The Location and Nature of General Anesthetic Binding Sites on the Active Conformation of Firefly Luciferase; A Time Resolved Photolabeling Study

Firefly luciferase is one of the few soluble proteins that is acted upon by a wide variety of general anesthetics and alcohols; they inhibit the ATP–driven production of light. We have used time–resolved photolabeling to locate the binding sites of alcohols during the initial light output, some 200 ms after adding ATP. The photolabel 3-azioctanol inhibited the initial light output with an IC50 of 200 µM, close to its general anesthetic potency. Photoincorporation of [3H]3-azioctanol into luciferase was saturable but weak. It was enhanced 200 ms after adding ATP but was negligible minutes later. Sequencing of tryptic digests by HPLC–MSMS revealed a similar conformation–dependence for photoincorporation of 3-azioctanol into Glu-313, a residue that lines the bottom of a deep cleft (vestibule) whose outer end binds luciferin. An aromatic diazirine analog of benzyl alcohol with broader side chain reactivity reported two sites. First, it photolabeled two residues in the vestibule, Ser-286 and Ile-288, both of which are implicated with Glu-313 in the conformation change accompanying activation. Second, it photolabeled two residues that contact luciferin, Ser-316 and Ser-349. Thus, time resolved photolabeling supports two mechanisms of action. First, an allosteric one, in which anesthetics bind in the vestibule displacing water molecules that are thought to be involved in light output. Second, a competitive one, in which anesthetics bind isosterically with luciferin. This work provides structural evidence that supports the competitive and allosteric actions previously characterized by kinetic studies

Nucleotide Binding Switches the Information Flow in Ras GTPases

The Ras superfamily comprises many guanine nucleotide-binding proteins (G proteins) that are essential to intracellular signal transduction. The guanine nucleotide-dependent intrinsic flexibility patterns of five G proteins were investigated in atomic detail through Molecular Dynamics simulations of the GDP- and GTP-bound states (SGDP and SGTP, respectively). For all the considered systems, the intrinsic flexibility of SGDP was higher than that of SGTP, suggesting that Guanine Exchange Factor (GEF) recognition and nucleotide switch require higher amplitude motions than effector recognition or GTP hydrolysis. Functional mode, dynamic domain, and interaction energy correlation analyses highlighted significant differences in the dynamics of small G proteins and Gα proteins, especially in the inactive state. Indeed, SGDP of Gαt, is characterized by a more extensive energy coupling between nucleotide binding site and distal regions involved in GEF recognition compared to small G proteins, which attenuates in the active state. Moreover, mechanically distinct domains implicated in nucleotide switch could be detected in the presence of GDP but not in the presence of GTP. Finally, in small G proteins, functional modes are more detectable in the inactive state than in the active one and involve changes in solvent exposure of two highly conserved amino acids in switches I and II involved in GEF recognition. The average solvent exposure of these amino acids correlates in turn with the rate of GDP release, suggesting for them either direct or indirect roles in the process of nucleotide switch. Collectively, nucleotide binding changes the information flow through the conserved Ras-like domain, where GDP enhances the flexibility of mechanically distinct portions involved in nucleotide switch, and favors long distance allosteric communication (in Gα proteins), compared to GTP

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Vibrations in the B-4 rhombic structure

A double minimum six-dimensional Potential energy surface (PES) is determined in symmetry coordinates for the most stable rhombic (D-2h) B-4 isomer in its (1)A(g) electronic ground state by fitting to energies calculated ab initio. The PES exhibits a barrier to the D-4h square structure of 255 cm(-1). The vibrational levels (J=0) are calculated variationally using an approach which involves the Watson kinetic energy operator expressed in normal coordinates. The pattern of about 65 vibrational levels up to 1600 cm-1 for all stable isotopomers is analyzed. Analogous to the inversion in ammonia-like molecules, the rhombus rearrangements lead to splittings of the vibrational levels. In B-4 it is the B-1g (D-4h mode which distorts the square molecule to its planar rhombic form. The anharmonic fundamental vibrational transitions of B-11(4) are calculated to be (splittings in parentheses): G(O) = 2352(22) cm(-1), v(1)(A(1g)) - 1136(24) cm(-1,) v(2)(B-1g)=209(144) cm(-1) v(3)(B-2g)=1198(19)cm(-1), v(4)(B-2u) = 271(24) cm(-1), and v(5) (E-u) = 1030( 166) cm(-1) (D-4h notation). Their variations in all stable isotoporners were investigated. Due to the presence of strong anharmonic resonances between the B-1g in-plane distortion and the B-2u, out-of-plane bending modes. the hiaher overtones and combination levels are difficult to assign unequivocally. (C) 2005 American Institute of Physics

Modeling Chromophores in a Biological Environment: From MM to QM/MM Methods.

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Modeling Chromophores in a Biological Environment: From MM to QM/MM Methods.

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S0 -> S3 transition in recombination products of photodissociated dihalomethanes

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Modeling Chromophores in a Biological Environment: From MM to QM/MM Methods.

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