Rationalizing Fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies
IR@IICB: CSIR-Indian Institute of Chemical Biology, Kolkata
View Archive Info| Field | Value | |
| Title |
Rationalizing Fragment based drug discovery for BACE1: insights
from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF
studies
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| Creator |
Manoharan, Prabu
Vijayan, R S K Ghoshal, Nanda |
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| Subject |
Structural Biology & Bioinformatics
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| Description |
The ability to identify fragments that interact
with a biological target is a key step in FBDD. To date, the
concept of fragment based drug design (FBDD) is
increasingly driven by bio-physical methods. To expand
the boundaries of QSAR paradigm, and to rationalize
FBDD using In silico approach, we propose a fragment
based QSAR methodology referred here in as FB-QSAR.
The FB-QSAR methodology was validated on a dataset
consisting of 52 Hydroxy ethylamine (HEA) inhibitors,
disclosed by GlaxoSmithKline Pharmaceuticals as potential
anti-Alzheimer agents. To address the issue of target
selectivity, a major confounding factor in the development
of selective BACE1 inhibitors, FB-QSSR models were
developed using the reported off target activity values. A
heat map constructed, based on the activity and selectivity
profile of the individual R-group fragments, and was in turn
used to identify superior R-group fragments. Further,
simultaneous optimization of multiple properties, an issue
encountered in real-world drug discovery scenario, and
often overlooked in QSAR approaches, was addressed
using a Multi Objective (MO-QSPR) method that balances
properties, based on the defined objectives. MO-QSPR was
implemented using Derringer and Suich desirability algorithm
to identify the optimal level of independent variables
(X) that could confer a trade-off between selectivity and
activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields)
studies. To exemplify the potentials of FB-QSAR and
MO-QSPR in a pragmatic fashion, the insights gleaned from
the MO-QSPR study was reverse engineered using Inverse-
QSAR in a combinatorial fashion to enumerate some prospective
novel, potent and selective BACE1 inhibitors.
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| Date |
2010
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| Type |
Article
PeerReviewed |
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| Relation |
http:/dx.doi.org/10.1007/s10822-010-9378-9
http://www.eprints.iicb.res.in/81/ |
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| Identifier |
Manoharan, Prabu and Vijayan, R S K and Ghoshal, Nanda (2010) Rationalizing Fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies. J Comput Aided Mol Des, 24 (10). pp. 843-864.
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