scholarly journals Molecular Basis of Artemisinin Derivatives Inhibition of Myeloid Differentiation Protein 2 by Combined in Silico and Experimental Study

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5698
Author(s):  
Sennan Qiao ◽  
Hansi Zhang ◽  
Fei Sun ◽  
Zhenyan Jiang

Artemisinin (also known as Qinghaosu) , an active component of the Qinghao extract, is widely used as antimalarial drug. Previous studies reveal that artemisinin and its derivatives also have effective anti-inflammatory and immunomodulatory properties, but the direct molecular target remains unknown. Recently, several reports mentioned that myeloid differentiation factor 2 (MD-2, also known as lymphocyte antigen 96) may be the endogenous target of artemisinin in the inhibition of lipopolysaccharide signaling. However, the exact interaction between artemisinin and MD-2 is still not fully understood. Here, experimental and computational methods were employed to elucidate the relationship between the artemisinin and its inhibition mechanism. Experimental results showed that artemether exhibit higher anti-inflammatory activity performance than artemisinin and artesunate. Molecular docking results showed that artemisinin, artesunate, and artemether had similar binding poses, and all complexes remained stable throughout the whole molecular dynamics simulations, whereas the binding of artemisinin and its derivatives to MD-2 decreased the TLR4(Toll-Like Receptor 4)/MD-2 stability. Moreover, artemether exhibited lower binding energy as compared to artemisinin and artesunate, which is in good agreement with the experimental results. Leu61, Leu78, and Ile117 are indeed key residues that contribute to the binding free energy. Binding free energy analysis further confirmed that hydrophobic interactions were critical to maintain the binding mode of artemisinin and its derivatives with MD-2.

Author(s):  
Leili Zhang ◽  
Ruhong Zhou

Starting from December 2019, coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures and supporting apparatuses. Remdesivir was reported by World Health Organization (WHO) as the most promising drug currently available for the treatment of COVID-19. Here, we use molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). In the absence of a crystal structure of the SARS-CoV-2 RdRp, we first construct the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identify of 95.8%). We then build the putative binding mode by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp. The putative binding structure is further optimized with molecular dynamics simulations and demonstrated to be stable, indicating a reasonable binding mode for remdesivir. The relative binding free energy of remdesivir is calculated to be -8.28 ± 0.65 kcal/mol, much stronger than the natural substrate ATP (-4.14 ± 0.89 kcal/mol) which is needed for the polymerization. The ~800-fold improvement in the Kd from remdesivir over ATP indicates an effective replacement of APT in blocking of the RdRp binding pocket. Key residues D618, S549 and R555 are found to be the contributors to the binding affinity of remdesivir. These findings demonstrate that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA reproduction, with key residues also identified for future lead optimization and/or drug resistance studies.


2019 ◽  
Author(s):  
David Wright ◽  
Fouad Husseini ◽  
Shunzhou Wan ◽  
Christophe Meyer ◽  
Herman Van Vlijmen ◽  
...  

<div>Here, we evaluate the performance of our range of ensemble simulation based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) for use in fragment based drug design scenarios. ESMACS is designed to generate reproducible binding affinity predictions from the widely used molecular mechanics Poisson-Boltzmann surface area (MMPBSA) approach. We study ligands designed to target two binding pockets in the lactate dehydogenase A target protein, which vary in size, charge and binding mode. When comparing to experimental results, we obtain excellent statistical rankings across this highly diverse set of ligands. In addition, we investigate three approaches to account for entropic contributions not captured by standard MMPBSA calculations: (1) normal mode analysis, (2) weighted solvent accessible surface area (WSAS) and (3) variational entropy. </div>


2011 ◽  
Vol 17 (11) ◽  
pp. 2805-2816 ◽  
Author(s):  
Mathew Varghese Koonammackal ◽  
Unnikrishnan Viswambharan Nair Nellipparambil ◽  
Chellappanpillai Sudarsanakumar

Oncology ◽  
2017 ◽  
pp. 829-847
Author(s):  
Shubhandra Tripathi ◽  
Akhil Kumar ◽  
Amandeep Kaur Kahlon ◽  
Ashok Sharma

Molecular docking was earlier considered to predict the binding affinity of the receptor and ligand molecules. With the progress in computational power and developing approaches, new horizons are now opening for accurate prediction of molecular binding affinity. In the current book chapter, recent strategies for Computer-Aided Drug Designing (CADD) including virtual screening and molecular docking, encompassing molecular dynamics simulations, and binding free energy calculation methods are discussed. Brief overview of different binding free energy methods MMPBSA, MMGBSA, LIE and TI have also been given along with the recent Relaxed Complex Scheme protocol.


2012 ◽  
Vol 11 (04) ◽  
pp. 907-924 ◽  
Author(s):  
DAWEI HUANG ◽  
XIAOHUI LI ◽  
ZHILONG XIU

Inhibitors of histone deacetylases (HDACs) have become an attractive class of anticancer agent. To understand the interaction between HDAC8 and inhibitors, including "pan-" inhibitors that inhibit many HDACs isoforms and selective inhibitors with no linker domain, docking and molecular dynamics simulation were conducted. Docking results showed the presence of π-π interactions between "linkerless" inhibitors and the aromatic amino acid residues of HDAC8 in the active site. Binding between HDAC8 and inhibitors was also stabilized by hydrogen bond and hydrophobic interaction. In molecular dynamics simulations, the zinc ion was shown to coordinate one more atom of HDAC8-"linkerless" inhibitor complexes than HDAC8-"pan-" inhibitor complexes. Persistent hydrogen bonds also existed between Tyr306 of HDAC8 and some inhibitors. When inhibitors with large cap groups bound to the active pocket of HDAC8, Phe152 and Met274 shifted from their initial positions and the entrance of the active pocket became more open, resulting in the formation of sub-pocket. Hydrophobic interactions contributed most favorably to the binding free energy between HDAC8 and inhibitors. Lys33, Asp178, Asp267, Tyr306 and Leu308 of HDAC8 were favorable for binding with all inhibitors.


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