Binding Modes of Peptidomimetics Designed to Inhibit STAT3

STAT3 is a transcription factor that has been found to be constitutively activated in a number of human cancers. Dimerization of STAT3 via its SH2 domain and the subsequent translocation of the dimer to the nucleus leads to transcription of anti-apoptotic genes. Prevention of the dimerization is thus an attractive strategy for inhibiting the activity of STAT3. Phosphotyrosine-based peptidomimetic inhibitors, which mimic pTyr-Xaa-Yaa-Gln motif and have strong to weak binding affinities, have been previously investigated. It is well-known that structures of protein-inhibitor complexes are important for understanding the binding interactions and designing stronger inhibitors. Experimental structures of inhibitors bound to the SH2 domain of STAT3 are, however, unavailable. In this paper we describe a computational study that combined molecular docking and molecular dynamics to model structures of 12 peptidomimetic inhibitors bound to the SH2 domain of STAT3. A detailed analysis of the modeled structures was performed to evaluate the characteristics of the binding interactions. We also estimated the binding affinities of the inhibitors by combining MMPB/GBSA-based energies and entropic cost of binding. The estimated affinities correlate strongly with the experimentally obtained affinities. Modeling results show binding modes that are consistent with limited previous modeling studies on binding interactions involving the SH2 domain and phosphotyrosine(pTyr)-based inhibitors. We also discovered a stable novel binding mode that involves deformation of two loops of the SH2 domain that subsequently bury the C-terminal end of one of the stronger inhibitors. The novel binding mode could prove useful for developing more potent inhibitors aimed at preventing dimerization of cancer target protein STAT3

Thermal Transport in Micro- and Nanoscale Systems

Small-scale (micro-/nanoscale) heat transfer has broad and exciting range of applications. Heat transfer at small scale quite naturally is influenced – sometimes dramatically – with high surface area-to-volume ratios. This in effect means that heat transfer in small-scale devices and systems is influenced by surface treatment and surface morphology. Importantly, interfacial dynamic effects are at least non-negligible, and there is a strong potential to engineer the performance of such devices using the progress in micro- and nanomanufacturing technologies. With this motivation, the emphasis here is on heat conduction and convection. The chapter starts with a broad introduction to Boltzmann transport equation which captures the physics of small-scale heat transport, while also outlining the differences between small-scale transport and classical macroscale heat transport. Among applications, examples are thermoelectric and thermal interface materials where micro- and nanofabrication have led to impressive figure of merits and thermal management performance. Basic of phonon transport and its manipulation through nanostructuring materials are discussed in detail. Small-scale single-phase convection and the crucial role it has played in developing the thermal management solutions for the next generation of electronics and energy-harvesting devices are discussed as the next topic. Features of microcooling platforms and physics of optimized thermal transport using microchannel manifold heat sinks are discussed in detail along with a discussion of how such systems also facilitate use of low-grade, waste heat from data centers and photovoltaic modules. Phase change process and their control using surface micro-/nanostructure are discussed next. Among the feature considered, the first are microscale heat pipes where capillary effects play an important role. Next the role of nanostructures in controlling nucleation and mobility of the discrete phase in two-phase processes, such as boiling, condensation, and icing is explained in great detail. Special emphasis is placed on the limitations of current surface and device manufacture technologies while also outlining the potential ways to overcome them. Lastly, the chapter is concluded with a summary and perspective on future trends and, more importantly, the opportunities for new research and applications in this exciting field

Increased signalling of EGFR and IGF1R, and deregulation of PTEN/PI3K/Akt pathway are related with trastuzumab resistance in HER2 breast carcinomas

Trastuzumab resistance hampers its well-known efficacy to control HER2-positive breast cancer. The involvement of PI3K/Akt pathway in this mechanism is still not definitively confirmed. We selected 155 patients treated with trastuzumab after development of metastasis or as adjuvant/neoadjuvant therapy. We performed immunohistochemistry for HER2, ER/PR, epidermal growth factor 1-receptor (EGFR), α -insulin-like growth factor 1-receptor (IGF1R), phosphatase and tensin homologue (PTEN), p110 α, pAkt, pBad, pmTOR, pMAPK, MUC1, Ki67, p53 and p27; mutational analysis of PIK3CA and PTEN, and PTEN promoter hypermethylation. We found 46% ER/PR-positive tumours, overexpression of EGFR (15%), α -IGF1R (25%), p110 α (19%), pAkt (28%), pBad (22%), pmTOR (23%), pMAPK (24%), MUC1 (80%), PTEN loss (20%), and PTEN promoter hypermethylation (20%). PIK3CA and PTEN mutations were detected in 17% and 26% tumours, respectively. Patients receiving adjuvant trastuzumab with α -IGF1R or pBad overexpressing tumours presented shorter progression-free survival (PFS) (all P ⩽0.043). Also, p110 α and mTOR overexpression, liver and brain relapses implied poor overall survival (OS) (all P ⩽0.041). In patients with metastatic disease, decreased PFS correlated with p110 α expression (P =0.024), whereas for OS were the presence of vascular invasion and EGFR expression (P ⩽0.019; Cox analysis). Our results support that trastuzumab resistance mechanisms are related with deregulation of PTEN/PI3K/Akt/mTOR pathway, and/or EGFR and IGF1R overexpression in a subset of HER2-positive breast carcinomas

Teaching learning based optimization for frequency regulation in two area thermal-solar hybrid power system

This novel work analyses the model of Automatic generation control having two unequal deregulated power system in Lab VIEW platform. Teaching learning based optimization (TLBO) has been implemented for tuning the gains of the PID controller. Further a comparative study has been given in this work with DE-based PID and TLBO-based PID controller. From the Simulation results implementing approaches of DE-optimized PID and TLBO-optimized PID establishes that the performance of TLBO optimization is better in improving the system performance index. The execution of TLBO-PID enhances performance in comparison with PI, PID controller with regards to stability, overshoot, and damping

Performance enhancement of AGC under open market scenario using TDOFPID and IPFC controller

Present work introduces a most popular evolution based algorithm and application of two degree of freedom proportional integral Derivative (TDOFPID) Controller based multi area power system. Differential Evolution (DE) optimization technique is applied here to tune the TDOFPID gains. Each area consists of Automatic generation control with addition of non-linarites. In this model time delay, Generation rate constraints (GRC) and reheat turbine are added to introduce non-linearity. At first attempt simulation is being done in two areas with DE optimization technique. Further a series connected Flexible Alternating Current Transmission (FACT) device such as interline power flow controller (IPFC) is included into the system and simulated. DE is also used to get the optimum value of TDOFPID controller having Integral time absolute error (ITAE) as the objective function. At last robustness analysis is done with varying parameter and different loading conditions. It is seen that, TDOFPID with IPFC gives better response compared to others

Non-destructive discrimination of Bell states by NMR using a single ancilla qubit

Discrimination of Bell states plays an important role in a number of quantum computational protocols such as teleportation and secret sharing. However, most of the protocols dealing with Bell state discrimination in the literature either involve performing correlated measurements or destroying the entanglement of the system. Here, we demonstrate an NMR-based experimental realization of a protocol for Bell state discrimination, following a scheme proposed by Gupta et al (quant-ph/0504183v1, 23 April 2005), which does not destroy the Bell state under consideration. Using the proposed protocol, one can deterministically distinguish the Bell states, without performing a measurement using the entangled basis. State discrimination is performed through two independent measurements on one ancilla qubit, which leaves the Bell states unchanged

Automated error correction in IBM quantum computer and explicit generalization

Construction of a fault-tolerant quantum computer remains a challenging problem due to unavoidable noise and fragile quantum states. However, this goal can be achieved by introducing quantum error-correcting codes. Here, we experimentally realize an automated error correction code and demonstrate the nondestructive discrimination of GHZ states in IBM 5-qubit quantum computer. After performing quantum state tomography, we obtain the experimental results with a high fidelity. Finally, we generalize the investigated code for maximally entangled n-qudit case, which could both detect and automatically correct any arbitrary phase-change error, or any phase-flip error, or any bit-flip error, or combined error of all types of error