Characterization of Ionizable Groups' Environments in Proteins and Protein-Ligand Complexes through a Statistical Analysis of the Protein Data Bank

We conduct a statistical analysis of the molecular environment of common ionizable functional groups in both protein-ligand complexes and inside proteins from the Protein Data Bank (PDB). In particular, we characterize the frequency, type, and density of the interacting atoms as well as the presence of a potential counterion. We found that for ligands, most guanidinium groups, half of primary and secondary amines, and one-fourth of imidazole neighbor a carboxylate group. Tertiary amines bind more rarely near carboxylate groups, which may be explained by a crowded neighborhood and hydrophobic character. In comparison to the environment seen by the ligands, inside proteins, an environment enriched in main-chain atoms is found, and the prevalence of direct charge neutralization by carboxylate groups is different. When the ionizable character of water molecules and phenolic or hydroxyl groups is accounted, considering a high-resolution dataset (less than 1.5 A), charge neutralization could occur for well above 80% of the ligand functional groups considered, but for tertiary amines.Peer reviewe

Determinants of Orexin Receptor Binding and Activation—A Molecular Dynamics Study

We assess the stability of two previously suggested binding modes for the neuropeptide orexin-A in the OX2 receptor through extensive molecular dynamics simulations. As the activation determinants of the receptor remain unknown, we simulated an unliganded receptor and two small-molecular ligands, the antagonist suvorexant and the agonist Nag26 for comparison. Each system was simulated in pure POPC membrane as well as in the 25% cholesterol–POPC membrane. In total, we carried out 36 μs of simulations. Through this set of simulations, we report a stable binding mode for the C-terminus of orexin-A. In addition, we suggest interactions that would promote orexin receptor activation, as well as others that would stabilize the inactive state.Peer reviewe

Cartography of rhodopsin-like G protein-coupled receptors across vertebrate genomes

We conduct a cartography of rhodopsin-like non-olfactory G protein-coupled receptors in the Ensembl database. The most recent genomic data (releases 90-92, 90 vertebrate genomes) are analyzed through the online interface and receptors mapped on phylogenetic guide trees that were constructed based on a set of similar to 14.000 amino acid sequences. This snapshot of genomic data suggest vertebrate genomes to harbour 142 clades of GPCRs without human orthologues. Among those, 69 have not to our knowledge been mentioned or studied previously in the literature, of which 28 are distant from existing receptors and likely new orphans. These newly identified receptors are candidates for more focused evolutionary studies such as chromosomal mapping as well for in-depth pharmacological characterization. Interestingly, we also show that 37 of the 72 human orphan (or recently deorphanized) receptors included in this study cluster into nineteen closely related groups, which implies that there are less ligands to be identified than previously anticipated. Altogether, this work has significant implications when discussing nomenclature issues for GPCRs.Peer reviewe

Modeling of the OX1R-orexin-A complex suggests two alternative binding modes

Background: Interactions between the orexin peptides and their cognate OX1 and OX2 receptors remain poorly characterized. Site-directed mutagenesis studies on orexin peptides and receptors have indicated amino acids important for ligand binding and receptor activation. However, a better understanding of specific pairwise interactions would benefit small molecule discovery. Results: We constructed a set of three-dimensional models of the orexin 1 receptor based on the 3D-structures of the orexin 2 receptor (released while this manuscript was under review), neurotensin receptor 1 and chemokine receptor CXCR4, conducted an exhaustive docking of orexin-A(16-33) peptide fragment with ZDOCK and RDOCK, and analyzed a total of 4301 complexes through multidimensional scaling and clustering. The best docking poses reveal two alternative binding modes, where the C-terminus of the peptide lies deep in the binding pocket, on average about 5-6 angstrom above Tyr(6.48) and close to Gln(3.32). The binding modes differ in the about 100 degrees rotation of the peptide; the peptide His26 faces either the receptor's fifth transmembrane helix or the seventh helix. Both binding modes are well in line with previous mutation studies and partake in hydrogen bonding similar to suvorexant. Conclusions: We present two binding modes for orexin-A into orexin 1 receptor, which help rationalize previous results from site-directed mutagenesis studies. The binding modes should serve small molecule discovery, and offer insights into the mechanism of receptor activation.Peer reviewe

Integral membrane pyrophosphatases : A novel drug target for human pathogens?

Membrane-integral pyrophosphatases (mPPases) are found in several human pathogens, including Plasmodium species, the protozoan parasites that cause malaria. These enzymes hydrolyze pyrophosphate and couple this to the pumping of ions (H+ and/or Na+) across a membrane to generate an electrochemical gradient. mPPases play an important role in stress tolerance in plants, protozoan parasites, and bacteria. The solved structures of mPPases from Vigna radiata and Thermotoga maritima open the possibility of using structure-based drug design to generate novel molecules or repurpose known molecules against this enzyme. Here, we review the current state of knowledge regarding mPPases, focusing on their structure, the proposed mechanism of action, and their role in human pathogens. We also summarize different methodologies in structure-based drug design and propose an example region on the mPPase structure that can be exploited by these structure-based methods for drug targeting. Since mPPases are not found in animals and humans, this enzyme is a promising potential drug target against livestock and human pathogens. © 2016, Adrian Goldman, et al.Peer reviewe

IDAAPM : integrated database of ADMET and adverse effects of predictive modeling based on FDA approved drug data

Background: The disposition of a pharmaceutical compound within an organism, i.e. its Absorption, Distribution, Metabolism, Excretion, Toxicity (ADMET) properties and adverse effects, critically affects late stage failure of drug candidates and has led to the withdrawal of approved drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and ADMET or adverse effects, but this is limited by the size, quality, and heterogeneity of the data available from individual sources. Thus, large, clean and integrated databases of approved drug data, associated with fast and efficient predictive tools are desirable early in the drug discovery process. Description: We have built a relational database (IDAAPM) to integrate available approved drug data such as drug approval information, ADMET and adverse effects, chemical structures and molecular descriptors, targets, bioactivity and related references. The database has been coupled with a searchable web interface and modern data analytics platform (KNIME) to allow data access, data transformation, initial analysis and further predictive modeling. Data were extracted from FDA resources and supplemented from other publicly available databases. Currently, the database contains information regarding about 19,226 FDA approval applications for 31,815 products (small molecules and bio-logics) with their approval history, 2505 active ingredients, together with as many ADMET properties, 1629 molecular structures, 2.5 million adverse effects and 36,963 experimental drug-target bioactivity data. Conclusion: IDAAPM is a unique resource that, in a single relational database, provides detailed information on FDA approved drugs including their ADMET properties and adverse effects, the corresponding targets with bioactivity data, coupled with a data analytics platform. It can be used to perform basic to complex drug-target ADMET or adverse effects analysis and predictive modeling. IDAAPM is freely accessible at http://idaapm.helsinki.fi and can be exploited through a KNIME workflow connected to the database.Peer reviewe

Stapled truncated orexin peptides as orexin receptor agonists

The peptides orexin-A and -B, the endogenous agonists of the orexin receptors, have similar 19-amino-acid C-termini which retain full maximum response as truncated peptides with only marginally reduced potency, while further N-terminal truncations successively reduce the activity. The peptides have been suggested to bind in an α‐helical conformation, and truncation beyond a certain critical length is likely to disrupt the overall helical structure. In this study, we set out to stabilize the α‐helical conformation of orexin‐A15–33 via peptide stapling at four different sites. At a suggested hinge region, we varied the length of the cross-linker as well as replaced the staple with two α-aminoisobutyric acid residues. Modifications close to the peptide C‐terminus, which is crucial for activity, were not allowed. However, central and N‐terminal modifications yielded bioactive peptides, albeit with decreased potencies. This provides evidence that the orexin receptors can accommodate and be activated by α-helical peptides. The decrease in potency is likely linked to a stabilization of suboptimal peptide conformation or blocking of peptide backbone–receptor interactions at the hinge region by the helical stabilization or the modified amino acids.Peer reviewe

Orexin receptor agonist Yan 7874 is a weak agonist of orexin/hypocretin receptors and shows orexin receptor-independent cytotoxicity

Two promising lead structures of small molecular orexin receptor agonist have been reported, but without detailed analyses of the pharmacological properties. One of them, 1(3,4-dichloropheny1)-242-imino-3-(4-methylbenzy1)-2,3-dihydro-1H-benzo[climidazol-1-yl] ethan-1-ol (Yan 7874), is commercially available, and we set out to analyze its properties. As test system we utilized human OX1 and OX2 orexin receptor -expressing Chinese hamster ovary (CHO) K1 cells as well as control CHO-K1 and neuro-2a neuroblastoma cells. Gq-coupling was assessed by measurement of intracellular Ca2+ and phospholipase C activity, and the coupling to G(i) and G(s) by adenylyl cyclase inhibition and stimulation, respectively. At concentrations above 1 pM, strong Ca' and low phospholipase C responses to Yan 7874 were observed in both OX1- and OX2-expressing cells. However, a major fraction of the response was not mediated by orexin receptors, as determined utilizing the nonselective orexin receptor antagonist N-biphenyl-2-y1-1-{[(1-methyl-1H-benzimidazol-2-y1) sulfanyl]acetyl}-L-prolinamide (TCS 1102) as well as control CHO-K1 cells. Yan 7874 did not produce any specific adenylyl cyclase response. Some experiments suggested an effect on cell viability by Yan 7874, and we thus analyzed this. Within a few hours of exposure, Yan 7874 markedly changed cell morphology (shrunken, rich in vacuoles), reduced growth, promoted cell detachment, and induced necrotic cell death. The effect was equal in cells expressing orexin receptors or not. Thus, Yan 7874 is a weak partial agonist of orexin receptors. It also displays strong off -target effects in the same concentration range, culminating in necrotic cell demise. This makes Yan 7874 unsuitable as orexin receptor agonist.Peer reviewe

Analysis of Biologics Molecular Descriptors towards Predictive Modelling for Protein Drug Development Using Time-Gated Raman Spectroscopy

Pharmaceutical proteins, compared to small molecular weight drugs, are relatively fragile molecules, thus necessitating monitoring protein unfolding and aggregation during production and post-marketing. Currently, many analytical techniques take offline measurements, which cannot directly assess protein folding during production and unfolding during processing and storage. In addition, several orthogonal techniques are needed during production and market surveillance. In this study, we introduce the use of time-gated Raman spectroscopy to identify molecular descriptors of protein unfolding. Raman spectroscopy can measure the unfolding of proteins in-line and in real-time without labels. Using K-means clustering and PCA analysis, we could correlate local unfolding events with traditional analytical methods. This is the first step toward predictive modeling of unfolding events of proteins during production and storage