e-Pharmacophores

The Advantage of e-Pharmacophores

Ligand-based pharmacophore modeling and structure-based protein-ligand docking are both recognized as integral parts of drug discovery, each method offering particular strengths. Ligand-based technologies, such as 3D-pharmacophore modeling, are fast and thus useful for quickly screening large compound databases. On the other hand, structure-based approaches can yield more diverse actives and lead to important target insights, but can be time-consuming. The e-Pharmacophores method achieves the advantages of both ligand- and structure-based approaches by generating energetically optimized, structure-based pharmacophores that can be used to rapidly screen millions of compounds.

Features

Glide XP scoring function accuracy:
The e-Pharmacophores method utilizes the Glide XP scoring function to accurately characterize protein-ligand interactions, resulting in improved database screening enrichments.

Receptor-based excluded volumes:
e-Pharmacophores allow for excluded volumes that correspond to regions of space that are occupied by the receptor.

Single and fragment modes:
Single-mode is suited to generating e-Pharmacophores from the co-crystal or docked pose of a known ligand in the target receptor. Fragment-mode will generate e-Pharmacophores from the energetically selected sites of docked fragment in cases where experimental information is unavailable. Both modes produce viable hypotheses, good database enrichments, and a diverse set of retrieved hits.

Greater levels of diversity:
e-Pharmacophores have been shown to retrieve a more diverse set of actives than traditional structure-based pharmacophore methods, making it a powerful tool for lead hopping. Speed and performance: Screen hundreds of molecules per second using either a pre-generated conformer database or generate conformers on-the-fly.

"ePharmaLib: A Versatile Library of e-Pharmacophores to Address Small-Molecule (Poly-)Pharmacology"

Aurélien F. A. Moumbock, Jianyu Li, Hoai T. T. Tran, Rahel Hinkelmann, Evelyn Lamy, Henning J. Jessen, and Stefan Günther, JCIM, 2022, 61(7), 3659-3666

· "Exploring Conformational Search Protocols for Ligand-based Virtual Screening and 3-D QSAR Modeling"

Cappel, D.; Dixon, S.L.; Sherman, W.; Duan, J., J. Comput. Aided Mol. Des., 2015, 29(2), 165-182

"Discovery of Thienoquinolone Derivatives as Selective and ATP Non-Competitive CDK5/p25 Inhibitors by Structure-Based Virtual Screening"

Chatterjee, A.; Cutler, S.J.; Doerksen, R.J.; Khan, I.A.; Williamson, J.S., Bioorg. Med. Chem., 2014, 22, 6409-6421

"Multiple e-pharmacophore modeling combined with high-throughput virtual screening and docking to identify potential inhibitors of β-Secretase(BACE1)"

Palakurti, R.; Sriram, D.; Yogeeswari, P.; Vadrevu, R., Mol. Inf., 2013, 32, 385-398

"E-Pharmacophore mapping and docking studies on Vitamin D receptor (VDR)"

Nagamani, S.; Kesavan, C.; Muthusamy, K., Bioinformation, 2012, 8(15), 705-10

"Identification of Novel Human Dipeptidyl Peptidase-IV Inhibitors of Natural Origin (Part I): Virtual Screening and Activity Assay"

Guasch, L.; Ojeda, M.J.; González-Abuín, N.; Sala, E.; Cereto-Massagué, A., PLoS ONE, 2012, 7(9), e44971. doi:10.1371/journal.pone.0044971

"Identification of Novel Human Dipeptidyl Peptidase-IV Inhibitors of Natural Origin (Part II): In Silico Prediction in Antidiabetic Extracts"

Guasch, L.; Sala, E.; Ojeda, M.J.; Valls, C.; Bladé, C., PLoS ONE, 2012, 7(9), e44972. doi:10.1371/journal.pone.0044972

"A plausible explanation for enhanced bioavailability of P-gp substrates in presence of piperine: simulation for next generation of P-gp inhibitors"

Singh, D.V.; Godbole, M.M.; Misra, K., J. Mol. Model., 2012, 19(1), 227-238

"Homology modeling, molecular dynamics, e-pharmacophore mapping and docking study of Chikungunya virus nsP2 protease"

Singh, Kh.D.; Kirubakaran, P.; Nagarajan, S.; Sakkiah, S.; Muthusamy, K.; Velmurgan, D.; Jeyakanthan, J., J. Mol. Model., 2012, 18(1), 39-51

· "Novel Method for Generating Structure-Based Pharmacophores Using Energetic Analysis"

Salam, N.K.; Nuti, R.; Sherman, W., J. Chem. Inf. Model., 2009, 49, 2356–2368

· "Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation"

Loving, K.; Salam, N.K.; Sherman, W., J. Comput. Aided Mol. Des., 2009, 23, 541–554

· "PHASE: A New Engine for Pharmacophore Perception, 3D QSAR Model Development, and 3D Database Screening. 1. Methodology and Preliminary Results"

Dixon, S.L.; Smondyrev, A.M.; Knoll, E.H.; Rao, S.N.; Shaw, D.E.; Friesner, R.A., J. Comput. Aided Mol. Des., 2006, 20, 647-671

· "Extra Precision Glide: Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein-Ligand Complexes"

Friesner, R.A.; Murphy, R.B.; Repasky, M.P.; Frye, L.L.; Greenwood, J.R.; Halgren, T.A.; Sanschagrin, P.C.; Mainz, D.T., J. Med. Chem., 2006, 49, 6177–6196

· "PHASE: A Novel Approach to Pharmacophore Modeling and 3D Database Searching"

Dixon, S.L.; Smondyrev, A.M.; Rao, S.N., Chem. Biol. Drug Des., 2006, 67, 370-372

Citations

Salam, N.K.; Nuti, R.; Sherman, W., "Novel Method for Generating Structure-Based Pharmacophores Using Energetic Analysis," J. Chem. Inf. Model., 2009, 49, 2356–2368

Loving, K.; Salam, N.K.; Sherman, W., "Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation," J. Comput. Aided Mol. Des., 2009, 23, 541–554