scholarly journals Exploring the therapeutic nature of limonoids and triterpenoids against SARS-CoV-2 by targeting nsp13, nsp14, and nsp15 through molecular docking and dynamic simulations

2021 ◽  
Author(s):  
Seshu Vardhan ◽  
Suban K. Sahoo
Keyword(s):  
Molecular Docking ◽  
Dynamic Simulations

scholarly journals The Significance of Halogen Bonding in Ligand–Receptor Interactions: The Lesson Learned from Molecular Dynamic Simulations of the D4 Receptor

Molecules ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 91 ◽  
Author(s):  
Rafał Kurczab ◽  
Katarzyna Kucwaj-Brysz ◽  
Paweł Śliwa
Keyword(s):  
Molecular Docking ◽  
Hot Spots ◽  
Binding Free Energy ◽  
Halogen Bonding ◽  
Free Energy Calculations ◽  
Dynamic Simulations ◽  
Receptor Complexes ◽  
Molecular Core ◽  
D4 Receptor ◽  
Dynamics Simulations

Recently, a computational approach combining a structure–activity relationship library containing pairs of halogenated ligands and their corresponding unsubstituted ligands (called XSAR) with QM-based molecular docking and binding free energy calculations was developed and used to search for amino acids frequently targeted by halogen bonding, also known as XB hot spots. However, the analysis of ligand–receptor complexes with halogen bonds obtained by molecular docking provides a limited ability to study the role and significance of halogen bonding in biological systems. Thus, a set of molecular dynamics simulations for the dopamine D4 receptor, recently crystallized with the antipsychotic drug nemonapride (5WIU), and the five XSAR sets were performed to verify the identified hot spots for halogen bonding, in other words, primary (V5x40), and secondary (S5x43, S5x461 and H6x55). The simulations confirmed the key role of halogen bonding with V5x40 and H6x55 and supported S5x43 and S5x461. The results showed that steric restrictions and the topology of the molecular core have a crucial impact on the stabilization of the ligand–receptor complex by halogen bonding.

scholarly journals Deciphering PD1 activation mechanism from molecular docking and molecular dynamic simulations

2021 ◽  
Author(s):  
Luis F. Ponce ◽  
Daniel P. Ramirez-Echemendia ◽  
Kalet Leon ◽  
Pedro A. Valiente
Keyword(s):  
T Cells ◽  
Molecular Docking ◽  
Cellular Membrane ◽  
Umbrella Sampling ◽  
Activation Mechanism ◽  
Binding Modes ◽  
Dynamic Simulations ◽  
Linear Lattice ◽  
High Molecular Weight Complex ◽  
Inhibitory Mechanisms

AbstractThe activation of T cells is normally accompanied by inhibitory mechanisms within which the PD1 receptor stands out. Upon binding the ligands PDL1 and PDL2, PD1 drives T cells to an unresponsive state called exhaustion characterized by a markedly decreased capacity to exert effector functions. For this reason, PD1 has become one of the most important targets in cancer immunotherapy. Despite the numerous studies about PD1 signaling modulation, how the PD1 signaling is activated upon the ligands’ binding remains an open question. Several experimental facts suggest that the activation of the PD1-PLD1 pathway depends on the interaction with an unknown partner at the cellular membrane. In this work, we investigate the possibility that the target of PD1-PDL1 is the same PD1-PDL1 complex. We combined molecular docking to explore different binding modes with molecular dynamics and umbrella sampling simulations to assess the complexes’ stability. We found a high molecular weight complex that explains the activation of PD1 upon PDL1 binding. This complex has an affinity comparable to the PD1-PDL1 interaction and resembles the form of a linear lattice.

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 Computational approach to design of aptamers to the receptor binding domain of SARS-CoV-2

2021 ◽  
pp. 66-67
Author(s):  
P.V. Artyushenko ◽  
◽  
V.A. Mironov ◽  
D.I. Morozov ◽  
I.A. Shchugoreva ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Dynamic ◽  
Quantum Chemical Calculations ◽  
In Silico ◽  
Quantum Chemical ◽  
Computational Approach ◽  
Receptor Binding Domain ◽  
Dynamic Simulations ◽  
X Ray ◽  
X Ray Scattering

The aim of the research. In this work, in silico selection of DNA-aptamers to the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein was performed using molecular modeling methods. Material and methods. A new computational approach to aptamer in silico selection is based on a cycle of simulations, including the stages of molecular modeling, molecular docking, molecular dynamic simulations, and quantum chemical calculations. To verify the obtained calculated results flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods were applied. Results. An initial library consisted of 256 16-mer oligonucleotides was modeled. Based on molecular docking results, the only one aptamer (Apt16) was selected from the library as a starting aptamer to the RBD protein. For Apt16/RBD complex, molecular dynamic and quantum chemical calculations revealed the pairs of nucleotides and amino acids whose contribution to the binding between aptamer and RBD is the largest. Taking into account these data, Apt16 was subjected to the structure modifi cations in order to increase the binding with the RBD. Th us, a new aptamer Apt25 was designed. Th e procedure of 1) aptamer structure modeling/modifi cation, 2) molecular docking, 3) molecular dynamic simulations, 4) quantum chemical calculations was performed several times. As a result, four aptamers (Apt16, Apt25, Apt27, Apt31) to the RBD were designed in silico without any preliminary experimental data. Binding of the each modeled aptamer to the RBD was studied in terms of interactions between residues in protein and nucleotides in the aptamers. Based on the simulation results, the strongest binding with the RBD was predicted for two Apt27 and Apt31aptamers. The calculated results are in good agreement with experimental data obtained by flow cytometry, fluorescence polarization, and small-angle X-ray scattering methods. Conclusion. Th e proposed computational approach to selection and refi nement of aptamers is universal and can be used for wide range of molecular ligands and targets

scholarly journals Molecular docking and dynamic simulations of benzimidazoles with beta-tubulins

2021 ◽  
Vol 17 (3) ◽  
pp. 404
Author(s):  
Chennu Maruthi Malya Prasada Rao ◽  
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Anthelmintic Activity ◽  
Dynamic Simulations

It is of interest to document the molecular docking and dynamic simulations of benzimidazoles with beta-tubulins in the context of anthelmintic activity. We document the compound BI-02 (2-(3,4-dimethyl phenyl)-1H-1,3-benzimidazole (BI-02) with optimal bindig features compared to the standard molecule albendazole (7.0 Kcal/mol) with binding energy -8.50 Kcal/mol and PIC50 value 583.62 nM.

scholarly journals Identification of the Potential Hits for Hindering Interaction of SARS-CoV-2 Main Protease (M pro ) from the Pool of Antiviral Phytochemicals utilizing Molecular Docking and Molecular Dynamics (MD) Simulations

2021 ◽  
Author(s):  
Chirag N. Patel ◽  
Dharmesh G. Jaiswal ◽  
Siddhi P. Jani ◽  
Naman Mangukia ◽  
Robin M. Parmar ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Docking ◽  
Virus Assembly ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Free Energy Calculations ◽  
Host Protein ◽  
Dynamic Simulations ◽  
Main Protease

Abstract The novel SARS-CoV-2 is an etiological factor that triggers Coronavirus disease in 2019 (COVID-19) and tends to be an imminent occurrence of a pandemic. Out of all recognized solved complexes linked to SARS-CoV, Main protease (Mpro) is considered a desirable antiviral phytochemical that play a crucial role in virus assembly and possibly non-interactive capacity to adhere to any viral host protein. In this research, SARS-CoV-2 MPro was chosen as a focus for the detection of possible inhibitors using a variety of different analytical methods such as molecular docking, ADMET analysis, dynamic simulations and binding free energy measurements. Virtual screening of known natural compounds recognized Withanoside V, Withanoside VI, Racemoside B, Racemoside A and Shatavarin IX as future inhibitors of SARS-CoV-2 MPro with stronger energy binding. Also, simulations of molecular dynamics for a 100 ns time scale showed that much of the main SARS-CoV-2 MPro interactions had been maintained in the simulation routes. Binding free energy calculations using the MM/PBSA method ranked the top five possible natural compounds that can act as effective SARS-CoV-2 MPro inhibitors.

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