Combinatorial Library Enumeration and Lead Hopping using Comparative Interaction Fingerprint Analysis and Classical 2D QSAR Methods for Seeking Novel GABAA r3 Modulators
IR@IICB: CSIR-Indian Institute of Chemical Biology, Kolkata
View Archive Info| Field | Value | |
| Title |
Combinatorial Library Enumeration and Lead Hopping using Comparative Interaction
Fingerprint Analysis and Classical 2D QSAR Methods for Seeking Novel GABAA r3
Modulators
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| Creator |
Vijayan, R S K
Bera, Indrani Prabu, M Saha, Sangita Ghoshal, Nanda |
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| Subject |
Structural Biology & Bioinformatics
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| Description |
Selective modulators of GABAA R3 (gamma amino butyric acid R3) receptor are known to alleviate the side
effects associated with nonspecific modulators. A follow up study was undertaken on a series of functionally
selective phthalazines with an ideological credo of identifying more potent isofunctional chemotypes. A
bioisosteric database enumerated using the combichem approach endorsed mining in a lead-like chemical
space. Primary screening of the massive library was undertaken using the “Miscreen” toolkit, which uses
sophisticated bayesian statistics for calculating bioactivity score. The resulting subset, thus, obtained was
mined using a novel proteo-chemometric method that integrates molecular docking and QSAR formalism
termed CoIFA (comparative interaction fingerprint analysis). CoIFA encodes protein-ligand interaction
terms as propensity values based on a statistical inference to construct categorical QSAR models that assist
in decision making during virtual screening. In the absence of an experimentally resolved structure of GABAA
R3 receptor, standard comparative modeling techniques were employed to construct a homology model of
GABAA R3 receptor. A typical docking study was then carried out on the modeled structure, and the interaction
fingerprints generated based on the docked binding mode were used to derive propensity values for the
interacting atom pairs that served as pseudo-energy variables to generate a CoIFA model. The classification
accuracy of the CoIFA model was validated using different metrics derived from a confusion matrix. Further
predictive lead mining was carried out using a consensus two-dimensional QSAR approach, which offers a
better predictive protocol compared to the arbitrary choice of a single QSAR model. The predictive ability
of the generated model was validated using different statistical metrics, and similarity-based coverage
estimation was carried out to define applicability boundaries. Few analogs designed using the concept of
bioisosterism were found to be promising and could be considered for synthesis and subsequent screening.
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| Date |
2009
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| Type |
Article
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://www.eprints.iicb.res.in/196/1/JOURNAL_OF_CHEMICAL_INFORMATION_AND_MODELING%2C_49(11)%2C2498%2D2511%2C2009[12].pdf
Vijayan, R S K and Bera, Indrani and Prabu, M and Saha, Sangita and Ghoshal, Nanda (2009) Combinatorial Library Enumeration and Lead Hopping using Comparative Interaction Fingerprint Analysis and Classical 2D QSAR Methods for Seeking Novel GABAA r3 Modulators. Journal of Chemical Information and Modeling, 49 (11). pp. 2498-2511. |
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| Relation |
http://dx.doi.org/10.1021/ci900309s CCC: $40.75
http://www.eprints.iicb.res.in/196/ |
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