinylglycine. Next, we screened in silico a library of 9357 compounds with the Fingerprints for Ligands and Proteins (FLAP) software, by using the three-dimensional structure of cystalysin as a template. From the library, 17 compounds were selected and experimentally evaluated by enzyme assays and spectroscopic methods. Two compounds were found to competitively inhibit recombinant T. denticola cystalysin, with inhibition constant (Ki ) values of 25 and 37 μM. One of them exhibited a minimum inhibitory concentration (MIC) value of 64 μg mL(-1) on Moraxella catarrhalis ATCC 23246, which proves its ability to cross bacterial membranes.

Large, chemically diverse dataset of logP measurements for benchmarking studies

Lipophilicity is a crucial parameter in drug development since it impacts both ADME properties and target affinity of drug candidates. In early drug discovery stage, accurate tools for logP prediction are highly desired. Many calculation methods were developed to aid pharmaceutical scientists in drug research; however almost all suffer from insufficient accuracy and variation of performance in several regions of the chemical space associated with new chemical entities. The low predictive power of existing software packages can be explained by limited availability and/or variable quality of experimental logP values associated with training set used, which stem from various protocols and poorly cover chemical space. In this study, a dataset of 1000 diverse test compounds out of 4.5 million was generated; logP values of 759 purchasable compounds (46% non-ionizable, 30% basic, 17% acidic, 0.5% zwitterionic and 6.5% ampholytes) from this selected set were experimentally determined by UHPLC followed by UV detection or MS detection when necessary. Finally, a data collection of 707 validated logP values ranging from 0.30 to 7.50 is now available for benchmarking of existing and development of new approaches to predict octanol/water partition coefficients of chemical compounds.

Absolute configuration and biological profile of two thiazinooxadiazol-3-ones with L-type calcium channel activity: a study of the structural effects

In the framework of our interest in racemic thiazinooxadiazol-3-ones we determined the absolute configuration and the biological activity as L-type calcium channel blockers of two compounds that differ in the length of the acetal chain, which could affect the pharmacological profile. We observed an interesting inversion of the stereoselectivity, with the activity residing on the R-form for a short chain compound (n = 1) and on the S-form for a long chain one (n = 12). The length of the linear acetal chain appears to be able to invert the stereoselectivity of such a class of compounds, and in silico simulations suggested that this different behaviour might be explained by different hydrophilic and hydrophobic interactions with the binding site.

QSAR modeling and data mining link Torsades de Pointes risk to the interplay of extent of metabolism, active transport, and HERG liability

We collected 1173 hERG patch clamp (PC) data (IC50) from the literature to derive twelve classification models for hERG inhibition, covering a large variety of chemical descriptors and classification algorithms. Models were generated using 545 molecules and validated through 258 external molecules tested in PC experiments. We also evaluated the suitability of the best models to predict the activity of 26 proprietary compounds tested in radioligand binding displacement (RBD). Results proved the necessity to use multiple validation sets for a true estimation of model accuracy and demonstrated that using various descriptors and algorithms improves the performance of ligand-based models. Intriguingly, one of the most accurate models uncovered an unexpected link between extent of metabolism and hERG liability. This hypothesis was fairly reinforced by using the Biopharmaceutics Drug Disposition Classification System (BDDCS) that recognized 94% of the hERG inhibitors as extensively metabolized in vivo. Data mining suggested that high Torsades de Pointes (TdP) risk results from an interplay of hERG inhibition, extent of metabolism, active transport, and possibly solubility. Overall, these new findings might improve both the decision making skills of pharmaceutical scientists to mitigate hERG liability during the drug discovery process and the TdP risk assessment during drug development.

Ligand Promiscuity between the Efflux Pumps Human P-Glycoprotein and S. aureus NorA

Thirty-two diverse compounds were evaluated for their ability to inhibit both Pgp-mediated efflux in mouse T-lymphoma L5178 MDR1 and NorA-mediated efflux in S. aureus SA-1199B. Only four compounds were strong inhibitors of both efflux pumps. Three compounds were found to inhibit Pgp exclusively and strongly, while seven compounds inhibited only NorA. These results demonstrate that Pgp and NorA inhibitors do not necessarily overlap, opening the way to safer therapeutic use of effective NorA inhibitors.

The flavonoid scaffold as a template for the design of modulators of the vascular Ca(v) 1.2 channels

BACKGROUND AND PURPOSE

Previous studies have pointed to the plant flavonoids myricetin and quercetin as two structurally related stimulators of vascular Ca(v) 1.2 channel current (I(Ca1.2) ). Here we have tested the proposition that the flavonoid structure confers the ability to modulate Ca(v) 1.2 channels.

EXPERIMENTAL APPROACH

Twenty-four flavonoids were analysed for their effects on I(Ca1.2) in rat tail artery myocytes, using the whole-cell patch-clamp method.

KEY RESULTS

Most of the flavonoids stimulated or inhibited I(Ca1.2) in a concentration- and voltage-dependent manner with EC(50) values ranging between 4.4 µM (kaempferol) and 16.0 µM (myricetin) for the stimulators and IC(50) values between 13.4 µM (galangin) and 100 µM [(±)-naringenin] for the inhibitors. Key structural requirements for I(Ca1.2) stimulatory activity were the double bond between C2 and C3 and the hydroxylation pattern on the flavonoid scaffold, the latter also determining the molecular charge, as shown by molecular modelling techniques. Absence of OH groups in the B ring was key in I(Ca1.2) inhibition. The functional interaction between quercetin and either the stimulator myricetin or the antagonists resokaempferol, crysin, genistein, and 5,7,2'-trihydroxyflavone revealed that quercetin expressed the highest apparent affinity, in the low µM range, for Ca(v) 1.2 channels. Neither protein tyrosine kinase nor protein kinase Cα were involved in quercetin-induced stimulation of I(Ca1.2).

CONCLUSIONS AND IMPLICATIONS

Quercetin-like plant flavonoids were active on vascular Ca(v)1.2 channels. Thus, the flavonoid scaffold may be a template for the design of novel modulators of vascular smooth muscle Ca(v)1.2 channels, valuable for the treatment of hypertension and stroke.

A novel approach for predicting P-glycoprotein (ABCB1) inhibition using molecular interaction fields

P-glycoprotein (Pgp or ABCB1) is an ABC transporter protein involved in intestinal absorption, drug metabolism, and brain penetration, and its inhibition can seriously alter a drug's bioavailability and safety. In addition, inhibitors of Pgp can be used to overcome multidrug resistance. Given this dual purpose, reliable in silico procedures to predict Pgp inhibition are of great interest. A large and accurate literature collection yielded more than 1200 structures; a model was then constructed using various molecular interaction field-based technologies, considering pharmacophoric features and those physicochemical properties related to membrane partitioning. High accuracy was demonstrated internally with two different validation sets and, moreover, using a number of molecules, for which Pgp inhibition was not experimentally available but was evaluated in-house. All of the validations confirmed the robustness of the model and its suitability to help medicinal chemists in drug discovery. The information derived from the model was rationalized as a pharmacophore for competitive Pgp inhibition.

FLAP: GRID molecular interaction fields in virtual screening. validation using the DUD data set

The performance of FLAP (Fingerprints for Ligands and Proteins) in virtual screening is assessed using a subset of the DUD (Directory of Useful Decoys) benchmarking data set containing 13 targets each with more than 15 different chemotype classes. A variety of ligand and receptor-based virtual screening approaches are examined, using combinations of individual templates 2D structures of known actives, a cocrystallized ligand, a receptor structure, or a cocrystallized ligand-biased receptor structure. We examine several data fusion approaches to combine the results of the individual virtual screens. In doing so, we show that excellent chemotype enrichment is achieved in both single target ligand-based and receptor-based approaches, of approximately 17-fold over random on average at a false positive rate of 1%. We also show that using as much starting knowledge as possible improves chemotype enrichment, and that data fusion using Pareto ranking is an effective method to do this giving up to 50% improvement in enrichment over the single methods. Finally we show that if inactivity or decoy data is incorporated, automatically training the scoring function in FLAP improves recovery still further, with almost 2-fold improvement over the enrichments shown by the single methods. The results clearly demonstrate the utility of FLAP for virtual screening when either a limited or wide range of prior knowledge is available.

Discovery of novel inhibitors of the NorA multidrug transporter of Staphylococcus aureus

Four novel inhibitors of the NorA efflux pump of Staphylococcus aureus, discovered through a virtual screening process, are reported. The four compounds belong to different chemical classes and were tested for their in vitro ability to block the efflux of a well-known NorA substrate, as well as for their ability to potentiate the effect of ciprofloxacin (CPX) on several strains of S. aureus, including a NorA overexpressing strain. Additionally, the MIC values of each of the compounds individually are reported. A structure-activity relationship study was also performed on these novel chemotypes, revealing three new compounds that are also potent NorA inhibitors. The virtual screening procedure employed FLAP, a new methodology based on GRID force field descriptors.

From 6-aminoquinolone antibacterials to 6-amino-7-thiopyranopyridinylquinolone ethyl esters as inhibitors of Staphylococcus aureus multidrug efflux pumps

The thiopyranopyridine moiety was synthesized as a new heterocyclic base to be inserted at the C-7 position of selected quinolone nuclei followed by a determination of antibacterial activity against strains of Staphylococcus aureus. Selected thiopyranopyridinylquinolones showed significant antimicrobial activity, including strains having mutations in gyrA and grlA as well as other strains overexpressing the NorA multidrug (MDR) efflux pump. Most derivatives did not appear to be NorA substrates. The effect of the thiopyranopyridinyl substituent on making these quinolones poor substrates for NorA was investigated further. Several quinolone ester intermediates, devoid of any intrinsic antibacterial activity, were tested for their abilities to inhibit the activities of NorA (MFS family) and MepA (MATE family) S. aureus MDR efflux pumps. Selected quinolone esters were capable of inhibiting both MDR pumps more efficiently than the reference compound reserpine. Moreover, they also were able to restore, and even enhance, the activity of ciprofloxacin toward some genetically modified resistant S. aureus strains.

Homodimeric enzymes as drug targets

Many enzymes and proteins are regulated by their quaternary structure and/or by their association in homo- and/or hetero-oligomer complexes. Thus, these protein-protein interactions can be good targets for blocking or modulating protein function therapeutically. The large number of oligomeric structures in the Protein Data Bank (http://www.rcsb.org/) reflects growing interest in proteins that function as multimeric complexes. In this review, we consider the particular case of homodimeric enzymes as drug targets. There is intense interest in drugs that inhibit dimerization of a functionally obligate homodimeric enzyme. Because amino acid conservation within enzyme interfaces is often low compared to conservation in active sites, it may be easier to achieve drugs that target protein interfaces selectively and specifically. Two main types of dimerization inhibitors have been developed: peptides or peptidomimetics based on sequences involved in protein-protein interactions, and small molecules that act at hot spots in protein-protein interfaces. Examples include inhibitors of HIV protease and HIV integrase. Studying the mechanisms of action and locating the binding sites of such inhibitors requires different techniques for different proteins. For some enzymes, ligand binding is only detectable in vivo or after unfolding of the complexes. Here, we review the structural features of dimeric enzymes and give examples of inhibition through interference in dimer stability. Several techniques for studying these complex phenomena will be presented.

IAP antagonists: promising candidates for cancer therapy

A promising strategy in cancer therapy aims to promote apoptosis in cancer cells. Targeting inhibitor of apoptosis proteins (IAPs) with small-molecule inhibitors has attracted increasing interest in triggering cancer cell death. It is considered to have great potential for cancer drug discovery because IAPs block apoptosis at the core of the apoptotic machinery and are aberrantly expressed in various tumors. This review focuses on the current development of small-molecule IAP antagonists for cancer therapy.

Transporter-mediated Efflux Influences CNS Side Effects: ABCB1, from Antitarget to Target

We examined the relationship between sedation and orthostatic hypotension, two central side effects and ABCB1 transporter-mediated efflux for a set of 64 launched drugs that are documented as histamine H1 receptor antagonists. This relationship was placed in the context of passive diffusion (estimated using LogP, the octanol/water partition coefficient), receptor affinity, and the adjusted therapeutic daily dose, in order to account for side effect variability. Within this set, CNS permeability was not dependent on passive diffusion, as no significant differences were found for LogP and its pH-corrected equivalent, LogD(74). Sedation and orthostatic hypotension can be explained within the framework of ABCB1-mediated efflux and adjusted dose, while target potency has less influence. ABCB1, an antitarget for anti-cancer agents, acts in fact as a drug target for non-sedating antihistamines. An empirical set of rules, based on the incidence of these two side-effects, target affinity and dose was used to predict efflux effects for a number of drugs. Among them, azelastine and mizolastine are predicted to be effluxed via ABCB1-mediated transport, whereas aripiprazole, clozapine, cyproheptadine, iloperidone, olanzapine, and ziprasidone are likely to be non-effluxed.

Novel TOPP descriptors in 3D-QSAR analysis of apoptosis inducing 4-aryl-4H-chromenes: comparison versus other 2D- and 3D-descriptors

Novel 3D-descriptors using Triplets Of Pharmacophoric Points (TOPP) were evaluated in QSAR-studies on 80 apoptosis-inducing 4-aryl-4H-chromenes. A predictive QSAR model was obtained using PLS, confirmed by means of internal and external validations. Performance of the TOPP approach was compared with that of other 2D- and 3D-descriptors; statistical analysis indicates that TOPP descriptors perform best. A ranking of TOPP>GRIND>BCI 4096=ECFP>FCFP>GRID-GOLPE>>DRAGON>>>MDL 166 was achieved. Finally, in a 'consensus' analysis predictions obtained using the single methods were compared with an average approach using six out of eight methods. The use of the average is statistically superior to the single methods. Beyond it, the use of several methods can help to easily investigate the presence/absence of outliers according to the 'consensus' of the predicted values: agreement among all the methods indicates a precise prediction, whereas large differences between predicted values (for the same compounds by different methods) would demand caution when using such predictions.

Virtual Screening for Novel Openers of Pancreatic KATPChannels

Ligand-based virtual screening approaches were applied to search for new chemotype KCOs activating Kir6.2/SUR1 KATP channels. A total of 65 208 commercially available compounds, extracted from the ZINC archive, served as database for screening. In a first step, pharmacokinetic filtering via VolSurf reduced the initial database to 1913 compounds. Afterward, six molecules were selected as templates for similarity searches: similarity scores, obtained toward these templates, were calculated with the GRIND, FLAP, and TOPP approaches, which differently encode structural information into potential pharmacophores. In this way, we obtained 32 hit candidates, 16 via GRIND and eight each via FLAP and TOPP. For biological testing of the hit candidates, their effects on membrane potentials in HEK 293 cells expressing Kir6.2/SUR1 were studied. GRIND, FLAP, and TOPP all yielded hits, but no method top-ranked all the actives. Thus, parallel application of different approaches probably improves hit detection.

Diltiazem analogues: the last ten years on structure activity relationships

Cardiovascular diseases as hypertension, angina and/or supraventricular arrhythmias are among the most important death causes in the world. For the treatment of heart pathologies, calcium channel entry blockers are very important drugs, owing to their therapeutic versatility. Although few calcium antagonists described until today are structurally related to diltiazem and to the benzothiazepine class, the still high pharmaceutical interest on diltiazem analogues justifies this review. Diltiazem and its first analogues developed in the early '70s became popular in the '80s, and were pharmacologically characterized for a long time. It is in the '90s that several research groups carried out structural variations identifying novel scaffolds for diltiazem-related compounds, with significant calcium antagonist behaviour. Recently, a series of thiazino-oxadiazolone derivatives were identified as potent and selective antagonists for calcium influx into cardiac cells, and they were subsequently used to search for novel chemotypes by means of virtual screening techniques. The resulting hits could open interesting perspectives for the development of drugs to treat cardiovascular diseases. In the present review, an updated collection of diltiazem analogues is reported over the last ten years. The chemical structure and the structure activity relationships will be given, with additional mention to the potential therapeutic applications.

Calcium channel antagonists discovered by a multidisciplinary approach

A multidisciplinary project has led to the discovery of novel, structurally diverse, L-type calcium entry blockers (CEBs). The absolute configuration of a recently reported CEB has been determined by vibrational circular dichroism spectroscopy, to assign the stereospecificity of the ligand-channel interaction. Thereafter, a virtual screening procedure was performed with the aim of identifying novel chemotypes for CEBs, starting from a database of purchasable compounds; 340,000 molecules were screened in silico in order to prioritize structures of interest for bioscreening. As a result, 20 compounds were tested in vitro, and functional and binding assays revealed several hits with promising behavior as CEBs.

Binding studies and GRIND/ALMOND-based 3D QSAR analysis of benzothiazine type K(ATP)-channel openers

For seventeen 1,4-benzothiazine potassium channel openers, we performed binding studies in rat aortic smooth muscle cells and cardiomyocytes, compared their binding affinities with published relaxation data, and derived 3D-QSAR models using GRIND/ALMOND descriptors. Binding affinities in smooth muscle cells range from a pK(D) of 4.76 for compound 3e to 9.10 for compound 4c. Comparison of data for smooth muscle relaxation and binding shows preferentially higher pEC(50)s for the former. In cardiomyocytes, pK(D) values range from 4.21 for 3e to 8.16 for 4c. 3D-QSAR analysis resulted in PLS models of two latent variables for all three activities with determination coefficients of 0.97 (smooth muscle relaxation) and 0.94 (smooth muscle cells- and cardiomyocytes-binding). Internal validation yielded q(2) values of 0.69, 0.66, and 0.64. The carbonyl on the N-4 substituent, the hydrogen bond acceptor at C-6, the five-membered ring at N-4, and the gem-dimethyls mainly guide strong binding and strong smooth muscle relaxation.

MetaSite: Understanding Metabolism in Human Cytochromes from the Perspective of the Chemist

Identification of metabolic biotransformations can significantly affect the drug discovery process. Since bioavailability, activity, toxicity, distribution, and final elimination all depend on metabolic biotransformations, it would be extremely advantageous if this information could be produced early in the discovery phase. Once obtained, this information can help chemists to judge whether a potential candidate should be eliminated from the pipeline or modified to improve chemical stability or safety of new compounds. The use of in silico methods to predict the site of metabolism in phase I cytochrome-mediated reactions is a starting point in any metabolic pathway prediction. This paper presents a new method, specifically designed for chemists, that provides the cytochrome involved and the site of metabolism for any human cytochrome P450 (CYP) mediated reaction acting on new substrates. The methodology can be applied automatically to all the cytochromes for which 3D structure is known and can be used by chemists to detect positions that should be protected in order to avoid metabolic degradation or to check the suitability of a new scaffold or prodrug. The fully automated procedure is also a valuable new tool in early ADME-Tox assays (absorption, distribution, metabolism, and excretion toxicity assays), where drug safety and metabolic profile patterns must be evaluated as soon, and as early, as possible.

Comparison of Ligand-Based and Structure-Based 3D-QSAR Approaches: A Case Study on (Aryl-)Bridged 2-Aminobenzonitriles Inhibiting HIV-1 Reverse Transcriptase

Ligand- (GRIND) and structure-based (GLUE/GRIND) 3D-QSAR approaches were compared for 55 (aryl-)bridged 2-aminobenzonitriles inhibiting HIV-1 reverse transcriptase (HIV-1 RT). The ligand-based model was built from conformers selected by in vacuo minimization. The available X-ray structure of 3v in complex with HIV-1 RT allowed comparative structure-based calculations using the new docking software GLUE for conformer selection. Both models were validated via statistics and via virtual receptor sites (VRS) considering pharmacophoric regions and mutual distances, which were also compared with experimental evidence. The statistics show slight superiority of the structure-based approach in terms of fitting and prediction. By encoding relevant molecular interaction fields (MIF) into pharmacophoric regions, 10 such regions were derived from both models; they all fit the real receptor except HBD2. Also mutual distances highly agree between the real site and both VRS. Although distances from the structure-based approach are closer to the real receptor, present data prove the validity of the ligand-based GRIND approach.

A New Class of Selective Myocardial Calcium Channel Modulators. 2. Role of the Acetal Chain in Oxadiazol-3-one Derivatives

In the framework of the continuing interest of this research group in the use of 8-aryl-8-hydroxy-8H-[1,4]thiazino[3,4-c][1,2,4]oxadiazol-3-ones (1) as calcium entry blockers, a number of acetals were synthesized and assayed "in vitro". All of them are structurally related to diltiazem and pyrrolobenzothiazines. The effect on the biological profile was measured by functional assays for a wide variety of acetal residues: saturated linear and branched chains, short and long unsaturated E and/or Z chains as well as benzyl and methylcyclohexyl residues. From selective assays on the most active derivative (5b) (EC(50) = 0.04 microM), which is 20 times more active than diltiazem (EC(50) = 0.79 microM), a muscarinic or adenosinic mechanism of action was excluded. A 3D QSAR model was obtained and validated with homologous literature data, and a virtual receptor scheme was derived for the unknown binding site. The following pharmacophoric features favorably affect the potency: one positively charged center, three lipophilic groups, and two hydrogen-bonding acceptor groups.

Hydrogen Bonding Interactions of Covalently Bonded Fluorine Atoms: From Crystallographic Data to a New Angular Function in the GRID Force Field

Through the years the GRID force field has been tuned to fit experimental observations in crystal structures. This paper describes the determination of the hydrogen bonding pattern for organic fluorines based on an exhaustive inspection of the Protein Data Bank. All the PDB complexes, whose protein structures have cocrystallized fluorine-containing ligands, were examined and geometrically inspected. By applying statistics, the hydrogen bonding geometry was described as a distribution function of the angle at the fluorine: a new specific angular function was consequently defined and inserted in the program GRID to estimate the effect of fluorine hydrogen bonds on the ligand-protein binding. All the fluorine-containing ligands collected from the PDB were docked within their corresponding protein binding sites: introducing the fluorine hydrogen bonding contribution improves the results of the docking experiments in terms of accuracy and ranking.