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Items: 1 to 20 of 108

1.

CSAR benchmark exercise 2011-2012: evaluation of results from docking and relative ranking of blinded congeneric series.

Damm-Ganamet KL, Smith RD, Dunbar JB Jr, Stuckey JA, Carlson HA.

J Chem Inf Model. 2013 Aug 26;53(8):1853-70. doi: 10.1021/ci400025f.

2.

Target-specific native/decoy pose classifier improves the accuracy of ligand ranking in the CSAR 2013 benchmark.

Fourches D, Politi R, Tropsha A.

J Chem Inf Model. 2015 Jan 26;55(1):63-71. doi: 10.1021/ci500519w.

PMID:
25521713
3.

Incorporating backbone flexibility in MedusaDock improves ligand-binding pose prediction in the CSAR2011 docking benchmark.

Ding F, Dokholyan NV.

J Chem Inf Model. 2013 Aug 26;53(8):1871-9. doi: 10.1021/ci300478y.

PMID:
23237273
4.

CSAR data set release 2012: ligands, affinities, complexes, and docking decoys.

Dunbar JB Jr, Smith RD, Damm-Ganamet KL, Ahmed A, Esposito EX, Delproposto J, Chinnaswamy K, Kang YN, Kubish G, Gestwicki JE, Stuckey JA, Carlson HA.

J Chem Inf Model. 2013 Aug 26;53(8):1842-52. doi: 10.1021/ci4000486.

5.

Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise.

Koes DR, Baumgartner MP, Camacho CJ.

J Chem Inf Model. 2013 Aug 26;53(8):1893-904. doi: 10.1021/ci300604z.

6.

Docking and Scoring with Target-Specific Pose Classifier Succeeds in Native-Like Pose Identification But Not Binding Affinity Prediction in the CSAR 2014 Benchmark Exercise.

Politi R, Convertino M, Popov K, Dokholyan NV, Tropsha A.

J Chem Inf Model. 2016 Jun 27;56(6):1032-41. doi: 10.1021/acs.jcim.5b00751.

PMID:
27050767
7.

Predicting binding affinity of CSAR ligands using both structure-based and ligand-based approaches.

Fourches D, Muratov E, Ding F, Dokholyan NV, Tropsha A.

J Chem Inf Model. 2013 Aug 26;53(8):1915-22. doi: 10.1021/ci400216q.

8.

Automated large-scale file preparation, docking, and scoring: evaluation of ITScore and STScore using the 2012 Community Structure-Activity Resource benchmark.

Grinter SZ, Yan C, Huang SY, Jiang L, Zou X.

J Chem Inf Model. 2013 Aug 26;53(8):1905-14. doi: 10.1021/ci400045v.

9.

Improving docking results via reranking of ensembles of ligand poses in multiple X-ray protein conformations with MM-GBSA.

Greenidge PA, Kramer C, Mozziconacci JC, Sherman W.

J Chem Inf Model. 2014 Oct 27;54(10):2697-717. doi: 10.1021/ci5003735.

PMID:
25266271
10.

Comparative assessment of scoring functions on an updated benchmark: 2. Evaluation methods and general results.

Li Y, Han L, Liu Z, Wang R.

J Chem Inf Model. 2014 Jun 23;54(6):1717-36. doi: 10.1021/ci500081m.

PMID:
24708446
11.

Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

Brylinski M.

J Chem Inf Model. 2013 Nov 25;53(11):3097-112. doi: 10.1021/ci400510e.

PMID:
24171431
12.

CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma.

Carlson HA, Smith RD, Damm-Ganamet KL, Stuckey JA, Ahmed A, Convery MA, Somers DO, Kranz M, Elkins PA, Cui G, Peishoff CE, Lambert MH, Dunbar JB Jr.

J Chem Inf Model. 2016 Jun 27;56(6):1063-77. doi: 10.1021/acs.jcim.5b00523.

PMID:
27149958
13.

CSAR Benchmark Exercise 2013: Evaluation of Results from a Combined Computational Protein Design, Docking, and Scoring/Ranking Challenge.

Smith RD, Damm-Ganamet KL, Dunbar JB Jr, Ahmed A, Chinnaswamy K, Delproposto JE, Kubish GM, Tinberg CE, Khare SD, Dou J, Doyle L, Stuckey JA, Baker D, Carlson HA.

J Chem Inf Model. 2016 Jun 27;56(6):1022-31. doi: 10.1021/acs.jcim.5b00387.

PMID:
26419257
14.

Docking challenge: protein sampling and molecular docking performance.

Elokely KM, Doerksen RJ.

J Chem Inf Model. 2013 Aug 26;53(8):1934-45. doi: 10.1021/ci400040d.

15.

Combined Approach of Patch-Surfer and PL-PatchSurfer for Protein-Ligand Binding Prediction in CSAR 2013 and 2014.

Zhu X, Shin WH, Kim H, Kihara D.

J Chem Inf Model. 2016 Jun 27;56(6):1088-99. doi: 10.1021/acs.jcim.5b00625.

PMID:
26691286
16.

Application of the docking program SOL for CSAR benchmark.

Sulimov AV, Kutov DC, Oferkin IV, Katkova EV, Sulimov VB.

J Chem Inf Model. 2013 Aug 26;53(8):1946-56. doi: 10.1021/ci400094h.

PMID:
23829357
17.

Investigation on the effect of key water molecules on docking performance in CSARdock exercise.

Kumar A, Zhang KY.

J Chem Inf Model. 2013 Aug 26;53(8):1880-92. doi: 10.1021/ci400052w.

PMID:
23617355
18.

SFCscore(RF): a random forest-based scoring function for improved affinity prediction of protein-ligand complexes.

Zilian D, Sotriffer CA.

J Chem Inf Model. 2013 Aug 26;53(8):1923-33. doi: 10.1021/ci400120b.

PMID:
23705795
19.

A pose prediction approach based on ligand 3D shape similarity.

Kumar A, Zhang KY.

J Comput Aided Mol Des. 2016 Jun;30(6):457-69. doi: 10.1007/s10822-016-9923-2.

PMID:
27379501
20.

HarmonyDOCK: the structural analysis of poses in protein-ligand docking.

Plewczynski D, Philips A, Von Grotthuss M, Rychlewski L, Ginalski K.

J Comput Biol. 2014 Mar;21(3):247-56. doi: 10.1089/cmb.2009.0111.

PMID:
21091053
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