Kurt Kristiansen

Interaction codes within the family of mammalian Phox and Bem1p domain-containing proteins.

The Phox and Bem1p (PB1) domain constitutes a recently recognized protein-protein interaction domain found in the atypical protein kinase C (aPKC) isoenzymes, λ/ι- and ζPKC; members of mitogen-activated protein kinase (MAPK) modules like MEK5, MEKK2, and MEKK3; and in several scaffold proteins involved in cellular signaling. Among the last group, p62 and Par6 (partitioning-defective 6) are involved in coupling the aPKCs to signaling pathways involved in cell survival, growth control, and cell polarity. By mutation analyses and molecular modeling, we have identified critical residues at the interaction surfaces of the PB1 domains of aPKCs and p62. A basic charge cluster interacts with an acidic loop and helix both in p62 oligomerization and in the aPKC-p62 interaction. Subsequently, we determined the abilities of mammalian PB1 domain proteins to form heteromeric and homomeric complexes mediated by this domain. We report several novel interactions within this family. An interaction between the cell polarity scaffold protein Par6 and MEK5 was found. Furthermore, p62 interacts both with MEK5 and NBR1 in addition to the aPKCs. Evidence for involvement of p62 in MEK5-ERK5 signaling is presented.

A database of mutants and effects of site-directed mutagenesis experiments on G protein-coupled receptors

A database system and computer programs for storage and retrieval of information about guanine nucleotide‐binding protein (G protein) ‐coupled receptor mutants and associated biological effects have been developed. Mutation data on the receptors were collected from the literature and a database of mutants and effects of mutations was developed. The G protein‐coupled receptor, family A, point mutation database (GRAP) provides detailed information on ligand‐binding and signal transduction properties of more than 2130 receptor mutants. The amino acid sequences of receptors for which mutation experiments have been reported were aligned, and from this alignment mutation data may be retrieved. Alternatively, a search form allowing detailed specification of which mutants to retrieve may be used, for example, to search for specific amino acid substitutions, substitutions in specific protein domains or reported biological effects. Furthermore, ligand and bibliographic oriented queries may be performed. GRAP is available on the Internet (URL: http://www‐grap.fagmed.uit.no/GRAP/homepage.html) using the World‐Wide Web system.

TinyGRAP database: a bioinformatics tool to mine G-protein-coupled receptor mutant data.

We gratefully acknowledge the European Union for sponsoring the GPCRDB (project PL950224), and the Norwegian Research Council and the Forskerakademiet, Denmark for their support of O. Edvardsen and K. Kristiansen, respectively.

Molecular modeling of serotonin, ketanserin, ritanserin and their 5-HT2C receptor interactions

Molecular modeling techniques were used to build a three-dimensional model of the rat 5-HT2C receptor, which was used to examine receptor interactions for protonated forms of serotonin, ketanserin and ritanserin. Molecular dynamics simulations which were started with the fluoro benzene moiety of ketanserin and ritanserin oriented towards the cytoplasmic side of the receptor model, produced the strongest antagonist-receptor interactions. The fluoro bezene ring(s) of the antagonists interacted strongly with aromatic residues in the receptor model, which predicts slightly different orientations and ligand-receptor interactions of ketanserin and ritanserin at a putative binding site. The model suggests that Asn333 (transmembrane helix 6) is involved in a hydrogen-bonding interaction with ketanserin, but not with ritanserin. The model also also suggests that the position corresponding to Cys362 (transmembrane helix 7) may be an important determinant for specifying 5-HT2A receptor selectivity in ketanserin binding.

The third helix of the homeodomain of paired class homeodomain proteins acts as a recognition helix both for DNA and protein interactions

The transcription factor Pax6 is essential for the development of the eyes and the central nervous system of vertebrates and invertebrates. Pax6 contains two DNA-binding domains; an N-terminal paired domain and a centrally located homeodomain. We have previously shown that the vertebrate paired-less isoform of Pax6 (Pax6ΔPD), and several other homeodomain proteins, interact with the full-length isoform of Pax6 enhancing Pax6-mediated transactivation from paired domain-DNA binding sites. By mutation analyses and molecular modeling we now demonstrate that, surprisingly, the recognition helix for specific DNA binding of the homeodomains of Pax6 and Chx10 interacts with the C-terminal RED subdomain of the paired domain of Pax6. Basic residues in the recognition helix and the N-terminal arm of the homeodomain form an interaction surface that binds to an acidic patch involving residues in helices 1 and 2 of the RED subdomain. We used fluorescence resonance energy transfer assays to demonstrate such interactions between Pax6 molecules in the nuclei of living cells. Interestingly, two mutations in the homeodomain recognition helix, R57A and R58A, reduced protein–protein interactions, but not DNA binding of Pax6ΔPD. These findings suggest a critical role for the recognition helix and N-terminal arm of the paired class homeodomain in protein–protein interactions.

Protein binding site analysis by means of structural interaction fingerprint patterns.

We introduce a new approach to the known concept of interaction profiles, based on Structural Interaction Fingerprints (SIFt), for precise and rapid binding site description. A set of scripts for batch generation and analysis of SIFt were prepared, and the implementation is computationally efficient and supports parallelization. It is based on a 9-digit binary interaction pattern that describes physical ligand-protein interactions in structures and models of ligand-protein complexes. The tool performs analysis and identifies binding site residues (crucial and auxiliary) and classifies interactions according to type (hydrophobic, aromatic, charge, polar, side chain, and backbone). It is convenient and easy to use, and gives manageable output data for both, interpretation and further processing. In the presented Letter, SIFts are applied to analyze binding sites in models of antagonist-5-HT7 receptor complexes and structures of cyclin dependent kinase 2-ligand complexes.

tGRAP, the G-protein coupled receptors mutant database.

The searchable mutant database tGRAP (previously called tinyGRAP) at the University of Tromsø contains data on mutated G-protein coupled receptors (GPCRs). All data have been extracted from scientific papers and entered manually into the database. The current version of the tGRAP mutant database (tGRAP.uit.no, release 10, April 2001) contains around 10 500 mutants extracted from almost 1400 research papers containing mutant data on five families of GPCRs, i.e. Family A, rhodopsin-like; Family B, secretin-like; Family C, metabotropic glutamate-like; Family D, pheromone; Family E, cAMP receptors. A query form provides rapid and simple access to relevant mutant information. In addition to this query form, a tool that enables the user to access mutation data via sequence alignments has been introduced. The ability to access mutant data from such alignments increases the usefulness of the mutant database and facilitates comparison of mutagenesis data between receptors. Moreover, this tool allows the construction of tailor-made sequence alignment views from any combination of receptors belonging to the same class. The database is available at http://tGRAP.uit.no/.

Identification of Novel Serotonin Transporter Compounds by Virtual Screening

The serotonin (5-hydroxytryptamine, 5-HT) transporter (SERT) plays an essential role in the termination of serotonergic neurotransmission by removing 5-HT from the synaptic cleft into the presynaptic neuron. It is also of pharmacological importance being targeted by antidepressants and psychostimulant drugs. Here, five commercial databases containing approximately 3.24 million drug-like compounds have been screened using a combination of two-dimensional (2D) fingerprint-based and three-dimensional (3D) pharmacophore-based screening and flexible docking into multiple conformations of the binding pocket detected in an outward-open SERT homology model. Following virtual screening (VS), selected compounds were evaluated using in vitro screening and full binding assays and an in silico hit-to-lead (H2L) screening was performed to obtain analogues of the identified compounds. Using this multistep VS/H2L approach, 74 active compounds, 46 of which had Ki values of ≤1000 nM, belonging to 16 structural classes, have been identified, and multiple compounds share no structural resemblance with known SERT binders.

A linear combination of pharmacophore hypotheses as a new tool in search of new active compounds--an application for 5-HT1A receptor ligands.

This study explores a new approach to pharmacophore screening involving the use of an optimized linear combination of models instead of a single hypothesis. The implementation and evaluation of the developed methodology are performed for a complete known chemical space of 5-HT1AR ligands (3616 active compounds with K i < 100 nM) acquired from the ChEMBL database. Clusters generated from three different methods were the basis for the individual pharmacophore hypotheses, which were assembled into optimal combinations to maximize the different coefficients, namely, MCC, accuracy and recall, to measure the screening performance. Various factors that influence filtering efficiency, including clustering methods, the composition of test sets (random, the most diverse and cluster population-dependent) and hit mode (the compound must fit at least one or two models from a final combination) were investigated. This method outmatched both single hypothesis and random linear combination approaches.

Substrate binding and translocation of the serotonin transporter studied by docking and molecular dynamics simulations

AbstractThe serotonin (5-HT) transporter (SERT) plays an important role in the termination of 5-HT-mediated neurotransmission by transporting 5-HT away from the synaptic cleft and into the presynaptic neuron. In addition, SERT is the main target for antidepressant drugs, including the selective serotonin reuptake inhibitors (SSRIs). The three-dimensional (3D) structure of SERT has not yet been determined, and little is known about the molecular mechanisms of substrate binding and transport, though such information is very important for the development of new antidepressant drugs. In this study, a homology model of SERT was constructed based on the 3D structure of a prokaryotic homologous leucine transporter (LeuT) (PDB id: 2A65). Eleven tryptamine derivates (including 5-HT) and the SSRI (S)-citalopram were docked into the putative substrate binding site, and two possible binding modes of the ligands were found. To study the conformational effect that ligand binding may have on SERT, two SERT–5-HT and two SERT–(S)-citalopram complexes, as well as the SERT apo structure, were embedded in POPC lipid bilayers and comparative molecular dynamics (MD) simulations were performed. Our results show that 5-HT in the SERT–5-HTB complex induced larger conformational changes in the cytoplasmic parts of the transmembrane helices of SERT than any of the other ligands. Based on these results, we suggest that the formation and breakage of ionic interactions with amino acids in transmembrane helices 6 and 8 and intracellular loop 1 may be of importance for substrate translocation. Graphical abstractSERT–5-HTB binding mode