Nonfitting protein-ligand interaction scoring function based on first-principles theoretical chemistry methods: Development and application on kinase inhibitors

2013 ◽  
Vol 34 (19) ◽  
pp. 1636-1646 ◽  
Author(s):  
Li Rao ◽  
Igor Ying Zhang ◽  
Wenping Guo ◽  
Li Feng ◽  
Eric Meggers ◽  
...  
Keyword(s):  
First Principles ◽  
Kinase Inhibitors ◽  
Scoring Function ◽  
Theoretical Chemistry ◽  
Ligand Interaction ◽  
Methods Development ◽  
Protein Ligand Interaction

scholarly journals Flavonoids as Putative Epi-Modulators: Insight into Their Binding Mode with BRD4 Bromodomains Using Molecular Docking and Dynamics

Biomolecules ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 61 ◽  
Author(s):  
Fernando Prieto-Martínez ◽  
José Medina-Franco
Keyword(s):  
Kinase Inhibitors ◽  
Binding Mode ◽  
Binding Modes ◽  
Ligand Interaction ◽  
Bet Inhibitors ◽  
Protein Ligand Interaction ◽  
Brd4 Inhibition ◽  
Dynamics Simulations ◽  
Insight Into

Flavonoids are widely recognized as natural polydrugs, given their anti-inflammatory, antioxidant, sedative, and antineoplastic activities. Recently, different studies showed that flavonoids have the potential to inhibit bromodomain and extraterminal (BET) bromodomains. Previous reports suggested that flavonoids bind between the Z and A loops of the bromodomain (ZA channel) due to their orientation and interactions with P86, V87, L92, L94, and N140. Herein, a comprehensive characterization of the binding modes of fisetin and the biflavonoid, amentoflavone, is discussed. To this end, both compounds were docked with BET bromodomain 4 (BRD4) using four docking programs. The results were post-processed with protein–ligand interaction fingerprints. To gain further insight into the binding mode of the two natural products, the docking results were further analyzed with molecular dynamics simulations. The results showed that amentoflavone makes numerous contacts in the ZA channel, as previously described for flavonoids and kinase inhibitors. It was also found that amentoflavone can potentially make contacts with non-canonical residues for BET inhibition. Most of these contacts were not observed with fisetin. Based on these results, amentoflavone was experimentally tested for BRD4 inhibition, showing activity in the micromolar range. This work may serve as the basis for scaffold optimization and the further characterization of flavonoids as BET inhibitors.

Improving structure-based virtual screening performance via learning from scoring function components

2020 ◽  
Author(s):  
Guo-Li Xiong ◽  
Wen-Ling Ye ◽  
Chao Shen ◽  
Ai-Ping Lu ◽  
Ting-Jun Hou ◽  
...  
Keyword(s):  
Scoring Function ◽  
Scoring Functions ◽  
Ligand Interaction ◽  
Promising Alternative ◽  
Screening Performance ◽  
Comparable Performance ◽  
Protein Ligand Interaction ◽  
New Protein ◽  
Virtual Screening Performance ◽  
Energy Components

Abstract Scoring functions (SFs) based on complex machine learning (ML) algorithms have gradually emerged as a promising alternative to overcome the weaknesses of classical SFs. However, extensive efforts have been devoted to the development of SFs based on new protein–ligand interaction representations and advanced alternative ML algorithms instead of the energy components obtained by the decomposition of existing SFs. Here, we propose a new method named energy auxiliary terms learning (EATL), in which the scoring components are extracted and used as the input for the development of three levels of ML SFs including EATL SFs, docking-EATL SFs and comprehensive SFs with ascending VS performance. The EATL approach not only outperforms classical SFs for the absolute performance (ROC) and initial enrichment (BEDROC) but also yields comparable performance compared with other advanced ML-based methods on the diverse subset of Directory of Useful Decoys: Enhanced (DUD-E). The test on the relatively unbiased actives as decoys (AD) dataset also proved the effectiveness of EATL. Furthermore, the idea of learning from SF components to yield improved screening power can also be extended to other docking programs and SFs available.

scholarly journals Flavonoids as Putative epi-modulators: Insights into their Binding Mode with BRD4 Bromodomain using Molecular Docking and Dynamics.

2018 ◽  
Author(s):  
Fernando Daniel Prieto-Martínez ◽  
José Luis Medina-Franco
Keyword(s):  
Kinase Inhibitors ◽  
Binding Mode ◽  
Ligand Interaction ◽  
Bet Inhibitors ◽  
Protein Ligand Interaction ◽  
Brd4 Inhibition ◽  
Molecular Dynamics Results ◽  
Molecular Docking And Dynamics ◽  
Micromolar Range

Flavonoids are widely recognized as natural polydrugs, given their anti-inflammatory, antioxidant, sedative and antineoplastic activities. Recently, different studies have shown that flavonoid have the potential to inhibit BET bromodomains. Previous reports suggest that flavonoids are putative inhibitors of the ZA channel due to their orientation and interactions with P86, V87, L92, L94 and N140. Herein, a comprehensive characterization of the binding mode of the biflavonoid amentoflavone and fisetin is discussed. To this end, both compounds were docked with BRD4 using four docking programs. Results were post-processed with protein-ligand interaction fingerprints. To gain further insights into the binding mode of the two natural products, docking results were further analyzed with molecular dynamics. Results showed that amentoflavone makes numerous contacts in the ZA channel, as previously described for flavonoids and kinase inhibitors. It was also found that amentoflavone can potentially make contacts with non-canonical residues for BET inhibition. Most of these contacts were not observed with fisetin. Based on these results, amentoflavone was tested for BRD4 inhibition, showing activity in the micromolar range. This work may serve as basis for scaffold optimization and further characterization of flavonoids as BET inhibitors.

scholarly journals CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network

2019 ◽  
Vol 7 (1) ◽  
pp. 121-134
Author(s):  
Raulia R. Syrlybaeva ◽  
Marat R. Talipov
Keyword(s):  
Neural Network ◽  
Scoring Function ◽  
Binding Energies ◽  
Average Error ◽  
Ligand Interaction ◽  
Interacting Protein ◽  
Final Score ◽  
Protein Ligand Interaction ◽  
Weighting Coefficients ◽  
Empirical Scoring Function

AbstractA new CBSF empirical scoring function for the estimation of binding energies between proteins and small molecules is proposed in this report. The final score is obtained as a sum of three energy terms calculated using descriptors based on a simple counting of the interacting protein-ligand atomic pairs. All the required weighting coefficients for this method were derived from a pretrained neural network. The proposed method demonstrates a high accuracy and reproduces binding energies of protein-ligand complexes from the CASF-2016 test set with a standard deviation of 2.063 kcal/mol (1.511 log units) and an average error of 1.682 kcal/mol (1.232 log units). Thus, CBSF has a significant potential for the development of rapid and accurate estimates of the protein-ligand interaction energies.

scholarly journals Two Rules on the Protein-Ligand Interaction

2008 ◽  
Author(s):  
Xiaodong Pang ◽  
Linxiang Zhou ◽  
Lily Zhang ◽  
Lina Xu ◽  
Xinyi Zhang
Keyword(s):  
Ligand Interaction ◽  
Protein Ligand Interaction

scholarly journals Protein-ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange-correlation functional

2021 ◽  
Author(s):  
Lennart Gundelach ◽  
Christofer S Tautermann ◽  
Thomas Fox ◽  
Chris-Kriton Skylaris
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Dft Calculations ◽  
Quantum Mechanical ◽  
Free Energies ◽  
Ligand Interaction ◽  
Exchange Correlation ◽  
Ligand Free ◽  
Protein Ligand Interaction ◽  
Binding Free Energies

The accurate prediction of protein-ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein-ligand interaction at a quantum mechanical level, instead of...

scholarly journals Fragment-centric topographic mapping method guides the understanding of ABCG2-inhibitor interactions

RSC Advances ◽  
2019 ◽  
Vol 9 (14) ◽  
pp. 7757-7766 ◽  
Author(s):  
Yao Wu ◽  
Xin-Ying Gao ◽  
Xin-Hui Chen ◽  
Shao-Long Zhang ◽  
Wen-Juan Wang ◽  
...  
Keyword(s):  
Mapping Method ◽  
Topographic Mapping ◽  
Ligand Interaction ◽  
Mapping Tool ◽  
Protein Ligand Interaction ◽  
Insight Into ◽  
Computational Strategy

Our study gains insight into the development of novel specific ABCG2 inhibitors, and develops a comprehensive computational strategy to understand protein ligand interaction with the help of AlphaSpace, a fragment-centric topographic mapping tool.

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