Protein Quakes in Redox Metalloenzymes: Clues to Molecular Enzyme Conductivity Triggered by Binding of Small Substrate Molecules.

Multicentre redox metalloproteins undergo conformational changes on electrochemical surfaces, or on enzyme substrate binding. The two-centre copper enzymes, laccase (Type I and TypeII/III Cu) and nitrite reductase (CuNIR) (Type I and Type II Cu) are examples. With some exceptions, these enzymes show no non-turnover voltammetry on Au(111)-surfaces modified by thiol based self-assembled molecular monolayers, but dioxygen or nitrite substrate triggers strong electrocatalytic signals. Scanning tunnelling microscopy also shows high conductivity only when dioxygen or nitrite is present. Atomic force microscopy shows constant CuNIR height but pronounced structural expansion in the electrocatalytic range on nitrite binding. We have recently offered a rationale, based on ab initio quantum chemical studies of water/nitrite substitution in a 740-atom CuNIR fragment. Presently we provide much more detailed structural assignment mapped to single-residue resolution. NO2 --binding induces both a 2 ŠCu-Cu distance increase, and pronounced frontier orbital delocalization strongly facilitating ET between the Cu regions. The conformational changes transmit from the catalytic Type II centre to the electron inlet Type I centre, via the His129-Cys130 ligands, and via Type I-Cys130 or Type I-His129 ending at Type II Asp92. The ET patterns are reflected in different atomic Mulliken charges in the water and nitrite CuNIR fragment.

In vivo uptake of antisense oligonucleotide drugs predicted by ab initio quantum mechanical calculations.

Liver and kidney uptake and antisense activity is studied for a series of Locked Nucleic Acid (LNA) oligonucleotides with fully stereo-defined, internucleoside linkages. These stereo-specific phosphorothioates are made with a newly developed synthesis method and are being analyzed both theoretically and experimentally. Their structures are obtained theoretically by using many-body Schrödinger equations applied to a group of 11 stereo-defined LNA antisense oligonucleotides selected for biological experiments. The fully converged electronic structures were obtained from ab initio quantum calculations providing the specific electronic structures. One important result was the observation that the calculated electronic structure, represented by the iso-surface area of the electron density in Å2, correlated linearly with LNA oligonucleotide uptake in the liver and kidney. This study also shows that more complex biological phenomena, such as drug activity, will require more molecular and cellular identifiers than used here before a correlation can be found. Establishing biological correlations between quantum mechanical (QM) calculated structures and antisense oligonucleotides is novel, and this method may constitute new tools in drug discovery.

Electronic Structures of LNA Phosphorothioate Oligonucleotides.

Important oligonucleotides in anti-sense research have been investigated in silico and experimentally. This involves quantum mechanical (QM) calculations and chromatography experiments on locked nucleic acid (LNA) phosphorothioate (PS) oligonucleotides. iso-potential electrostatic surfaces are essential in this study and have been calculated from the wave functions derived from the QM calculations that provide binding information and other properties of these molecules. The QM calculations give details of the electronic structures in terms of e.g., energy and bonding, which make them distinguish or differentiate between the individual PS diastereoisomers determined by the position of sulfur atoms. Rules are derived from the electronic calculations of these molecules and include the effects of the phosphorothioate chirality and formation of electrostatic potential surfaces. Physical and electrochemical descriptors of the PS oligonucleotides are compared to the experiments in which chiral states on these molecules can be distinguished. The calculations demonstrate that electronic structure, electrostatic potential, and topology are highly sensitive to single PS configuration changes and can give a lead to understanding the activity of the molecules.

A Novel Model on DST-Induced Transplantation Tolerance by the Transfer of Self-Specific Donor tTregs to a Haplotype-Matched Organ Recipient.

Donor-specific blood transfusion (DST) can lead to significant prolongation of allograft survival in experimental animal models and sometimes human recipients of solid organs. The mechanisms responsible for the beneficial effect on graft survival have been a topic of research and debate for decades and are not yet fully elucidated. Once we discover how the details of the mechanisms involved are linked, we could be within reach of a procedure making it possible to establish donor-specific tolerance with minimal or no immunosuppressive medication. Today, it is well established that CD4+Foxp3+ regulatory T cells (Tregs) are indispensable for maintaining immunological self-tolerance. A large number of animal studies have also shown that Tregs are essential for establishing and maintaining transplantation tolerance. In this paper, we present a hypothesis of one H2-haplotype-matched DST-induced transplantation tolerance (in mice). The formulated hypothesis is based on a re-interpretation of data from an immunogenetic experiment published by Niimi and colleagues in 2000. It is of importance that the naïve recipient mice in this study were never immunosuppressed and were therefore fully immune competent during the course of tolerance induction. Based on the immunological status of the recipients, we suggest that one H2-haplotype-matched self-specific Tregs derived from the transfusion blood can be activated and multiply in the host by binding to antigen-presenting cells presenting allopeptides in their major histocompatibility complex (MHC) class II (MHC-II). We also suggest that the endothelial and epithelial cells within the solid organ allograft upregulate the expression of MHC-II and attract the expanded Treg population to suppress inflammation within the graft. We further suggest that this biological process, here termed MHC-II recruitment, is a vital survival mechanism for organs (or the organism in general) when attacked by an immune system.

Analysis of Drug Design for a Selection of G Protein-Coupled Neuro- Receptors Using Neural Network Techniques.

A study is presented on how well possible drug-molecules can be predicted with respect to their function and binding to a selection of neuro-receptors by the use of artificial neural networks. The ligands investigated in this study are chosen to be corresponding to the G protein-coupled receptors µ-opioid, serotonin 2B (5-HT2B) and metabotropic glutamate D5. They are selected due to the availability of pharmacological drug-molecule binding data for these receptors. Feedback and deep belief artificial neural network architectures (NNs) were chosen to perform the task of aiding drugdesign. This is done by training on structural features, selected using a "minimum redundancy, maximum relevance"-test, and testing for successful prediction of categorized binding strength. An extensive comparison of the neural network performances was made in order to select the optimal architecture. Deep belief networks, trained with greedy learning algorithms, showed superior performance in prediction over the simple feedback NNs. The best networks obtained scores of more than 90 % accuracy in predicting the degree of binding drug molecules to the mentioned receptors and with a maximal Matthew`s coefficient of 0.925. The performance of 8 category networks (8 output classes for binding strength) obtained a prediction accuracy of above 60 %. After training the networks, tests were done on how well the systems could be used as an aid in designing candidate drug molecules. Specifically, it was shown how a selection of chemical characteristics could give the lowest observed IC50 values, meaning largest bio-effect pr. nM substance, around 0.03-0.06 nM. These ligand characteristics could be total number of atoms, their types etc. In conclusion, deep belief networks trained on drug-molecule structures were demonstrated as powerful computational tools, able to aid in drug-design in a fast and cheap fashion, compared to conventional pharmacological techniques.

Quantum mechanical studies of DNA and LNA.

Quantum mechanical (QM) methodology has been employed to study the structure activity relations of DNA and locked nucleic acid (LNA). The QM calculations provide the basis for construction of molecular structure and electrostatic surface potentials from molecular orbitals. The topologies of the electrostatic potentials were compared among model oligonucleotides, and it was observed that small structural modifications induce global changes in the molecular structure and surface potentials. Since ligand structure and electrostatic potential complementarity with a receptor is a determinant for the bonding pattern between molecules, minor chemical modifications may have profound changes in the interaction profiles of oligonucleotides, possibly leading to changes in pharmacological properties. The QM modeling data can be used to understand earlier observations of antisense oligonucleotide properties, that is, the observation that small structural changes in oligonucleotide composition may lead to dramatic shifts in phenotypes. These observations should be taken into account in future oligonucleotide drug discovery, and by focusing more on non RNA target interactions it should be possible to utilize the exhibited property diversity of oligonucleotides to produce improved antisense drugs.

Surface enhanced Raman scattering on Tardigrada--towards monitoring and imaging molecular structures in live cryptobiotic organisms.

Tardigrades are microscopic metazoans which are able to survive extreme physical and chemical conditions by entering a stress tolerant state called cryptobiosis. At present, the molecular mechanisms behind cryptobiosis are still poorly understood. We show that surface enhanced Raman scattering supported by plasmonic gold nanoparticles can measure molecular constituents and their local distribution in live tardigrades. Surface enhanced Raman signatures allow to differentiate between two species and indicate molecular structural differences between tardigrades in water and in a dry state. This opens new avenues for exploring cryptobiosis by studying molecular changes in live cryptobiotic organisms.

Structure-activity relationship study of selective excitatory amino acid transporter subtype 1 (EAAT1) inhibitor 2-amino-4-(4-methoxyphenyl)-7-(naphthalen-1-yl)-5-oxo-5,6,7,8-tetrahydro-4H-chromene-3-carbonitrile (UCPH-101) and absolute configurational assignment using infrared and vibrational circular dichroism spectroscopy in combination with ab initio Hartree-Fock calculations.

The excitatory amino acid transporters (EAATs) play essential roles in regulating the synaptic concentration of the neurotransmitter glutamate in the mammalian central nervous system. To date, five subtypes have been identified, named EAAT1-5 in humans, and GLAST, GLT-1, EAAC1, EAAT4, and EAAT5 in rodents, respectively. In this paper, we present the design, synthesis, and pharmacological evaluation of seven 7-N-substituted analogues of UCPH-101/102. Analogue 9 inhibited EAAT1 in the micromolar range (IC(50) value 20 µM), whereas analogues 8 and 10 were inactive (IC(50) values >100 µM). The diastereomeric pairs 11a/11b and 12a/12b were separated by HPLC and the absolute configuration assigned by VCD technique in combination with ab initio Hartree-Fock calculations. Analogues 11a (RS-isomer) and 12b (RR-isomer) inhibited EAAT1 (IC(50) values 5.5 and 3.8 µM, respectively), whereas analogues 11b (SS-isomer) and 12a (SR-isomer) failed to inhibit EAAT1 uptake (IC(50) values >300 µM).

Large scale biomimetic membrane arrays.

To establish planar biomimetic membranes across large scale partition aperture arrays, we created a disposable single-use horizontal chamber design that supports combined optical-electrical measurements. Functional lipid bilayers could easily and efficiently be established across CO(2) laser micro-structured 8 x 8 aperture partition arrays with average aperture diameters of 301 +/- 5 microm. We addressed the electro-physical properties of the lipid bilayers established across the micro-structured scaffold arrays by controllable reconstitution of biotechnological and physiological relevant membrane peptides and proteins. Next, we tested the scalability of the biomimetic membrane design by establishing lipid bilayers in rectangular 24 x 24 and hexagonal 24 x 27 aperture arrays, respectively. The results presented show that the design is suitable for further developments of sensitive biosensor assays, and furthermore demonstrate that the design can conveniently be scaled up to support planar lipid bilayers in large square-centimeter partition arrays.

Protein-induced bilayer perturbations: Lipid ordering and hydrophobic coupling.

The host lipid bilayer is increasingly being recognized as an important non-specific regulator of membrane protein function. Despite considerable progress the interplay between hydrophobic coupling and lipid ordering is still elusive. We use electron spin resonance (ESR) to study the interaction between the model protein gramicidin and lipid bilayers of varying thickness. The free energy of the interaction is up to -6kJ/mol; thus not strongly favored over lipid-lipid interactions. Incorporation of gramicidin results in increased order parameters with increased protein concentration and hydrophobic mismatch. Our findings also show that at high protein:lipid ratios the lipids are motionally restricted but not completely immobilized. Both exchange on and off rate values for the lipid<-->gramicidin interaction are lowest at optimal hydrophobic matching. Hydrophobic mismatch of few A results in up to 10-fold increased exchange rates as compared to the 'optimal' match situation pointing to the regulatory role of hydrophobic coupling in lipid-protein interactions.

Correction to the Beer-Lambert-Bouguer law for optical absorption.

The Beer-Lambert-Bouguer absorption law, known as Beer's law for absorption in an optical medium, is precise only at power densities lower than a few kW. At higher power densities this law fails because it neglects the processes of stimulated emission and spontaneous emission. In previous models that considered those processes, an analytical expression for the absorption law could not be obtained. We show here that by utilizing the Lambert W-function, the two-level energy rate equation model is solved analytically, and this leads into a general absorption law that is exact because it accounts for absorption as well as stimulated and spontaneous emission. The general absorption law reduces to Beer's law at low power densities. A criterion for its application is given along with experimental examples.

Detection of initiation sites in protein folding of the four helix bundle ACBP by chemical shift analysis.

A simple alternative method for obtaining "random coil" chemical shifts by intrinsic referencing using the protein's own peptide sequence is presented. These intrinsic random coil backbone shifts were then used to calculate secondary chemical shifts, that provide important information on the residual secondary structure elements in the acid-denatured state of an acyl-coenzyme A binding protein. This method reveals a clear correlation between the carbon secondary chemical shifts and the amide secondary chemical shifts 3-5 residues away in the primary sequence. These findings strongly suggest transient formation of short helix-like segments, and identify unique sequence segments important for protein folding.

Polymer density functional approach to efficient evaluation of path integrals.

A polymer density functional theory (P-DFT) has been extended to the case of quantum statistics within the framework of Feynman path integrals. We start with the exact P-DFT formalism for an ideal open chain and adapt its efficient numerical solution to the case of a ring. We show that, similarly, the path integral problem can, in principle, be solved exactly by making use of the two-particle pair correlation function (2p-PCF) for the ends of an open polymer, half of the original. This way the exact data for one-dimensional quantum harmonic oscillator are reproduced in a wide range of temperatures. The exact solution is not, though, reachable in three dimensions (3D) because of a vast amount of storage required for 2p-PCF. In order to treat closed paths in 3D, we introduce a so-called "open ring" approximation which proves to be rather accurate in the limit of long chains. We also employ a simple self-consistent iteration so as to correctly account for the interparticle interactions. The algorithm is speeded up by taking convolutions with the aid of fast Fourier transforms. We apply this approximate path integral DFT (PI-DFT) method to systems within spherical symmetry: 3D harmonic oscillator, atoms of hydrogen and helium, and ions of He and Li. Our results compare rather well to the known data, while the computational effort (some seconds or minutes) is about 100 times less than that with Monte Carlo simulations. Moreover, the well-known "sign problem" is expected to be considerably reduced within the reported PI-DFT, since it allows for a direct estimate of the corresponding partition functions.

Analytical tools for solitons and periodic waves corresponding to phonons on Lennard-Jones lattices in helical proteins.

We study the propagation of solitons along the hydrogen bonds of an alpha helix. Modeling the hydrogen and peptide bonds with Lennard-Jones potentials, we show that the solitons can appear spontaneously and have long lifetimes. Remarkably, even if no explicit solution is known for the Lennard-Jones potential, the solitons can be characterized analytically with a good quantitative agreement using formulas for a Toda potential with parameters fitted to the Lennard-Jones potential. We also discuss and show the robustness of the family of periodic solutions called cnoidal waves, corresponding to phonons. The soliton phenomena described in the simulations of alpha helices may help to explain recent x-ray experiments on long alpha helices in Rhodopsin where a long lifetime of the vibrational modes has been observed.

The probability distribution of side-chain conformations in [Leu] and [Met]enkephalin determines the potency and selectivity to mu and delta opiate receptors.

The structure of enkephalin, a small neuropeptide with five amino acids, has been simulated on computers using molecular dynamics. Such simulations exhibit a few stable conformations, which also have been identified experimentally. The simulations provide the possibility to perform cluster analysis in the space defined by potentially pharmacophoric measures such as dihedral angles, side-chain orientation, etc. By analyzing the statistics of the resulting clusters, the probability distribution of the side-chain conformations may be determined. These probabilities allow us to predict the selectivity of [Leu]enkephalin and [Met]enkephalin to the known mu- and delta-type opiate receptors to which they bind as agonists. Other plausible consequences of these probability distributions are discussed in relation to the way in which they may influence the dynamics of the synapse.

A new family of global protein shape descriptors.

A family of global geometric measures is constructed for protein structure classification. These measures originate from integral formulas of Vassiliev knot invariants and give rise to a unique classification scheme. Our measures can better discriminate between many known protein structures than the simple measures of the secondary structure content of these protein structures.

Threshold disorder as a source of diverse and complex behavior in random nets.

We study the diversity of complex spatio-temporal patterns in the behavior of random synchronous asymmetric neural networks (RSANNs). Special attention is given to the impact of disordered threshold values on limit-cycle diversity and limit-cycle complexity in RSANNs which have 'normal' thresholds by default. Surprisingly, RSANNs exhibit only a small repertoire of rather complex limit-cycle patterns when all parameters are fixed. This repertoire of complex patterns is also rather stable with respect to small parameter changes. These two unexpected results may generalize to the study of other complex systems. In order to reach beyond this seemingly disabling 'stable and small' aspect of the limit-cycle repertoire of RSANNs, we have found that if an RSANN has threshold disorder above a critical level, then there is a rapid increase of the size of the repertoire of patterns. The repertoire size initially follows a power-law function of the magnitude of the threshold disorder. As the disorder increases further, the limit-cycle patterns themselves become simpler until at a second critical level most of the limit cycles become simple fixed points. Nonetheless, for moderate changes in the threshold parameters, RSANNs are found to display specific features of behavior desired for rapidly responding processing systems: accessibility to a large set of complex patterns.