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1
DFT‐based de novo QSAR of Phenoloxidase Inhibitors

Pasha, Farhan Ahmad,Muddassar, Muhhammad,Beg, Yakub,Cho, Seung Joo Blackwell Publishing Ltd 2008 Chemical biology & drug design Vol.71 No.5
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The phenoloxidase or tyrosinase is a key enzyme in insects, which is responsible for hydroxylation of tyrosine into o‐quinones via o‐diphenols. A series of benzaldehyde thiosemicarbazone, benzaldehyde and benzoic acid families were taken with their pragmatic pIC50 values against phenoloxidase from pieris rapae (Lepidoptera) larvae. Density functional theory‐based quantitative structure–activity relationship (QSAR) analyses were performed to speculate the key interaction. The most fitted four different QSAR models were identified and discussed. The softness, electrophilicity index, molar refractivity and log P were identified as best descriptors; however, the atomic values of softness and philicity obtained from Fukui function are more significant than global values. The study reveals that electrostatic and steric fields jointly contribute to activity. To gain further insight, the three‐dimensional quantitative structure–activity relationship (3D‐QSAR) analyses were performed using two molecular field techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The successful 3D‐QSAR models were obtained from CoMFA (q2 = 0.94, r2 = 0.99, = 0.92) and CoMSIA (q2 = 0.94, r2 = 0.98, = 0/95). The CoMFA and CoMSIA results indicate that, a bulky and negative group around sulfur atom but a small and positive group around nitrogen atom might have good effects on activity. The ortho and meta positions of ring are favorable for small group. These QSAR models might be helpful to design the novel and potent inhibitors.
2
In silico QSAR studies of anilinoquinolines as EGFR inhibitors.

Pasha, Farhan Ahmad,Muddassar, Muhammad,Srivastava, Anil Kumar,Cho, Seung Joo Springer 2010 JOURNAL OF MOLECULAR MODELING Vol.16 No.2
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Members of the epidermal growth factor receptor (EGFR) family of proteins are frequently overactive in solid tumors. A relatively new therapeutic approach to inhibit the kinase activity is the use of ATP-competitive small molecules. In silico techniques were employed to identify the key interactions between inhibitors and their protein receptors. A series of EGFR inhibitory anilinoquinolines was studied within the framework of hologram quantitative structure activity relationship (HQSAR), density functional theory (DFT)-based QSAR, and three-dimensional (3D) QSAR (CoMFA/CoMSIA). The HQSAR analysis implied that substitutions at certain sites on the inhibitors play an important role in EGFR inhibition. DFT-based QSAR results suggested that steric and electronic interactions contributed significantly to the activity. Ligand-based 3D-QSAR and receptor-guided 3D-QSAR analyses such as CoMFA and CoMSIA techniques were carried out, and the results corroborated the previous two approaches. The 3D QSAR models indicated that steric and hydrophobic interactions are dominant, and that substitution patterns are an important factor in determining activity. Molecular docking was helpful in identifying a bioactive conformer as well as a plausible binding mode. The docked geometry-based CoMFA model with steric and electrostatic fields effect gave q(2) = 0.66, r(2) = 0.94 with r(2) (predictive) = 0.72. Similarly, CoMSIA with hydrophobic field gave q(2) = 0.59, r(2) = 0.85 with r(2) (predictive) = 0.63. Bulky groups around site 3 of ring 'C', and hydrophilic and bulky groups at position 6 of ring 'A' are desirable, with a hydrophobic and electron-donating group at site 7 of ring 'A' being helpful. Accordingly, potential EGFR inhibitors may be designed by modification of known inhibitors.
3
Pharmacophore Identification and Validation Study of CK2 Inhibitors Using CoMFA/CoMSIA

Morshed, Mohammad Neaz,Muddassar, Muhammad,Pasha, Farhan Ahmad,Cho, Seung Joo Blackwell Publishing Ltd 2009 Chemical biology & drug design Vol.74 No.2
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Protein kinase CK2, also known as casein kinase-2, has been found to be involved in cell growth, proliferation and suppression of apoptosis, which is related to human cancers. The series of compounds were identified as casein kinase-2 inhibitors and their inhibitory activities are a function of a variation of their structures. The current study deals with the pharmacophore identification and, accordingly, the three-dimensional quantitative structure–activity relationship model development using Pharmacophore Alignment and Scoring Engine. Several hypotheses were developed for the molecular alignments. On the basis of statistical values, the best-fitted model was identified and the same alignment was used for 3D-QSAR using comparative molecular field analysis/comparative molecular similarity index analysis. Both the CoMFA (R 2CV = 0.58, R 2 = 0.82 and r 2pred = 0.62) and the comparative molecular similarity index analysis (R 2CV = 0.74, R 2 = 0.98 and r 2pred = 0.81) gave reasonable results. Besides pharmacophore-based alignment, the maximum common substructure-based alignment was also used for the comparative molecular field analysis and comparative molecular similarity index analysis. The pharmacophore-based alignment was more prominent and it has provided important information for the modelling of potent inhibitors. The overall study implies that a highly positive and bulky group with H-bond donating property is desirable around the nitrogen atom adjacent to the pyrrolidine ring.

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