Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions

Fragment-based drug design of nature-inspired compounds

Natural product (NP)-derived drugs can be extracts, biological macromolecules, or purified small molecule substances. Small molecule drugs can be originally purified from NPs, can represent semisynthetic molecules, natural fragments containing small molecules, or are fully synthetic molecules that mimic natural compounds. New semisynthetic NP-like drugs are entering the pharmaceutical market almost every year and reveal growing interests in the application of fragment-based approaches for NPs. Thus, several NP databases were constructed to be implemented in the fragment-based drug design (FBDD) workflows. FBDD has been established previously as an approach for hit identification and lead generation. Several biophysical and computational methods are used for fragment screening to identify potential hits. Once the fragments within the binding pocket of the protein are identified, they can be grown, linked, or merged to design more active compounds. This work discusses applications of NPs and NP scaffolds to FBDD. Moreover, it briefly reviews NP databases containing fragments and reports on case studies where the approach has been successfully applied for the design of antimalarial and anticancer drug candidates.

Targeting the Bacterial Membrane with a New Polycyclic Privileged Structure: A Powerful Tool To Face Staphylococcus aureus Infections

In this paper, a small series of anthracene-maleimide-based compounds was prepared and evaluated to assess the antimicrobial potential of this polycyclic core, a scaffold previously unexplored for new antibiotic development. Some of the new compounds showed appreciable anti-Staphylococcus aureus activity, together with good safety profiles. In particular, compound 13 proved to be the most promising of the series, showing remarkable antimicrobial activity toward planktonic and sessile bacterial cells within a mature preformed biofilm. The mechanism of action seems to be related to the ability of this compound to interfere with bacterial membrane functionality, probably through the targeting of key enzymes responsible for membrane redox homeostasis and energy production. The data reported confirm the ability of this polycyclic nucleus to behave as a new "privileged structure", suitable to be further exploited in the antimicrobial field.

GC-MS Analysis and Inhibitory Evaluation of Terminalia catappa Leaf Extracts on Major Enzymes Linked to Diabetes

Terminalia catappa leaves are used in managing both diabetes mellitus and its complications in Southwest Nigeria. However, its inhibitory activity on enzymes implicated in diabetes is not very clear. This study investigated the in vitro inhibitory properties and mode of inhibition of T. catappa leaf extracts on enzymes associated with diabetes. The study also identified some bioactive compounds as well as their molecular interaction in the binding pocket of these enzymes. Standard enzyme inhibition and kinetics assays were performed to determine the inhibitory effects of aqueous extract (TCA) and ethanol extract (TCE) of T. catappa leaves on α-glucosidase and α-amylase activities. The phytoconstituents of TCA and TCE were determined using GC-MS. Molecular docking of the phytocompounds was performed using Autodock Vina. TCA and TCE were the most potent inhibitors of α-glucosidase (IC₅₀ = 3.28 ± 0.47 mg/mL) and α-amylase (IC₅₀ = 0.24 ± 0.08 mg/mL), respectively. Both extracts displayed a mixed mode of inhibition on α-amylase activity, while mixed and noncompetitive modes of inhibition were demonstrated by TCA and TCE, respectively, on α-glucosidase activity. The GC-MS analytic chromatogram revealed the presence of 24 and 22 compounds in TCE and TCA, respectively, which were identified mainly as phenolic compounds, terpenes/terpenoids, fatty acids, and other phytochemicals. The selected compounds exhibited favourable interactions with the enzymes compared with acarbose. Overall, the inhibitory effect of T. catappa on α-amylase and α-glucosidase may be ascribed to the synergistic action of its rich phenolic and terpene composition giving credence to the hypoglycaemic nature of T. catappa leaves.

Virtual screening of a MDR-TB WhiB6 target identified by gene expression profiling

Multidrug resistance in M. tb has become a huge global problem due to drug resistance. Hence, the treatment remains a challenge, even though short term chemotherapy is available. Therefore, it is of interest to identify novel drug targets in M.tb through gene expression profiling complimented by a subtractive proteome model. WhiB6 is a transcriptional regulator protein and a known drug resistant marker that is critical in the secretion dependent regulation of ESX-1, which is specialized for the deployment of host membrane-targeting proteins. The WhiB6 protein structure was modelled ab initio and was docked with a library of 173 phytochemicals with potential antituberculosis activity to the identified drug marker to find novel lead molecules. UDP-galactopyranose and GDP-L-galactose were identified to be potential lead molecules to inhibit the target WhiB6. The results were compared with the first line drugs for MDR-TB by docking with WhiB6. Data showed that Ethambutol showed better binding ability to WhiB6 but the afore mentioned top ranked phytochemicals were found to be better candidate molecules. The chosen candidate lead molecules should be further validated by suitable in vitro or in vivo investigation.

Activity of methylgerambullin from Glycosmis species (Rutaceae) against Entamoeba histolytica and Giardia duodenalis in vitro

Entamoeba histolytica and Giardia duodenalis are widespread intestinal protozoan parasites which both spread via cysts that have to be ingested to infect a new host. Their environment, the small intestine for G. duodenalis and the colon for E. histolytica, contains only very limited amounts of oxygen, so both parasites generate energy by fermentation and substrate level phosphorylation rather than by oxidative phosphorylation. They both contain reducing agents able to reduce and activate nitroimidazole drugs such as metronidazole which is the gold standard drug to treat Entamoeba or Giardia infections. Although metronidazole works well in the majority of cases, it has a number of drawbacks. In animal models, the drug has carcinogenic activity, and concerns about a possible teratogenic activity remain. In addition, the treatment of G. duodenalis infections is hampered by emerging metronidazole resistance. Plant-derived drugs play a dominant role in human medicine, therefore we tested the activity of 14 isolated plant compounds belonging to seven different classes in vitro against both parasites. The tests were performed in a new setting in microtiter plates under anaerobic conditions. The compound with the highest activity was methylgerambullin, a sulphur-containing amide found in Glycosmis species of the family Rutaceae with an EC₅₀ of 14.5 μM (6.08 μg/ml) after 24 h treatment for E. histolytica and 14.6 μM (6.14 μg/ml) for G. duodenalis. The compound was successfully synthesised in the laboratory which opens the door for the generation of new derivatives with higher activity.

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Fourteen plant compounds of seven classes were isolated.

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The activity against Entamoeba histolytica and Giardia duodenalis was tested.

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Methylgerambullin had the highest activity against both parasites.

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Methylgerambullin is a sulphur-containing amide from Glycosmis spp. (Citrus plants).

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High cysteine concentrations interfered with methylgerambullin activity.

A Qualified Success: Discovery of a New Series of ATAD2 Bromodomain Inhibitors with a Novel Binding Mode Using High-Throughput Screening and Hit Qualification

The bromodomain of ATAD2 has proved to be one of the least-tractable proteins within this target class. Here, we describe the discovery of a new class of inhibitors by high-throughput screening and show how the difficulties encountered in establishing a screening triage capable of finding progressible hits were overcome by data-driven optimization. Despite the prevalence of nonspecific hits and an exceptionally low progressible hit rate (0.001%), our optimized hit qualification strategy employing orthogonal biophysical methods enabled us to identify a single active series. The compounds have a novel ATAD2 binding mode with noncanonical features including the displacement of all conserved water molecules within the active site and a halogen-bonding interaction. In addition to reporting this new series and preliminary structure-activity relationship, we demonstrate the value of diversity screening to complement the knowledge-based approach used in our previous ATAD2 work. We also exemplify tactics that can increase the chance of success when seeking new chemical starting points for novel and less-tractable targets.

The Cattle Fever Tick, Rhipicephalus microplus, as a Model for Forward Pharmacology to Elucidate Kinin GPCR Function in the Acari

The success of the acaricide amitraz, a ligand of the tick tyramine/octopamine receptor (a G protein-coupled receptor; GPCR), stimulated interest on arthropod-specific GPCRs as targets to control tick populations. This search advances tick physiology because little is known about the pharmacology of tick GPCRs, their endogenous ligands or their physiological functions. Here we explored the tick kinin receptor, a neuropeptide GPCR, and its ligands. Kinins are pleiotropic insect neuropeptides but their function in ticks is unknown. The endogenous tick kinins are unknown and their cDNAs have not been cloned in any species. In contrast, more than 271 insect kinin sequences are available in the DINeR database. To fill this gap, we cloned the kinin cDNA from the cattle fever tick, Rhipicephalus microplus, which encodes 17 predicted kinins, and verified the kinin gene structure. We predicted the kinin precursor sequences from additional seven tick species, including Ixodes scapularis. All species showed an expansion of kinin paracopies. The "kinin core" (minimal active sequence) of tick kinins FX1X2WGamide is similar to those in insects. Pro was predominant at the X2 position in tick kinins. Toward accelerating the discovery of kinin function in ticks we searched for novel synthetic receptor ligands. We developed a dual-addition assay for functional screens of small molecules and/or peptidomimetics that uses a fluorescent calcium reporter. A commercial library of fourteen small molecules antagonists of mammalian neurokinin (NK) receptors was screened using this endpoint assay. One acted as full antagonist (TKSM02) with inhibitory concentration fifty (IC50) of ∼45 μM, and three were partial antagonists. A subsequent calcium bioluminescence assay tested these four antagonists through kinetic curves and confirmed TKSM02 as full antagonist and one as partial antagonist (TKSM14). Antagonists of NK receptors displayed selectivity (>10,000-fold) on the tick kinin receptor. Three peptidomimetic ligands of the mammalian NK receptors (hemokinin 1, antagonist G, and spantide I) were tested in the bioluminescence assay but none were active. Forward approaches may accelerate discovery of kinin ligands, either as reagents for tick physiological research or as lead molecules for acaricide development, and they demonstrate that selectivity is achievable between mammalian and tick neuropeptide systems.

Synthesis, structural studies and biological properties of some phosphono-perfluorophenylalanine derivatives formed by SNAr reactions

Several novel phosphono-perfluorophenylalanine derivatives, as mimetics of phenylalanine, were synthesized by subjecting diethyl (2-(perfluorophenyl)-1-(phenylamino)ethyl)-phosphonate to SNAr reactions with different types of nucleophiles such as thiols, amines and phenols. The structure of the products was confirmed using spectroscopic and spectrometric techniques. For two compounds X-ray single crystal diffraction analysis and DFT investigations were performed providing information in regard to the preferable conformation, hydrogen bonds and other interactions. The antiproliferative potency of some of the new phosphono-perfluorophenylalanine derivatives obtained as well as representatives of previously synthesized perfluorophenyl phosphonate analogues of phenylalanine was studied on selected glioma cell lines. Preliminary evaluation of the compounds drug likeness was examined with respect to Lipinski's and Veber's rules, and showed that they meet the criteria perfectly. MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide) assay results demonstrated that the compounds exhibit moderate activity against the glioblastoma multiforme cell lines (T98G and U-118 MG). Moreover most of the studied SNAr reaction products displayed significantly higher inhibitory activity against both cancer cell lines than the parent diethyl (2-(perfluorophenyl)-1-(phenylamino)ethyl)phosphonate.

Natural compounds from plants controlling leishmanial growth via DNA damage and inhibiting trypanothione reductase and trypanothione synthetase: an in vitro and in silico approach

In the present study, four different natural compounds including quercetin, gallic acid, rutin, and lupeol were studied for their anti-leishmanial potentials with anticipated mechanism of action through in vitro and in silico approaches. Results showed that rutin was exceedingly active (IC₅₀; 91.2 µg/ml) against the promastigote form of Leishmania tropica compared to quercetin (IC₅₀; 182.3 µg/ml), gallic acid (IC₅₀; 198.00 µg/ml) and lupeol (IC₅₀; 200.77 µg/ml). Similarly, rutin was highly active against the amastigote form as well, followed by quercetin, gallic acid and lupeol with IC₅₀ values of 101.3 µg/ml, 137.4 µg/ml, 277.2 µg/ml, and 298.9 µg/ml, respectively. These compounds were found to be nontoxic to human blood erythrocytes even at the highest concentration (1000 µg/ml) tested. Rutin and lupeol showed promising DNA degradation/fragmentation activity against the DNA of treated promastigotes which increased with the increase in concentration of the compounds. The in silico investigation revealed that these ligands have high affinity with the important catalytic residues of trypanothione reductase (Try-R) where, rutin showed the lowest docking score (i.e., - 6.191) followed by lupeol (- 5.799), gallic acid and quercetin. In case of ligands' interaction with trypanothione synthetase (Try-S), rutin again showed highest interaction with docking score of - 6.601 followed by quercetin (- 4.996), lupeol and gallic acid. The ADMET prediction of these compounds showed that all the parameters were within the acceptable range as defined for human use while molecular dynamics simulation supported the good interaction of quercetin and rutin against both enzymes. These findings suggest that the studied compounds may control leishmanial growth via DNA damage and inhibiting Try-R and Try-S, the two unique but critical enzymes for leishmania growth.

Physics-Based Method for Modeling Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules

Assessment of permeability is a critical step in the drug development process for selection of drug candidates with favorable ADME properties. We have developed a novel physics-based method for fast computational modeling of passive permeation of diverse classes of molecules across lipid membranes. The method is based on heterogeneous solubility-diffusion theory and operates with all-atom 3D structures of solutes and the anisotropic solvent model of the lipid bilayer characterized by transbilayer profiles of dielectric and hydrogen bonding capacity parameters. The optimal translocation pathway of a solute is determined by moving an ensemble of representative conformations of the molecule through the dioleoyl-phosphatidylcholine (DOPC) bilayer and optimizing their rotational orientations in every point of the transmembrane trajectory. The method calculates (1) the membrane-bound state of the solute molecule; (2) free energy profile of the solute along the permeation pathway; and (3) the permeability coefficient obtained by integration over the transbilayer energy profile and assuming a constant size-dependent diffusivity along the membrane normal. The accuracy of the predictions was evaluated against experimental permeability coefficients measured in pure lipid membranes (for 78 compounds, R² was 0.88 and rmse was 1.15 log units), PAMPA-DS (for 280 compounds, R² was 0.75 and rmse was 1.59 log units), BBB (for 182 compounds, R² was 0.69 and rmse was 0.87 log units), and Caco-2/MDCK assays (for 165 compounds, R² was 0.52 and rmse was 0.89 log units).

A non-beta-lactam antibiotic inhibitor for enterohemorrhagic Escherichia coli O104:H4

The overuse of antibiotics has caused an increased prevalence of drug-resistant bacteria. Bacterial resistance in E. coli is regulated via production of β-lactam-hydrolyzing β-lactamases enzymes. Escherichia coli O104: H4 is a multi-drug resistant strain known to resist β-lactam as well as several other antibiotics. Here, we report a molecular dynamic simulation-combined docking approach to identify, screen, and verify active pharmacophores against enterohemorrhagic Escherichia coli (EHEC). Experimental studies revealed a boronic acid cyclic monomer (BACM), a non-β-lactam compound, to inhibit the growth of E. coli O104: H4. In vitro Kirby Bauer disk diffusion susceptibility testing coupled interaction analysis suggests BACM inhibits E. coli O104:H4 growth by not only inhibiting the β-lactamase pathway but also via direct inhibition of the penicillin-binding protein. These results suggest that BACM could be used as a lead compound to develop potent drugs targeting beta-lactam resistant Gram-negative bacterial strains. KEY MESSAGES: • An in silico approach was reported to identify pharmacophores against E. coli O104: H4. • In vitro studies revealed a non-β-lactam compound to inhibit the growth of E. coli O104: H4. • This non-β-lactam compound could be used as a lead compound for targeting beta-lactam strains.

An appraisal of natural products active against parasitic nematodes of animals

Here, the scientific and patent literature on the activities of purified natural compounds has been reviewed, with the aim of assessing their suitability as anthelmintic drug discovery starting points. Only compounds described as active against parasitic nematodes of animals or against the model nematode Caenorhabditis elegans have been analysed. Scientific articles published since 2010 and patents granted from 2000, both inclusive, have been included in this analysis. The results show a scarcity of novel chemical structures, a limited follow-up of compounds disclosed before 2010 and a bias towards the screening of plant products, almost to the exclusion of other sources, when microbial extracts have, historically, provided most starting points for anti-infective drugs. All plant products published in this period were previously known, alerting to the high re-discovery rates of a limited number of chemical classes from this source. The most promising compounds described in the literature reviewed here, namely the linear nemadectin-derivatives, are novel and of bacterial origin. Patented but otherwise unpublished spiroketal structures also appear as interesting scaffolds for future development. The patent literature confirmed that it is possible to patent derivatives of previously known products, making them valid starting points for translational research.

A primer on natural product-based virtual screening

Databases play an important role in various computational techniques, including virtual screening (VS) and molecular modeling in general. These collections of molecules can contain a large amount of information, making them suitable for several drug discovery applications. For example, vendor, bioactivity data or target type can be found when searching a database. The introduction of these data resources and their characteristics is used for the design of an experiment. The description of the construction of a database can also be a good advisor for the creation of a new one. There are free available databases and commercial virtual libraries of molecules. Furthermore, a computational chemist can find databases for a general purpose or a specific subset such as natural products (NPs). In this chapter, NP database resources are presented, along with some guidelines when preparing an NP database for drug discovery purposes.

Automated De Novo Drug Design: Are We Nearly There Yet?

Medicinal chemistry and, in particular, drug design have often been perceived as more of an art than a science. The many unknowns of human disease and the sheer complexity of chemical space render decision making in medicinal chemistry exceptionally demanding. Computational models can assist the medicinal chemist in this endeavour. Provided here is an overview of recent examples of automated de novo molecular design, a discussion of the concepts and computational approaches involved, and the daring prediction of some of the possibilities and limitations of drug design using machine intelligence.

A Molecular Docking Approach to Evaluate the Pharmacological Properties of Natural and Synthetic Treatment Candidates for Use against Hypertension

Cardiovascular diseases (CVDs) have become the leading cause of disability and death worldwide, particularly in low- and middle-income countries. Hypertension, a major cause of CVD progression, is widely attributable to genetic, behavioral, and environmental risk factors. Among the genetic reasons, angiotensin II enzyme, produced as a result of abnormal functioning of the renin⁻angiotensin system, is reported as the foremost cause of hypertension. A cascade of genes, including those encoding for WNK kinases (WNK1 and WNK4), Bp1, Bp2, angiotensinogen, and other enzymes, is involved in the conversion of angiotensin I to angiotensin II. However, the angiotensin-converting enzyme (ACE) plays a crucial role in this pathway. Therefore, ACE could be a potential therapeutic target in regulating the conversion of angiotensin I to angiotensin II and eventually controlling hypertension. In this study, a molecular docking-based approach was utilized for identifying and evaluating potential inhibitors of ACE present in herbs, other natural sources, and synthetic sources, on the basis of these compounds' binding affinities and other physicochemical features. In addition, the suitability of these inhibitors as drugs for biological systems, considering their adsorption, distribution, metabolism, and excretion (ADME), was predicted using Lipinski's rule. In conclusion, our study provides a novel and clearer insight into the interaction properties of known putative inhibitors of ACE.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

Hitting Undruggable Targets: Viewing Stabilized Peptide Development through the Lens of Quantitative Systems Pharmacology

Stabilized peptide therapeutics have the potential to hit currently undruggable targets, dramatically expanding the druggable genome. However, major obstacles to their development include poor intracellular delivery, rapid degradation, low target affinity, and membrane toxicity. With the emergence of multiple stabilization techniques and screening technologies, the high efficacy of various bioactive peptides has been demonstrated in vitro, albeit with limited success in vivo. We discuss here the chemical and pharmacokinetic barriers to achieving in vivo efficacy, analyze the characteristics of FDA-approved peptide drugs, and propose a developmental tool that considers the molecular properties of stabilized peptides in a comprehensive and quantitative manner to achieve the necessary rates for in vivo delivery to the target, efficacy, and ultimately clinical translation.

Targeting ERK1/2 protein-serine/threonine kinases in human cancers

ERK1 and ERK2 are key protein kinases that contribute to the Ras-Raf-MEK-ERK MAP kinase signalling module. This pathway participates in the control of numerous processes including apoptosis, cell proliferation, the immune response, nervous system function, and RNA synthesis and processing. MEK1/2 activate human ERK1/2 by first catalyzing the phosphorylation of Y204/187 and then T202/185, both residues of which occur within the activation segment. The phosphorylation of both residues is required for enzyme activation. The only Raf substrates are MEK1/2 and the only MEK1/2 substrates are ERK1/2. In contrast, ERK1/2 catalyze the phosphorylation of many cytoplasmic and nuclear substrates including transcription factors and regulatory molecules. The linear MAP kinase pathway branches extensively at the ERK1/2 node. ERK1/2 are proline-directed kinases that preferentially catalyze the phosphorylation of substrates containing a PxS/TP sequence. The dephosphorylation and inactivation of ERK1/2 is catalyzed by dual specificity phosphatases, protein-tyrosine specific phosphatases, and protein-serine/threonine phosphatases. The combined functions of kinases and phosphatases make the overall process reversible. To provide an idea of the complexities involved in these reactions, somatic cell cycle progression involves the strict timing of more than 32,000 phosphorylation and dephosphorylation events as determined by mass spectrometry. The MAP kinase cascade is perhaps the most important oncogenic driver of human cancers and the blockade of this signalling module by targeted inhibitors is an important anti-tumor strategy. Although numerous cancers are driven by MAP kinase pathway activation, thus far the only orally effective approved drugs that target this signaling module are used for the treatment of BRAF-mutant melanomas. The best treatments include the combination of B-Raf and MEK inhibitors (dabrafenib and trametinib, encorafenib and binimetinib, vemurafenib and cobimetanib). However, resistance to these antagonists occurs within one year and additional treatment options are necessary. Owing to the large variety of malignancies that are driven by dysregulation of the MAP kinase pathway, additional tumor types should be amenable to MAP kinase pathway inhibitor therapy. In addition to new B-Raf and MEK inhibitors, the addition of ERK inhibitors should prove helpful. Ulixertinib, MK-8353, and GDC-0994 are orally effective, potent, and specific inhibitors of ERK1/2 that are in early clinical trials for the treatment of various advanced/metastatic solid tumors. These agents are effective against cell lines that are resistant to B-Raf and MEK1/2 inhibitor therapy. Although MK-8353 does not directly inhibit MEK1/2, it decreases the phosphorylation of ERK1/2 as well as the phosphorylation of RSK, an ERK1/2 substrate. The decrease in RSK phosphorylation appears to be a result of ERK inhibition and the decrease in ERK1/2 phosphorylation is related to the inability of MEK to catalyze the phosphorylation of the ERK-MK-8353 complex; these decreases characterize the ERK dual mechanism inhibition paradigm. Additional work will be required to determine whether ERK inhibitors will be successful in the clinic and are able to forestall the development of drug resistance of the MAP kinase pathway.

Discovery of Macrocyclic Inhibitors of Apurinic/Apyrimidinic Endonuclease 1

Apurinic/apyrimidinic endonuclease 1 (APE1) is an essential base excision repair enzyme that is upregulated in a number of cancers, contributes to resistance of tumors treated with DNA-alkylating or -oxidizing agents, and has recently been identified as an important therapeutic target. In this work, we identified hot spots for binding of small organic molecules experimentally in high resolution crystal structures of APE1 and computationally through the use of FTMAP analysis ( http://ftmap.bu.edu/ ). Guided by these hot spots, a library of drug-like macrocycles was docked and then screened for inhibition of APE1 endonuclease activity. In an iterative process, hot-spot-guided docking, characterization of inhibition of APE1 endonuclease, and cytotoxicity of cancer cells were used to design next generation macrocycles. To assess target selectivity in cells, selected macrocycles were analyzed for modulation of DNA damage. Taken together, our studies suggest that macrocycles represent a promising class of compounds for inhibition of APE1 in cancer cells.

OptiPharm: An evolutionary algorithm to compare shape similarity

Virtual Screening (VS) methods can drastically accelerate global drug discovery processes. Among the most widely used VS approaches, Shape Similarity Methods compare in detail the global shape of a query molecule against a large database of potential drug compounds. Even so, the databases are so enormously large that, in order to save time, the current VS methods are not exhaustive, but they are mainly local optimizers that can easily be entrapped in local optima. It means that they discard promising compounds or yield erroneous signals. In this work, we propose the use of efficient global optimization techniques, as a way to increase the quality of the provided solutions. In particular, we introduce OptiPharm, which is a parameterizable metaheuristic that improves prediction accuracy and offers greater computational performance than WEGA, a Gaussian-based shape similarity method. OptiPharm includes mechanisms to balance between exploration and exploitation to quickly identify regions in the search space with high-quality solutions and avoid wasting time in non-promising areas. OptiPharm is available upon request via email.

The Impact of Novel Assessment Methodologies in Toxicology on Green Chemistry and Chemical Alternatives

The field of experimental toxicology is rapidly advancing by incorporating novel techniques and methods that provide a much more granular view into the mechanisms of potential adverse effects of chemical exposures on human health. The data from various in vitro assays and computational models are useful not only for increasing confidence in hazard and risk decisions, but also are enabling better, faster and cheaper assessment of a greater number of compounds, mixtures, and complex products. This is of special value to the field of green chemistry where design of new materials or alternative uses of existing ones is driven, at least in part, by considerations of safety. This article reviews the state of the science and decision-making in scenarios when little to no data may be available to draw conclusions about which choice in green chemistry is "safer." It is clear that there is no "one size fits all" solution and multiple data streams need to be weighed in making a decision. Moreover, the overall level of familiarity of the decision-makers and scientists alike with new assessment methodologies, their validity, value and limitations is evolving. Thus, while the "impact" of the new developments in toxicology on the field of green chemistry is great already, it is premature to conclude that the data from new assessment methodologies have been widely accepted yet.

Examining pharmacodynamic and pharmacokinetic properties of eleven analogues of saquinavir for HIV protease inhibition

HIV is one of the most lethal viral diseases in the human population. Patients often suffer from drug resistance, which hampers HIV therapy. Eleven different structural analogues of saquinavir (SQV), designed using ChemSketch™ and named S1 through S11, were compared with SQV with respect to their pharmacodynamic and pharmacokinetic properties. Pharmacokinetic predictions were carried out using AutoDock, and molecular docking between macromolecule HIV protease (PDB ID: 3IXO) and analogues S1 - S11 as ligands was performed. Analogues S1, S3, S4, S9 and S11 had lower binding scores when compared with saquinavir, whereas that of analogue S5 was similar. Pharmacokinetic predictions made using ACDilab2, including the Lipinski profile, general physical features, absorption, distribution, metabolism and excretion parameters, and toxicity values, for the eleven analogues and SQV suggested that S1 and S5 are pharmacodynamically and pharmacokinetically robust molecules that could be developed and established as lead molecules after in vitro and in vivo studies.

All that glitters is not gold: Panning cytotoxic natural products and derivatives with a fused tricyclic backbone by the estimation of their leadlikeness for cancer treatment

Tricyclic compounds call the attention because of their pharmacological properties, and are considered a preferred platform for the development of drugs. Especially, in cancer treatment, these planar compounds are known for their ability to stack with DNA base pairs, acting as intercalators. In this sense, natural products (NPs) are a prodigal source of polycyclic compounds, comprising classes, such as carbolines, anthraquinones and xanthones. However, most of these compounds lack suitable physico-chemical properties, compatible to oral bioaviability. In this perspective, this paper aims to overview the role of tricyclic cores in the development of cytotoxic compounds, focusing on the leadlikeness estimation of the most prominent NP classes and their synthetic derivatives.

Potential Anti-Cancer Flavonoids Isolated From Caesalpinia bonduc Young Twigs and Leaves: Molecular Docking and In Silico Studies

Tyrosine kinase (TK), vascular endothelial growth factor (VEGF), and matrix metalloproteinases (MMP) are important cancer therapeutic target proteins. Based on reported anti-cancer and cytotoxic activities of Caesalpinia bonduc, this study isolated phytochemicals from young twigs and leaves of C bonduc and identified the interaction between them and cancer target proteins (TK, VEGF, and MMP) in silico. AutoDock Vina, iGEMDOCK, and analysis of pharmacokinetic and pharmacodynamic properties of the isolated bioactives as therapeutic molecules were performed. Seven phytochemicals (7-hydroxy-4′-methoxy-3,11-dehydrohomoisoflavanone, 4,4′-dihydroxy-2’-methoxy-chalcone, 7,4′-dihydroxy-3,11-dehydrohomoisoflavanone, luteolin, quercetin-3-methyl, kaempferol-3-O-β-d-xylopyranoside and kaempferol-3-O-α-l-rhamnopyranosyl-(1 → 2)-β-D-xylopyranoside) were isolated. Molecular docking analysis showed that the phytochemicals displayed strong interactions with the proteins compared with their respective drug inhibitors. Pharmacokinetic and pharmacodynamic properties of the compounds were promising suggesting that they can be developed as putative lead compounds for developing new anti-cancer drugs.

Distribution of superparamagnetic Au/Fe nanoparticles in an isolated guinea pig brain with an intact blood brain barrier

Diagnosis and treatment of brain disorders, such as epilepsy, neurodegenerative diseases and tumors, would benefit from innovative approaches to deliver therapeutic or diagnostic compounds into the brain parenchyma, with either a homogeneous or a targeted localized distribution pattern. To assess the mechanistic aspect of penetration of nanoparticles (NPs) into the brain parenchyma, a complex, yet controlled and facilitated environment was used: the isolated guinea pig brain maintained in vitro by arterial perfusion. In this unique preparation the blood-brain barrier and the interactions between vascular and neuronal compartments are morphologically and functionally preserved. In this study, superparamagnetic Au/Fe nanoparticles (MUS:OT Au/Fe NPs), recently studied as a promising magnetic resonance T2 contrast agent with high cellular penetration, were arterially perfused into the in vitro isolated brain and showed high and homogeneous penetration through transcytosis into the brain parenchyma. Ultramicroscopy investigation of the in vitro isolated brain sections by TEM analysis of the electron-dense core of the MUS:OT Au/Fe NPs was conducted to understand NPs' brain penetration through the BBB after in vitro arterial perfusion and their distribution in the parenchyma. Our data suggest that MUS:OT Au/Fe NPs enter the brain utilizing a physiological route and therefore can be exploited as brain penetrating nanomaterials with potential contrast agent and theranostics capabilities.

Müller glial dysfunction during diabetic retinopathy in rats is reduced by the acrolein-scavenging drug, 2-hydrazino-4,6-dimethylpyrimidine

AIMS/HYPOTHESIS

Recent studies suggest that abnormal function in Müller glial cells plays an important role in the pathogenesis of diabetic retinopathy. This is associated with the selective accumulation of the acrolein-derived advanced lipoxidation end-product, N^ε-(3-formyl-3,4-dehydropiperidino)lysine (FDP-lysine), on Müller cell proteins. The aim of the current study was to identify more efficacious acrolein-scavenging drugs and determine the effects of the most potent on Müller cell FDP-lysine accumulation and neuroretinal dysfunction during diabetes.

METHODS

An ELISA-based in vitro assay was optimised to compare the acrolein-scavenging abilities of a range of drugs. This identified 2-hydrazino-4,6-dimethylpyrimidine (2-HDP) as a new and potent acrolein scavenger. The ability of this agent to modify the development of diabetic retinopathy was tested in vivo. Male Sprague Dawley rats were divided into three groups: (1) non-diabetic; (2) streptozotocin-induced diabetic; and (3) diabetic treated with 2-HDP in their drinking water for the duration of diabetes. Liquid chromatography high-resolution mass spectrometry was used to detect 2-HDP reaction products in the retina. Immunohistochemistry, real-time quantitative (q)RT-PCR and electroretinography were used to assess retinal changes 3 months after diabetes induction.

RESULTS

2-HDP was the most potent of six acrolein-scavenging agents tested in vitro (p < 0.05). In vivo, administration of 2-HDP reduced Müller cell accumulation of FDP-lysine at 3 months in rats rendered diabetic with streptozotocin (p < 0.001). A 2-HDP adduct was identified in the retinas of diabetic animals treated with this compound. 2-HDP supplementation was associated with reduced Müller cell gliosis (p < 0.05), reduced expression of the oxidative stress marker haem oxygenase-1 (p < 0.001) and partial normalisation of inwardly rectifying K⁺ channel 4.1 (Kir4.1) expression (p < 0.001 for staining in perivascular regions and the innermost region of the ganglion cell layer). Diabetes-induced retinal expression of inflammatory markers, inflammatory signalling compounds and activation of retinal microglial cells were all reduced in 2-HDP-treated animals. Retinal neurophysiological defects in diabetic animals, as indicated by changes in the electroretinogram 7 weeks after induction of diabetes, were also reduced by 2-HDP (p < 0.05-0.01 for b-wave amplitudes at flash intensities from -10 to +10 dB; p < 0.01 for time to peak of summed oscillatory potentials at +10 dB).

CONCLUSIONS/INTERPRETATION

These findings support the hypothesis that Müller cell accumulation of FDP-lysine plays an important role in the development of diabetic retinopathy. Our results also suggest that 2-HDP may have therapeutic potential for delaying or treating this sight-threatening complication.

Signalling and differentiation in emulsion-based multi-compartmentalized in vitro gene circuits

Multicellularity enables the growth of complex life forms as it allows for specialization of cell types, differentiation, and large scale spatial organization. In a similar way, modular construction of synthetic multicellular systems will lead to dynamic biomimetic materials that can respond to their environment in complex ways. In order to achieve this goal, artificial cellular communication and developmental programs still have to be established. Here, we create geometrically controlled spatial arrangements of emulsion-based artificial cellular compartments containing synthetic in vitro gene circuitry, separated by lipid bilayer membranes. We quantitatively determine the membrane pore-dependent response of the circuits to artificial morphogen gradients, which are established via diffusion from dedicated organizer cells. Utilizing different types of feed-forward and feedback in vitro gene circuits, we then implement artificial signaling and differentiation processes, demonstrating the potential for the realization of complex spatiotemporal dynamics in artificial multicellular systems.

Pharmacophore-based virtual screening for identification of potential selective inhibitors of human histone deacetylase 6

Histone deacetylase (HDAC) 6 plays a role in oncogenic transformation and cancer metastasis via tubulin deacetylation, making it a critical target for anticancer drug design. However, lack of selectivity shown by many of the current HDAC6 inhibitors in clinical use and trials prompts the continuous search for selective inhibitors. Here, 10 pharmacophore hypotheses were developed based on the 3D common features of training set of 20 HDAC inhibitors in clinical use and trials. The hypotheses were validated using a test set of another 20 HDAC inhibitors along with 400 inactive (decoys) molecules based on Güner-Henry pharmacophore scoring method. Hypothesis 1 consisting of 1 H-bond donor, 1 H-bond acceptor and 2 hydrophobic features, was used to screen "DruglikeDiverse" database using Biovia Discovery Studio 4.5. The top 10 hit compounds were selected based on the pharmacophore fit values (>3.00). Their binding affinity against HDAC6 compared to class I HDACs (1, 2, 3 & 8) and a class IIa member (HDAC7), was calculated by molecular docking using AutoDock4. The stability of binding modes of 2 potential HDAC6-selective inhibitors (ENA501965 and IBS399024) was examined by 30 ns-molecular dynamics (MD) simulation using nanoscale MD (NAMD) software. Both ligands showed potential stability in HDAC6 active site over time. Therefore, these may provide additional scaffolds for further optimization towards the design of safe, potent and selective HDAC6 inhibitors.

G protein-coupled receptors in arthropod vectors: omics and pharmacological approaches to elucidate ligand-receptor interactions and novel organismal functions

Regulation of many physiological processes in animals, certainly those controlled by neuropeptide hormones, involves G protein-coupled receptors (GPCRs). Our work focusing on endocrine regulation of diuresis and water balance in mosquitoes and ticks started in 1997 with the kinin receptor, at the dawn of the omics era. After the genomic revolution, we began work on the endocrinology of reproduction in the red imported fire ant. We will use the template of this comparative work to summarize key points about GPCRs and signaling, and emphasize the most recent developments in the pharmacology of arthropod neuropeptide GPCRs. We will discuss omics' contributions to the advancement of this field, and its influence on peptidomimetic design while emphasizing work on blood feeding arthropods.

PPI inhibitor and stabilizer development in human diseases

All processes in living organisms are regulated by, or at least influenced by, protein-protein interactions (PPI). Membrane proteins play a fundamental part in this class of interactions: by providing inter-cellular communication and sensing capabilities to the cell, they lead to downstream regulation signaling events. It is therefore not surprising that PPI modulators are of keen interest when developing drug-like molecules for a range of diseases and medical conditions. However, techniques for exploiting PPIs in meaningful ways have only recently become readily available. This review is meant to provide a brief overview of applied techniques for PPI elucidation, and present various case studies of PPI exploitation ranging from early discovery efforts to now-approved market drugs.

Prediction Methods of Herbal Compounds in Chinese Medicinal Herbs

Chinese herbal medicine has recently gained worldwide attention. The curative mechanism of Chinese herbal medicine is compared with that of western medicine at the molecular level. The treatment mechanism of most Chinese herbal medicines is still not clear. How do we integrate Chinese herbal medicine compounds with modern medicine? Chinese herbal medicine drug-like prediction method is particularly important. A growing number of Chinese herbal source compounds are now widely used as drug-like compound candidates. An important way for pharmaceutical companies to develop drugs is to discover potentially active compounds from related herbs in Chinese herbs. The methods for predicting the drug-like properties of Chinese herbal compounds include the virtual screening method, pharmacophore model method and machine learning method. In this paper, we focus on the prediction methods for the medicinal properties of Chinese herbal medicines. We analyze the advantages and disadvantages of the above three methods, and then introduce the specific steps of the virtual screening method. Finally, we present the prospect of the joint application of various methods.

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.

Pharmaceutical Applications of Cellulose Ethers and Cellulose Ether Esters

Cellulose ethers have proven to be highly useful natural-based polymers, finding application in areas including food, personal care products, oil field chemicals, construction, paper, adhesives, and textiles. They have particular value in pharmaceutical applications due to characteristics including high glass transition temperatures, high chemical and photochemical stability, solubility, limited crystallinity, hydrogen bonding capability, and low toxicity. With regard to toxicity, cellulose ethers have essentially no ability to permeate through gastrointestinal enterocytes and many are already in formulations approved by the U.S. Food and Drug Administration. We review pharmaceutical applications of these valuable polymers from a structure-property-function perspective, discussing each important commercial cellulose ether class; carboxymethyl cellulose, methyl cellulose, hydroxypropylcellulose, hydroxypropyl methyl cellulose, and ethyl cellulose, and cellulose ether esters including hydroxypropyl methyl cellulose acetate succinate and carboxymethyl cellulose acetate butyrate. We also summarize their syntheses, basic material properties, and key pharmaceutical applications.

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose-Response Assessments for Noncancer Effects

BACKGROUND

The National Academies recommended risk assessments redefine the traditional noncancer Reference Dose (RfD) as a probabilistically derived risk-specific dose, a framework for which was recently developed by the World Health Organization (WHO).

OBJECTIVES

Our aim was to assess the feasibility and implications of replacing traditional RfDs with probabilistic estimates of the human dose associated with an effect magnitude M and population incidence I (HD_MI).

METHODS

We created a comprehensive, curated database of RfDs derived from animal data and developed a standardized, automated, web-accessible probabilistic dose-response workflow implementing the WHO framework.

RESULTS

We identified 1,464 RfDs and associated endpoints, representing 608 chemicals across many types of effects. Applying our standardized workflow resulted in 1,522 HD_MI values. Traditional RfDs are generally within an order of magnitude of the HD_MI lower confidence bound for I=1% and M values commonly used for benchmark doses. The greatest contributor to uncertainty was lack of benchmark dose estimates, followed by uncertainty in the extent of human variability. Exposure at the traditional RfD frequently implies an upper 95% confidence bound of several percent of the population affected. Whether such incidences are considered acceptable is likely to vary by chemical and risk context, especially given the wide range of severity of the associated effects, from clinical chemistry to mortality.

CONCLUSIONS

Overall, replacing RfDs with HD_MI estimates can provide a more consistent, scientifically rigorous, and transparent basis for risk management decisions, as well as support additional decision contexts such as economic benefit-cost analysis, risk-risk tradeoffs, life-cycle impact analysis, and emergency response. https://doi.org/10.1289/EHP3368.

Cryptic binding sites on proteins: definition, detection, and druggability

Many proteins in their unbound structures lack surface pockets appropriately sized for drug binding. Hence, a variety of experimental and computational tools have been developed for the identification of cryptic sites that are not evident in the unbound protein but form upon ligand binding, and can provide tractable drug target sites. The goal of this review is to discuss the definition, detection, and druggability of such sites, and their potential value for drug discovery. Novel methods based on molecular dynamics simulations are particularly promising and yield a large number of transient pockets, but it has been shown that only a minority of such sites are generally capable of binding ligands with substantial affinity. Based on recent studies, current methodology can be improved by combining molecular dynamics with fragment docking and machine learning approaches.

Screening of potential lead molecules against prioritised targets of multi-drug-resistant-Acinetobacter baumannii - insights from molecular docking, molecular dynamic simulations and in vitro assays

Acinetobacter baumannii, an opportunistic pathogen, has become multi-drug resistant (MDR) to major classes of antibacterial and poses grave threat to public health. The current study focused to screen novel phytotherapeutics against prioritised targets of Acinetobacter baumannii by computational investigation. Fourteen potential drug targets were screened based on their functional role in various biosynthetic pathways and the 3D structures of 9 targets were retrieved from Protein Data Bank and others were computationally predicted. By extensive literature survey, 104 molecules from 48 herbal sources were screened and subjected to virtual screening. Ten clinical isolates of A. baumannii were tested for antibiotic susceptibility towards clinafloxacin, imipenem and polymyxin-E. Computational screening suggested that Ajmalicine ((19α)-16, 17-didehydro-19-methyloxayohimban-16-carboxylic acid methyl ester from Rauwolfia serpentina), Strictamin (Akuammilan-17-oic acid methyl ester from Alstonia scholaris) and Limonin (7, 16-dioxo-7, 16-dideoxylimondiol from Citrus sps) exhibited promising binding towards multiple drug targets of A. baumannii in comparison with the binding between standard drugs and their targets. Limonin displayed promising binding potential (binding energy -9.8 kcal/mol) towards diaminopimelate epimerase (DapF) and UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA). Ajmalicine and Strictamin demonstrated good binding potential (-9.5, -8.5 kcal/mol, respectively) towards MurA and shikimate dehydrogenase (-7.8 kcal/mol). Molecular dynamic simulations further validated the docking results. In vitro assay suggested that the tested isolates exhibited resistance to clinafloxacin, imipenem and polymyxin-E and the herbal preparations (crude extract) demonstrated a significant antibacterial potential (p ≤ .05). The study suggests that the aforementioned lead candidates and targets can be used for structure-based drug screening towards MDR A. baumannii.

Antibiotic Hybrids: the Next Generation of Agents and Adjuvants against Gram-Negative Pathogens?

The global incidence of drug-resistant Gram-negative bacillary infections has been increasing, and there is a dire need to develop novel strategies to overcome this problem. Intrinsic resistance in Gram-negative bacteria, such as their protective outer membrane and constitutively overexpressed efflux pumps, is a major survival weapon that renders them refractory to current antibiotics. Several potential avenues to overcome this problem have been at the heart of antibiotic drug discovery in the past few decades. We review some of these strategies, with emphasis on antibiotic hybrids either as stand-alone antibacterial agents or as adjuvants that potentiate a primary antibiotic in Gram-negative bacteria. Antibiotic hybrid is defined in this review as a synthetic construct of two or more pharmacophores belonging to an established agent known to elicit a desired antimicrobial effect. The concepts, advances, and challenges of antibiotic hybrids are elaborated in this article. Moreover, we discuss several antibiotic hybrids that were or are in clinical evaluation. Mechanistic insights into how tobramycin-based antibiotic hybrids are able to potentiate legacy antibiotics in multidrug-resistant Gram-negative bacilli are also highlighted. Antibiotic hybrids indeed have a promising future as a therapeutic strategy to overcome drug resistance in Gram-negative pathogens and/or expand the usefulness of our current antibiotic arsenal.

Metabolism and hydrophilicity of the polarised 'Janus face' all-cis tetrafluorocyclohexyl ring, a candidate motif for drug discovery

The metabolism and polarity of the all-cis tetra-fluorocyclohexane motif is explored in the context of its potential as a motif for inclusion in drug discovery programmes. Biotransformations of phenyl all-cis tetra-, tri- and di- fluoro cyclohexanes with the human metabolism model organism Cunninghamella elegans illustrates various hydroxylated products, but limited to benzylic hydroxylation for the phenyl all-cis tetrafluorocyclohexyl ring system. Evaluation of the lipophilicities (log P) indicates a significant and progressive increase in polarity with increasing fluorination on the cyclohexane ring system. Molecular dynamics simulations indicate that water associates much more closely with the hydrogen face of these Janus face cyclohexyl rings than the fluorine face owing to enhanced hydrogen bonding interactions with the polarised hydrogens and water.

Imaginative Order from Reasonable Chaos: Conformation-Driven Activity and Reactivity in Exploring Protein–Ligand Interactions

Sir Derek Barton’s seminal work on steroid conformational analysis opened up a new era of enquiry into how the preferred conformation of any molecule could have profound effects on its physical–chemical properties and activities. Conformation-based effects on molecular activity and reactivity continue to manifest, with one key area of investigation currently focussed on conformational entropy in driving protein–ligand interactions. Carrying on from Barton’s initial insight on natural product conformational properties, new questions now address how conformational flexibility within a bioactive natural product structural framework (reasonable chaos), can be directed to confer dynamically new protein–ligand interactions beyond the basic lock–key model (imaginative order). Here we summarise our work on exploring conformational diversity from fluorinated natural product fragments, and how this approach of conformation-coupled diversity-oriented synthesis can be used to iteratively derive ligands with enhanced specificity against highly homologous protein domains. Our results demonstrate that the conformation entropic states of highly conserved protein domains differ significantly, and this conformational diversity, beyond primary sequence analysis, can be duly captured and exploited by natural-product derived ligands with complementary conformational dynamics for enhancing recognition specificity in drug lead discovery.

Computer-Aided Drug Design: An Overview

The term drug design describes the search of novel compounds with biological activity, on a systematic basis. In its most common form, it involves modification of a known active scaffold or linking known active scaffolds, although de novo drug design (i.e., from scratch) is also possible. Though highly interrelated, identification of active scaffolds should be conceptually separated from drug design. Traditionally, the drug design process has focused on the molecular determinants of the interactions between the drug and its known or intended molecular target. Nevertheless, current drug design also takes into consideration other relevant processes than influence drug efficacy and safety (e.g., bioavailability, metabolic stability, interaction with antitargets).This chapter provides an overview on possible approaches to identify active scaffolds (including in silico approximations to approach that task) and computational methods to guide the subsequent optimization process. It also discusses in which situations each of the overviewed techniques is more appropriate.