Internal chirality descriptors iR and iS and ire and isi . A proposed notation to extend the usefulness of the R /S system by retaining the sense of stereochemistry in cases of ligand ranking changes

Chirality ◽  
2018 ◽  
Vol 30 (9) ◽  
pp. 1054-1066 ◽  
Author(s):  
Karel D. Klika ◽  
Alicja Wzorek ◽  
Vadim A. Soloshonok
Keyword(s):  
Ligand Ranking

Improving ligand‐ranking of AutoDock Vina by changing the empirical parameters

2021 ◽  
Author(s):  
T. Ngoc Han Pham ◽  
Trung Hai Nguyen ◽  
Nguyen Minh Tam ◽  
Thien Y. Vu ◽  
Nhat Truong Pham ◽  
...  
Keyword(s):  
Autodock Vina ◽  
Ligand Ranking

Improving Ligand-Ranking of AutoDock Vina by Changing the Empirical Parameters

2021 ◽  
Author(s):  
T. Ngoc Han Pham ◽  
Trung Hai Nguyen ◽  
Nguyen Minh Tam ◽  
Thien Y Vu ◽  
Nhat Truong Pham ◽  
...  
Keyword(s):  
Hydrogen Bond ◽  
Ligand Binding ◽  
Success Rate ◽  
Binding Affinity ◽  
Correlation Coefficient ◽  
Autodock Vina ◽  
Docking Simulations ◽  
Low Correlation ◽  
Very High ◽  
Ligand Ranking

AutoDock Vina (Vina) achieved a very high docking-success rate, p ̂, but give a rather low correlation coefficient, R, for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p ̂ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment R_set1=0.556±0.025 compared with R_Default=0.493±0.028 obtained by the original Vina and R_(Vina 1.2)=0.503±0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R≥0.500 for 32/48 targets, compared with the default package, giving R≥0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient (R_set1=0.621±0.016) than the default package (R_Default=0.552±0.018) and Vina version 1.2 (R_(Vina 1.2)=0.549±0.017). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

Target-Specific Native/Decoy Pose Classifier Improves the Accuracy of Ligand Ranking in the CSAR 2013 Benchmark

2014 ◽  
Vol 55 (1) ◽  
pp. 63-71 ◽  
Author(s):  
Denis Fourches ◽  
Regina Politi ◽  
Alexander Tropsha
Keyword(s):  
Ligand Ranking
Sign in / Sign up

Export Citation Format

Share Document