Review of Electrostatic Force Calculation Methods and Their Acceleration in Molecular Dynamics Packages Using Graphics Processors

Phytochemical Analysis, Computational Study, and in vitro Assay of Etlingera elatior Inflorescence Extract Towards Inducible Nitric Oxide Synthase

Background

Overproduction of nitric oxide (NO), catalyzed by inducible nitric oxide synthase (iNOS), in the gastric mucosa, contributes to the inflammatory process caused by oxidative stress. Current medications for gastric ulcers, such as proton pump inhibitors and histamine-2 receptor antagonists, have been reported to generate adverse reactions.

Purpose

To obtain the phytochemical profile of Etlingera elatior inflorescence extract, computational studies, and in vitro assay of the extract towards iNOS.

Methods

Fresh E. elatior inflorescence petals collected from West Java, Indonesia, were extracted using ethanol, and their nutritional composition, anthocyanin content, and levels of vitamin C, C3G, and quercetin in the extract were determined. Drug-likeness and ADMET properties were predicted, and the binding affinity and stability of the phytoconstituents towards iNOS were studied using molecular docking and molecular dynamic simulation, and in vitro assay of the extract towards human iNOS.

Results

The extract contains protein 21.81%, fat 0.99%, carbohydrate 38.27%, water 24.56%, and ash 14.37%. The total anthocyanin and vitamin C levels were 47.535 mg/100 g and 985.250 mg/100 g, respectively. The levels of C3G and quercetin were 0.0007% w/w, 0.004% w/w, and 0.0005% w/w, respectively. Drug-likeness and ADMET properties of the constituents showed that most followed Lipinski Rules of Five (Ro5), with few violations. All phytoconstituents occupied the catalytic site by binding to Glu377, and Trp372, similar to S-ethylisothiourea (SEITU) and quinazoline, the iNOS inhibitors. Among these, the flavylium cation of cyanidin, demethoxycurcumin, C3G, cyanidin, and quercetin showed the best binding affinities. Root mean square deviation (RMSD), root mean square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg) graphs confirmed the stability of the complexes. E. elatior inflorescence extract inhibited human iNOS with an IC50 value of 24.718 µg/mL.

Conclusion

Etlingera elatior inflorescence may inhibit iNOS activity due to its anthocyanin and flavonoid content. The flavylium cation of cyanidin, demethoxycurcumin, C3G, cyanidin, and quercetin play leading roles in the interaction with iNOS.

Elucidating the binding specificity of interactive compounds targeting ATP-binding cassette subfamily G member 2 (ABCG2)

The ATP-binding cassette transporter superfamily plays a pivotal role in cellular detoxification and drug efflux. ATP-binding cassette subfamily G member 2 (ABCG2) referred to as the Breast cancer resistance protein has emerged as a key member involved in multidrug resistance displayed by cancer cells. Understanding the molecular basis of substrate and inhibitor recognition, and binding within the transmembrane domain of ABCG2 is crucial for the development of effective therapeutic strategies. Herein, utilizing state-of-the-art molecular docking algorithms and molecular dynamic (MD) simulations, molecular binding of substrates and inhibitors with ABCG2 are defined, distinctly. We performed extensive virtual screening of Drugbank to identify the potential candidates, and MD simulations of docked complexes were carried out in POPC lipid bilayer. Further, the binding affinities of compounds were estimated by free binding energy employing MM-GBSA. To gain deeper insight into the binding affinities and molecular characteristics contributing to inhibitory potential of certain substrates, we included some well-known inhibitors, like Imatinib, Tariquidar, and Ko 143, in our analysis. Docking results show three compounds, Docetaxel > Tariquidar > Tezacaftor having the highest binding affinities (≤ 12.00 kcal/mol) for ABCG2. Remarkably, MM-GBSA results suggest the most stable binding of Tariquidar with ABCG2 as compared to the other inhibitors. Furthermore, our results suggested that Docetaxel, Ozanimod, Pitavastatin, and Tezacaftor have the strongest affinity for the drug-binding site(s) of ABCG2. These results provide valuable insights into the key residues that may govern substrate/inhibitor recognition, shedding light on the molecular determinants influencing substrate specificity, transport kinetics, and ABCG2-mediated drug efflux.

Evaluating experimental, knowledge-based and computational cocrystal screening methods to advance drug-drug cocrystal fixed-dose combination development

Fixed-dose combinations (FDCs) offer significant advantages to patients and the pharmaceutical industry alike through improved dissolution profiles, synergistic effects and extended patent lifetimes. Identifying whether two active pharmaceutical ingredients have the potential to form a drug-drug cocrystal (DDC) or interact is an essential step in determining the most suitable type of FDC to formulate. The lack of coherent strategies to determine if two active pharmaceutical ingredients that can be co-administered can form a cocrystal, has significantly impacted DDC commercialisation. This review aims to accelerate the development of FDCs and DDCs by evaluating existing experimental, knowledge-based and computational cocrystal screening methods; the background of their development, their application in screening for cocrystals and DDCs, and their limitations are discussed. The evaluation provided in this review will act as a guide for selecting suitable screening methods to accelerate FDC development.

Embracing exascale computing in nucleic acid simulations

This mini-review reports the recent advances in biomolecular simulations, particularly for nucleic acids, and provides the potential effects of the emerging exascale computing on nucleic acid simulations, emphasizing the need for advanced computational strategies to fully exploit this technological frontier. Specifically, we introduce recent breakthroughs in computer architectures for large-scale biomolecular simulations and review the simulation protocols for nucleic acids regarding force fields, enhanced sampling methods, coarse-grained models, and interactions with ligands. We also explore the integration of machine learning methods into simulations, which promises to significantly enhance the predictive modeling of biomolecules and the analysis of complex data generated by the exascale simulations. Finally, we discuss the challenges and perspectives for biomolecular simulations as we enter the dawning exascale computing era.

Molecular dynamics study of stigmasterol and beta-sitosterol of Morinda citrifolia L. towards α-amylase and α-glucosidase

Previous in vivo studies of Morinda citrifolia (Rubiaceae) reported that the extract inhibited α-amylase and reduced blood glucose levels in streptozotocin-induced diabetes mice. Moreover, molecular docking studies confirmed that ursolic acid and sterol compounds contained in the fruit interacted with important residues in the binding site of α-amylase and α-glucosidase. Our work aimed to study the complex stability of stigmasterol (which has been isolated from the M. citrifolia fruit for the first time) and beta-sitosterol towards α-amylase and α-glucosidase by employing molecular dynamics simulation on GROMACS 2016.3 embedded with the AMBER99SB-ILDN force field. The simulation was carried out for 100 ns at 310 oK. Based on the RMSD and RMSF graphs, the complexes of stigmasterol/α-amylase and stigmasterol/α-glucosidase are more stable compared to acarbose, the known inhibitor of both enzymes. Moreover, beta-sitosterol indicates a better stability complex with α-glucosidase compared to that of acarbose. Interestingly, the affinity of stigmasterol and beta-sitosterol to both enzymes, in terms of the total binding energy, is stronger than that of acarbose. Taken together, stigmasterol and beta-sitosterol in M. citrifolia fruit may have the potency to be developed as α-amylase and α-glucosidase inhibitors.Communicated by Ramaswamy H. Sarma.