Biochemical and structural characterization of β-lactamases tem-180 and tem-201

With the constant development of new antibiotics, selective pressure is a force to reckon when investigating antibiotic resistance. Although advantageous for medical treatments, it leads to increasing resistance. It is essential to use more potent and toxic antibiotics. Enzymes capable of hydrolyzing antibiotics are among the most common ways of resistance and TEM variants have been detected in several resistant isolates. Due to the rapid evolution of these variants, complex phenotypes have emerged and the need to understand their biological activity becomes crucial. To investigate the biochemical properties of TEM-180 and TEM-201 several computational methodologies have been used, allowing the comprehension of their structure and catalytic activity, which translates into their biological phenotype. In this work we intent to characterize the interface between these proteins and the several antibiotics used as ligands. We performed explicit solvent molecular dynamics (MD) simulations of these complexes and studied a variety of structural and energetic features. The interfacial residues show a distinct behavior when in complex with different antibiotics. Nevertheless, it was possible to identify some common Hot Spots among several complexes – Lys73, Tyr105 and Glu166. The structural changes that occur during the Molecular Dynamic (MD) simulation lead to the conclusion that these variants have an inherent capacity of adapting to the various antibiotics. This capability might be the reason why they can hydrolyze antibiotics that have not been described until now to be degraded by TEM variants. The results obtained with computational and experimental methodologies for the complex with Imipenem have shown that in order to this type of enzymes be able to acylate the antibiotics, they need to be capable to protect the ligand from water molecules.

Ligand-Induced structural changes in TEM‑1 probed by molecular dynamics and relative binding free energy calculations

The TEM family of enzymes has had a crucial impact on the pharmaceutical industry due to their important role in antibiotic resistance. Even with the latest technologies in structural biology and genomics, no 3D structure of a TEM- 1/antibiotic complex is known previous to acylation. Therefore, the comprehension of their capability in acylate antibiotics is based on the protein macromolecular structure uncomplexed. In this work, molecular docking, molecular dynamic simulations, and relative free energy calculations were applied in order to get a comprehensive and thorough analysis of TEM-1/ampicillin and TEM-1/amoxicillin complexes. We described the complexes and analyzed the effect of ligand binding on the overall structure. We clearly demonstrate that the key residues involved in the stability of the ligand (hot-spots) vary with the nature of the ligand. Structural effects such as (i) the distances between interfacial residues (Ser70−Oγ and Lys73−Nζ, Lys73−Nζ and Ser130−Oγ, and Ser70−Oγ−Ser130−Oγ), (ii) side chain rotamer variation (Tyr105 and Glu240), and (iii) the presence of conserved waters can be also influenced by ligand binding. This study supports the hypothesis that TEM-1 suffers structural modifications upon ligand binding.

A microscope for the data center

Nowadays, data centers are large energy consumers and the trend for next years is expected to increase further, considering the growth in the order of cloud services. A large portion of this power consumption is due to the control of physical parameters of the data center (such as temperature and humidity). However, these physical parameters are tightly coupled with computations, and even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in the cloud infrastructure hosted in the data center. Therefore, managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumptions. Having a high-resolution picture of the data center conditions, also enables minimizing local hot-spots, perform more accurate predictive maintenance (failures in all infrastructure equipments can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.