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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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PoLi: A Virtual Screening Pipeline Based on Template Pocket and Ligand Similarity.

Ambrish Roy1, Bharath Srinivasan1, Jeffrey Skolnick1

  • 1Center for the Study of Systems Biology, Georgia Institute of Technology , 250 14th Street NW, Atlanta, Georgia 30318, United States.

Journal of Chemical Information and Modeling
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Summary

A new pocket-based virtual screening (VS) method, PoLi, identifies drug candidates for protein targets lacking known structures. PoLi outperforms traditional VS methods, enabling discovery of novel ligands for challenging targets.

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Structural bioinformatics

Background:

  • Pharmaceutical research frequently aims to find small molecules for novel protein targets.
  • Many protein targets lack structures and known binders, limiting traditional virtual screening (VS) approaches.
  • Ligand homology modeling (LHM) is effective but fails when no homologous template structures exist for specific binding pockets.

Purpose of the Study:

  • To develop a generalized VS approach, PoLi, that overcomes LHM limitations for targeting specific pockets without homologous structures.
  • To create a pocket-based method that leverages the limited diversity of small molecule-binding pockets in proteins.
  • To improve VS performance by integrating structural and ligand-based similarity metrics.

Main Methods:

  • PoLi identifies similar ligand-binding pockets across a library of template proteins.
  • It selectively adapts template ligands for VS against the target pocket.
  • The algorithm is a hybrid structure and ligand-based VS, combining 2D fingerprint and 3D shape similarity.

Main Results:

  • PoLi achieved average enrichment factors of 13.4 (DUD) and 9.6 (DUD-E) in the top 1% of screened libraries using modeled receptor structures.
  • These results significantly surpass traditional docking-based VS (AutoDock Vina: 1.6/3.0) and homology-based VS (FINDSITE(filt): 9.0/7.9).
  • Experimental validation on dihydrofolate reductase (DHFR) using differential scanning fluorimetry (DSF) confirmed PoLi's ability to identify diverse ligands.

Conclusions:

  • PoLi represents a significant advancement in VS, particularly for targets lacking homologous structures.
  • The pocket-based approach effectively generalizes ligand homology modeling.
  • PoLi demonstrates superior performance compared to existing state-of-the-art VS methods, facilitating the discovery of novel drug candidates.