Molecular docking via quantum approximate optimization algorithm

Molecular docking plays a pivotal role in drug discovery and precision medicine, enabling us to understand protein functions and advance novel therapeutics. Here, we introduce a potential alternative solution to this problem, the digitized-counterdiabatic quantum approximate optimization algorithm (DC-QAOA), which utilizes counterdiabatic driving and QAOA on a quantum computer. Our method was applied to analyze diverse biological systems, including the SARS-CoV-2 Mpro complex with PM-2-020B, the DPP-4 complex with piperidine fused imidazopyridine 34, and the HIV-1 gp120 complex with JP-III-048. The DC-QAOA exhibits superior performance, providing more accurate and biologically relevant docking results, especially for larger molecular docking problems. Moreover, QAOA-based algorithms demonstrate enhanced hardware compatibility in the noisy intermediate-scale quantum era, indicating their potential for efficient implementation under practical docking scenarios. Our findings underscore quantum computing's potential in drug discovery and offer valuable insights for optimizing protein-ligand docking processes.Comment: 10 pages, 5 figures, All comments are welcom

The effect of transforming growth factor-β1 on nasopharyngeal carcinoma cells: insensitive to cell growth but functional to TGF-β/Smad pathway

<p>Abstract</p> <p>Objectives</p> <p>This study explored the response of nasopharyngeal carcinoma cells to TGF-β1-induced growth suppression and investigated the roles of the TGF-β/Smad signaling pathway in nasopharyngeal carcinoma cells.</p> <p>Methods</p> <p>The cells of nasopharyngeal carcinoma cell line CNE2 were treated with TGF-β1. The growth responses of CNE2 cells were analyzed by MTT assay. The mRNA expression and protein subcellular localization of the TGF-β/Smad signaling components in the CNE2 were determined by real time RT-PCR and immunocytochemical analysis.</p> <p>Results</p> <p>We found that the growth of CNE2 cells was not suppressed by TGF-β1. The signaling proteins TβRII, Smad 7 were expressed normally, while Smad2, Smad3, and Smad4 increased significantly at the mRNA level. TGF-β type II receptor and Smad7 had no change compared to the normal nasopharyngeal epithelial cells. In addition, Smad2 was phosphorylated to pSmad2, and the activated pSmad2 translocated into the nucleus from the cytoplasm, while the inhibitory Smad-Smad7 translocated from the nucleus to the cytoplasm after TGF-β1 stimulation.</p> <p>Conclusion</p> <p>The results suggested that CNE2 cells are not sensitive to growth suppression by TGF-β1, but the TGF-β/Smad signaling transduction is functional. Further work is needed to address a more detailed spectrum of the TGF-β/Smad signaling pathway in CNE2 cells.</p

Efficiency Enhancement in Polymer Solar Cells With a Polar Small Molecule Both at Interface and in the Bulk Heterojunction Layer

The polar molecules, including ferroelectric materials with large dipole moments, have been applied as interfacial layers to increase the efficiency of organic solar cells by increasing the bounded charge separation, tuning the energy levels, etc. Here, we report a small polar molecule 2-cyano-3- (4-(diphenylamino) phenyl)acrylic acid (TPACA) that can be either blended in the active layer or at the polymer/electrode interface to increase the efficiency of organic solar cell devices after poling. It is found that the built-in potential of the device is increased by 0.2 V after poling under negative bias. Blending TPACA into the active layer has shown to be a universal method to increase the efficiency of polymer solar cells. The efficiency is increased by 30–90% for all the polymer:fullerene systems tested, with the highest efficiency reaching 7.83% for the poly[4,8-bis-(2-ethyl-hexyl-thiophene-5-yl)-benzo[1,2-b:4,5-b’]dithiophene-2,6-diyl]-alt-[2-(2’-ethyl-hexanoyl)-thieno[3,4-b]thiophen-4,6-diyl]: [6,6]-phenyl-C71 -butyric acid methyl ester (PBDTTT-CT:PC70BM) system

Weighted Complex Network Analysis of the Difference Between Nodal Centralities of the Beijing Subway System

The centrality of stations is one of the most important issues in urban transit systems. The central stations of such networks have often been identified using network to-pological centrality measures. In real networks, passenger flows arise from an interplay between the dynamics of the individual person movements and the underlying physical structure. In this paper, we apply a two-layered model to identify the most central stations in the Beijing Subway System, in which the lower layer is the physical infrastruc-ture and the upper layer represents the passenger flows. We compare various centrality indicators such as degree, strength and betweenness centrality for the two-layered model. To represent the influence of exogenous factors of stations on the subway system, we reference the al-pha centrality. The results show that the central stations in the geographic system in terms of the betweenness are not consistent with the central stations in the network of the flows in terms of the alpha centrality. We clarify this difference by comparing the two centrality measures with the real load, indicating that the alpha centrality approx-imates the real load better than the betweenness, as it can capture the direction and volume of the flows along links and the flows into and out of the systems. The empirical findings can give us some useful insights into the node cen-trality of subway systems