|
Internet Electronic Journal of Molecular Design - IEJMD, ISSN 1538-6414, CODEN IEJMAT
| ABSTRACT - Internet Electron. J. Mol. Des. September 2004, Volume 3, Number 9, 528-543 |
Ligand-based Computation of HIV-1 Integrase Inhibition Strength
within a Series of β-ketoamide Derivatives
Frederik F. D. Daeyaert, H. Maarten Vinkers, Marc R. de Jonge, Jan Heeres, Lucien M. H. Koymans, Paul J. Lewi, and Paul A. J. Janssen
Internet Electron. J. Mol. Des. 2004, 3, 528-543
|
Abstract:
A continuous demand exists for novel bioactive molecules. When a
lead structure has been discovered and looks promising for further
development, series of analogues will be made. Normally, the
synthesis of many compounds is required to improve on the
activity, or to keep good activity while optimizing other properties
of relevance. A computational model that accurately predicts the
activity of derivatives before their synthesis is beneficial to the
speed and cost of lead optimization. It can be advantageous when
such a model does not require geometrical information on the
target protein structure. A conformational analysis was performed
on 201 ketoamide ester derivatives that inhibit HIV integrase. The
derivatives were aligned to the lowest energy conformer of the
most potent inhibitor with the SEAL method. Five CoMSIA fields
were computed for each compound taking into account steric,
polarizability, charge, H-bond acceptor, and H-bond donor
properties. A model for integrase-inhibitor interaction was derived
by PLS regression. The predictivity of the model was tested by
scrambling the data, leave-n-out experiments and applying the
model to a ketoamide acid series of integrase inhibitors. In order to
elucidate the binding mode of the inhibitors, the model was
mapped on a crystal structure of the integrase enzyme. The
CoMSIA model derived from the 201 ketoamide ester derivatives
has an R2 of 0.75. The resulting fields of the molecular properties
required for strong inhibition can be qualitatively understood.
Scrambling the data prohibited the derivation of a predictive
model. The models derived from 100 derivatives when applied to
the remaining 101 compounds, resulted in a prediction with an
absolute deviation of 0.28 log10 unit/compound. The accuracy of
prediction when the model was applied to 74 ketoamide acids was
0.42 log10 unit/compound. Mapping the model onto the integrase
enzyme did not lead to an obvious binding mode. The predictivity
of our model allows for guiding the synthesis of novel analogues.
Our approach holds its predictive value when applied to a different
series of inhibitors. The geometry of integrase-inhibitor binding is
not very well understood at the present time, which emphasizes the
advantages of an approach that does not require this knowledge for
the design of novel active compounds.
|