Stereocontrolled access to thioisosteres of nucleoside di- and triphosphates.

Nucleoside diphosphates and triphosphates impact nearly every aspect of biochemistry; however, the use of such compounds as tools or medicinal leads for nucleotide-dependent enzymes and receptors is hampered by their rapid in vivo metabolism. Although a successful strategy to address the instability of the monophosphate moiety in oligonucleotide therapeutics has been accomplished by their isosteric replacement with phosphorothioates, no practical methods exist to rapidly and controllably access stereopure di- and triphosphate thioisosteres of both natural and unnatural nucleosides. Here we show how a modular, reagent-based platform can enable the stereocontrolled and scalable synthesis of a library of such molecules. This operationally simple approach provides access to pure stereoisomers of nucleoside α-thiodiphosphates and α-thiotriphosphates, as well as symmetrical or unsymmetrical dinucleoside thiodiphosphates and thiotriphosphates (including RNA cap reagents). We demonstrate that ligand-receptor interactions can be dramatically influenced by P-stereochemistry, showing that such thioisosteric replacements can have profound effects on the potency and stability of lead candidates.

The World of GPCR dimers - Mapping dopamine receptor D2 homodimers in different activation states and configuration arrangements.

G protein-coupled receptors (GPCRs) are known to dimerize, but the molecular and structural basis of GPCR dimers is not well understood. In this study, we developed a computational framework to generate models of symmetric and asymmetric GPCR dimers using different monomer activation states and identified their most likely interfaces with molecular details. We chose the dopamine receptor D2 (D2R) homodimer as a case study because of its biological relevance and the availability of structural information. Our results showed that transmembrane domains 4 and 5 (TM4 and TM5) are mostly found at the dimer interface of the D2R dimer and that these interfaces have a subset of key residues that are mostly nonpolar from TM4 and TM5, which was in line with experimental studies. In addition, TM2 and TM3 appear to be relevant for D2R dimers. In some cases, the inactive configuration is unaffected by the partnered protomer, whereas in others, the active protomer adopts the properties of an inactive receptor. Additionally, the ß-arrestin configuration displayed the properties of an active receptor in the absence of an agonist, suggesting that a switch to another meta-state during dimerization occurred. Our findings are consistent with the experimental data, and this method can be adapted to study heterodimers and potentially extended to include additional proteins such as G proteins or ß-arrestins. In summary, this approach provides insight into the impact of the conformational status of partnered protomers on the overall quaternary GPCR macromolecular structure and dynamics.

MUG: A mutation overview of GPCR subfamily A17 receptors.

G protein-coupled receptors (GPCRs) mediate several signaling pathways through a general mechanism that involves their activation, upholding a chain of events that lead to the release of molecules responsible for cytoplasmic action and further regulation. These physiological functions can be severely altered by mutations in GPCR genes. GPCRs subfamily A17 (dopamine, serotonin, adrenergic and trace amine receptors) are directly related with neurodegenerative diseases, and as such it is crucial to explore known mutations on these systems and their impact in structure and function. A comprehensive and detailed computational framework - MUG (Mutations Understanding GPCRs) - was constructed, illustrating key reported mutations and their effect on receptors of the subfamily A17 of GPCRs. We explored the type of mutations occurring overall and in the different families of subfamily A17, as well their localization within the receptor and potential effects on receptor functionality. The mutated residues were further analyzed considering their pathogenicity. The results reveal a high diversity of mutations in the GPCR subfamily A17 structures, drawing attention to the considerable number of mutations in conserved residues and domains. Mutated residues were typically hydrophobic residues enriched at the ligand binding pocket and known activating microdomains, which may lead to disruption of receptor function. MUG as an interactive web application is available for the management and visualization of this dataset. We expect that this interactive database helps the exploration of GPCR mutations, their influence, and their familywise and receptor-specific effects, constituting the first step in elucidating their structures and molecules at the atomic level.

The Many Faces of G Protein-Coupled Receptor 143, an Atypical Intracellular Receptor.

GPCRs transform extracellular stimuli into a physiological response by activating an intracellular signaling cascade initiated via binding to G proteins. Orphan G protein-coupled receptors (GPCRs) hold the potential to pave the way for development of new, innovative therapeutic strategies. In this review we will introduce G protein-coupled receptor 143 (GPR143), an enigmatic receptor in terms of classification within the GPCR superfamily and localization. GPR143 has not been assigned to any of the GPCR families due to the lack of common structural motifs. Hence we will describe the most important motifs of classes A and B and compare them to the protein sequence of GPR143. While a precise function for the receptor has yet to be determined, the protein is expressed abundantly in pigment producing cells. Many GPR143 mutations cause X-linked Ocular Albinism Type 1 (OA1, Nettleship-Falls OA), which results in hypopigmentation of the eyes and loss of visual acuity due to disrupted visual system development and function. In pigment cells of the skin, loss of functional GPR143 results in abnormally large melanosomes (organelles in which pigment is produced). Studies have shown that the receptor is localized internally, including at the melanosomal membrane, where it may function to regulate melanosome size and/or facilitate protein trafficking to the melanosome through the endolysosomal system. Numerous additional roles have been proposed for GPR143 in determining cancer predisposition, regulation of blood pressure, development of macular degeneration and signaling in the brain, which we will briefly describe as well as potential ligands that have been identified. Furthermore, GPR143 is a promiscuous receptor that has been shown to interact with multiple other melanosomal proteins and GPCRs, which strongly suggests that this orphan receptor is likely involved in many different physiological actions.

Class A and C GPCR Dimers in Neurodegenerative Diseases.

Neurodegenerative diseases affect over 30 million people worldwide with an ascending trend. Most individuals suffering from these irreversible brain damages belong to the elderly population, with onset between 50 and 60 years. Although the pathophysiology of such diseases is partially known, it remains unclear upon which point a disease turns degenerative. Moreover, current therapeutics can treat some of the symptoms but often have severe side effects and become less effective in long-term treatment. For many neurodegenerative diseases, the involvement of G proteincoupled receptors (GPCRs), which are key players of neuronal transmission and plasticity, has become clearer and holds great promise in elucidating their biological mechanism. With this review, we introduce and summarize class A and class C GPCRs, known to form heterodimers or oligomers to increase their signalling repertoire. Additionally, the examples discussed here were shown to display relevant alterations in brain signalling and had already been associated with the pathophysiology of certain neurodegenerative diseases. Lastly, we classified the heterodimers into two categories of crosstalk, positive or negative, for which there is known evidence.

Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer.

Globally with over 10 million deaths per year, cancer is the most transversal disease across countries, cultures, and ethnicities, affecting both developed and developing regions. Tumorigenesis is dynamically altered by distinct events and can be lethal when untreated. Despite the innovative therapeutics available, multidrug resistance (MDR) to chemotherapy remains the major hindrance to the success of cancer therapy. The multiple mechanisms by which cancer cells evade cell death are diverse, indicating that MDR involves complex interconnected biological networks. Molecular profiling is currently able to stratify cancer into its distinct subtypes and help identify the best therapeutics, leading to "translational systems medicine". Highly specialized methodologies are generating a large amount of "omics" data - including epigenetics, genomics, transcriptomics, proteomics, metabolomics, as well as pharmacogenomics. Many of the resulting databases store data in non-standard formats, which need to be converted, interpreted, and merged into readable formats. The latest development of artificial intelligence (AI) methodologies and tools, coupled with advancements in large-scale data management and powerful graphic processing computing units, potentiate the integration of these large data sources into relevant biological networks, which will enhance our understanding of cancer MDR. In this review, we revisit common MDR mechanisms and compile a list of the most relevant "omics" public databases. We highlight examples of AI methods that are now decisively contributing to clear advances in cancer research, such as identification of new drugs from large databases and prediction of relevant drug, target, and system properties. An overview of several freely available "ready-to-use" algorithms is also provided. The described molecular scale AI algorithms and tools will undoubtedly guide important improvements in efficiency and efficacy of traditional methods of cancer diagnostics and treatment.

Evidence for Protein-Protein Interaction between Dopamine Receptors and the G Protein-Coupled Receptor 143.

Protein-protein interactions between G protein-coupled receptors (GPCRs) can augment their functionality and increase the repertoire of signaling pathways they regulate. New therapeutics designed to modulate such interactions may allow for targeting of a specific GPCR activity, thus reducing potential for side effects. Dopamine receptor (DR) heteromers are promising candidates for targeted therapy of neurological conditions such as Parkinson's disease since current treatments can have severe side effects. To facilitate development of such therapies, it is necessary to identify the various DR binding partners. We report here a new interaction partner for DRD2 and DRD3, the orphan receptor G protein-coupled receptor 143 (GPR143), an atypical GPCR that plays multiple roles in pigment cells and is expressed in several regions of the brain. We previously demonstrated that the DRD2/ DRD3 antagonist pimozide also modulates GPR143 activity. Using confocal microscopy and two FRET methods, we observed that the DRs and GPR143 colocalize and interact at intracellular membranes. Furthermore, co-expression of wildtype GPR143 resulted in a 57% and 67% decrease in DRD2 and DRD3 activity, respectively, as determined by ß-Arrestin recruitment assay. GPR143-DR dimerization may negatively modulate DR activity by changing affinity for dopamine or delaying delivery of the DRs to the plasma membrane.

An Overview of Antiretroviral Agents for Treating HIV Infection in Paediatric Population.

Paediatric Acquired ImmunoDeficiency Syndrome (AIDS) is a life-threatening and infectious disease in which the Human Immunodeficiency Virus (HIV) is mainly transmitted through Mother-To- Child Transmission (MTCT) during pregnancy, labour and delivery, or breastfeeding. This review provides an overview of the distinct therapeutic alternatives to abolish the systemic viral replication in paediatric HIV-1 infection. Numerous classes of antiretroviral agents have emerged as therapeutic tools for downregulation of different steps in the HIV replication process. These classes encompass Non- Nucleoside Analogue Reverse Transcriptase Inhibitors (NNRTIs), Nucleoside/Nucleotide Analogue Reverse Transcriptase Inhibitors (NRTIs/NtRTIs), INtegrase Inhibitors (INIs), Protease Inhibitors (PIs), and Entry Inhibitors (EIs). Co-administration of certain antiretroviral drugs with Pharmacokinetic Enhancers (PEs) may boost the effectiveness of the primary therapeutic agent. The combination of multiple antiretroviral drug regimens (Highly Active AntiRetroviral Therapy - HAART) is currently the standard therapeutic approach for HIV infection. So far, the use of HAART offers the best opportunity for prolonged and maximal viral suppression, and preservation of the immune system upon HIV infection. Still, the frequent administration of high doses of multiple drugs, their inefficient ability to reach the viral reservoirs in adequate doses, the development of drug resistance, and the lack of patient compliance compromise the complete HIV elimination. The development of nanotechnology-based drug delivery systems may enable targeted delivery of antiretroviral agents to inaccessible viral reservoir sites at therapeutic concentrations. In addition, the application of Computer-Aided Drug Design (CADD) approaches has provided valuable tools for the development of anti-HIV drug candidates with favourable pharmacodynamics and pharmacokinetic properties.

A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods.

Background: Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a molecular basis has not been fully elucidated. Methods: Homology modeling and molecular dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D1-like and D2-like). Fifteen structurally diverse ligands were docked. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for selective binding to DR subtypes. Results: Residues of the aromatic microdomain were shown to be responsible for the majority of ligand interactions established to all DRs. Hydrophobic contacts involved a huge network of conserved and non-conserved residues between three transmembrane domains (TMs), TM2-TM3-TM7. Hydrogen bonds were mostly mediated by the serine microdomain. TM1 and TM2 residues were main contributors for the coupling of large ligands. Some amino acid groups form electrostatic interactions of particular importance for D1R-like selective ligands binding. Conclusions: This in silico approach was successful in showing known receptor-ligand interactions as well as in determining unique combinations of interactions, which will support mutagenesis studies to improve the design of subtype-specific ligands.

Prediction and Targeting of Interaction Interfaces in G-protein Coupled Receptor Oligomers.

BACKGROUND: Communication within a protein complex is mediated by physical interactions made among the protomers. Evidence for both the allosteric regulation present among the protomers of the protein oligomer and of the direct effect of membrane composition on this regulation has made it essential to investigate the underlying molecular mechanism that drives oligomerization, the type of interactions present within the complex, and to determine the identity of the interaction interface. This knowledge allows a holistic understanding of dynamics and also modulation of the function of the resulting oligomers/signalling complexes. G-Protein-Coupled Receptors (GPCRs), which are targeted by 40% of currently prescribed drugs in the market, are widely involved in the formation of such physiological oligomers/signalling complexes. SCOPE: This review highlights the importance of studying Protein-Protein Interactions (PPI) by using a combination of data obtained from cutting-edge experimental and computational methods that were developed for this purpose. In particular, we focused on interaction interfaces found at GPCR oligomers as well as signalling complexes, since any problem associated with these interactions causes the onset of various crucial diseases. CONCLUSION: In order to have a holistic mechanistic understanding of allosteric PPIs that drive the formation of GPCR oligomers and also to determine the composition of interaction interfaces with respect to different membrane compositions, it is essential to combine both relevant experimental and computational data. In this way, efficient and specific targeting of these interaction interfaces in oligomers/ complexes can be achieved. Thus, effective therapeutic molecules with fewer side effects can be designed to modulate the function of these physiologically important receptor family.