Development of quantitative structure-property relationships for predictive modeling and design of energetic materials
ABSTRACT A quantitative structure-property relationship (QSPR) based on the AM1 semiempirical quantum mechanical method was derived using the program, CODESSA, to describe published drop height impact sensitivities for 227 nitroorganic compounds. An eight-descriptor correlation equation having R(2)=0.8141 was obtained through a robust least median squares regression. The resulting model is the most comprehensive and systematic quantum mechanically derived QSPR for energetic materials of those that have been published. The predictive capability of the model is also presented and discussed.
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ABSTRACT: New quantitative structure property relationships (QSPR) have been developed to predict accurately the impact sensitivity of nitro compounds from their molecular structures. Such predictive approaches represent good alternative to complete experimental testing in development process or for regulatory issues (e.g. within the European REACH regulation). To achieve highly predictive models, two approaches were used to explore the whole diversity of nitro compounds included in a data set of 161 molecules. In a first step, local models, dedicated to the nitramines, nitroaliphatics and nitroaromatics, were proposed. After that, a global model was developed to be applicable for the whole range of the nitro compounds of the data set. In both cases, large series of molecular descriptors were calculated from quantum chemically calculated molecular structures and multilinear regressions were computed to correlate them with experimental impact sensitivities. All proposed models were validated for regulatory use according to the OECD principles, including internal, external validation and the definition of their applicability domain. So, they could then be used for prediction separately or in a consensus approach.2012 AIChE Spring National Meeting; 04/2012
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ABSTRACT: The study of mobile networks with users following different mobility behaviour has been considered. Obtaining a low dropping probability, and consequently a good grade of service, seems only possible using channel reservation schemes. We have studied the performance of a variable reservation mechanism (proposed by Oliver and Paradells (see 4th Workshop on Mobile Multimedia Communications MoMuC'97, Seoul, South Korea, 1997)) considering that not all the mobile stations move in the same way. We have studied two scenarios mixing mobiles at different speeds that move around following predictable or non-predictable mobility patterns. In this environment we show that the mentioned mechanism improves the grade of service of the networkVehicular Technology Conference, 1998. VTC 98. 48th IEEE; 06/1998
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ABSTRACT: The traditional Chinese medicines (TCM), Epimedium sagittatum (ESs), Cnidium monnieri (CMs), and Semen cuscutae (SCs), were used for treating erectile dysfunction since the ancient Han dynasty (202 BC-AD 220). Phosphodiesterase-5 (PDE-5) is deemed the target protein for inhibition to treat erectile dysfunction. In this study, a reliable multiple linear regression (MLR) model (r value=0.8484) was used to predict the activities of new candidates which were designed from ES, CM, and SC. From docking and pharmacophore analysis, the potent candidates among ES, CM, and SC were screened. SC01, SC03, and ES03b were predicted to have high potencies based on MLR analysis and high docking scores. Additionally, from our analysis, we make the follow conclusion (1) Hydrophobic compounds tend to be more potent PDE-5 inhibitors; (2) Because of the big binding site, inhibitors with molecular weights over 500 remain potent; (3) From the pharmacophore analysis, the features of hydrogen bond acceptors are the basis for designing novel inhibitors of PDE-5 and (4) According to MLR analysis, the number of ring groups could be up to 6, but the number of aromatic rings was limited to 4 to be potent. This study offers an alternative way to screen PDE-5 inhibitors from TCM and provides a scientific basis for confirming pharmacological actions of TCM.Journal of molecular graphics & modelling 08/2009; 28(3):261-9. DOI:10.1016/j.jmgm.2009.08.004 · 2.02 Impact Factor