02420nas a2200193   4500008004100000245010900041210006900150260000800219300000900227520172400236653001501960653002401975653002301999653002502022100001402047700001802061700001902079856012802098       2017                        eng d00aDeciphering structural stability and binding mechanisms of potential antagonists with smoothened protein0 aDeciphering structural stability and binding mechanisms of poten  cSEP  a1-213 aIdentification of new potential inhibitors against Hedgehog pathway activator protein Smoothened (SMO) is considered to be of higher importance to improvise the future cancer therapeutics. Different SMO inhibitors/drugs (e.g. Cyclopamine, Vismodegib, Taladegib) used till date are found to be associated with several drug-related resistivity and toxicity. To explore the ability of new drug/inhibitor molecules, which can show better/similar binding and dynamic stability as compared to known inhibitors, virtual screening against SMO is performed followed by the comparative docking and molecular dynamic studies. ‘ZINC12368305’ is found to be the best molecule among the entire data-set, as it shows the highest binding affinity and stable conformations. Here, an integrative approach using Dynamic Graph Theory is introduced to gain the molecular insights of the structural integrity of these protein complexes at the residue level by analyzing the corresponding Protein Contact Networks along the Molecular Dynamics trajectories. The study further focuses to understand the detailed binding mechanisms of available inhibitor/drug molecules along with the newly predicted molecule. It is observed that a unique big cluster of low fluctuating residues at the vicinity of the drug binding pocket of the SMO in ZINC12368305-bound complex is present and driving it toward a more stable region. A close inspection on this site reveals the presence of a stable Pi–Pi interaction between the pyrazole group-associated phenanthrene ring of ZINC12368305 and aromatic ring of Phe484 of SMO, which could be the potential factor of ZINC12368305 to create a more stable complex with SMO as compared to the other inhibitors.10ainhibitors10aPi–Pi Interaction10aSmoothened Protein10aStructural stability1 aSinha, N.1 aChowdhury, S.1 aSarkar, R., R.  uhttps://library.ncl.res.in/content/deciphering-structural-stability-and-binding-mechanisms-potential-antagonists-smoothened02028nas a2200205   4500008004100000022001400041245011800055210006900173260000900242490000700251520132500258100001801583700001401601700001601615700001701631700001401648700001401662700001901676856012701695       2018                        eng d  a1613-451600aBIOPYDB: a dynamic human cell specific biochemical pathway database with advanced computational analyses platform0 aBIOPYDB a dynamic human cell specific biochemical pathway databa  cMAR 0 v153 aBIOPYDB: BIOchemical PathwaY DataBase is developed as a manually curated, readily updatable, dynamic resource of human cell specific pathway information along with integrated computational platform to perform various pathway analyses. Presently, it comprises of 46 pathways, 3189 molecules, 5742 reactions and 6897 different types of diseases linked with pathway proteins, which are referred by 520 literatures and 17 other pathway databases. With its repertoire of biochemical pathway data, and computational tools for performing Topological, Logical and Dynamic analyses, BIOPYDB offers both the experimental and computational biologists to acquire a comprehensive understanding of signaling cascades in the cells. Automated pathway image reconstruction, cross referencing of pathway molecules and interactions with other databases and literature sources, complex search operations to extract information from other similar resources, integrated platform for pathway data sharing and computation, etc. are the novel and useful features included in this database to make it more acceptable and attractive to the users of pathway research communities. The RESTful API service is also made available to the advanced users and developers for accessing this database more conveniently through their own computer programmes.1 aChowdhury, S.1 aSinha, N.1 aGanguli, P.1 aBhowmick, R.1 aSingh, V.1 aNandi, S.1 aSarkar, R., R.  uhttps://library.ncl.res.in/content/biopydb-dynamic-human-cell-specific-biochemical-pathway-database-advanced-computational