Small molecule peptidomimetic inhibitors of importin α/ß mediated nuclear transport.

Nucleocytoplasmic transport of macromolecules is a fundamental process of eukaryotic cells. Translocation of proteins and many RNAs between the nucleus and cytoplasm is carried out by shuttling receptors of the ß-karyopherin family, also called importins and exportins. Leptomycin B, a small molecule inhibitor of the exportin CRM1, has proved to be an invaluable tool for cell biologists, but up to now no small molecule inhibitors of nuclear import have been described. We devised a microtiter plate based permeabilized cell screen for small molecule inhibitors of the importin α/ß pathway. By analyzing peptidomimetic libraries, we identified ß-turn and α-helix peptidomimetic compounds that selectively inhibit nuclear import by importin α/ß but not by transportin. Structure-activity relationship analysis showed that large aromatic residues and/or a histidine side chain are required for effective import inhibition by these compounds. Our validated inhibitors can be useful for in vitro studies of nuclear import, and can also provide a framework for synthesis of higher potency nuclear import inhibitors.

AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user.

Protein conformational flexibility prediction using machine learning.

Using a data set of 16 proteins, a neural network has been trained to predict backbone 15N generalized order parameters from the three-dimensional structures of proteins. The final network parameterization contains six input features. The average prediction accuracy, as measured by the Pearson's correlation coefficient between experimental and predicted values of the square of the generalized order parameter is >0.70. Predicted order parameters for non-terminal amino acid residues depends most strongly on the local packing density and the probability that the residue is located in regular secondary structure.

Theoretical study of R(1rho) rotating-frame and R2 free-precession relaxation in the presence of n-site chemical exchange.

The n-site Bloch-McConnell equations describe the evolution of nuclear spin magnetization in the laboratory or rotating frames of reference for molecules subject to chemical or conformational interconversions between n species with distinct NMR chemical shifts. Perturbation theory is used to approximate the largest eigenvalue of the Bloch-McConnell equations and obtain analytical expressions for the rotating-frame relaxation rate constant and for the laboratory frame resonance frequency and transverse relaxation rate constant. The perturbation treatment is valid whenever the population of one site is dominant. The new results are generally applicable to investigations of kinetic processes by NMR spectroscopy.

Temperature-dependent dynamics of the villin headpiece helical subdomain, an unusually small thermostable protein.

(15)N spin relaxation experiments were used to measure the temperature-dependence of protein backbone conformational fluctuations in the thermostable helical subdomain, HP36, of the F-actin-binding headpiece domain of chicken villin. HP36 is the smallest domain of a naturally occurring protein that folds cooperatively to a compact native state. Spin-lattice, spin-spin, and heteronuclear nuclear Overhauser effect relaxation data for backbone amide (15)N spins were collected at five temperatures in the range of 275-305 K. The data were analyzed using a model-free formalism to determine generalized order parameters, S, that describe the distribution of N-H bond vector orientations in a molecular reference frame. A novel parameter, Lambda=dln(1-S)/dln T is introduced to characterize the temperature-dependence of S. An average value of Lambda=4.5 is obtained for residues in helical conformations in HP36. This value of Lambda is not reproduced by model potential energy functions commonly used to parameterize S. The maximum entropy principle was used to derive a new model potential function that reproduces both S and Lambda. Contributions to the entropy, S(r), and heat capacity, C(r)(p), from reorientational conformational fluctuations were analyzed using this potential energy function. Values of S(r) show a qualitative dependence on S similar to that obtained for the diffusion-in-a-cone model; however, quantitative differences of up to 0.5k, in which k is the Boltzmann constant, are observed. Values of C(r)(p) approach zero for small values of S and approach k for large values of S; the largest values of C(r)(p) are predicted to occur for intermediate values of S. The results suggest that backbone dynamics, as probed by relaxation measurements, make very little contribution to the heat capacity difference between folded and unfolded states for HP36.

R1rho relaxation outside of the fast-exchange limit.

Chemical-exchange effects in NMR spectroscopy enable kinetic processes to be characterized at equilibrium in solution. Beginning with the Bloch-McConnell equations, new expressions are derived for the spin relaxation rate constant in the rotating frame, R1rho, for chemical exchange between two sites that have distinct magnetic environments and Larmor frequencies. The results are accurate provided that the spin relaxation decay is dominated by a single exponential damping constant and are applicable to a wider range of conditions than existing theoretical descriptions. The new expressions for R1rho will be particularly useful in analyzing experimental data when exchange is not fast and site populations are unequal.