Quinazoline derivative from indigenous isolate, Nocardiopsis alba inhibits human telomerase enzyme.

AIM: Aim of this study was isolation and screening of various secondary metabolites produced by indigenous isolates of soil Actinomycetes for human telomerase inhibitory activity. METHODS AND RESULTS: Extracellular extract from culture suspension of various soil Actinomycetes species were tested for telomerase inhibitory activity. The organism which produced telomerase inhibitor was identified by 16S rRNA gene sequencing. The active fraction was purified by HPLC and analysed by GC-MS to identify the compound. In GC-MS analysis, the active principle was identified as 3-[4'-(2″-chlorophenyl)-2'-thiazolyl]-2,4-dioxo-1,2,3,4-tetrahydro quinazoline. The G-quadruplex stabilizing ability of the compound was checked by molecular docking and simulation experiments with G-quadruplex model (PDB ID-1L1H). The selective binding ability of the compound with G-quadruplex over Dickerson-Drew dodecamer DNA structures showed that the compound possess high selectivity towards G-quadruplex. CONCLUSIONS: Quinazoline derivative isolated from an indigenous strain of Nocardiopsis alba inhibited telomerase. Molecular docking and simulation studies predicted that this compound is a strong stabilizer of G-quadruplex conformation. It also showed a preferable binding to G-quadruplex DNA over normal DNA duplex. SIGNIFICANCE AND IMPACT OF THE STUDY: This particular compound can be suggested as a suitable compound for developing a future anticancer drug. The selectivity towards G-quadruplex over normal DNA duplex gives a clue that it is likely to show lower cytotoxicity in normal cells.

Reconfigurable Architectures with High-Frequency Noise Suppression for Wearable ECG Devices.

Recent advances in electronics and microelectronics have aided the development of low-cost devices that are widely used as well-being or preventive monitoring devices by many people. Remote health monitoring, which includes wearable sensors, actuators, and modern communication and information systems, offers effective programs that allow people to live peacefully in their own homes while also being protected in some way. High-frequency noise, power-line interface, and baseline drift are prevalent during the data-acquisition system of an ECG signal, and they can limit signal understanding. They (noises) must be isolated in order to provide an appropriate diagnostic of the patient. When removing high-frequency components (noise) from an ECG signal with an FIR filter, the critical path delay increases considerably as the filter's duration increases. To reduce high-frequency noise, simple moving average filters with pipelining and look-ahead transformation techniques are extensively used in this study. With the use of pipelining and look-ahead techniques, the only objective is to increase the clock speed of the designs. The moving average filters (conventional and proposed) were created on an Altera Cyclone IV FPGA EP4CE115F29C7 chip using the Quartus II software v13.1 tool. Finally, performance metrics such logic elements, clock speed, and power consumption were compared and studied thoroughly. The recursive pipelined 8-tap MA filter with look-ahead approach outperforms the other designs (685.48 MHz) in this investigation.