DOX: A new computational protocol for accurate prediction of the protein-ligand binding structures

2015 ◽  
Vol 37 (3) ◽  
pp. 336-344 ◽  
Author(s):  
Li Rao ◽  
Bo Chi ◽  
Yanliang Ren ◽  
Yongjian Li ◽  
Xin Xu ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Accurate Prediction ◽  
Computational Protocol

Accurate prediction of 195Pt NMR chemical shifts for a series of Pt(ii) and Pt(iv) antitumor agents by a non-relativistic DFT computational protocol

2014 ◽  
Vol 43 (14) ◽  
pp. 5409-5426 ◽  
Author(s):  
Athanassios C. Tsipis ◽  
Ioannis N. Karapetsas
Keyword(s):  
Dft Calculations ◽  
Anticancer Agents ◽  
Antitumor Agents ◽  
Chemical Shifts ◽  
Accurate Prediction ◽  
Nmr Chemical Shifts ◽  
Relativistic Dft ◽  
Square Planar ◽  
Wide Range ◽  
Computational Protocol

Exhaustive benchmark DFT calculations reveal that the non-relativistic GIAO-PBE0/SARC-ZORA(Pt)∪6-31+G(d)(E) computational protocol predicts accurate 195Pt NMR chemical shifts for a wide range of square planar Pt(ii) and octahedral Pt(iv) anticancer agents.

farPPI: a webserver for accurate prediction of protein-ligand binding structures for small-molecule PPI inhibitors by MM/PB(GB)SA methods

2018 ◽  
Vol 35 (10) ◽  
pp. 1777-1779 ◽  
Author(s):  
Zhe Wang ◽  
Xuwen Wang ◽  
Youyong Li ◽  
Tailong Lei ◽  
Ercheng Wang ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Small Molecule ◽  
Accurate Prediction

Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation

2020 ◽  
Vol 60 (11) ◽  
pp. 5563-5579 ◽  
Author(s):  
Francesca Deflorian ◽  
Laura Perez-Benito ◽  
Eelke B Lenselink ◽  
Miles Congreve ◽  
Herman W. T. van Vlijmen ◽  
...  
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Accurate Prediction ◽  
Free Energy Perturbation ◽  
Energy Perturbation

scholarly journals MDO: A Computational Protocol for Accurate Prediction of Full Flexibility Receptor-Ligand Binding Mode Structures

2021 ◽  
Author(s):  
Amar Y. Al-Ansi ◽  
Zijing Lin
Keyword(s):  
Ligand Binding ◽  
Success Rate ◽  
Md Simulation ◽  
Binding Mode ◽  
Structure Based Drug Design ◽  
Promising Tool ◽  
Local Sampling ◽  
Binding Structure ◽  
Computational Protocol ◽  
Oniom Calculations

Abstract Predicting the binding structure of bio-complex is essential for understanding its properties, functions, and mechanisms, but is rather difficult due to the huge sampling space involved. A new computational protocol, MDO, for finding the ligand binding structure is proposed. MDO consists of global sampling via MD simulation and clustering of the receptor configurations, local sampling via molecular docking and clustering of the ligand conformations, and binding structure optimization by the ONIOM (QM/QM) method. MDO is tested on 15 protein-ligand complexes with known accurate structures. The success rate of MDO predictions, with RMSD < 2 Å, is found to be 67%, substantially higher than the 40% success rate of conventional methods. The MDO success rate can be increased to 83% if the ONIOM calculations are applied only for the starting poses with ligands inside the binding cavities. The MDO protocol is a promising tool for the structure based drug design.

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