Inhibitors of \u3cem\u3eN\u3csup\u3eα\u3c/sup\u3e\u3c/em\u3e-acetyl-l-ornithine Deacetylase: Synthesis, Characterization and Analysis of their Inhibitory Potency

A series of N α-acyl (alkyl)- and N α-alkoxycarbonyl-derivatives of l- and d-ornithine were prepared, characterized, and analyzed for their potency toward the bacterial enzyme N α-acetyl-l-ornithine deacetylase (ArgE). ArgE catalyzes the conversion of N α-acetyl-l-ornithine to l-ornithine in the fifth step of the biosynthetic pathway for arginine, a necessary step for bacterial growth. Most of the compounds tested provided IC50 values in the μM range toward ArgE, indicating that they are moderately strong inhibitors. N α-chloroacetyl-l-ornithine (1g) was the best inhibitor tested toward ArgE providing an IC50 value of 85 μM while N α-trifluoroacetyl-l-ornithine (1f), N α-ethoxycarbonyl-l-ornithine (2b), and N α-acetyl-d-ornithine (1a) weakly inhibited ArgE activity providing IC50 values between 200 and 410 μM. Weak inhibitory potency toward Bacillus subtilis-168 for N α-acetyl-d-ornithine (1a) and N α-fluoro- (1f), N α-chloro- (1g), N α-dichloro- (1h), and N α-trichloroacetyl-ornithine (1i) was also observed. These data correlate well with the IC50 values determined for ArgE, suggesting that these compounds might be capable of getting across the cell membrane and that ArgE is likely the bacterial enzymatic target

Enhanced selectivity of oxytocin antagonists containing sarcosine in position 7

Neurohypophyseal hormone analogues containing sarcosine (Sar) in position 7 were prepared to design more potent and selective oxytocin antagonists. The three analogues (1-3) of [Sar7]arginine-vasopressin ([Sar7]AVP) and six analogues (4-9) of [Sar7]arginine-vasotocin ([Sar7]AVT) had a reduced affinity for antidiuretic V2 receptors. The [Sar7]AVP derivatives (1-3) were potent antiuterotonic (in vitro pA2 = 7.5-8.4, in vivo 6.6-7.1) and antipressor (pA2 = 7.2-8.0) agents. The [Sar7]AVT analogues (4-9) were more potent and selective uterotonic antagonists (in vitro pA2 = 7.9-8.6, in vivo 7.1-7.5); their antipressor potencies were reduced (pA2 = 6.4-7.7). The change of the antagonistic potencies was paralleled by a change in the receptor affinities. Among other antiuterotonic analogues, [Mca1, D-Phe2, Sar7]AVT (4, Mca = beta-mercapto- beta,beta-cyclopentamethyl-enepropionic acid) and [Mca1, D-Tyr(OEt)2,Sar7]AVT (6) were synthesized, two highly potent antiuterotonic compounds (in vitro pA2 = 8.3, in vivo 7.4 and 7.5, respectively) with reduced antipressor activity (pA2 = 6.4) and reduced binding affinity to V2 receptors (Kd = 421 and 35 nM, respectively) and no anti-antidiuretic effect. Another potent antiuterotonic analogue, [Mca1,D-Trp2,-Sar7]AVT (9, in vitro pA2capability to V2 receptors (Kd approximately 0.3 mM). These analogues should lead to the design of even more potent and selective oxytocin antagonists

Pegasus: Performance Engineering for Software Applications Targeting HPC Systems

Developing and optimizing software applications for high performance and energy efficiency is a very challenging task, even when considering a single target machine. For instance, optimizing for multicore-based computing systems requires in-depth knowledge about programming languages, application programming interfaces, compilers, performance tuning tools, and computer architecture and organization. Many of the tasks of performance engineering methodologies require manual efforts and the use of different tools not always part of an integrated toolchain. This paper presents Pegasus, a performance engineering approach supported by a framework that consists of a source-to-source compiler, controlled and guided by strategies programmed in a Domain-Specific Language, and an autotuner. Pegasus is a holistic and versatile approach spanning various decision layers composing the software stack, and exploiting the system capabilities and workloads effectively through the use of runtime autotuning. The Pegasus approach helps developers by automating tasks regarding the efficient implementation of software applications in multicore computing systems. These tasks focus on application analysis, profiling, code transformations, and the integration of runtime autotuning. Pegasus allows developers to program their strategies or to automatically apply existing strategies to software applications in order to ensure the compliance of non-functional requirements, such as performance and energy efficiency. We show how to apply Pegasus and demonstrate its applicability and effectiveness in a complex case study, which includes tasks from a smart navigation system

The Dose-Dependent Effects of Multifunctional Enkephalin Analogs on the Protein Composition of Rat Spleen Lymphocytes, Cortex, and Hippocampus; Comparison with Changes Induced by Morphine

This work aimed to test the effect of 7-day exposure of rats to multifunctional enkephalin analogs LYS739 and LYS744 at doses of 3 mg/kg and 10 mg/kg on the protein composition of rat spleen lymphocytes, brain cortex, and hippocampus. Alterations of proteome induced by LYS739 and LYS744 were compared with those elicited by morphine. The changes in rat proteome profiles were analyzed by label-free quantification (MaxLFQ). Proteomic analysis indicated that the treatment with 3 mg/kg of LYS744 caused significant alterations in protein expression levels in spleen lymphocytes (45), rat brain cortex (31), and hippocampus (42). The identified proteins were primarily involved in RNA processing and the regulation of cytoskeletal dynamics. In spleen lymphocytes, the administration of the higher 10 mg/kg dose of both enkephalin analogs caused major, extensive modifications in protein expression levels: LYS739 (119) and LYS744 (182). Among these changes, the number of proteins associated with immune responses and apoptotic processes was increased. LYS739 treatment resulted in the highest number of alterations in the rat brain cortex (152) and hippocampus (45). The altered proteins were functionally related to the regulation of transcription and cytoskeletal reorganization, which plays an essential role in neuronal plasticity. Administration with LYS744 did not increase the number of altered proteins in the brain cortex (26) and hippocampus (26). Our findings demonstrate that the effect of κ-OR full antagonism of LYS744 is opposite in the central nervous system and the peripheral region (spleen lymphocytes). © 2022 by the authors.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Expressing and Applying C plus plus Code Transformations for the HDF5 API Through a DSL

Hierarchical Data Format (HDF5) is a popular binary storage solution in high performance computing (HPC) and other scientific fields. It has bindings for many popular programming languages, including C++, which is widely used in the HPC field. Its C++ API requires mapping of the native C++ data types to types native to the HDF5 API. This task can be error prone, especially when working with complex data structures, which are usually stored using HDF5 compound data types. Due to the lack of a comprehensive reflection mechanism in C++, the mapping code for data manipulation has to be hand-written for each compound type separately. This approach is vulnerable to bugs and mistakes, which can be eliminated by using an automated code generation phase. In this paper we present an approach implemented in the LARA language and supported by the tool Clava, which allows us to automate the generation of the HDF5 data access code for complex data structures in C++

An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to take tuning decisions on the number of samples improving the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36% and 81%) with respect to a static approach while considering different traffic situations, paths and error requirements. The corresponding speedup is reflected at infrastructure-level in terms of a reduction of around 36% of the computing resources needed to support the whole navigation pipeline