Exploring experimental sources of multiple protein conformations in structure-based drug design

Area of Science:

• Structural biology
• Computational chemistry
• Drug discovery

Background:

• Protein flexibility is crucial for accurate structure-based drug design.
• Previous work utilized computer-generated conformations for human immunodeficiency virus-1 protease (HIV-1p) pharmacophore modeling.

Purpose of the Study:

• To compare the utility of NMR ensembles versus crystal structures for generating multiple protein structure (MPS) pharmacophore models.
• To assess the impact of protein flexibility on structure-based drug design for HIV-1p.

Main Methods:

• Generated MPS pharmacophore models using an NMR ensemble and a collection of crystal structures of HIV-1p.
• Compared the performance of these models against models derived from single protein conformations.
• Evaluated the ability of models to discriminate known inhibitors from decoy molecules.

Main Results:

• Both NMR ensemble and crystal structure-based MPS models successfully discriminated HIV-1p inhibitors.
• MPS models outperformed single-conformation models.
• An NMR ensemble exhibited greater structural variation than a large set of crystal structures.
• The NMR-derived MPS model provided the most general and accurate active site representation.

Conclusions:

• Multiple protein structure pharmacophore modeling enhances structure-based drug design.
• NMR ensembles are valuable for capturing protein flexibility and generating robust drug design models.
• This study advocates for the use of NMR models in structure-based drug design.