Lead Finder™

Great leads from high-throughput docking

Lead Finder™ is equipped with a dedicated algorithm and scoring function for virtual screening. The algorithm is designed to rapidly dock and score ligands using a method that has been optimized to separate actives from inactives.

A study on the DUD dataset showed an impressive overall ROC AUC of 0.74 and a median ROC AUC of 0.76.

Flexible licensing terms enable you to use your entire cluster, maximizing your return on investment.

  • Process thousands of molecules per hour
  • Find novel leads through virtual screening
  • Design focused libraries with a high enrichment of active compounds through screening of larger sets of virtual compounds
  • Predict the 3D structure of active molecules
  • Dock covalent and non-covalent ligands to your protein
  • Rapidly assess new molecule designs for their fit to the protein active site

Lead Finder is a BioMolTech product distributed by Cresset.

References

  1. Stroganov O.V. et al., Lead Finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening, J Chem Inf Model. 2008 Dec;48(12):2371-85. PubMed ID: 19007114
  2. Novikov F. et al., CSAR scoring challenge reveals the need for new concepts in estimating protein-ligand binding affinity, J Chem Inf Model. 2011 Sep 26;51(9):2090-2096. PubMed ID: 21612285
  3. Novikov F.N. et al., Improving performance of docking-based virtual screening by structural filtration, J Mol Model. 2010 Jul;16(7):1223-30. Epub 2009 Dec 30
  4. Novikov F.N. et al., Lead Finder docking and virtual screening evaluation with Astex and DUD test sets, J Comput Aided Mol Des. 2012 Jun;26(6):725-35
  5. Zeifman A.A. et al., Hit clustering can improve virtual fragment screening: CDK2 and PARP1 case studies, J Mol Model. 2012 Jun;18(6):2553-66. Epub 2011 Nov 9
  6. Stroganov O.V. et al., TSAR, a new graph-theoretical approach to computational modeling of protein side-chain flexibility: Modeling of ionization properties of proteins. Proteins, 2011 Sep; 79(9):2693-2710. PubMed ID: 21769942

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