Transient tether between the SRP RNA and SRP receptor ensures efficient cargo delivery during cotranslational protein targeting

Kinetic control of macromolecular interactions plays key roles in biological regulation. An example of such control occurs in cotranslational protein targeting by the signal recognition particle (SRP), during which the SRP RNA and the cargo both accelerate complex assembly between the SRP and SRP receptor FtsY 10^2-fold. The molecular mechanism underlying these rate accelerations was unclear. Here we show that a highly conserved basic residue, Lys399, on the lateral surface of FtsY provides a novel RNA tetraloop receptor to mediate the SRP RNA- and cargo-induced acceleration of SRP–FtsY complex assembly. We propose that the SRP RNA, by using its tetraloop to interact with FtsY–Lys399, provides a transient tether to stabilize the early stage and transition state of complex formation; this accelerates the assembly of a stable SRP–FtsY complex and allows the loading of cargo to be efficiently coupled to its membrane delivery. The use of a transient tether to increase the lifetime of collisional intermediates and reduce the dimension of diffusional search represents a novel and effective mechanism to accelerate macromolecular interactions

Likelihood estimation for distributed parameter models for NASA Mini-MAST truss

A maximum likelihood estimation for distributed parameter models of large flexible structures was formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics or finite element models. The closed form solutions for the partial differential equations with corresponding boundary conditions were derived. The closed-form expressions of sensitivity functions led to highly efficient algorithms for analyzing ground or on-orbit test results. For an illustration of this approach, experimental data of the NASA Mini-MAST truss was used. The estimations of modal properties involve lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures

An interdomain hydrogen bond in the Rag GTPases maintains stable mTORC1 signaling in sensing amino acids

Cellular growth and proliferation are primarily dictated by the mechanistic target of rapamycin complex 1 (mTORC1), which balances nutrient availability against the cell\u27s anabolic needs. Central to the activity of mTORC1 is the RagA-RagC GTPase heterodimer, which under favorable conditions recruits the complex to the lysosomal surface to promote its activity. The RagA-RagC heterodimer has a unique architecture in that both subunits are active GTPases. To promote mTORC1 activity, the RagA subunit is loaded with GTP and the RagC subunit is loaded with GDP, while the opposite nucleotide-loading configuration inhibits this signaling pathway. Despite its unique molecular architecture, how the Rag GTPase heterodimer maintains the oppositely loaded nucleotide state remains elusive. Here, we applied structure-function analysis approach to the crystal structures of the Rag GTPase heterodimer and identified a key hydrogen bond that stabilizes the GDP-loaded state of the Rag GTPases. This hydrogen bond is mediated by the backbone carbonyl of Asn30 in the nucleotide-binding domain of RagA or Lys84 of RagC and the hydroxyl group on the side chain of Thr210 in the C-terminal roadblock domain of RagA or Ser266 of RagC, respectively. Eliminating this interdomain hydrogen bond abolishes the ability of the Rag GTPase to maintain its functional state, resulting in a distorted response to amino acid signals. Our results reveal that this long-distance interdomain interaction within the Rag GTPase is required for the maintenance and regulation of the mTORC1 nutrient-sensing pathway

Towards chemical accuracy using a multi-mesh adaptive finite element method in all-electron density functional theory

Chemical accuracy serves as an important metric for assessing the effectiveness of the numerical method in Kohn--Sham density functional theory. It is found that to achieve chemical accuracy, not only the Kohn--Sham wavefunctions but also the Hartree potential, should be approximated accurately. Under the adaptive finite element framework, this can be implemented by constructing the \emph{a posteriori} error indicator based on approximations of the aforementioned two quantities. However, this way results in a large amount of computational cost. To reduce the computational cost, we propose a novel multi-mesh adaptive method, in which the Kohn--Sham equation and the Poisson equation are solved in two different meshes on the same computational domain, respectively. With the proposed method, chemical accuracy can be achieved with less computational consumption compared with the adaptive method on a single mesh, as demonstrated in a number of numerical experiments.Comment: 19pages, 17 figure

Automatic System Testing of Programs without Test Oracles

Metamorphic testing has been shown to be a simple yet effective technique in addressing the quality assurance of applications that do not have test oracles, i.e., for which it is difficult or impossible to know what the correct output should be for arbitrary input. In metamorphic testing, existing test case input is modified to produce new test cases in such a manner that, when given the new input, the application should produce an output that can be easily be computed based on the original output. That is, if input x produces output f (x), then we create input x' such that we can predict f (x') based on f(x); if the application does not produce the expected output, then a defect must exist, and either f (x) or f (x') (or both) is wrong. In practice, however, metamorphic testing can be a manually intensive technique for all but the simplest cases. The transformation of input data can be laborious for large data sets, or practically impossible for input that is not in human-readable format. Similarly, comparing the outputs can be error-prone for large result sets, especially when slight variations in the results are not actually indicative of errors (i.e., are false positives), for instance when there is non-determinism in the application and multiple outputs can be considered correct. In this paper, we present an approach called Automated Metamorphic System Testing. This involves the automation of metamorphic testing at the system level by checking that the metamorphic properties of the entire application hold after its execution. The tester is able to easily set up and conduct metamorphic tests with little manual intervention, and testing can continue in the field with minimal impact on the user. Additionally, we present an approach called Heuristic Metamorphic Testing which seeks to reduce false positives and address some cases of non-determinism. We also describe an implementation framework called Amsterdam, and present the results of empirical studies in which we demonstrate the effectiveness of the technique on real-world programs without test oracles

Using JML Runtime Assertion Checking to Automate Metamorphic Testing in Applications without Test Oracles

It is challenging to test applications and functions for which the correct output for arbitrary input cannot be known in advance, e.g. some computational science or machine learning applications. In the absence of a test oracle, one approach to testing these applications is to use metamorphic testing: existing test case input is modified to produce new test cases in such a manner that, when given the new input, the application should produce an output that can be easily be computed based on the original output. That is, if input x produces output f(x), then we create input x' such that we can predict f(x') based on f(x); if the application or function does not produce the expected output, then a defect must exist, and either f(x) or f(x') (or both) is wrong. By using metamorphic testing, we are able to provide built-in 'pseudo-oracles' for these so-called 'nontestable programs' that have no test oracles. In this paper, we describe an approach in which a function's metamorphic properties are specified using an extension to the Java Modeling Language (JML), a behavioral interface specification language that is used to support the 'design by contract' paradigm in Java applications. Our implementation, called Corduroy, pre-processes these specifications and generates test code that can be executed using JML runtime assertion checking, for ensuring that the specifications hold during program execution. In addition to presenting our approach and implementation, we also describe our findings from case studies in which we apply our technique to applications without test oracles

Synergistic actions between the SRP RNA and translating ribosome allow efficient delivery of the correct cargos during cotranslational protein targeting

During cotranslational protein targeting by the Signal Recognition Particle (SRP), the correct cargo accelerates stable complex assembly between the SRP and SRP receptor (FtsY) by several orders of magnitude, thus enabling rapid and faithful cargo delivery to the target membrane. The molecular mechanism underlying this cargo-induced rate acceleration has been unclear. Here we show that the SRP RNA allows assembly of the SRP–FtsY complex to be specifically stimulated by a correct cargo, and, reciprocally, a correct cargo enables the SRP RNA to optimize its electrostatic interactions with FtsY. These results combined with recent structural work led us to suggest a “conformational selection” model that explains the synergistic action of the SRP RNA with the cargo in accelerating complex assembly. In addition to its previously proposed role in preventing the premature dissociation of SRP and FtsY, we found that the SRP RNA also plays an active role in ensuring the formation of productive assembly intermediates, thus guiding the SRP and FtsY through the most efficient pathway of assembly

Automatic System Testing of Programs without Test Oracles

Metamorphic testing has been shown to be a simple yet effective technique in addressing the quality assurance of applications that do not have test oracles, i.e., for which it is difficult or impossible to know what the correct output should be for arbitrary input. In metamorphic testing, existing test case input is modified to produce new test cases in such a manner that, when given the new input, the application should produce an output that can be easily be computed based on the original output. That is, if input x produces output f (x), then we create input x' such that we can predict f (x') based on f(x); if the application does not produce the expected output, then a defect must exist, and either f (x) or f (x') (or both) is wrong. In practice, however, metamorphic testing can be a manually intensive technique for all but the simplest cases. The transformation of input data can be laborious for large data sets, or practically impossible for input that is not in human-readable format. Similarly, comparing the outputs can be error-prone for large result sets, especially when slight variations in the results are not actually indicative of errors (i.e., are false positives), for instance when there is non-determinism in the application and multiple outputs can be considered correct. In this paper, we present an approach called Automated Metamorphic System Testing. This involves the automation of metamorphic testing at the system level by checking that the metamorphic properties of the entire application hold after its execution. The tester is able to easily set up and conduct metamorphic tests with little manual intervention, and testing can continue in the field with minimal impact on the user. Additionally, we present an approach called Heuristic Metamorphic Testing which seeks to reduce false positives and address some cases of non-determinism. We also describe an implementation framework called Amsterdam, and present the results of empirical studies in which we demonstrate the effectiveness of the technique on real-world programs without test oracles