Structure-based Protocol for Identifying Mutations that Enhance Protein–Protein Binding Affinities

The ability to manipulate protein binding affinities is important for the development of proteins as biosensors, industrial reagents, and therapeutics. We have developed a structure-based method to rationally predict single mutations at protein-protein interfaces that enhance binding affinities. The protocol is based on the premise that increasing buried hydrophobic surface area and/or reducing buried hydrophilic surface area will generally lead to enhanced affinity if large steric clashes are not introduced and buried polar groups are not left without a hydrogen bond partner. The procedure selects affinity enhancing point mutations at the protein-protein interface using three criteria: 1) the mutation must be from a polar amino acid to a non-polar amino acid or from a non-polar amino acid to a larger non-polar amino acid, 2) the free energy of binding as calculated with the Rosetta protein modeling program should be more favorable than the free energy of binding calculated for the wild type complex and 3) the mutation should not be predicted to significantly destabilize the monomers. The Rosetta energy function emphasizes short-range interactions: steric repulsion, Van der Waals forces, hydrogen bonding, and an implicit solvation model that penalizes placing atoms adjacent to polar groups. The performance of the computational protocol was experimentally tested on two separate protein complexes; Gαi1 from the heterotrimeric G-protein system bound to the RGS14 GoLoco motif, and the E2, UbcH7, bound to the E3, E6AP from the ubiquitin pathway. 12 single-site mutations that were predicted to be stabilizing were synthesized and characterized in the laboratory. 9 of the 12 mutations successfully increased binding affinity with 5 of these increasing binding by over 1.0 kcal/mol. To further assess our approach we searched the literature for point mutations that pass our criteria and have experimentally determined binding affinities. Of the 8 mutations identified, 5 were accurately predicted to increase binding affinity, further validating the method as a useful tool to increase protein-protein binding affinities

Estimating the Economic Costs of Espionage

Economic espionage is a serious threat to the vitality of the U.S. economy. While this is a widely accepted fact, there is no formal way to measure the damage an incident of economic espionage has on the U.S. economy. The U.S. government would like to know how damaging economic espionage is on the economy. However, the full repercussions of an incident of economic espionage are never known. A stolen trade secret, over the course of many years, could be used in different products and in different industries. The loss of a trade secret is an immeasurable value. Instead of attempting to measure such an overarching elusive concept, the research team sought to measure the potential consequence of economic espionage. In this study, the research team constructed a model to identify the severity of an incident of economic espionage and its consequences on the U.S. economy. The model was designed for use by federal government employees with the intent that the federal government could apply publically available case information to the model. The model provides a qualitative estimate of “consequence” as it relates to economic loss. The model generates a severity score between 0 and 1, which corresponds to a „low‟, „moderate‟, and „high‟ consequence. The severity score incorporates the model‟s four main variables into two primary components: „Industry‟ and „Case Variables‟. „Industry‟ assesses the significance of where the incident of economic espionage occurred. „Industry‟ is derived from a combination of the percentage of GDP in terms of value added for each of the 14 industries and the „susceptibility‟ of each of the 14 industries. This process enables the model to be individualized to a specific industry, which allows a different potential consequence to the U.S. economy. „Case Variables‟ assess the significance of the incident of economic espionage. „Case Variables‟ include the „Characteristics of the Theft‟, „Cost‟, and „Beneficiary‟ variables. The model requires the user to first select the „Industry‟ where the incident occurred and then to identify the „Case Variables‟. Therefore, the potential consequence on the U.S. economy from an incident of economic espionage is dependent on the industry. To greater individualize the model, the research team designed a method whereby questions within the model would matter more when compared to others. As no two incidents of economic espionage are identical, the research team developed a system of weighing the variables and their respective questions. With all the variables measured, standardized, and weighed against each other, the model calculates an overall severity score, which corresponds to the level of consequence for an incident of economic espionage.CENTRA Technolog

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

Structure-Based Design of Non-Natural Amino Acid Inhibitors of Amyloid Fibrillation

Many globular and natively disordered proteins can convert into amyloid fibers. These fibers are associated with numerous pathologies1 as well as with normal cellular functions2,3, and frequently form during protein denaturation4,5. Inhibitors of pathological amyloid fibers could serve as leads for therapeutics, provided the inhibitors were specific enough to avoid interfering with normal processes. Here we show that computer-aided, structure-based design can yield highly specific peptide inhibitors of amyloid formation. Using known atomic structures of segments of amyloid fibers as templates, we have designed and characterized an all D-amino acid inhibitor of fibrillation of the tau protein found in Alzheimer’s disease, and a non-natural L-amino acid inhibitor of an amyloid fiber that enhances sexual transmission of HIV. Our results indicate that peptides from structure-based designs can disrupt the fibrillation of full-length proteins, including those like tau that lack fully ordered native structures.We thank M.I. Ivanova, J. Corn, T. Kortemme, D. Anderson, M.R. Sawaya, M. Phillips, S. Sambashivan, J. Park, M. Landau, Q. Zhang, R. Clubb, F. Guo, T. Yeates, J. Nowick, J. Zheng, and M.J. Thompson for discussions, HHMI, NIH, NSF, the GATES foundation, and the Joint Center for Translational Medicine for support, R. Peterson for help with NMR experiments, E. Mandelkow for providing tau constructs, R. Riek for providing amyloid beta, J. Stroud for amyloid beta preparation. Support for JK was from the Damon Runyon Cancer Research Foundation, for HWC by the Ruth L. Kirschstein National Research Service Award, for JM from the programme for junior-professors by the ministry of science, Baden-Württemberg, and for SAS by a UCLA-IGERT bioinformatics traineeship

Adaptive Evolution of the Lactose Utilization Network in Experimentally Evolved Populations of Escherichia coli

Adaptation to novel environments is often associated with changes in gene regulation. Nevertheless, few studies have been able both to identify the genetic basis of changes in regulation and to demonstrate why these changes are beneficial. To this end, we have focused on understanding both how and why the lactose utilization network has evolved in replicate populations of Escherichia coli. We found that lac operon regulation became strikingly variable, including changes in the mode of environmental response (bimodal, graded, and constitutive), sensitivity to inducer concentration, and maximum expression level. In addition, some classes of regulatory change were enriched in specific selective environments. Sequencing of evolved clones, combined with reconstruction of individual mutations in the ancestral background, identified mutations within the lac operon that recapitulate many of the evolved regulatory changes. These mutations conferred fitness benefits in environments containing lactose, indicating that the regulatory changes are adaptive. The same mutations conferred different fitness effects when present in an evolved clone, indicating that interactions between the lac operon and other evolved mutations also contribute to fitness. Similarly, changes in lac regulation not explained by lac operon mutations also point to important interactions with other evolved mutations. Together these results underline how dynamic regulatory interactions can be, in this case evolving through mutations both within and external to the canonical lactose utilization network

Tumor Biology and Immune Infiltration Define Primary Liver Cancer Subsets Linked to Overall Survival After Immunotherapy

Primary liver cancer is a rising cause of cancer deaths in the US. Although immunotherapy with immune checkpoint inhibitors induces a potent response in a subset of patients, response rates vary among individuals. Predicting which patients will respond to immune checkpoint inhibitors is of great interest in the field. In a retrospective arm of the National Cancer Institute Cancers of the Liver: Accelerating Research of Immunotherapy by a Transdisciplinary Network (NCI-CLARITY) study, we use archived formalin-fixed, paraffin-embedded samples to profile the transcriptome and genomic alterations among 86 hepatocellular carcinoma and cholangiocarcinoma patients prior to and following immune checkpoint inhibitor treatment. Using supervised and unsupervised approaches, we identify stable molecular subtypes linked to overall survival and distinguished by two axes of aggressive tumor biology and microenvironmental features. Moreover, molecular responses to immune checkpoint inhibitor treatment differ between subtypes. Thus, patients with heterogeneous liver cancer may be stratified by molecular status indicative of treatment response to immune checkpoint inhibitors

<i>De novo</i> design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of 4-fold symmetrical (β/α)(8)-barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of sidechain-backbone hydrogen bonding for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical with the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has only sampled a subset of the sequence space available to the TIM-barrel fold. The ability to de novo design TIM-barrels opens new possibilities for custom-made enzymes

Determining crystal structures through crowdsourcing and coursework

We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality

The role of Social Value Orientation in response to an unfair offer in the Ultimatum Game

Two studies examined the influence of Social Value Orientation (SVO) on the decision to accept or reject an unfair offer in the Ultimatum Game (UG). In both studies, participants with different SVOs (Prosocials, Individualists and Competitors), measured about 3 weeks prior to the UG, responded to an offer of "$8 for Proposer,$2 for Participant", believing it came from a human Proposer. In both studies Prosocials accepted the offer more frequently than Individualists and Competitors, who did not differ. Further, we found that SVO differences in positive emotions in response to the offer (Study 1), and positive cognitions toward the offer and the proposer (Study 2) underlie the SVO effect on UG decision, suggesting a role for SVO differences in the utilization of emotion regulation strategies. Implications of the present findings for "altruistic punishment" and "emotions/self-regulation" accounts as motivators of UG decisions are discussed. (C) 2012 Elsevier Inc. All rights reserved

Intergeneric hybrid plants and methods for production thereof

Methods for the production of an intergeneric hybrid plants and plants produced thereby. In certain aspects, intergeneric hybrid plants are produced by crossing a sorghum parent plant comprising a mutant sorghum iap allele with a second moncot plant. Methods for the use of such plants and products obtained therefrom are also provided.U