<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maark, Tuhina Adit</style></author><author><style face="normal" font="default" size="100%">Pal, Sourav</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Model study of effect of M = Li+, Na+, Be2+, Mg2+, and Al3+ ion decoration on hydrogen adsorption of metal-organic framework-5</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Hydrogen Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding energy</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrogen adsorption</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydrogen storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Metal organic frameworks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">23, SI</style></number><publisher><style face="normal" font="default" size="100%">PERGAMON-ELSEVIER SCIENCE LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND</style></pub-location><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">12846-12857</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The effect of light metal ion decoration of the organic linker in metal organic framework MOF 5 on its hydrogen adsorption with respect to its hydrogen binding energy (Delta B E) and gravimetric storage capacity is examined theoretically by employing models of the form MC6H6 nH(2) where M = Li+ Na+ Be2+ Mg2+ and Al3+ A systematic investigation of the suitability of DFT functionals for studying such systems is also carried out Our results show that the interaction energy (Delta E) of the metal ion M with the benzene ring Delta B E and charge transfer (Q(trans)) from the metal to benzene ring exhibit the same increasing order Na+ &amp;lt; Li+ &amp;lt; Mg2+ &amp;lt; Be2+ &amp;lt; Al3+ Organic hnker decoration with the above metal ions strengthened H-2 MOF 5 interactions relative to its pure state However amongst these ions only Mg2+ ion resulted in Delta B E magnitudes that were optimal for allowing room temperature hydrogen storage applications of MOF 5 A much higher gravimetric storage capacity (6 15 wt % H-2) is also predicted for Mg2+ decorated MOF 5 as compared to both pure MOF 5 and Li+ decorated MOF (C) 2010 Professor T Nejat Veziroglu Published by Elsevier Ltd All rights reserved&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">23</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">4.053</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vyas, Renu</style></author><author><style face="normal" font="default" size="100%">Karthikeyan, Muthukumarasamy</style></author><author><style face="normal" font="default" size="100%">Nainaru, Ganesh</style></author><author><style face="normal" font="default" size="100%">Muthukrishnan, Murugan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pharmacophore and docking based virtual screening of validated mycobacterium tuberculosis targets</style></title><secondary-title><style face="normal" font="default" size="100%">Combinatorial Chemistry &amp; High Throughput Screening</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding energy</style></keyword><keyword><style  face="normal" font="default" size="100%">docking</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycobacterium tuberculosis</style></keyword><keyword><style  face="normal" font="default" size="100%">open source drug discovery (OSDD)</style></keyword><keyword><style  face="normal" font="default" size="100%">pharmacophore</style></keyword><keyword><style  face="normal" font="default" size="100%">structure based drug design (SBDD)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">7</style></number><publisher><style face="normal" font="default" size="100%">BENTHAM SCIENCE PUBL LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">EXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES</style></pub-location><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">624-637</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Target based virtual screening has surpassed ligand based virtual screening methods in the recent past mainly as it provides more clues regarding intermolecular interactions and takes into consideration the flexible receptor as well. The current methodology describes a computational strategy of predicting Mycobacterium tuberculosis (M. tuberculosis) binders for five well studied targets representing M. tuberculosis proteome encompassing most of the known mechanisms of action. The diversity of the targets was affirmed by their active site analysis and structural studies. The current approach employed pharmacophore searching, docking and clustering techniques in tandem and was validated by enrichment studies using the available Schrodinger data set consisting of 1000 decoys. The application of this methodology was demonstrated by predicting potential molecular targets for fifty newly synthesized compounds. Cross docking studies on the targets were carried out with 4512 known inhibitors utilizing a high performance computing platform to reveal underlying affinity and promiscuity patterns. Optimum binding energy range for all targets as determined by high throughput docking was found to be -3 to -13 kcal/mol.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">1.041</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Joshi, Krati</style></author><author><style face="normal" font="default" size="100%">Krishnamurty, Sailaja</style></author><author><style face="normal" font="default" size="100%">Singh, Iksha</style></author><author><style face="normal" font="default" size="100%">Selvaraj, Kaliaperumal</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DFT based assay for tailor-made terpyridine ligand-metal complexation properties</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Simulations</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding energy</style></keyword><keyword><style  face="normal" font="default" size="100%">charge redistribution</style></keyword><keyword><style  face="normal" font="default" size="100%">Density functional theory</style></keyword><keyword><style  face="normal" font="default" size="100%">functionalisation</style></keyword><keyword><style  face="normal" font="default" size="100%">Metal organic complexes</style></keyword><keyword><style  face="normal" font="default" size="100%">metal-ligand interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">terpyridine</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAY</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">8</style></number><publisher><style face="normal" font="default" size="100%">TAYLOR &amp; FRANCIS LTD</style></publisher><pub-location><style face="normal" font="default" size="100%">4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND</style></pub-location><volume><style face="normal" font="default" size="100%">42</style></volume><pages><style face="normal" font="default" size="100%">618-627</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Electron-rich terpyridine ligand and its metal complexes have a potential to grow as responsive surfaces by adapting their physicochemical properties as a function of environment. The responsiveness is brought about by judicious molecular level designing that is currently hindered due to lack of information and control on terpyridine (TPy)-metal (M) interactions at single molecule level. So far there is no organised understanding on the binding of different metals with TPy ligand and ways to modulate it. Being a large conjugated [GRAPHICS] system, TPy has a large scope to be functionalised with electron exchanging groups to alter its electronic structure and consequently its binding with metal atoms. In first report of such a kind, using density functional theory (DFT), we demonstrate that convenient modulation of TPy-M binding is possible through functionalisation of TPy for [GRAPHICS] , Ru, Fe, Mo and Au. Electron donating groups viz., CH [GRAPHICS] , OCH [GRAPHICS] , C [GRAPHICS] H [GRAPHICS] , NH [GRAPHICS] and electron withdrawing groups viz., CF [GRAPHICS] , COOH, CN and NO [GRAPHICS] are considered for functionalisation of TPy ligand. Significantly, the present work focuses on the functionalisation at 4 and 4 [GRAPHICS] positions of TPy molecule. The role of such a functionalisation in influencing the ligands structure-property correlation is missing in the literature to the best of our knowledge. The present investigation quantifies that by pertinent functionalisation of TPy, TPy-M binding energies can be modified up to [GRAPHICS] 60kcal/mol. Our results reveal that functionalisation leads to a considerable charge redistribution within the TPy-M complex with carbon atoms in pyridine rings functioning as major electron sink/source with a corresponding red/blue shift of [GRAPHICS] stretching frequency. This modifies the red-ox, optical and other chemical properties of TPy-M complexes. In brief, the present report illustrates a way to design ligands such as TPy for diverse applications through tailor-made functionalisation using electronic structure methodology.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">1.678</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vyas, Renu</style></author><author><style face="normal" font="default" size="100%">Bapat, Sanket</style></author><author><style face="normal" font="default" size="100%">Goel, Purva</style></author><author><style face="normal" font="default" size="100%">Karthikeyan, Muthukumarasamy</style></author><author><style face="normal" font="default" size="100%">Tambe, Sanjeev S.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Bhaskar D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of genetic programming (GP) formalism for building disease predictive models from protein-protein interactions (PPI) data</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE-ACM Transactions on Computational Biology and Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Binding energy</style></keyword><keyword><style  face="normal" font="default" size="100%">cancer</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">genetic programming</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">protein-protein interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">symbolic regression</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">FEB</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">27-37</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Protein-protein interactions (PPIs) play a vital role in the biological processes involved in the cell functions and disease pathways. The experimental methods known to predict PPIs require tremendous efforts and the results are often hindered by the presence of a large number of false positives. Herein, we demonstrate the use of a new Genetic Programming (GP) based Symbolic Regression (SR) approach for predicting PPIs related to a disease. In this case study, a dataset consisting of 135 PPI complexes related to cancer was used to construct a generic PPI predicting model with good PPI prediction accuracy and generalization ability. A high correlation coefficient (CC) magnitude of 0.893, and low root mean square error (RMSE), and mean absolute percentage error (MAPE) values of 478.221 and 0.239, respectively, were achieved for both the training and test set outputs. To validate the discriminatory nature of the model, it was applied on a dataset of diabetes complexes where it yielded significantly low CC values. Thus, the GP model developed here serves a dual purpose: (a) a predictor of the binding energy of cancer related PPI complexes, and (b) a classifier for discriminating PPI complexes related to cancer from those of other diseases.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">1.955</style></custom4></record></records></xml>