A constructive approach for discovering new drug leads: Using a kernel methodology for the inverse-QSAR problem

<p>Abstract</p> <p>Background</p> <p>The inverse-QSAR problem seeks to find a new molecular descriptor from which one can recover the structure of a molecule that possess a desired activity or property. Surprisingly, there are very few papers providing solutions to this problem. It is a difficult problem because the molecular descriptors involved with the inverse-QSAR algorithm must adequately address the forward QSAR problem for a given biological activity if the subsequent recovery phase is to be meaningful. In addition, one should be able to construct a feasible molecule from such a descriptor. The difficulty of recovering the molecule from its descriptor is the major limitation of most inverse-QSAR methods.</p> <p>Results</p> <p>In this paper, we describe the reversibility of our previously reported descriptor, the vector space model molecular descriptor (VSMMD) based on a vector space model that is suitable for kernel studies in QSAR modeling. Our inverse-QSAR approach can be described using five steps: (1) generate the VSMMD for the compounds in the training set; (2) map the VSMMD in the input space to the kernel feature space using an appropriate kernel function; (3) design or generate a new point in the kernel feature space using a kernel feature space algorithm; (4) map the feature space point back to the input space of descriptors using a pre-image approximation algorithm; (5) build the molecular structure template using our VSMMD molecule recovery algorithm.</p> <p>Conclusion</p> <p>The empirical results reported in this paper show that our strategy of using kernel methodology for an inverse-Quantitative Structure-Activity Relationship is sufficiently powerful to find a meaningful solution for practical problems.</p

Lipid biosynthesis and its coordination with cell cycle progression

The activation of cell cycle regulators at the G(1)/S boundary has been linked to the cellular protein synthesis rate. It is conceivable that regulatory mechanisms are required to allow cells to coordinate the synthesis of other macromolecules with cell cycle progression. The availability of highly synchronized cells and flow cytometric methods facilitates investigation of the dynamics of lipid synthesis in the entire cell cycle of the heterotrophic dinoflagellate Crypthecodinium cohnii. Flow cytograms of Nile red-stained cells revealed a stepwise increase in the polar lipid content and a continuous increase in neutral lipid content in the dinoflagellate cell cycle. A cell cycle delay at early G but not G(2)/M, was observed upon inhibition of lipid synthesis. However, lipid synthesis continued during cell cycle arrest at the G(1)/S transition. A cell cycle delay was not observed when inhibitors of cellulose synthesis and fatty acid synthesis were added after the late G, phase of the cell cycle. This implicates a commitment point that monitors the synthesis of fatty acids at the late G, phase of the dinoflagellate cell cycle. Reduction of the glucose concentration in the medium down-regulated the G, cell size with a concomitant forward shift of the commitment point. Inhibition of lipid synthesis up-regulated cellulose synthesis and resulted in an increase in cellulosic contents, while an inhibition of cellulose synthesis had no effects on lipid synthesis. Fatty acid synthesis,and cellulose synthesis are apparently coupled to the cell cycle via independent pathways

A hybrid PSO-BFGS strategy for global optimization of multimodal functions

Particle swarm optimizer (PSO) is a powerful optimization algorithm that has been applied to a variety of problems. It can, however, suffer from premature convergence and slow convergence rate. Motivated by these two problems, a hybrid global optimization strategy combining PSOs with a modified Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is presented in this paper. The modified BFGS method is integrated into the context of the PSOs to improve the particles' local search ability. In addition, in conjunction with the territory technique, a reposition technique to maintain the diversity of particles is proposed to improve the global search ability of PSOs. One advantage of the hybrid strategy is that it can effectively find multiple local solutions or global solutions to the multimodal functions in a box-constrained space. Based on these local solutions, a reconstruction technique can be adopted to further estimate better solutions. The proposed method is compared with several recently developed optimization algorithms on a set of 20 standard benchmark problems. Experimental results demonstrate that the proposed approach can obtain high-quality solutions on multimodal function optimization problems. © 2011 IEEE

Quality of life among adolescents in Hong Kong : general and gender-specific effects of self-efficacy and mindfulness

202208 bcchSelf-funde

Predictors to happiness in primary students : positive relationships or academic achievement

202305 bcwwAccepted ManuscriptOthersBei Shan Tang FoundationPublishe

A multidimensional PERMA-H positive education model, general satisfaction of school life, and character strengths use in Hong Kong senior primary school students : confirmatory factor analysis and path analysis using the APASO-II

2017-2018 > Academic research: refereed > Publication in refereed journal201810 bcrcVersion of RecordPublishe

Corrigendum: A multidimensional PERMA-H positive education model, general satisfaction of school life, and character strengths use in Hong Kong senior primary school students : confirmatory factor analysis and path analysis using the APASO-II [Front. Psychol., 9, 1090, (2018)] doi: 10.3389/fpsyg.2018.01090

201902 bcmaVersion of RecordPublishe