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L-type amino acid transporter 1 (LAT1) transfers essential amino acids across cell membranes. Owing to its predominant expression in the blood-brain barrier and tumor cells, LAT1 has been exploited for drug delivery and targeting to the central nervous system (CNS) and various cancers. Although the interactions of amino acids and their mimicking compounds with LAT1 have been extensively investigated, the specific structural features for an optimal drug scaffold have not yet been determined. Here, we evaluated a series of LAT1-targeted drug-phenylalanine conjugates (ligands) by determining their uptake rates by in vitro studies and investigating their interaction with LAT1 via induced-fit docking. Combining the experimental and computational data, we concluded that although LAT1 can accommodate various types of structures, smaller compounds are preferred. As the ligand size increased, its flexibility became more crucial in determining the compound's transportability and interactions. Compounds with linear or planar structures exhibited reduced uptake; those with rigid lipophilic structures lacked interactions and likely utilized other transport mechanisms for cellular entry. Introducing polar groups between aromatic structures enhanced interactions. Interestingly, compounds with a carbamate bond in the aromatic ring's para-position displayed very good transport efficiencies for the larger compounds. Compared to the ester bond, the corresponding amide bond had superior hydrogen bond acceptor properties and increased interactions. A reverse amide bond was less favorable than a direct amide bond for interactions with LAT1. The present information can be applied broadly to design appropriate CNS or antineoplastic drug candidates with a prodrug strategy and to discover novel LAT1 inhibitors used either as direct or adjuvant cancer therapy.

Salt-inducible kinases 1-3 (SIK1-3) are key regulators of the LKB1-AMPK pathway and play an important role in cellular homeostasis. Dysregulation of any of the three isoforms has been associated with tumorigenesis in liver, breast, and ovarian cancers. We have recently developed the dual pan-SIK/group I p21-activated kinase (PAK) chemical probe MRIA9. However, inhibition of p21-activated kinases has been associated with cardiotoxicityin vivo, which complicates the use of MRIA9 as a tool compound. Here, we present a structure-based approach involving the back-pocket and gatekeeper residues, for narrowing the selectivity of pyrido[2,3-d]pyrimidin-7(8H)-one-based inhibitors towards SIK kinases, eliminating PAK activity. Optimization was guided by high-resolution crystal structure analysis and computational methods, resulting in a pan-SIK inhibitor, MR22, which no longer exhibited activity on STE group kinases and displayed excellent selectivity in a representative kinase panel. MR22-dependent SIK inhibition led to centrosome dissociation and subsequent cell-cycle arrest in ovarian cancer cells, as observed with MRIA9, conclusively linking these phenotypic effects to SIK inhibition. Taken together, MR22 represents a valuable tool compound for studying SIK kinase function in cells.

Farnesoid X receptor (FXR) is a nuclear receptor with an essential role in regulating bile acid synthesis and cholesterol homeostasis. FXR activation by agonists is explained by an alpha AF-2-trapping mechanism; however, antagonism mechanisms are diverse. We discuss microsecond molecular dynamics (MD) simulations investigating our recently reported FXR antagonists 2a and 2 h. We study the antagonist-induced conformational changes in the FXR ligand-binding domain, when compared to the synthetic (GW4064) or steroidal (chenodeoxycholic acid, CDCA) FXR agonists in the FXR monomer or FXR/RXR heterodimer r, and in the presence and absence of the coactivator. Our MD data suggest ligand-specific influence on conformations of different FXR-LBD regions, including the alpha 5/alpha 6 region, alpha AF-2, and alpha 9-11. Changes in the heterodimerization interface induced by antagonists seem to be associated with alpha AF-2 destabilization, which prevents both co-activator and co-repressor recruitment. Our results provide new insights into the conformational behaviour of FXR, suggesting that FXR antagonism/agonism shift requires a deeper assessment than originally proposed by crystal structures.

The atypical chemokine receptor 3 (ACKR3), formerly known as CXC-chemokine receptor 7 (CXCR7), has been postulated to regulate platelet function and thrombus formation. Herein, we report the discovery and development of first-in-class ACKR3 agonists, which demonstrated superagonistic properties with

Salt-inducible kinases (SIKs) are key metabolic regulators. The imbalance in SIK function is associated with the development of diverse cancers, including breast, gastric, and ovarian cancers. Chemical tools to clarify the roles of SIK in different diseases are, however, sparse and are generally characterized by poor kinome-wide selectivity. Here, we have adapted the pyrido[2,3-d]pyrimidin-7-one-based p21-activated kinase (PAK) inhibitor G-5555 for the targeting of SIK, by exploiting differences in the back-pocket region of these kinases. Optimization was supported by high-resolution crystal structures of G-5555 bound to the known off-targets, MST3 and MST4, leading to a chemical probe, MRIA9, with dual SIK/PAK activity and excellent selectivity over other kinases. Furthermore, we show that MRIA9 sensitizes ovarian cancer cells to treatment with the mitotic agent paclitaxel, confirming earlier data from genetic knockdown studies and suggesting a combination therapy with SIK inhibitors and paclitaxel for the treatment of paclitaxel-resistant ovarian cancer.

Multidrug resistance (MDR) is one of the major factors in the failure of many chemotherapy approaches. In cancer cells, MDR is mainly associated with the expression of ABC transporters such as P‐glycoprotein, MRP1 and ABCG2. Despite major efforts to develop new selective and potent inhibitors of ABC drug transporters, no ABCG2‐specific inhibitors for clinical use are yet available. Here, we report the evaluation of sixteen tetrahydroquinoline/4,5‐dihydroisoxazole derivatives as a new class of ABCG2 inhibitors. The affinity of the five best inhibitors was further investigated by the vanadate‐sensitive ATPase assay. Molecular modelling data, proposing a potential binding mode, suggest that they can inhibit the ABCG2 activity by binding on site S1, previously reported as inhibitors binding region, as well targeting site S2, a selective region for substrates, and by specifically interacting with residues Asn436, Gln398, and Leu555. Altogether, this study provided new insights into THQ/4,5‐dihydroisoxazole molecular hybrids, generating great potential for the development of novel most potent ABCG2 inhibitors., Tetrahydroquinoline/4,5‐dihydroisoxazole hybrids can inhibit the ABCG2 transporter activity and increase the ATP hydrolysis in cells overexpressing ABCG2. Molecular docking and molecular dynamics simulation results suggest that molecular hybrids inhibit ABCG2 activity by binding at the inhibitor binding region, as well as the substrate binding regions.

The main protease (M

We herein report the conventional and microscale parallel synthesis of selective inhibitors of human blood coagulation factor XIIa and thrombin exhibiting a 1,2,4-triazol-5-amine scaffold. Structural variations of this scaffold allowed identifying derivative 21i, a potent 29 nM inhibitor of FXIIa, with improved selectivity over other tested serine proteases and also finding compound 21m with 27 nM inhibitory activity toward thrombin. For the first time, acylated 1,2,4-triazol-5-amines were proved to have anticoagulant properties and the ability to affect thrombin- and cancer-cell-induced platelet aggregation. Performed mass spectrometric analysis and molecular modeling allowed us to discover previously unknown interactions between the synthesized inhibitors and the active site of FXIIa, which uncovered the mechanistic details of FXIIa inhibition. Synthesized compounds represent a promising starting point for the development of novel antithrombotic drugs or chemical tools for studying the role of FXIIa and thrombin in physiological and pathological processes.

After the initial wave of antibiotic discovery, few novel classes of antibiotics have emerged, with the latest dating back to the 1980's. Furthermore, the pace of antibiotic drug discovery is unable to keep up with the increasing prevalence of antibiotic drug resistance. However, the increasing amount of available data promotes the use of machine learning techniques (MLT) in drug discovery projects (In this review, the authors cover some of the applications of MLT in medicinal chemistry, focusing on the development of new antibiotics, the prediction of resistance and its mechanisms. The aim of this review is to illustrate the main advantages and disadvantages and the major trends from studies over the past 5 years.The application of MLT to antibacterial drug discovery can aid the selection of new and potent lead compounds, with desirable pharmacokinetic and toxic profiles for further optimization. The increasing volume of available data along with the constant improvement in computational power and algorithms has meant that we are experiencing a transition in the way we face modern issues such as drug resistance, where our decisions are data-driven and experiments can be focused by data-suggested hypotheses.

Motivation An essential part of drug discovery is the accurate prediction of the binding affinity of new compound–protein pairs. Most of the standard computational methods assume that compounds or proteins of the test data are observed during the training phase. However, in real-world situations, the test and training data are sampled from different domains with different distributions. To cope with this challenge, we propose a deep learning-based approach that consists of three steps. In the first step, the training encoder network learns a novel representation of compounds and proteins. To this end, we combine convolutional layers and long-short-term memory layers so that the occurrence patterns of local substructures through a protein and a compound sequence are learned. Also, to encode the interaction strength of the protein and compound substructures, we propose a two-sided attention mechanism. In the second phase, to deal with the different distributions of the training and test domains, a feature encoder network is learned for the test domain by utilizing an adversarial domain adaptation approach. In the third phase, the learned test encoder network is applied to new compound–protein pairs to predict their binding affinity. Results To evaluate the proposed approach, we applied it to KIBA, Davis and BindingDB datasets. The results show that the proposed method learns a more reliable model for the test domain in more challenging situations. Availability and implementation https://github.com/LBBSoft/DeepCDA.

Structure-based virtual screening of the Enamine database of 1.7 million compounds followed by WaterMap calculations (a molecular-dynamics-simulation-based method) was applied to identify novel acetylcholinesterase (AChE) inhibitors. The inhibitory potency of 29 selected compounds against electric eel (ee) AChE was determined using Ellman's method. Three compounds were found to be active (success rate 10 %). For the most potent compound (∼40 % inhibition at 10 μM), 20 derivatives were discovered based on the Enamine similarity search. Finally, five compounds were found to be promising (IC

In this study, we investigated the delivery of synthetic neurosteroids into MCF-7 human breast adenocarcinoma cells via Organic Anionic Transporting Polypeptides (OATPs) (pH 7.4 and 5.5) to identify the structural components required for OATP-mediated cellular uptake and to get insight into brain drug delivery. Then, we identified structure-uptake relationships using in-house developed OATP1A2 homology model to predict binding sites and modes for the ligands. These binding modes were studied by molecular dynamics simulations to rationalize the experimental results. Our results show that carboxylic acid needs to be at least at 3 carbon-carbon bonds distance from amide bond at the C-3 position of the androstane skeleton and have an amino group to avoid efflux transport. Replacement of hydroxyl group at C-3 with any of the 3, 4, and 5-carbon chained terminal carboxylic groups improved the affinity. We attribute this to polar interactions between carboxylic acid and side-chains of Lys33 and Arg556. The additional amine group showed interactions with Glu172 and Glu200. Based on transporter capacities and efficacies, it could be speculated that the functionalization of acetyl group at the C-17 position of the steroidal skeleton might be explored further to enable OAT1A2-mediated delivery of neurosteroids into the cells and also across the blood-brain barrier.

Compounds simultaneously inhibiting two targets that are involved in the progression of the same complex disease may exhibit additive or even synergistic therapeutic effects. Here we unveil 2,4,5-trisubstituted imidazoles as dual inhibitors of p38α mitogen-activated protein kinase and glycogen synthase kinase 3β (GSK3β). Both enzymes are potential therapeutic targets for neurodegenerative disorders, like Alzheimer's disease. A set of 39 compounds was synthesized and evaluated in kinase activity assays for their ability to inhibit both target kinases. Among the synthesized compounds, potent dual-target-directed inhibitors showing IC50 values down to the low double-digit nanomolar range, were identified. One of the best balanced dual inhibitors presented in here is N-(4-(2-ethyl-4-(4-fluorophenyl)-1H-imidazol-5-yl)pyridin-2-yl)cyclopropanecarboxamide (20c) (p38α, IC50 = 16 nM; GSK3β, IC50 = 35 nM) featuring an excellent metabolic stability and an appreciable isoform selectivity over the closely related GSK3α. Our findings were rationalized by computational docking studies based on previously published X-ray structures.

l-Type amino acid transporter 1 (LAT1) is an interesting protein due to its peculiar expression profile. It can be utilized not only as a carrier for improved or targeted drug delivery, e.g., into the brain but also as a target protein by which amino acid supply can be restricted, e.g., from the cancer cells. The recognition and binding processes of LAT1-ligands, such as amino acids and clinically used small molecules, including l-dopa, gabapentin, and melphalan, are today well-known. Binding to LAT1 is crucial, particularly when designing the LAT1-inhibitors. However, it will not guarantee effective translocation across the cell membrane via LAT1, which is a definite requirement for LAT1-substrates, such as drugs that elicit their pharmacological effects inside the cells. Therefore, in the present study, the accumulation of known LAT1-utilizing compounds into the selected LAT1-expressing cancer cells (MCF-7) was explored experimentally over a time period. The differences found among the transport efficiency and affinity of the studied compounds for LAT1 were subsequently explained by docking the ligands into the human LAT1 model (based on the recent cryo-electron microscopy structure). Thus, the findings of this study clarify the favorable structural requirements of the size, shape, and polarity of the ligands that support the translocation and effective transport across the cell membrane via LAT1. This knowledge can be applied in future drug design to attain improved or targeted drug delivery and hence, successful LAT1-utilizing drugs with increased therapeutic effects.

Drug-target Interactions (DTIs) prediction plays a central role in drug discovery. Computational methods in DTIs prediction have gained more attention because carrying out in vitro and in vivo experiments on a large scale is costly and time-consuming. Machine learning methods, especially deep learning, are widely applied to DTIs prediction. In this study, the main goal is to provide a comprehensive overview of deep learning-based DTIs prediction approaches. Here, we investigate the existing approaches from multiple perspectives. We explore these approaches to find out which deep network architectures are utilized to extract features from drug compound and protein sequences. Also, the advantages and limitations of each architecture are analyzed and compared. Moreover, we explore the process of how to combine descriptors for drug and protein features. Likewise, a list of datasets that are commonly used in DTIs prediction is investigated. Finally, current challenges are discussed and a short future outlook of deep learning in DTI prediction is given.

Water networks within kinase inhibitor design and more widely within drug discovery are generally poorly understood. The successful targeting of these networks prospectively has great promise for all facets of inhibitor design, including potency and selectivity on target. Here we describe the design and testing of a targeted library of 4-anilinoquinolines for use as inhibitors of cyclin G associated kinase (GAK). The GAK cellular target engagement assays, ATP binding site modelling and extensive water mapping provide a clear route to access potent inhibitors for GAK and beyond.

Made available in DSpace on 2020-12-10T20:04:43Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-08-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The enzyme dihydrofolate reductase from M. tuberculosis (MtDHFR) has a high unexploited potential to be a target for new drugs against tuberculosis (TB), due to its importance for pathogen survival. Preliminary studies have obtained fragment-like molecules with low affinity to MtDHFR which can potentially become lead compounds. Taking this into account, the fragment MB872 was used as a prototype for analogue development by bioisosterism/retro-bioisosterism, which resulted in 20 new substituted 3-benzoic acid derivatives. Compounds were active against MtDHFR, with IC50, values ranging from 7 to 40 mu M, where compound 4e not only had the best inhibitory activity (IC50 = 7 mu M), but also was 71-fold more active than the original fragment MB872. The 4e inhibition kinetics indicated an uncompetitive mechanism, which was supported by molecular modeling which suggested that the compounds can access an independent backpocket from the substrate and competitive inhibitors. Thus, based on these results, substituted 3-benzoic acid derivatives have strong potential to be developed as novel MtDHFR inhibitors and also anti-TB agents. Univ Hosp Tubingen, Dept Oncol & Pneurnonol, Internal Med 8, Otfried Muller Str 10, DE-72076 Tubingen, Germany Univ Eastern Finland, Fac Hlth Sci, Sch Pharm, Kuopio 70211, Finland Univ Sao Paulo, Fac Pharmaceut Sci, Dept Pharm, Lab Mol Biol Appl Diag LBMAD, Sao Paulo, SP, Brazil Univ Sao Paulo, Fac Pharmaceut Sci, Lab Design & Synth Bioact Subst LAPESSB, Prof Lineu Prestes Ave 580,Bl 13, Sao Paulo, SP, Brazil Univ Sao Paulo, Fac Pharmaceut Sci, Dept Pharm, Lab Design & Synth Chemotherapeut Potentially Act, Sao Paulo, SP, Brazil Univ Sao Paulo, Inst Biomed Sci, Dept Microbiol, Sao Paulo, SP, Brazil Sao Paulo State Univ, UNESP Amraquara, Dept Biol Sci, Sch Pharmaceut Sci, Sao Paulo, Brazil Univ Sao Paulo, Fac Pharmaceut Sci, Dept Pharm, Prof Lineu Prestes Ave 580,Bl 13, Sao Paulo, SP, Brazil Univ Warwick, Dept Chem, Coventry CV4 7AL, W Midlands, England Sao Paulo State Univ, UNESP Amraquara, Dept Biol Sci, Sch Pharmaceut Sci, Sao Paulo, Brazil CNPq: 153232/2018-8 CNPq: 436791/2018-8 CNPq: 310232/2017-1 FAPESP: 2013/15906-5 FAPESP: 2013/18160-4 FAPESP: 2017/00689-0 FAPESP: 2017/25543-8

WRD5 is a promising target for anticancer drug discovery. In addition, it plays a vital role in epigenetic regulation. Since biological inactivation of WRD5 is difficult to reach via classical approach, PROTACs (Proteolysis Targeting Chimeras) are offering a new option. In a study, published in this journal, new WRD5 targeting PROTACS are introduced. These new compounds, which are also active in cells, make it possible to evaluate the value of WRD5 as a drug target.

Two decades of research into the ligand-dependent modulation of the activity of the peroxisome proliferator-activated receptor γ (PPARγ) have demonstrated the heterogeneous modes of action of PPARγ ligands, in terms of their interaction surfaces in the ligand-binding pocket, binding stoichiometry and ability to interact with functionally important parts of the receptor, through both direct and allosteric mechanisms. These findings signal the complex mechanistic bases of the distinct biological effects of different classes of PPARγ ligands. Today, the development of PPARγ ligands focuses on partial- and non-agonists as opposed to classical agonists, due to the severe side effects observed with PPARγ classical agonists as therapeutic agents. To aid this development, we performed principal component analyses of the atomic (Cartesian) coordinates (cPCA) and dihedral angles (dPCA) of the structures of human PPARγ from X-ray crystallography, available in the public domain, seeking to reveal ligand-induced trends. In the cPCA, projections of the structures along the principal components (PCs) demonstrated a moderate correlation between cPC1 and structural parameters related to the stabilization of helix 12, which is central to the transcriptional activation by PPARγ classical agonists. Consequently, the presented cPCA mapping of the PPARγ-ligand complexes may guide in silico drug discovery programs seeking to avoid stabilization of helix 12 in their development of partial- and non-agonistic PPARγ ligands. Notably, while the dPCA could identify key regions of dihedral fluctuation in the structural ensemble, the distributions along dPC1 - 2 could not be classified according to the same parameters as the distribution along cPC1. Proteins 2017; 85:1684-1698. © 2017 Wiley Periodicals, Inc.

In recent years, the demand and interest for functionalized polymers have increased for drug delivery purposes. Because of the increased interest, methods that can be used to predict physical and chemical properties of polymers prior to synthesis would be of high value for the design and development of novel polymer structures. Through use of molecular descriptors and Principal Component Analysis, this study explores the possibilities of using in silico methods for polymer design and characterization for property prediction. The results presented in this paper suggest that it is possible to produce a model, which can successfully distinguish between a set of both structurally similar and different polymers based on their surface properties.

Enoyl‐acyl carrier protein reductase (FabI) is the limiting step to complete the elongation cycle in type II fatty acid synthase (FAS) systems and is a relevant target for antibacterial drugs. E. coli FabI has been employed as a model to develop new inhibitors against FAS, especially triclosan and diphenyl ether derivatives. Chemical similarity models (CSM) were used to understand which features were relevant for FabI inhibition. Exhaustive screening of different CSM parameter combinations featured chemical groups, such as the hydroxy group, as relevant to distinguish between active/decoy compounds. Those chemical features can interact with the catalytic Tyr156. Further molecular dynamics simulation of FabI revealed the ionization state as a relevant for ligand stability. Also, our models point the balance between potency and the occupancy of the hydrophobic pocket. This work discusses the strengths and weak points of each technique, highlighting the importance of complementarity among approaches to elucidate EcFabI inhibitor's binding mode and offers insights for future drug discovery., Enoyl‐acyl carrier protein reductase (FabI) is an enzyme from the fatty acid synthesis pathway and is considered a relevant target for antibacterial drugs. Triclosan and diphenyl ether derivatives are known to exert their antibacterial activity by inhibiting FabI. In this sense, exhaustive chemical similarity models (CSM) and 200‐ns‐long molecular dynamics simulations were used to understand which features and intermolecular interactions were relevant for FabI inhibition.

Focused libraries of multi-substituted epidithiodiketopiperazines (ETP) were prepared and evaluated for efficacy of inhibiting the nucleocapsid protein function of the Feline Immunodeficiency Virus (FIV) as a model for HIV. This activity was compared and contrasted to observed toxicity utilising an in-vitro cell culture approach. This resulted in the identification of several promising lead compounds with nanomolar potency in cells with low toxicity and a favorable therapeutic index.

The 4-anilinoquinoline and 4-anilinoquinazoline ring systems have been the focus of significant efforts in prior kinase drug discovery programs, which have led to approved medicines. Broad kinome profiles of these compounds have now been assessed with the advent of advanced screening technologies. These ring systems, while originally designed for specific targets including epidermal growth factor receptor (EGFR), but actually display a number of potent collateral kinase targets, some of which have been associated with negative clinical outcomes. We have designed and synthesized a series of 4-anilinoquin(az)olines in order to better understand the structure-activity relationships of three main collateral kinase targets of quin(az)oline-based kinase inhibitors: cyclin G associated kinase (GAK), STE20-like serine/threonine-protein kinase (SLK) and serine/threonine-protein kinase 10 (STK10). This was achieved through a series of quantitative structure-activity relationship (QSAR) analysis, water mapping of the kinase ATP binding sites and extensive small-molecule X-ray structural analysis.

We report the first biological evaluation the 1,2,3-thiaselenazole class of compound and utilising a concise synthetic approach of sulfur extrusion, selenium insertion of the 1,2,3-dithiazoles. We created a small diverse library of compounds to contrast the two ring systems. This approach has highlighted new structure activity relationship insights and lead to the development of sub-micro molar anti-viral compounds with reduced toxicity. The 1,2,3-thiaselenazole represents a new class of potential compounds for the treatment of FIV and HIV.

Antibiotic resistance is posing a continuous threat to global public health and represents a huge burden for society as a whole. In the past decade, the interference with bacterial quorum sensing (QS) (i.e., cell cell communication) mechanisms has extensively been investigated as a valid therapeutic approach in the pursuit of a next generation of antimicrobials. (S)-4,5-Dihydroxy-2,3-pentanedione, commonly known as (S)-DPD, a small signaling molecule that modulates QS in both Gram-negative and Gram-positive bacteria, is phosphorylated by LsrK, and the resulting phospho-DPD activates QS. We designed and prepared a small library of DPD derivatives, characterized by five different scaffolds, and evaluated their LsrK inhibition in the context of QS interference. SAR studies highlighted the pyrazole moiety as an essential structural element for LsrK inhibition. Particularly, four compounds were found to be micromolar LsrK inhibitors (IC50 ranging between 100 mu M and 500 mu M) encouraging further exploration of novel analogues as potential new antimicrobials.

A diverse library of 5-thieno-, 5-oxo-, and 5-imino-1,2,3-dithiazole derivatives was synthesized and evaluated for efficacy against the feline immunodeficiency virus (FIV) as a model for HIV in cells. Several diverse compounds from this series displayed nanomolar activity and low toxicity, representing a potential new class of compounds for the treatment of FIV and HIV.

Structure-based virtual screening using a D2 receptor homology model was performed to identify dopamine D2 receptor ligands as potential antipsychotics. From screening a library of 6.5 million compounds, 21 were selected and were subjected to experimental validation. From these 21 compounds tested, ten D2 ligands were identified (47.6% success rate, among them D2 receptor antagonists, as expected) that have additional affinity for other receptors tested, in particular 5-HT2A receptors. The affinity (Ki values) of the compounds ranged from 58 nm to about 24 μM. Similarity and fragment analysis indicated a significant degree of structural novelty among the identified compounds. We found one D2 receptor antagonist that did not have a protonatable nitrogen atom, which is a key structural element of the classical D2 pharmacophore model necessary for interaction with the conserved Asp(3.32) residue. This compound exhibited greater than 20-fold binding selectivity for the D2 receptor over the D3 receptor. We provide additional evidence that the amide hydrogen atom of this compound forms a hydrogen bond with Asp(3.32), as determined by tests of its derivatives that cannot maintain this interaction.

In order to apply structure-based drug design techniques to GPCR complexes, it is essential to model their 3D structure. For this purpose, a multi-component protocol was derived based on protein-protein docking which generates populations of dimers compatible with membrane integration, considering all reasonable interfaces. At the next stage, we applied a scoring procedure based on up to eleven different parameters including shape or electrostatics complementarity. Two methods of consensus scoring were performed: (i) average scores of 100 best scored dimers with respect to each interface, and (ii) frequencies of interfaces among 100 best scored dimers. In general, our multi-component protocol gives correct indications for dimer interfaces that have been observed in X-ray crystal structures of GPCR dimers (opsin dimer, chemokine CXCR4 and CCR5 dimers, κ opioid receptor dimer, β1 adrenergic receptor dimer and smoothened receptor dimer) but also suggests alternative dimerization interfaces. Interestingly, at times these alternative interfaces are scored higher than the experimentally observed ones suggesting them to be also relevant in the life cycle of studied GPCR dimers. Further results indicate that GPCR dimer and higher-order oligomer formation may involve transmembrane helices (TMs) TM1-TM2-TM7, TM3-TM4-TM5 or TM4-TM5-TM6 but not TM1-TM2-TM3 or TM2-TM3-TM4 which is in general agreement with available experimental and computational data.

In the era of increased antibiotic resistance, targeting enzymes involved in bacterial communication (quorum sensing) represents a new strategy to fight bacterial infections. LsrK is a kinase responsible for the phosphorylation of autoinducer-2, a signaling molecule involved in quorum sensing. Inhibiting LsrK would lead to quorum sensing inactivation and interfere with the pathogenesis. In this study, we built the first LsrK 3D model and performed virtual screening of a locally available database. Selected compounds were tested against LsrK, and the analogue search conducted based on the positive hits led to the identification of low-micromolar LsrK inhibitors. These results prove the utility of the model and provide the first class of LsrK inhibitors to be further optimized as antivirulence agents.

Transcription factors are pivotal regulators of gene transcription, and many diseases are associated with the deregulation of transcriptional networks. In the heart, the transcription factors GATA4 and NKX2-5 are required for cardiogenesis. GATA4 and NKX2-5 interact physically, and the activation of GATA4, in cooperation with NKX2-5, is essential for stretch-induced cardiomyocyte hypertrophy. Here, we report the identification of four small molecule families that either inhibit or enhance the GATA4-NKX2-5 transcriptional synergy. A fragment-based screening, reporter gene assay, and pharmacophore search were utilized for the small molecule screening, identification, and optimization. The compounds modulated the hypertrophic agonist-induced cardiac gene expression. The most potent hit compound, N-[4-(diethylamino)phenyl]-5-methyl-3-phenylisoxazole-4-carboxamide (3, IC50 = 3 mu M), exhibited no activity on the protein kinases involved in the regulation of GATA4 phosphorylation. The identified and chemically and biologically characterized active compound, and its derivatives may provide a novel class of small molecules for modulating heart regeneration.

Two decades of research into the ligand-dependent modulation of the activity of the peroxisome proliferator-activated receptor γ (PPARγ) have demonstrated the heterogeneous modes of action of PPARγ ligands, in terms of their interaction surfaces in the ligand-binding pocket, binding stoichiometry and ability to interact with functionally important parts of the receptor, through both direct and allosteric mechanisms. These findings signal the complex mechanistic bases of the distinct biological effects of different classes of PPARγ ligands. Today, the development of PPARγ ligands focuses on partial- and non-agonists as opposed to classical agonists, due to the severe side effects observed with PPARγ classical agonists as therapeutic agents. To aid this development, we performed principal component analyses of the atomic (Cartesian) coordinates (cPCA) and dihedral angles (dPCA) of the structures of human PPARγ from X-ray crystallography, available in the public domain, seeking to reveal ligand-induced trends. In the cPCA, projections of the structures along the principal components (PCs) demonstrated a moderate correlation between cPC1 and structural parameters related to the stabilization of helix 12, which is central to the transcriptional activation by PPARγ classical agonists. Consequently, the presented cPCA mapping of the PPARγ-ligand complexes may guide in silico drug discovery programs seeking to avoid stabilization of helix 12 in their development of partial- and non-agonistic PPARγ ligands. Notably, while the dPCA could identify key regions of dihedral fluctuation in the structural ensemble, the distributions along dPC1 - 2 could not be classified according to the same parameters as the distribution along cPC1. Proteins 2017; 85:1684-1698. © 2017 Wiley Periodicals, Inc.

9 N-alkylated derivatives of dextromethorphan are synthesized and studied as non-competitive inhibitors of α3β4 nicotinic acetylcholine receptors (nAChRs). In vitro activity towards α3β4 nicotinic acetylcholine receptor is determined using a patch-clamp technique and is in the micromolar range. Homology modeling, molecular docking and molecular dynamics of ligand-receptor complexes in POPC membrane are used to find the mode of interactions of N-alkylated dextromethorphan derivatives with α3β4 nAChR. The compounds, similarly as dextromethorphan, interact with the middle portion of α3β4 nAChR ion channel. Finally, behavioral tests confirmed potential application of the studied compounds for the treatment of addiction.

L-Type amino acid transporter 1 (LAT1) is a transmembrane protein expressed abundantly at the blood-brain barrier (BBB), where it ensures the transport of hydrophobic acids from the blood to the brain. Due to its unique substrate specificity and high expression at the BBB, LAT1 is an intriguing target for carrier-mediated transport of drugs into the brain. In this study, a comparative molecular field analysis (CoMFA) model with considerable statistical quality (Q(2) =0.53, R(2) =0.75, Q(2) SE=0.77, R(2) SE=0.57) and good external predictivity (CCC=0.91) was generated. The model was used to guide the synthesis of eight new prodrugs whose affinity for LAT1 was tested by using an in situ rat brain perfusion technique. This resulted in the creation of a novel LAT1 prodrug with L-tryptophan as the promoiety; it also provided a better understanding of the molecular features of LAT1-targeted high-affinity prodrugs, as well as their promoiety and parent drug. The results obtained will be beneficial in the rational design of novel LAT1-binding prodrugs and other compounds that bind to LAT1.

Herein, we report the development of novel functionalized congeners of ropinirole toward the design of pharmacological tools to probe structural requirements at the dopamine D2 receptor. Subsequently, we have used the functionalized amine congener 11 and synthesized and pharmacologically evaluated a series of homobivalent ligands of ropinirole with designated spacer lengths ranging from 14 to 30 atoms. The most potent homobivalent ligands (22-, 26- and 30-atom spacers) showed approximately 20- to 80-fold greater potency (EC50 = 3.9, 6.2 and 14 nM, respectively) than ropinirole (304 nM) in a [35S]GTPγS functional assay. Molecular modeling studies suggest that the observed increase in potency of the homobivalent ligands is possibly due to a bitopic binding mode involving the orthosteric site and an allosteric interaction at the dopamine D2 receptor protomer rather than bridging interactions at two orthosteric sites across a dopamine D2 receptor dimer. This research has the potential to advance the development of structurally related bitopic ligands, biomarkers such as radioligands and fluorescently labeled probes, and furnish new homo- and heterobivalent ligands towards a better understanding of the dopamine D2 receptor and potential novel treatment for Parkinson's disease.

In the present study, identification of chiral 1,3,4-oxadiazol-2-ones as potent and selective FAAH inhibitors has been described. The separated enantiomers showed clear differences in the potency and selectivity toward both FAAH and MAGL. Additionally, the importance of the chirality on the inhibitory activity and selectivity was proven by the simplification approach by removing a methyl group at the 3-position of the 1,3,4-oxadiazol-2-one ring. The most potent compound of the series, the S-enantiomer of 3-(1-(4-isobutylphenyl)ethyl)-5-methoxy-1,3,4-oxadiazol-2(3H)-one (JZP-327A, 51), inhibited human recombinant FAAH (hrFAAH) in the low nanomolar range (IC50 = 11 nM), whereas its corresponding R-enantiomer 52 showed only moderate inhibition toward hrFAAH (IC50 = 0.24 μM). In contrast to hrFAAH, R-enantiomer 52 was more potent in inhibiting the activity of hrMAGL compared to S-enantiomer 51 (IC50 = 4.0 μM and 16% inhibition at 10 μM, respectively). The FAAH selectivity of the compound 51 over the supposed main off-targets, MAGL and COX, was found to be900-fold. In addition, activity-based protein profiling (ABPP) indicated high selectivity over other serine hydrolases. Finally, the selected S-enantiomers 51, 53, and 55 were shown to be tight binding, slowly reversible inhibitors of the hrFAAH.

Kallikrein-related peptidase 3 (KLK3) is a prostatic serine protease shown to possess antiangiogenic properties which are exerted via its proteolytic activity. The antiangiogenic effect indicates that KLK3 may slow down the growth of prostate cancer; this makes it an interesting target for new therapies for prostate cancer. In this work, new drug-like compounds were discovered that stimulate the proteolytic activity of KLK3. The compounds were identified using 2D similarity search and 3D pharmacophore-based virtual screening, and their ability to stimulate KLK3 was verified by enzymatic activity assays. The effect of the molecules alone was modest, but in synergy with a cyclic peptide the most potent molecule was found to stimulate KLK3 activity significantly: up to 351 % of the activity of KLK3. This demonstrates that small drug-like compounds can be beneficial tools in studying the antiangiogenic properties of KLK3.

SIRT6 belongs to the family of histone deacetylases (class III), but it also has mono-ADP-ribosyltransferase activity. SIRT6 is a nuclear sirtuin that has been associated with aging, cellular protection, and sugar metabolism. Despite these important roles for SIRT6, thus far, there are only a few weak SIRT6 inhibitors available, and no structure-activity relationship (SAR) studies have been published. This is the first study concerning peptides and pseudopeptides as SIRT6 deacetylation inhibitors and the first SAR data concerning SIRT6. We also investigated the molecular interactions using a homology model. We report three compounds exhibiting 62-91% SIRT6 inhibition at 200 μM concentration. These compounds can serve as starting points for systematic SAR studies and SIRT6 inhibitor design.

In 1982, Kuntz et al. published an article with the title “A Geometric Approach to Macromolecule-Ligand Interactions”, where they described a method “to explore geometrically feasible alignment of ligands and receptors of known structure”. Since then, small molecule docking has been employed as a fast way to estimate the binding pose of a given compound within a specific target protein and also to predict binding affinity. Remarkably, the first docking method suggested by Kuntz and colleagues aimed to predict binding poses but very little was specified about binding affinity. This raises the question as to whether docking is the right tool to estimate binding affinity. The short answer is no, and this has been concluded in several comprehensive analyses. However, in this opinion paper we discuss several critical aspects that need to be reconsidered before a reliable binding affinity prediction through docking is realistic. These are not the only issues that need to be considered, but they are perhaps the most critical ones. We also consider that in spite of the huge efforts to enhance scoring functions, the accuracy of binding affinity predictions is perhaps only as good as it was 10–20 years ago. There are several underlying reasons for this poor performance and these are analyzed. In particular, we focus on the role of the solvent (water), the poor description of H-bonding and the lack of the systems’ true dynamics. We hope to provide readers with potential insights and tools to overcome the challenging issues related to binding affinity prediction via docking.

Sirtuins catalyze the NAD+ dependent deacetylation of Ne-acetyl lysine residues to nicotinamide, O′-acetyl-ADP-ribose (OAADPR) and Ne-deacetylated lysine. Here, an easy-to-synthesize Ac-Ala-Lys-Ala sequence has been used as a probe for the screening of novel Ne-modified lysine containing inhibitors against SIRT1 and SIRT2. Ne-Selenoacetyl and Ne-isothiovaleryl were the most potent moieties found in this study, comparable to the widely studied Ne-thioacetyl group. The Ne-3,3-dimethylacryl and Ne-isovaleryl moieties gave significant inhibition in comparison to the Ne-acetyl group present in the substrates. In addition, the studied Ne-alkanoyl, Ne-α,β-unsaturated carbonyl and Ne-aroyl moieties showed that the acetyl binding pocket can accept rather large groups, but is sensitive to even small changes in electronic and steric properties of the Ne-modification. These results are applicable for further screening of Ne-acetyl analogues.

Carbamates are a well-established class of fatty acid amide hydrolase (FAAH) inhibitors. Here we describe the synthesis of meta-substituted phenolic N-alkyl/aryl carbamates and their in vitro FAAH inhibitory activities. The most potent compound, 3-(oxazol-2yl)phenyl cyclohexylcarbamate (2 a), inhibited FAAH with a sub-nanomolar IC(50) value (IC(50)=0.74 nM). Additionally, we developed and validated three-dimensional quantitative structure-activity relationships (QSAR) models of FAAH inhibition combining the newly disclosed carbamates with our previously published inhibitors to give a total set of 99 compounds. Prior to 3D-QSAR modeling, the degree of correlation between FAAH inhibition and in silico reactivity was also established. Both 3D-QSAR methods used, CoMSIA and GRID/GOLPE, produced statistically significant models with coefficient of correlation for external prediction (R(2) (PRED)) values of 0.732 and 0.760, respectively. These models could be of high value in further FAAH inhibitor design.