title: A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction.
abstract: BACKGROUND
  Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propose a general knowledge-guided scoring (KGS) strategy to tackle this problem. Our KGS strategy computes the binding constant of a given protein-ligand complex based on the known binding constant of an appropriate reference complex. A good training set that includes a sufficient number of protein-ligand complexes with known binding data needs to be supplied for finding the reference complex. The reference complex is required to share a similar pattern of key protein-ligand interactions to that of the complex of interest. Thus, some uncertain factors in protein-ligand binding may cancel out, resulting in a more accurate prediction of absolute binding constants.
  
  
  RESULTS
  In our study, an automatic algorithm was developed for summarizing key protein-ligand interactions as a pharmacophore model and identifying the reference complex with a maximal similarity to the query complex. Our KGS strategy was evaluated in combination with two scoring functions (X-Score and PLP) on three test sets, containing 112 HIV protease complexes, 44 carbonic anhydrase complexes, and 73 trypsin complexes, respectively. Our results obtained on crystal structures as well as computer-generated docking poses indicated that application of the KGS strategy produced more accurate predictions especially when X-Score or PLP alone did not perform well.
  
  
  CONCLUSIONS
  Compared to other targeted scoring functions, our KGS strategy does not require any re-parameterization or modification on current scoring methods, and its application is not tied to certain systems. The effectiveness of our KGS strategy is in theory proportional to the ever-increasing knowledge of experimental protein-ligand binding data. Our KGS strategy may serve as a more practical remedy for current scoring functions to improve their accuracy in binding affinity prediction.
authors.affiliation: State Key Laboratory of Bioorganic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, PR China.
authors.forename: Tiejun
authors.initials: T
authors.lastname: Cheng
authors.forename: Zhihai
authors.initials: Z
authors.lastname: Liu
authors.forename: Renxiao
authors.initials: R
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D030562:Databases, Protein; D015195:Drug Design; D008024:Ligands; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D013329:Structure-Activity Relationship
chemical_list: D008024:Ligands; D011506:Proteins
references.citation: J Chem Inf Model. 2008 Feb;48(2):288-95
references.pmid: 18229906
references.citation: J Chem Inf Model. 2008 Mar;48(3):602-12
references.pmid: 18293951
references.citation: J Med Chem. 2004 Jun 3;47(12):2977-80
references.pmid: 15163179
references.citation: J Med Chem. 2003 Feb 13;46(4):499-511
references.pmid: 12570372
references.citation: J Mol Graph Model. 2005 Apr;23(5):395-407
references.pmid: 15781182
references.citation: J Chem Inf Model. 2005 Sep-Oct;45(5):1291-302
references.pmid: 16180906
references.citation: Proteins. 1990;8(3):195-202
references.pmid: 2281083
references.citation: J Comput Chem. 2006 Nov 30;27(15):1866-75
references.pmid: 16983673
references.citation: J Med Chem. 2004 Jun 3;47(12):3032-47
references.pmid: 15163185
references.citation: J Comput Aided Mol Des. 2001 May;15(5):411-28
references.pmid: 11394736
references.citation: Chem Biol. 1995 May;2(5):317-24
references.pmid: 9383433
references.citation: J Chem Inf Model. 2007 Sep-Oct;47(5):1868-76
references.pmid: 17705464
references.citation: Drug Discov Today. 2002 Oct 15;7(20):1047-55
references.pmid: 12546894
references.citation: J Comput Chem. 2006 Nov 30;27(15):1876-82
references.pmid: 16983671
references.citation: Protein Eng. 1994 Mar;7(3):385-91
references.pmid: 8177887
references.citation: J Comput Aided Mol Des. 1996 Oct;10(5):427-40
references.pmid: 8951652
references.citation: J Chem Inf Model. 2007 Mar-Apr;47(2):279-94
references.pmid: 17381166
references.citation: J Mol Biol. 1995 Jan 6;245(1):43-53
references.pmid: 7823319
references.citation: J Med Chem. 2006 Oct 5;49(20):5895-902
references.pmid: 17004705
references.citation: Curr Opin Struct Biol. 1995 Apr;5(2):224-8
references.pmid: 7648325
references.citation: J Mol Biol. 1997 Apr 4;267(3):727-48
references.pmid: 9126849
references.citation: J Med Chem. 2006 Oct 19;49(21):6177-96
references.pmid: 17034125
references.citation: J Chem Inf Model. 2007 Jan-Feb;47(1):195-207
references.pmid: 17238265
references.citation: J Chem Inf Model. 2007 Sep-Oct;47(5):1858-67
references.pmid: 17685604
references.citation: J Med Chem. 2005 Oct 6;48(20):6296-303
references.pmid: 16190756
references.citation: Nucleic Acids Res. 2000 Jan 1;28(1):235-42
references.pmid: 10592235
references.citation: J Med Chem. 2004 Mar 25;47(7):1739-49
references.pmid: 15027865
references.citation: J Mol Graph Model. 2003 Jan;21(4):289-307
references.pmid: 12479928
references.citation: J Med Chem. 2003 Jun 5;46(12):2287-303
references.pmid: 12773034
references.citation: J Chem Inf Model. 2007 Jul-Aug;47(4):1379-85
references.pmid: 17530839
references.citation: Nature. 2004 Dec 16;432(7019):862-5
references.pmid: 15602552
references.citation: J Comput Aided Mol Des. 1997 Sep;11(5):425-45
references.pmid: 9385547
references.citation: J Comput Aided Mol Des. 1994 Jun;8(3):243-56
references.pmid: 7964925
references.citation: J Med Chem. 2005 Jun 16;48(12):4111-9
references.pmid: 15943484
references.citation: Proteins. 2004 Nov 1;57(2):225-42
references.pmid: 15340911
references.citation: J Mol Biol. 1996 Aug 23;261(3):470-89
references.pmid: 8780787
references.citation: J Chem Inf Comput Sci. 2004 Nov-Dec;44(6):2114-25
references.pmid: 15554682
references.citation: Proteins. 2005 Nov 1;61(2):272-87
references.pmid: 16106379
references.citation: J Chem Inf Model. 2009 Apr;49(4):1033-48
references.pmid: 19320460
references.citation: Drug Discov Today. 2009 Jun;14(11-12):562-9
references.pmid: 19508918
references.citation: J Comput Aided Mol Des. 2007 May;21(5):281-306
references.pmid: 17387436
references.citation: J Mol Biol. 2000 Jan 14;295(2):337-56
references.pmid: 10623530
references.citation: Proteins. 1998 Nov 15;33(3):367-82
references.pmid: 9829696
references.citation: J Med Chem. 1999 Mar 11;42(5):791-804
references.pmid: 10072678
references.citation: J Chem Inf Model. 2008 Apr;48(4):861-72
references.pmid: 18380449
references.citation: Org Biomol Chem. 2004 Nov 21;2(22):3267-73
references.pmid: 15534704
references.citation: J Chem Inf Model. 2006 Nov-Dec;46(6):2684-91
references.pmid: 17125208
references.citation: J Comput Aided Mol Des. 1996 Aug;10(4):293-304
references.pmid: 8877701
references.citation: J Chem Inf Model. 2006 Mar-Apr;46(2):636-41
references.pmid: 16562993
references.citation: J Chem Inf Model. 2007 Nov-Dec;47(6):2140-8
references.pmid: 17985865
references.citation: Curr Opin Chem Biol. 2007 Oct;11(5):494-502
references.pmid: 17936059
references.citation: Acc Chem Res. 2000 Dec;33(12):889-97
references.pmid: 11123888
references.citation: Curr Opin Drug Discov Devel. 2008 May;11(3):356-64
references.pmid: 18428089
references.citation: J Comput Aided Mol Des. 2002 Jan;16(1):11-26
references.pmid: 12197663
references.citation: J Med Chem. 2006 Oct 5;49(20):5912-31
references.pmid: 17004707
references.citation: J Comput Aided Mol Des. 1998 Jul;12(4):309-23
references.pmid: 9777490
references.citation: J Chem Inf Model. 2009 Apr;49(4):1079-93
references.pmid: 19358517