Computational assessment of herbal medicine-derived compounds as potential inhibitors of SARS-CoV-2 main protease.

Since the main protease (Mpro) is crucial for the COVID-19 virus replication and transcription, searching for Mpro inhibitors is one possible treatment option. In our study, 258 small molecules were collected from lung-related herbal medicines, and their structures were optimized with the B3LYP-D3/6-31G* method. After the molecular docking with Mpro, we selected the top 20 compounds for the further geometry optimization with the larger basis sets. After the further molecular docking, the top eight compounds were screened out. Then we performed molecular dynamics simulations and binding free energy calculations to determine stability of the complexes. Our results show that mulberrofuran G, Xambioona, and kuwanon D can bind Mpro well. In quantum chemistry studies, such as ESP and CDFT analyses, the compounds properties are predicted. Additionally, the drug-likeness analyses and ADME studies on these three candidate compounds verified that all of them conform to Libinski's rule and may be drug-like compounds.

Exploration of plant-derived natural polyphenols toward COVID-19 main protease inhibitors: DFT, molecular docking approach, and molecular dynamics simulations.

Recent outbreaks of coronavirus have brought serious challenges to public health around the world, and it is essential to find effective treatments. In this study, the 3C-like proteinase (3CLpro) of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has been considered as an important drug target because of its role in viral replication. We initially optimized 251 compounds at the PM7 level of theory for docking with 3CLpro, and then we selected the top 12 compounds for further optimization with the B3LYP-D3/6-311G** method and obtained the top four compounds by further molecular docking. Quantum chemistry calculations were performed to predict molecular properties, such as the electrostatic potential and some CDFT descriptors. We also performed molecular dynamics simulations and free energy calculations to determine the relative stability of the selected four potential compounds. We have identified key residues controlling the 3CLpro/ligand binding from per-residue based decomposition of the binding free energy. Convincingly, the comprehensive results support the conclusion that the compounds have the potential to become a candidate for anti-coronavirus treatment.

Data-Driven Parcellation Approaches Based on Functional Connectivity of Visual Cortices in Primary Open-Angle Glaucoma.

Purpose: Functional changes have been observed between diseased and healthy subjects, and functional brain atlases derived from healthy populations may fail to reflect functional characteristic of the diseased brain. Therefore the aim of this study was to generate a visual atlas based on functional connectivity from primary open-angle glaucoma (POAG) patients and to prove the applicability of the visual atlas in functional connectivity and network analysis. Methods: Functional magnetic resonance images were acquired from 36 POAG patients and 20 healthy controls. Two data-driven approaches, K-means and Ward clustering algorithms, were adopted for visual cortices parcellation. Dice coefficient and adjusted Rand index were used to assess reproducibility of the two approaches. Homogeneity index, silhouette coefficient, and network properties were adopted to assess functional validity for the data-driven approaches and frequently used brain atlas. Graph theoretical analysis was adopted to investigate altered network patterns in POAG patients based on data-driven visual atlas. Results: Parcellation results demonstrated asymmetric patterns between left and right hemispheres in POAG patients compared with healthy controls. In terms of evaluating metrics, K-means performed better than Ward clustering in reproducibility. Data-driven parcellations outperformed frequently used brain atlases in terms of functional homogeneity and network properties. Graph theoretical analysis revealed that atlases generated by data-driven approaches were more conducive in detecting network alterations between POAG patients and healthy controls. Conclusions: Our findings suggested that POAG patients experienced functional alterations in the visual cortices. Results also highlighted the necessity of data-driven atlases for functional connectivity and functional network analysis of POAG brain.