Mark A. Hallen

Crystal structure, conformational fixation and entry-related interactions of mature ligand-free HIV-1 Env

As the sole viral antigen on the HIV-1–virion surface, trimeric Env is a focus of vaccine efforts. Here we present the structure of the ligand-free HIV-1–Env trimer, fix its conformation and determine its receptor interactions. Epitope analyses revealed trimeric ligand-free Env to be structurally compatible with broadly neutralizing antibodies but not poorly neutralizing ones. We coupled these compatibility considerations with binding antigenicity to engineer conformationally fixed Envs, including a 201C 433C (DS) variant specifically recognized by broadly neutralizing antibodies. DS-Env retained nanomolar affinity for the CD4 receptor, with which it formed an asymmetric intermediate: a closed trimer bound by a single CD4 without the typical antigenic hallmarks of CD4 induction. Antigenicity-guided structural design can thus be used both to delineate mechanism and to fix conformation, with DS-Env trimers in virus-like-particle and soluble formats providing a new generation of vaccine antigens.

Dead-end elimination with perturbations (DEEPer): a provable protein design algorithm with continuous sidechain and backbone flexibility.

Computational protein and drug design generally require accurate modeling of protein conformations. This modeling typically starts with an experimentally determined protein structure and considers possible conformational changes due to mutations or new ligands. The DEE/A* algorithm provably finds the global minimum‐energy conformation (GMEC) of a protein assuming that the backbone does not move and the sidechains take on conformations from a set of discrete, experimentally observed conformations called rotamers. DEE/A* can efficiently find the overall GMEC for exponentially many mutant sequences. Previous improvements to DEE/A* include modeling ensembles of sidechain conformations and either continuous sidechain or backbone flexibility. We present a new algorithm, DEEPer (Dead‐End Elimination with Perturbations), that combines these advantages and can also handle much more extensive backbone flexibility and backbone ensembles. DEEPer provably finds the GMEC or, if desired by the user, all conformations and sequences within a specified energy window of the GMEC. It includes the new abilities to handle arbitrarily large backbone perturbations and to generate ensembles of backbone conformations. It also incorporates the shear, an experimentally observed local backbone motion never before used in design. Additionally, we derive a new method to accelerate DEE/A*‐based calculations, indirect pruning, that is particularly useful for DEEPer. In 67 benchmark tests on 64 proteins, DEEPer consistently identified lower‐energy conformations than previous methods did, indicating more accurate modeling. Additional tests demonstrated its ability to incorporate larger, experimentally observed backbone conformational changes and to model realistic conformational ensembles. These capabilities provide significant advantages for modeling protein mutations and protein–ligand interactions. Proteins 2013.

Anastral spindle assembly and γ-tubulin in Drosophila oocytes

BackgroundAnastral spindles assemble by a mechanism that involves microtubule nucleation and growth from chromatin. It is still uncertain whether γ-tubulin, a microtubule nucleator essential for mitotic spindle assembly and maintenance, plays a role. Not only is the requirement for γ-tubulin to form anastral Drosophila oocyte meiosis I spindles controversial, but its presence in oocyte meiosis I spindles has not been demonstrated and is uncertain.ResultsWe show, for the first time, using a bright GFP fusion protein and live imaging, that the Drosophila maternally-expressed γTub37C is present at low levels in oocyte meiosis I spindles. Despite this, we find that formation of bipolar meiosis I spindles does not require functional γTub37C, extending previous findings by others. Fluorescence photobleaching assays show rapid recovery of γTub37C in the meiosis I spindle, similar to the cytoplasm, indicating weak binding by γTub37C to spindles, and fits of a new, potentially more accurate model for fluorescence recovery yield kinetic parameters consistent with transient, diffusional binding.ConclusionsThe FRAP results, together with its mutant effects late in meiosis I, indicate that γTub37C may perform a role subsequent to metaphase I, rather than nucleating microtubules for meiosis I spindle formation. Weak binding to the meiosis I spindle could stabilize pre-existing microtubules or position γ-tubulin for function during meiosis II spindle assembly, which follows rapidly upon oocyte activation and completion of the meiosis I division.

Fluorescence Recovery Kinetic Analysis of γ-Tubulin Binding to the Mitotic Spindle

Fluorescence recovery after photobleaching has been widely used to study dynamic processes in the cell, but less frequently to analyze binding interactions and extract binding constants. Here we use it to analyze gamma-tubulin binding to the mitotic spindle and centrosomes to determine the role of gamma-tubulin in microtubule nucleation in the spindle. We find rapid gamma-tubulin turnover in mitotic spindles of Drosophila early embryos, characterized by diffusional interactions and weak binding, differing from centrosomes with tight binding interactions. The diffusion coefficient of gamma-tubulin is consistent with a major species existing in the cytoplasm as the less efficiently nucleating gamma-tubulin small complex (gammaTuSC) or gamma-tubulin, rather than gamma-tubulin ring complex (gammaTuRC). The fluorescence recovery kinetics we observe implies that gamma-tubulin functions by binding weakly to spindle microtubules. gamma-Tubulin may interact transiently with the spindle, nucleating microtubules very rapidly, differing from centrosomes, where gamma-tubulin binds tightly to nucleate microtubules.

Ncd motor binding and transport in the spindle

The Ncd kinesin-14 motor is required for meiotic spindle assembly in Drosophila oocytes and produces force in mitotic spindles that opposes other motors. Despite extensive studies, the way the motor binds to the spindle to perform its functions is not well understood. By analyzing Ncd deleted for the conserved head or the positively charged tail, we found that the tail is essential for binding to spindles and centrosomes, but both the head and tail are needed for normal spindle assembly and function. Fluorescence photobleaching assays to analyze binding interactions with the spindle yielded data for headless and full-length Ncd that did not fit well to previous recovery models. We report a new model that accounts for Ncd transport towards the equator revealed by fluorescence flow analysis of early mitotic spindles and gives rate constants that confirm the dominant role the Ncd tail plays in binding to the spindle. By contrast, the head binds weakly to spindles based on analysis of the tailless fluorescence recovery data. Minus-end Ncd thus binds tightly to spindles and is transported in early metaphase towards microtubule plus-ends, the opposite direction to that in which the motor moves, to produce force in the spindle later in mitosis.

A microtubule-destabilizing kinesin motor regulates spindle length and anchoring in oocytes

The kinesin-13 motor, KLP10A, destabilizes microtubules at their minus ends in mitosis and binds to polymerizing plus ends in interphase, regulating spindle and microtubule dynamics. Little is known about kinesin-13 motors in meiosis. In this study, we report that KLP10A localizes to the unusual pole bodies of anastral Drosophila melanogaster oocyte meiosis I spindles as well as spindle fibers, centromeres, and cortical microtubules. We frequently observe the pole bodies attached to cortical microtubules, indicating that KLP10A could mediate spindle anchoring to the cortex via cortical microtubules. Oocytes treated with drugs that suppress microtubule dynamics exhibit spindles that are reoriented more vertically to the cortex than untreated controls. A dominant-negative klp10A mutant shows both reoriented and shorter oocyte spindles, implying that, unexpectedly, KLP10A may stabilize rather than destabilize microtubules, regulating spindle length and positioning the oocyte spindle. By altering microtubule dynamics, KLP10A could promote spindle reorientation upon oocyte activation.

Mature Drosophila Meiosis I Spindles Comprise Microtubules of Mixed Polarity

New information has been obtained recently regarding microtubule organization in Xenopus extract spindles. These spindles assemble in vitro by chromatin-mediated microtubule nucleation and consist of randomly interspersed long and short microtubules with minus ends distributed throughout the spindle. Fluorescence speckle microscopy has led to the proposal that the Xenopus steady-state spindles contain two overlapping arrays of parallel or antiparallel microtubules with differing poleward-flux velocities. Although some of these features have also been reported for C. elegans female meiotic spindles, it is not clear whether they are representative of microtubule organization and dynamics in oocyte meiotic spindles. Here we examine anastral meiosis I spindles of live Drosophila oocytes expressing the microtubule plus end-tracking protein, EB1, fused to GFP, and find fluorescent particles throughout the spindle and movement toward both the poles and the equator. EB1 particle velocities, corresponding to microtubule growth rates, are similar in both directions, but slower than growth from the poles in mitotic spindles of early embryos. Meiosis I spindles yielded data from photobleaching analysis showing similar microtubule growth rates and dynamics at the poles and the equator, consistent with spindle microtubules of mixed polarity, differing from early-embryo mitotic spindles.

Computation of Steady-State Probability Distributions in Stochastic Models of Cellular Networks

Cellular processes are “noisy”. In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry.

Fast gap‐free enumeration of conformations and sequences for protein design

Despite significant successes in structure‐based computational protein design in recent years, protein design algorithms must be improved to increase the biological accuracy of new designs. Protein design algorithms search through an exponential number of protein conformations, protein ensembles, and amino acid sequences in an attempt to find globally optimal structures with a desired biological function. To improve the biological accuracy of protein designs, it is necessary to increase both the amount of protein flexibility allowed during the search and the overall size of the design, while guaranteeing that the lowest‐energy structures and sequences are found. DEE/A*‐based algorithms are the most prevalent provable algorithms in the field of protein design and can provably enumerate a gap‐free list of low‐energy protein conformations, which is necessary for ensemble‐based algorithms that predict protein binding. We present two classes of algorithmic improvements to the A* algorithm that greatly increase the efficiency of A*. First, we analyze the effect of ordering the expansion of mutable residue positions within the A* tree and present a dynamic residue ordering that reduces the number of A* nodes that must be visited during the search. Second, we propose new methods to improve the conformational bounds used to estimate the energies of partial conformations during the A* search. The residue ordering techniques and improved bounds can be combined for additional increases in A* efficiency. Our enhancements enable all A*‐based methods to more fully search protein conformation space, which will ultimately improve the accuracy of complex biomedically relevant designs. Proteins 2015; 83:1859–1877.

Expanding the scope of quantitative FRAP analysis.

In this study, new mathematical models were developed for analysis of fluorescence recovery after photobleaching (FRAP) data to account for features not represented in previous analysis: conical photobleaching geometry, spatial variations in binding of fluorescent molecules, and directed transport of fluorescent molecules. To facilitate computations in conical geometry, a fast computational method for calculation of fluorescence recovery is presented. Two approximations are presented to aid in FRAP analysis when binding varies spatially, one applying to cases of relatively fast diffusion and slow binding and the other to binding of molecules to small cellular structures. Numerical results show that using a model that represents the influential physical processes and that is formulated in the appropriate geometry can substantially improve the accuracy of FRAP calculations.