Primordial neurosecretory apparatus identified in the choanoflagellate Monosiga brevicollis.

SNARE protein-driven secretion of neurotransmitters from synaptic vesicles is at the center of neuronal communication. In the absence of the cytosolic protein Munc18-1, synaptic secretion comes to a halt. Although it is believed that Munc18-1 orchestrates SNARE complexes, its mode of action is still a matter of debate. In particular, it has been challenging to clarify the role of a tight Munc18/syntaxin 1 complex, because this interaction interferes strongly with syntaxin's ability to form a SNARE complex. In this complex, two regions of syntaxin, the N-peptide and the remainder in closed conformation, bind to Munc18 simultaneously. Until now, this binary complex has been reported for neuronal tissues only, leading to the hypothesis that it might be a specialization of the neuronal secretion apparatus. Here we aimed, by comparing the core secretion machinery of the unicellular choanoflagellate Monosiga brevicollis with that of animals, to reconstruct the ancestral function of the Munc18/syntaxin1 complex. We found that the Munc18/syntaxin 1 complex from M. brevicollis is structurally and functionally highly similar to the vertebrate complex, suggesting that it constitutes a fundamental step in the reaction pathway toward SNARE assembly. We thus propose that the primordial secretion machinery of the common ancestor of choanoflagellates and animals has been co-opted for synaptic roles during the rise of animals.

Analysis of natural variants of the human immunodeficiency virus type 1 gag-pol frameshift stem-loop structure.

Human immunodeficiency virus type 1 uses ribosomal frameshifting for translation of the Gag-Pol polyprotein. Frameshift activities are thought to be tightly regulated. Analysis of gag p1 sequences from 270 plasma virions identified in 64% of the samples the occurrence of polymorphism that could lead to changes in thermodynamic stability of the stem-loop. Expression in Saccharomyces cerevisiae of p1-beta-galactosidase fusion proteins from 10 representative natural stem-loop variants and three laboratory mutant constructs (predicted the thermodynamic stability [Delta G degrees] ranging from -23.0 to -4.3 kcal/mol) identified a reduction in frameshift activity of 13 to 67% compared with constructs with the wild-type stem-loop (Delta G degrees, -23.5 kcal/mol). Viruses carrying stem-loops associated with greater than 60% reductions in frameshift activity presented profound defects in viral replication. In contrast, viruses with stem-loop structures associated with 16 to 42% reductions in frameshift efficiency displayed no significant viral replication deficit.

Experimental analysis and computer prediction of CTF/NFI transcription factor DNA binding sites.

Accurate prediction of transcription factor binding sites is needed to unravel the function and regulation of genes discovered in genome sequencing projects. To evaluate current computer prediction tools, we have begun a systematic study of the sequence-specific DNA-binding of a transcription factor belonging to the CTF/NFI family. Using a systematic collection of rationally designed oligonucleotides combined with an in vitro DNA binding assay, we found that the sequence specificity of this protein cannot be represented by a simple consensus sequence or weight matrix. For instance, CTF/NFI uses a flexible DNA binding mode that allows for variations of the binding site length. From the experimental data, we derived a novel prediction method using a generalised profile as a binding site predictor. Experimental evaluation of the generalised profile indicated that it accurately predicts the binding affinity of the transcription factor to natural or synthetic DNA sequences. Furthermore, the in vitro measured binding affinities of a subset of oligonucleotides were found to correlate with their transcriptional activities in transfected cells. The combined computational-experimental approach exemplified in this work thus resulted in an accurate prediction method for CTF/NFI binding sites potentially functioning as regulatory regions in vivo.

Catechol-binding serines of beta(2)-adrenergic receptors control the equilibrium between active and inactive receptor states.

The binding free energy for the interaction between serines 204 and 207 of the fifth transmembrane helix of the beta(2)-adrenergic receptor (beta(2)-AR) and catecholic hydroxyl (OH) groups of adrenergic agonists was analyzed using double mutant cycles. Binding affinities for catecholic and noncatecholic agonists were measured in wild-type and mutant receptors, carrying alanine replacement of the two serines (S204A, S207A beta(2)-AR), a constitutive activating mutation, or both. The free energy coupling between the losses of binding energy attributable to OH deletion from the ligand and from the receptor indicates a strong interaction (nonadditivity) as expected for a direct binding between the two sets of groups. However, we also measured a significant interaction between the deletion of OH groups from the receptor and the constitutive activating mutation. This suggests that a fraction of the decrease in agonist affinity caused by serine mutagenesis may involve a shift in the conformational equilibrium of the receptor toward the inactive state. Direct measurements using a transient transfection assay confirm this prediction. The constitutive activity of the (S204A, S207A) beta(2)-AR mutant is 50 to 60% lower than that of the wild-type beta(2)-AR. We conclude that S204 and S207 do not only provide a docking site for the agonist, but also control the equilibrium of the receptor between active (R*) and inactive (R) forms.

Fourier transform convolution integrals applied to generalized Born molecular volume.

Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

Binding free energy differences in a TCR-peptide-MHC complex induced by a peptide mutation: a simulation analysis.

Recognition by the T-cell receptor (TCR) of immunogenic peptides presented by class I major histocompatibility complexes (MHCs) is the determining event in the specific cellular immune response against virus-infected cells or tumor cells. It is of great interest, therefore, to elucidate the molecular principles upon which the selectivity of a TCR is based. These principles can in turn be used to design therapeutic approaches, such as peptide-based immunotherapies of cancer. In this study, free energy simulation methods are used to analyze the binding free energy difference of a particular TCR (A6) for a wild-type peptide (Tax) and a mutant peptide (Tax P6A), both presented in HLA A2. The computed free energy difference is 2.9 kcal/mol, in good agreement with the experimental value. This makes possible the use of the simulation results for obtaining an understanding of the origin of the free energy difference which was not available from the experimental results. A free energy component analysis makes possible the decomposition of the free energy difference between the binding of the wild-type and mutant peptide into its components. Of particular interest is the fact that better solvation of the mutant peptide when bound to the MHC molecule is an important contribution to the greater affinity of the TCR for the latter. The results make possible identification of the residues of the TCR which are important for the selectivity. This provides an understanding of the molecular principles that govern the recognition. The possibility of using free energy simulations in designing peptide derivatives for cancer immunotherapy is briefly discussed.

Modelling the curing process in magneto-sensitive polymers: Rate-dependence and shrinkage

This paper deals with a phenomenologically motivated magneto-viscoelastic coupled finite strain framework for simulating the curing process of polymers under the application of a coupled magneto-mechanical road. Magneto-sensitive polymers are prepared by mixing micron-sized ferromagnetic particles in uncured polymers. Application of a magnetic field during the curing process causes the particles to align and form chain-like structures lending an overall anisotropy to the material. The polymer curing is a viscoelastic complex process where a transformation from fluid. to solid occurs in the course of time. During curing, volume shrinkage also occurs due to the packing of polymer chains by chemical reactions. Such reactions impart a continuous change of magneto-mechanical properties that can be modelled by an appropriate constitutive relation where the temporal evolution of material parameters is considered. To model the shrinkage during curing, a magnetic-induction-dependent approach is proposed which is based on a multiplicative decomposition of the deformation gradient into a mechanical and a magnetic-induction-dependent volume shrinkage part. The proposed model obeys the relevant laws of thermodynamics. Numerical examples, based on a generalised Mooney-Rivlin energy function, are presented to demonstrate the model capacity in the case of a magneto-viscoelastically coupled load.

CNDOL: A fast and reliable method for the calculation of electronic properties of very large systems. Applications to retinal binding pocket in rhodopsin and gas phase porphine.

Very large molecular systems can be calculated with the so called CNDOL approximate Hamiltonians that have been developed by avoiding oversimplifications and only using a priori parameters and formulas from the simpler NDO methods. A new diagonal monoelectronic term named CNDOL/21 shows great consistency and easier SCF convergence when used together with an appropriate function for charge repulsion energies that is derived from traditional formulas. It is possible to obtain a priori molecular orbitals and electron excitation properties after the configuration interaction of single excited determinants with reliability, maintaining interpretative possibilities even being a simplified Hamiltonian. Tests with some unequivocal gas phase maxima of simple molecules (benzene, furfural, acetaldehyde, hexyl alcohol, methyl amine, 2,5 dimethyl 2,4 hexadiene, and ethyl sulfide) ratify the general quality of this approach in comparison with other methods. The calculation of large systems as porphine in gas phase and a model of the complete retinal binding pocket in rhodopsin with 622 basis functions on 280 atoms at the quantum mechanical level show reliability leading to a resulting first allowed transition in 483 nm, very similar to the known experimental value of 500 nm of "dark state." In this very important case, our model gives a central role in this excitation to a charge transfer from the neighboring Glu(-) counterion to the retinaldehyde polyene chain. Tests with gas phase maxima of some important molecules corroborate the reliability of CNDOL/2 Hamiltonians.

Molecular mechanism of a green-shifted, pH-dependent red fluorescent protein mKate variant.

Fluorescent proteins that can switch between distinct colors have contributed significantly to modern biomedical imaging technologies and molecular cell biology. Here we report the identification and biochemical analysis of a green-shifted red fluorescent protein variant GmKate, produced by the introduction of two mutations into mKate. Although the mutations decrease the overall brightness of the protein, GmKate is subject to pH-dependent, reversible green-to-red color conversion. At physiological pH, GmKate absorbs blue light (445 nm) and emits green fluorescence (525 nm). At pH above 9.0, GmKate absorbs 598 nm light and emits 646 nm, far-red fluorescence, similar to its sequence homolog mNeptune. Based on optical spectra and crystal structures of GmKate in its green and red states, the reversible color transition is attributed to the different protonation states of the cis-chromophore, an interpretation that was confirmed by quantum chemical calculations. Crystal structures reveal potential hydrogen bond networks around the chromophore that may facilitate the protonation switch, and indicate a molecular basis for the unusual bathochromic shift observed at high pH. This study provides mechanistic insights into the color tuning of mKate variants, which may aid the development of green-to-red color-convertible fluorescent sensors, and suggests GmKate as a prototype of genetically encoded pH sensors for biological studies.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.