scholarly journals PyPLIF-ASSISTED REDOCKING INDOMETHACIN-(R)-ALPHA-ETHYL-ETHANOLAMIDE INTO CYCLOOXYGENASE-1

2013 ◽  
Vol 13 (3) ◽  
pp. 283-286 ◽  
Author(s):  
Muhammad Radifar ◽  
Nunung Yuniarti ◽  
Enade Perdana Istyastono
Keyword(s):  
Initial Step ◽  
Binding Pocket ◽  
Scoring Functions ◽  
Amino Acid Residues ◽  
Ligand Interaction ◽  
Cyclooxygenase 1 ◽  
External Software ◽  
Protein Ligand Interaction ◽  
Interaction Fingerprints ◽  
Cox 1

Identification of Protein-Ligand Interaction Fingerprints (PLIF) has been performed as the rescoring strategy to identify the best pose for the docked poses of indomethacin-(R)-α-ethyl-etanolamide (IMM) in the binding site of cyclooxygenase-1 (COX-1) from simulations using PLANTS molecular docking software version 1.2 (PLANTS1.2). Instead of using the scoring functions included in the docking software, the strategy presented in this article used external software called PyPLIF that could identify the interactions of the ligand to the amino acid residues in the binding pocket and presents them as binary bitstrings, which subsequently were compared to the interaction bitstrings of the co-crystal ligand pose. The results show that PyPLIF-assisted redocking strategy could select the correct pose much better compared to the pose selection without rescoring. Out of 1000 iterative attempts, PyPLIF-assisted redocking simulations could identify 971 correct poses (more than 95%), while the redocking simulations without PyPLIF could only identify 500 correct poses (50%).These works have also provided us with the initial step of the construction of a valid Structure-Based Virtual Screening (SBVS) protocol to identify COX-1 inhibitors.

scholarly journals Protein Ligand Interaction Fingerprints

2017 ◽  
pp. 1072-1091
Author(s):  
Ali HajiEbrahimi ◽  
Hamidreza Ghafouri ◽  
Mohsen Ranjbar ◽  
Amirhossein Sakhteman
Keyword(s):  
Virtual Screening ◽  
Docking Studies ◽  
Scoring Functions ◽  
Ligand Interaction ◽  
Advantages And Disadvantages ◽  
Protein Affinity ◽  
Binding Cavity ◽  
Protein Ligand Interaction ◽  
Interaction Fingerprints ◽  
Activity Information

A most challenging part in docking-based virtual screening is the scoring functions implemented in various docking programs in order to evaluate different poses of the ligands inside the binding cavity of the receptor. Precise and trustable measurement of ligand-protein affinity for Structure-Based Virtual Screening (SB-VS) is therefore, an outstanding problem in docking studies. Empirical post-docking filters can be helpful as a way to provide various types of structure-activity information. Different types of interaction have been presented between the ligands and the receptor so far. Based on the diversity and importance of PLIF methods, this chapter will focus on the comparison of different protocols. The advantages and disadvantages of all methods will be discussed explicitly in this chapter as well as future sights for further progress in this field. Different classifications approaches for the protein-ligand interaction fingerprints were also discussed in this chapter.

Protein Ligand Interaction Fingerprints

2016 ◽  
pp. 128-147
Author(s):  
Ali HajiEbrahimi ◽  
Hamidreza Ghafouri ◽  
Mohsen Ranjbar ◽  
Amirhossein Sakhteman
Keyword(s):  
Virtual Screening ◽  
Docking Studies ◽  
Scoring Functions ◽  
Ligand Interaction ◽  
Advantages And Disadvantages ◽  
Protein Affinity ◽  
Binding Cavity ◽  
Protein Ligand Interaction ◽  
Interaction Fingerprints ◽  
Activity Information

A most challenging part in docking-based virtual screening is the scoring functions implemented in various docking programs in order to evaluate different poses of the ligands inside the binding cavity of the receptor. Precise and trustable measurement of ligand-protein affinity for Structure-Based Virtual Screening (SB-VS) is therefore, an outstanding problem in docking studies. Empirical post-docking filters can be helpful as a way to provide various types of structure-activity information. Different types of interaction have been presented between the ligands and the receptor so far. Based on the diversity and importance of PLIF methods, this chapter will focus on the comparison of different protocols. The advantages and disadvantages of all methods will be discussed explicitly in this chapter as well as future sights for further progress in this field. Different classifications approaches for the protein-ligand interaction fingerprints were also discussed in this chapter.

scholarly journals Structural Basis of Enantioselective Inhibition of Cyclooxygenase-1 by S-α-Substituted Indomethacin Ethanolamides

2007 ◽  
Vol 282 (38) ◽  
pp. 28096-28105 ◽  
Author(s):  
Christine A. Harman ◽  
Melissa V. Turman ◽  
Kevin R. Kozak ◽  
Lawrence J. Marnett ◽  
William L. Smith ◽  
...  
Keyword(s):  
Binding Pocket ◽  
Drug Binding ◽  
Structural Basis ◽  
Cyclooxygenase 1 ◽  
Cox 2 ◽  
The Impact ◽  
First Time ◽  
Side Pocket ◽  
Cox 1 ◽  
Equal Efficacy

The modification of the nonselective nonsteroidal anti-inflammatory drug, indomethacin, by amidation presents a promising strategy for designing novel cyclooxygenase (COX)-2-selective inhibitors. A series of α-substituted indomethacin ethanolamides, which exist as R/S-enantiomeric pairs, provides a means to study the impact of stereochemistry on COX inhibition. Comparative studies revealed that the R- and S-enantiomers of the α-substituted analogs inhibit COX-2 with almost equal efficacy, whereas COX-1 is selectively inhibited by the S-enantiomers. Mutagenesis studies have not been able to identify residues that manifest the enantioselectivity in COX-1. In an effort to understand the structural impact of chirality on COX-1 selectivity, the crystal structures of ovine COX-1 in complexes with an enantiomeric pair of these indomethacin ethanolamides were determined at resolutions between 2.75 and 2.85Å. These structures reveal unique, enantiomer-selective interactions within the COX-1 side pocket region that stabilize drug binding and account for the chiral selectivity observed with the (S)-α-substituted indomethacin ethanolamides. Kinetic analysis of binding demonstrates that both inhibitors bind quickly utilizing a two-step mechanism. However, the second binding step is readily reversible for the R-enantiomer, whereas for the S-enantiomer, it is not. These studies establish for the first time the structural and kinetic basis of high affinity binding of a neutral inhibitor to COX-1 and demonstrate that the side pocket of COX-1, previously thought to be sterically inaccessible, can serve as a binding pocket for inhibitor association.

Assessing protein–ligand interaction scoring functions with the CASF-2013 benchmark

2018 ◽  
Vol 13 (4) ◽  
pp. 666-680 ◽  
Author(s):  
Yan Li ◽  
Minyi Su ◽  
Zhihai Liu ◽  
Jie Li ◽  
Jie Liu ◽  
...  
Keyword(s):  
Scoring Functions ◽  
Ligand Interaction ◽  
Protein Ligand Interaction

Synthesis and Antiplatelet Potential Evaluation of 1,3,4-Oxadiazoles Derivatives

2019 ◽  
Vol 233 (12) ◽  
pp. 1741-1759
Author(s):  
Ayesha Ramzan ◽  
Areesha Nazeer ◽  
Ahmad Irfan ◽  
Abdullah G. Al-Sehemi ◽  
Francis Verpoort ◽  
...  
Keyword(s):  
Arachidonic Acid ◽  
Antiplatelet Agents ◽  
Binding Pocket ◽  
Quantitative Structure Activity Relationship ◽  
New Drugs ◽  
Aggregation Effect ◽  
Antiplatelet Aggregation ◽  
Cyclooxygenase 1 ◽  
Aggregation Inhibition ◽  
Cox 1

AbstractA novel series of 2-(3-methyl-1,6-diphenyl-1H-pyrazolo[3,4-b]pyridin-4-yl)-5-aryl-1,3,4-oxadiazoles (4a–4h) has been synthesized from corresponding hydrazones (3a–3h) and evaluated their antiplatelet aggregation effect induced by arachidonic acid and collagen. Spectral data and elemental evaluation were used to confirm the structure of the compounds while molecular docking against cyclooxygenase 1 and 2 (COX1 & COX2) and quantitative structure-activity relationship (QSAR) were performed in describing their antiplatelet potential. All synthesized compound exhibited more than 50% platelet aggregation inhibition against both arachidonic acid and collagen. Antiplatelet activities results showed that 4b and 4f compounds have highest % inhibition against arachidonic acid. High Egap and ionization potential values showed that the compound 4d, 4e and 4f were supposed to be more active and good electron donor while 4b, 4c, 4d, 4e, 4g and 4h might be more active due to more electrophilic sites. Interaction with more than one residues in the binding pocket of COX-1 in comparison with aspirin and ligand efficacy (LE) consequences showed that compounds have excellent action potential for COX-1. Computational evaluations are in good agreement with antiplatelet activities of the compounds. All compounds might be promising antiplatelet agents especially 4b, 4f and helpful in the synthesis of new drugs for the treatment of cardiovascular diseases (CVDs).

Predicting Ligand Binding Modes from Neural Networks Trained on Protein–Ligand Interaction Fingerprints

2013 ◽  
Vol 53 (4) ◽  
pp. 763-772 ◽  
Author(s):  
Vladimir Chupakhin ◽  
Gilles Marcou ◽  
Igor Baskin ◽  
Alexandre Varnek ◽  
Didier Rognan
Keyword(s):  
Neural Networks ◽  
Ligand Binding ◽  
Binding Modes ◽  
Ligand Interaction ◽  
Protein Ligand Interaction ◽  
Interaction Fingerprints

Protein–ligand interaction fingerprints for accurate prediction of dissociation rates of p38 MAPK Type II inhibitors

2019 ◽  
Vol 11 (2) ◽  
pp. 53-60 ◽  
Author(s):  
Duo Zhang ◽  
Shuheng Huang ◽  
Hu Mei ◽  
MuliadiYeremia Kevin ◽  
Tingting Shi ◽  
...  
Keyword(s):  
P38 Mapk ◽  
Accurate Prediction ◽  
Type Ii ◽  
Ligand Interaction ◽  
Protein Ligand Interaction ◽  
Interaction Fingerprints
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