scholarly journals Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations

2019 ◽  
Vol 20 (23) ◽  
pp. 5834 ◽  
Author(s):  
Pavel Polishchuk ◽  
Alina Kutlushina ◽  
Dayana Bashirova ◽  
Olena Mokshyna ◽  
Timur Madzhidov
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Complex Structure ◽  
Three Dimensional ◽  
Cyclin Dependent Kinase ◽  
Dynamic Simulations ◽  
Crystal Complex ◽  
Pharmacophore Models ◽  
Selection And Ranking ◽  
Selection Of

Pharmacophore models are widely used for the identification of promising primary hits in compound large libraries. Recent studies have demonstrated that pharmacophores retrieved from protein-ligand molecular dynamic trajectories outperform pharmacophores retrieved from a single crystal complex structure. However, the number of retrieved pharmacophores can be enormous, thus, making it computationally inefficient to use all of them for virtual screening. In this study, we proposed selection of distinct representative pharmacophores by the removal of pharmacophores with identical three-dimensional (3D) pharmacophore hashes. We also proposed a new conformer coverage approach in order to rank compounds using all representative pharmacophores. Our results for four cyclin-dependent kinase 2 (CDK2) complexes with different ligands demonstrated that the proposed selection and ranking approaches outperformed the previously described common hits approach. We also demonstrated that ranking, based on averaged predicted scores obtained from different complexes, can outperform ranking based on scores from an individual complex. All developments were implemented in open-source software pharmd.

scholarly journals Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4829
Author(s):  
Sajjad Haider ◽  
Assem Barakat ◽  
Zaheer Ul-Haq
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Root Mean Square ◽  
Cancer Metastasis ◽  
Pharmacophore Model ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Radius Of Gyration ◽  
Mean Square ◽  
Dynamic Simulations

CXCL12 are small pro-inflammatory chemo-attractant cytokines that bind to a specific receptor CXCR4 with a role in angiogenesis, tumor progression, metastasis, and cell survival. Globally, cancer metastasis is a major cause of morbidity and mortality. In this study, we targeted CXCL12 rather than the chemokine receptor (CXCR4) because most of the drugs failed in clinical trials due to unmanageable toxicities. Until now, no FDA approved medication has been available against CXCL12. Therefore, we aimed to find new inhibitors for CXCL12 through virtual screening followed by molecular dynamics simulation. For virtual screening, active compounds against CXCL12 were taken as potent inhibitors and utilized in the generation of a pharmacophore model, followed by validation against different datasets. Ligand based virtual screening was performed on the ChEMBL and in-house databases, which resulted in successive elimination through the steps of pharmacophore-based and score-based screenings, and finally, sixteen compounds of various interactions with significant crucial amino acid residues were selected as virtual hits. Furthermore, the binding mode of these compounds were refined through molecular dynamic simulations. Moreover, the stability of protein complexes, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and radius of gyration were analyzed, which led to the identification of three potent inhibitors of CXCL12 that may be pursued in the drug discovery process against cancer metastasis.

scholarly journals A Search for Cyclin-Dependent Kinase 4/6 Inhibitors by Pharmacophore-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulations

2021 ◽  
Vol 22 (24) ◽  
pp. 13423
Author(s):  
Ni Made Pitri Susanti ◽  
Sophi Damayanti ◽  
Rahmana Emran Kartasasmita ◽  
Daryono Hadi Tjahjono
Keyword(s):  
Cell Cycle ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Cell Cycle Progression ◽  
Cell Cycle Control ◽  
Pharmacophore Model ◽  
Progression Free Survival ◽  
Cyclin Dependent Kinase ◽  
Dynamic Simulations ◽  
Reference Drug

The G1 phase of cell cycle progression is regulated by Cyclin-Dependent Kinase 4 (CDK4) as well as Cyclin-Dependent Kinase 6 (CDK6), and the acivities of these enzymes are regulated by the catalytic subunit, cyclin D. Cell cycle control through selective pharmacological inhibition of CDK4/6 has proven to be beneficial in the treatment of estrogen receptor-positive (ER-positive) breast cancer, particularly improving the progression-free survival of patients. Thus, targeting specific inhibition on CDK4/6 is bound to increase therapeutic efficiency. This study aimed to obtain CDK4/6 inhibitors through a pharmacophore-based virtual screening of the ZINC15 purchasable compound database using the in silico method. The pharmacophore model was designed based on the FDA-approved cdk4/6 inhibitor structures, and molecular docking was performed to further screen the hit compounds obtained. A total of eight compounds were selected based on docking results and interactions with CDK4 and CDK6, using palbociclib as the reference drug. According to the results, the compounds of ZINC585292724 and ZINC585291674 were the best compounds based on free binding energy, as well as hydrogen bond stability, and, therefore, exhibit potential as starting points in the development of CDK4/6 inhibitors.

scholarly journals Estimation of TiO2-FeO-Na2O slag viscosity through molecular dynamics simulations for an energy efficient ilmenite smelting process

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Youngjae Kim ◽  
Hyunsik Park
Keyword(s):  
Molecular Dynamic ◽  
Liquidus Temperature ◽  
Three Dimensional ◽  
Slag System ◽  
Smelting Process ◽  
Slag Viscosity ◽  
Molecular Dynamic Simulations ◽  
Dynamic Simulations ◽  
Increasing Demand ◽  
Dynamics Simulations

AbstractAlong with the increasing demand for the TiO2 pigment, the ilmenite smelting process has also become significant because it can utilize both rock- and sand-type ilmenite. However, due to the high liquidus temperature of the TiO2 slag system, the smelting process is highly energy consuming. In the present study, the viscosity of molten ilmenite slag was estimated using molecular dynamic simulations at a high temperature to achieve an appropriate and efficient slag design. To verify the validity of the simulation technique, experimental measurements were performed in parallel and their results were compared. The effects of FeO and Na2O addition on viscosity of TiO2 slag were also investigated. The addition of Na2O as a flux enhanced the ilmenite smelting process by not only lowering the liquidus temperature but also slowing the drastic viscosity increase. Statistical information obtained from the molecular dynamic simulations revealed a three-dimensional TiO6 octahedral network structure. The relationship between viscosity and structural change with varying FeO and Na2O concentrations was explored considering the coordination number of Ti and various bonding types.

Discovery, biological evaluation and molecular dynamic simulations of butyrylcholinesterase inhibitors through structure-based pharmacophore virtual screening

2021 ◽  
Vol 13 (9) ◽  
pp. 769-784
Author(s):  
Tao Lu ◽  
Yi Liu ◽  
Yan Liu ◽  
Hao Chen ◽  
Chengang Han ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Molecular Dynamic ◽  
Mixed Type ◽  
Neuroprotective Effect ◽  
Screening Method ◽  
Biological Evaluation ◽  
Molecular Dynamic Simulations ◽  
Dynamic Simulations ◽  
Computational Strategy ◽  
Mixed Type Inhibitor

Aim: Butyrylcholinesterase (BChE) is a crucial therapeutic target because it is associated with multiple pathological elements of Alzheimer’s disease (AD). An integrated computational strategy was employed to exploit effective BChE inhibitors. Methods & results: Ten compounds derived from the Enamine database by structure-based pharmacophore virtual screening were further evaluated for biological activity; out of the ten, only five had an IC50 of less than 100 μM. Among these five compounds, a new molecule, 970180, presented the most potency against BChE, with an IC50 of 4.24 ± 0.16 μM, and acted as a mixed-type inhibitor. Molecular dynamic simulations and absorption, distribution, metabolism and excretion prediction further confirmed its high potential as a good candidate of BChE inhibitor. Furthermore, cytotoxicity of molecule 970180 was not observed at concentrations up to 50 μM, and the molecule also showed a prominent neuroprotective effect compared with tacrine at 25 and 50 μM. Conclusion: This study provides an effective structure-based pharmacophore virtual screening method to discover BChE inhibitors and provide new choices for the development of BChE inhibitors, which may be beneficial for AD patients.

scholarly journals Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment

Molecules ◽  
2021 ◽  
Vol 26 (23) ◽  
pp. 7201
Author(s):  
Christian Permann ◽  
Thomas Seidel ◽  
Thierry Langer
Keyword(s):  
Virtual Screening ◽  
False Negative ◽  
Three Dimensional ◽  
False Negative Rate ◽  
Alignment Algorithm ◽  
Screening Experiments ◽  
Point Search ◽  
Optimal Alignments ◽  
Pharmacophore Models ◽  
Feature Pattern

Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when the actual goal is to match as many features as possible within the positional tolerances of the pharmacophore features. As a consequence, the obtained alignment results are often suboptimal in terms of the number of geometrically matched feature pairs, which increases the false-negative rate, thus negatively affecting the outcome of virtual screening experiments. We addressed this issue by introducing a new alignment algorithm, Greedy 3-Point Search (G3PS), which aims at finding optimal alignments by using a matching-feature-pair maximizing search strategy while at the same time being faster than competing methods.

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