These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
153 related articles for article (PubMed ID: 29221443)
1. Diverse effects of distance cutoff and residue interval on the performance of distance-dependent atom-pair potential in protein structure prediction. Yao Y; Gui R; Liu Q; Yi M; Deng H BMC Bioinformatics; 2017 Dec; 18(1):542. PubMed ID: 29221443 [TBL] [Abstract][Full Text] [Related]
2. ANDIS: an atomic angle- and distance-dependent statistical potential for protein structure quality assessment. Yu Z; Yao Y; Deng H; Yi M BMC Bioinformatics; 2019 Jun; 20(1):299. PubMed ID: 31159742 [TBL] [Abstract][Full Text] [Related]
3. An accurate, residue-level, pair potential of mean force for folding and binding based on the distance-scaled, ideal-gas reference state. Zhang C; Liu S; Zhou H; Zhou Y Protein Sci; 2004 Feb; 13(2):400-11. PubMed ID: 14739325 [TBL] [Abstract][Full Text] [Related]
4. DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking. Liu S; Vakser IA BMC Bioinformatics; 2011 Jul; 12():280. PubMed ID: 21745398 [TBL] [Abstract][Full Text] [Related]
5. Improving the orientation-dependent statistical potential using a reference state. Liu Y; Zeng J; Gong H Proteins; 2014 Oct; 82(10):2383-93. PubMed ID: 24810843 [TBL] [Abstract][Full Text] [Related]
6. Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction. Zhou H; Zhou Y Protein Sci; 2002 Nov; 11(11):2714-26. PubMed ID: 12381853 [TBL] [Abstract][Full Text] [Related]
7. Novel knowledge-based mean force potential at the profile level. Dong Q; Wang X; Lin L BMC Bioinformatics; 2006 Jun; 7():324. PubMed ID: 16803615 [TBL] [Abstract][Full Text] [Related]
8. Novel nonlinear knowledge-based mean force potentials based on machine learning. Dong Q; Zhou S IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(2):476-86. PubMed ID: 20820079 [TBL] [Abstract][Full Text] [Related]
9. What is the best reference state for designing statistical atomic potentials in protein structure prediction? Deng H; Jia Y; Wei Y; Zhang Y Proteins; 2012 Aug; 80(9):2311-22. PubMed ID: 22623012 [TBL] [Abstract][Full Text] [Related]
10. ICOSA: A Distance-Dependent, Orientation-Specific Coarse-Grained Contact Potential for Protein Structure Modeling. Elhefnawy W; Chen L; Han Y; Li Y J Mol Biol; 2015 Jul; 427(15):2562-2576. PubMed ID: 26055539 [TBL] [Abstract][Full Text] [Related]
11. A distance-dependent atomic knowledge-based potential for improved protein structure selection. Lu H; Skolnick J Proteins; 2001 Aug; 44(3):223-32. PubMed ID: 11455595 [TBL] [Abstract][Full Text] [Related]
12. A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction. Liu T; Horst JA; Samudrala R Proteins; 2009 Oct; 77(1):220-34. PubMed ID: 19422061 [TBL] [Abstract][Full Text] [Related]
13. Statistical mechanics-based method to extract atomic distance-dependent potentials from protein structures. Huang SY; Zou X Proteins; 2011 Sep; 79(9):2648-61. PubMed ID: 21732421 [TBL] [Abstract][Full Text] [Related]
14. GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction. Zhou H; Skolnick J Biophys J; 2011 Oct; 101(8):2043-52. PubMed ID: 22004759 [TBL] [Abstract][Full Text] [Related]
15. On the importance of the distance measures used to train and test knowledge-based potentials for proteins. Carlsen M; Koehl P; Røgen P PLoS One; 2014; 9(11):e109335. PubMed ID: 25411785 [TBL] [Abstract][Full Text] [Related]
16. Protein refolding in silico with atom-based statistical potentials and conformational search using a simple genetic algorithm. Fang Q; Shortle D J Mol Biol; 2006 Jun; 359(5):1456-67. PubMed ID: 16678202 [TBL] [Abstract][Full Text] [Related]
17. What is the best reference state for building statistical potentials in RNA 3D structure evaluation? Tan YL; Feng CJ; Jin L; Shi YZ; Zhang W; Tan ZJ RNA; 2019 Jul; 25(7):793-812. PubMed ID: 30996105 [TBL] [Abstract][Full Text] [Related]
18. Optimized distance-dependent atom-pair-based potential DOOP for protein structure prediction. Chae MH; Krull F; Knapp EW Proteins; 2015 May; 83(5):881-90. PubMed ID: 25693513 [TBL] [Abstract][Full Text] [Related]
19. Random Forest Refinement of the KECSA2 Knowledge-Based Scoring Function for Protein Decoy Detection. Pei J; Zheng Z; Merz KM J Chem Inf Model; 2019 May; 59(5):1919-1929. PubMed ID: 30726079 [TBL] [Abstract][Full Text] [Related]
20. Integrating Bonded and Nonbonded Potentials in the Knowledge-Based Scoring Function for Protein Structure Prediction. Wang X; Huang SY J Chem Inf Model; 2019 Jun; 59(6):3080-3090. PubMed ID: 31045366 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]