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Items: 1 to 20 of 128

1.

Implementation of the Hungarian algorithm to account for ligand symmetry and similarity in structure-based design.

Allen WJ, Rizzo RC.

J Chem Inf Model. 2014 Feb 24;54(2):518-29. doi: 10.1021/ci400534h.

2.

DOCK 6: Impact of new features and current docking performance.

Allen WJ, Balius TE, Mukherjee S, Brozell SR, Moustakas DT, Lang PT, Case DA, Kuntz ID, Rizzo RC.

J Comput Chem. 2015 Jun 5;36(15):1132-56. doi: 10.1002/jcc.23905.

3.

A fast protein-ligand docking algorithm based on hydrogen bond matching and surface shape complementarity.

Luo W, Pei J, Zhu Y.

J Mol Model. 2010 May;16(5):903-13. doi: 10.1007/s00894-009-0598-7.

PMID:
19823881
4.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

Ballante F, Marshall GR.

J Chem Inf Model. 2016 Jan 25;56(1):54-72. doi: 10.1021/acs.jcim.5b00603.

PMID:
26682916
5.

FRED and HYBRID docking performance on standardized datasets.

McGann M.

J Comput Aided Mol Des. 2012 Aug;26(8):897-906. doi: 10.1007/s10822-012-9584-8.

PMID:
22669221
6.

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
7.

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
8.

Beware of docking!

Chen YC.

Trends Pharmacol Sci. 2015 Feb;36(2):78-95. doi: 10.1016/j.tips.2014.12.001. Review. Erratum in: Trends Pharmacol Sci. 2015 Sep;36(9):617.

9.

AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility.

Ravindranath PA, Forli S, Goodsell DS, Olson AJ, Sanner MF.

PLoS Comput Biol. 2015 Dec 2;11(12):e1004586. doi: 10.1371/journal.pcbi.1004586.

10.

Beware of machine learning-based scoring functions-on the danger of developing black boxes.

Gabel J, Desaphy J, Rognan D.

J Chem Inf Model. 2014 Oct 27;54(10):2807-15. doi: 10.1021/ci500406k.

PMID:
25207678
11.

LIGSIFT: an open-source tool for ligand structural alignment and virtual screening.

Roy A, Skolnick J.

Bioinformatics. 2015 Feb 15;31(4):539-44. doi: 10.1093/bioinformatics/btu692.

12.

Similarity-driven flexible ligand docking.

Fradera X, Knegtel RM, Mestres J.

Proteins. 2000 Sep 1;40(4):623-36.

PMID:
10899786
13.

Pharmacophore-based similarity scoring for DOCK.

Jiang L, Rizzo RC.

J Phys Chem B. 2015 Jan 22;119(3):1083-102. doi: 10.1021/jp506555w.

14.

PSI-DOCK: towards highly efficient and accurate flexible ligand docking.

Pei J, Wang Q, Liu Z, Li Q, Yang K, Lai L.

Proteins. 2006 Mar 1;62(4):934-46.

PMID:
16395666
15.

MS-DOCK: accurate multiple conformation generator and rigid docking protocol for multi-step virtual ligand screening.

Sauton N, Lagorce D, Villoutreix BO, Miteva MA.

BMC Bioinformatics. 2008 Apr 10;9:184. doi: 10.1186/1471-2105-9-184.

16.

Strategies for lead discovery: application of footprint similarity targeting HIVgp41.

Holden PM, Allen WJ, Gochin M, Rizzo RC.

Bioorg Med Chem. 2014 Jan 1;22(1):651-61. doi: 10.1016/j.bmc.2013.10.022.

17.

PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

Ng MC, Fong S, Siu SW.

J Bioinform Comput Biol. 2015 Jun;13(3):1541007. doi: 10.1142/S0219720015410073.

PMID:
25800162
18.

A python-based docking program utilizing a receptor bound ligand shape: PythDock.

Chung JY, Cho SJ, Hah JM.

Arch Pharm Res. 2011 Sep;34(9):1451-8. doi: 10.1007/s12272-011-0906-5.

PMID:
21975806
19.
20.

Use of experimental design to optimize docking performance: the case of LiGenDock, the docking module of LiGen, a new de novo design program.

Beato C, Beccari AR, Cavazzoni C, Lorenzi S, Costantino G.

J Chem Inf Model. 2013 Jun 24;53(6):1503-17. doi: 10.1021/ci400079k.

PMID:
23590204
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