Targeting Natural Plant Metabolites for Hunting SARS-CoV-2 Omicron BA.1 Variant Inhibitors: Extraction, Molecular Docking, Molecular Dynamics, and Physicochemical Properties Study.

(1) Background: SARS-CoV-2 Omicron BA.1 is the most common variation found in most countries and is responsible for 99% of cases in the United States. To overcome this challenge, there is an urgent need to discover effective inhibitors to prevent the emerging BA.1 variant. Natural products, particularly flavonoids, have had widespread success in reducing COVID-19 prevalence. (2) Methods: In the ongoing study, fifteen compounds were annotated from Echium angustifolium and peach (Prunus persica), which were computationally analyzed using various in silico techniques. Molecular docking calculations were performed for the identified phytochemicals to investigate their efficacy. Molecular dynamics (MD) simulations over 200 ns followed by molecular mechanics Poisson-Boltzmann surface area calculations (MM/PBSA) were performed to estimate the binding energy. Bioactivity was also calculated for the best components in terms of drug likeness and drug score. (3) Results: The data obtained from the molecular docking study demonstrated that five compounds exhibited remarkable potency, with docking scores greater than -9.0 kcal/mol. Among them, compounds 1, 2 and 4 showed higher stability within the active site of Omicron BA.1, with ΔGbinding values of -49.02, -48.07, and -67.47 KJ/mol, respectively. These findings imply that the discovered phytoconstituents are promising in the search for anti-Omicron BA.1 drugs and should be investigated in future in vitro and in vivo research.

Conducting the RBD of SARS-CoV-2 Omicron Variant with Phytoconstituents from Euphorbia dendroides to Repudiate the Binding of Spike Glycoprotein Using Computational Molecular Search and Simulation Approach.

(1) Background: Natural constituents are still a preferred route for counteracting the outbreak of COVID-19. Essentially, flavonoids have been found to be among the most promising molecules identified as coronavirus inhibitors. Recently, a new SARS-CoV-2 B.1.1.529 variant has spread in many countries, which has raised awareness of the role of natural constituents in attempts to contribute to therapeutic protocols. (2) Methods: Using various chromatographic techniques, triterpenes (1-7), phenolics (8-11), and flavonoids (12-17) were isolated from Euphorbia dendroides and computationally screened against the receptor-binding domain (RBD) of the SARS-CoV-2 Omicron variant. As a first step, molecular docking calculations were performed for all investigated compounds. Promising compounds were subjected to molecular dynamics simulations (MD) for 200 ns, in addition to molecular mechanics Poisson-Boltzmann surface area calculations (MM/PBSA) to determine binding energy. (3) Results: MM/PBSA binding energy calculations showed that compound 14 (quercetin-3-O-ß-D-glucuronopyranoside) and compound 15 (quercetin-3-O-glucuronide 6″-O-methyl ester) exhibited strong inhibition of Omicron, with ΔGbinding of -41.0 and -32.4 kcal/mol, respectively. Finally, drug likeness evaluations based on Lipinski's rule of five also showed that the discovered compounds exhibited good oral bioavailability. (4) Conclusions: It is foreseeable that these results provide a novel intellectual contribution in light of the decreasing prevalence of SARS-CoV-2 B.1.1.529 and could be a good addition to the therapeutic protocol.

Elucidating novel antibacterial compounds from the NPASS database against the FimH lectin domain for the treatment of urinary tract infections: an in-silico study.

The increase in multidrug-resistant pathogens in urinary tract infections (UTIs) among communities and hospitals threatens our ability to treat these common pathogens. Uropathogenic Escherichia coli (UPEC) strains are the most frequent uropathies linked to the development of UTIs. This work aims to introduce bioactive natural products via virtual screening of small molecules from a public database to prevent biofilm formation by inhibiting FimH, a type 1 fimbriae that plays a crucial role in UPEC pathogenicity. A total of 30926 small molecules from the NPASS database were subjected to screening via molecular docking. Followed by performing in silico ADME studies, seven molecules showed promising docking results ranging from -6.8 to -8.7 kcal/mol. As a result of the docking score findings, 100 ns Molecular dynamics (MD) simulations were performed. Based on MM-PBSA analysis, NPC313334 ligand showed high binding affinity -42 and stability with the binding pocket of FimH protein during molecular dynamic simulations. DFT calculations were also performed on the ligands to calculate the HOMO-LUMO energies of the compounds in order to an idea about their structure and reactivity. This research suggests that NPC313334 may be a possible antibacterial drug candidate that targets FimH to reduce the number of UPEC-related urinary tract infections.Communicated by Ramaswamy H. Sarma.

Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database.

Antimicrobial peptides (AMPs) are short peptides with a broad spectrum of antimicrobial activity. They play a key role in the host innate immunity of many organisms. The growing threat of microorganisms resistant to antimicrobial agents and the lack of new commercially available antibiotics have made in silico discovery of AMPs increasingly important. Machine learning (ML) has improved the speed and efficiency of AMP discovery while reducing the cost of experimental approaches. Despite various ML platforms developed, there is still a lack of integrative use of ML platforms for AMP discovery from publicly available protein databases. Therefore, our study aims to screen potential AMPs with antibiofilm properties from databases using ML platforms, followed by protein-peptide molecular docking analysis and molecular dynamics (MD) simulations. A total of 5850 peptides classified as non-AMP were screened from UniProtKB and analyzed using various online ML platforms (e.g., CAMPr3, DBAASP, dPABBs, Hemopred, and ToxinPred). Eight potential AMP peptides against Klebsiella pneumoniae with antibiofilm, non-toxic and non-hemolytic properties were then docked to MrkH, a transcriptional regulator of type 3 fimbriae involved in biofilm formation. Five of eight peptides bound more strongly than the native MrkH ligand when analyzed using HADDOCK and HPEPDOCK. Following the docking studies, our MD simulated that a Neuropeptide B (Peptide 3) bind strongly to the MrkH active sites. The discovery of putative AMPs that exceed the binding energies of the native ligand underscores the utility of the combined ML and molecular simulation strategies for discovering novel AMPs with antibiofilm properties.

Unraveling effective extracellular signal-regulated kinase 2 inhibitors: a de novo drug design strategy enhanced by in-depth in silico analyses.

Extracellular signal-regulated kinase 2 (ERK-2) is a serine/threonine protein kinase in eukaryotic cells and belongs to the mitogen-activated protein kinase (MAPK) family. An activated form of ERK-2 phosphorylates substrates in the nucleus or cytoplasm and causes specific proteins to be expressed or activated, regulating cell proliferation, differentiation and other functions. Caffeic acid (3,4 - dihydroxy cinnamic acid), as previously reported, directly interacts with ERK-2 and reduces its effects in vitro. It is also reported to have a variety of pharmacological effects, including anti-inflammatory, immunomodulatory, antioxidant and anticancer activities. In the current study, a deep-learning protocol was employed to develop effective 100 compounds by modifying the chemical structure of DHC to improve its inhibitory performance against ERK-2. Calculations of physicochemical properties for those compounds revealed that 20 compounds had drug scores better than DHC (≥ 80%). Following that, molecular docking calculations were performed on the selected compounds and DHC. The obtained data revealed that five compounds had docking scores better than DHC (≥ -5.9 kcal/mol). Moreover, data from molecular mechanics and the Poisson - Boltzmann surface area (MM/PBSA) binding energy over 200 ns MD simulation confirmed that Cmd-1 and Cmd-4 exhibited higher stability with ΔGbinding of -40.8 and -49.1 kcal/mol, respectively, which is better than DHC (-35.1 kcal/mol). Finally, various energetic and structural studies showed the high stability of the two generated compounds within the active site of ERK-2. This study highlights the potential use of Cmd-1 and Cmd-4 as promising anti-ERK-2 drug candidates.Communicated by Ramaswamy H. Sarma.

Exploring the therapeutic potential of galidesivir analogs against Zaire ebolavirus protein 24 (V24): database screening, molecular docking, drug-relevant property evaluation and molecular dynamics simulations.

The recent outbreak of the Ebola virus (EBOV) has marked it as one of the most severe health threats globally. Among various anti-EBOV inhibitors studied, galidesivir (BCX4430) has shown remarkable efficacy. This study aims to identify novel potential anti-EBOV drugs among galidesivir analogs, focusing on the Zaire ebolavirus (Z-EBOV), which exhibits a mortality rate of 90%. We subjected 200 candidate compounds to molecular docking calculations, followed by an evaluation of the bioactivity of the top 25 compounds using the OSIRIS Property Explorer. Initial 50 ns molecular dynamics (MD) simulations were then performed. According to our findings, only six compounds exhibited positive drug scores. We further performed molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations of binding energy over 50 ns, selecting the two top-performing compounds for extended 150 ns MD simulations. CID 117698807 and CID 117712809 showed higher binding stability compared to galidesivir, with ΔGbinding values of -36.7 and -53.4 kcal/mol, respectively. Both compounds demonstrated high stability within the Z-EBOV-V24 active site over the 150 ns MD simulations. Hence, our study proposes CID 117698807 and CID 117712809 as potential anti-Z-EBOV-V24 drug candidates, warranting further investigation.Communicated by Ramaswamy H. Sarma.

In silico prediction of potential inhibitors for SARS-CoV-2 Omicron variant using molecular docking and dynamics simulation-based drug repurposing.

BACKGROUND: In November 2021, variant B.1.1.529 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified by the World Health Organization (WHO) and designated Omicron. Omicron is characterized by a high number of mutations, thirty-two in total, making it more transmissible than the original virus. More than half of those mutations were found in the receptor-binding domain (RBD) that directly interacts with human angiotensin-converting enzyme 2 (ACE2). This study aimed to discover potent drugs against Omicron, which were previously repurposed for coronavirus disease 2019 (COVID-19). All repurposed anti-COVID-19 drugs were compiled from previous studies and tested against the RBD of SARS-CoV-2 Omicron. METHODS: As a preliminary step, a molecular docking study was performed to investigate the potency of seventy-one compounds from four classes of inhibitors. The molecular characteristics of the best-performing five compounds were predicted by estimating the drug-likeness and drug score. Molecular dynamics simulations (MD) over 100 ns were performed to inspect the relative stability of the best compound within the Omicron receptor-binding site. RESULTS: The current findings point out the crucial roles of Q493R, G496S, Q498R, N501Y, and Y505H in the RBD region of SARS-CoV-2 Omicron. Raltegravir, hesperidin, pyronaridine, and difloxacin achieved the highest drug scores compared with the other compounds in the four classes, with values of 81%, 57%, 18%, and 71%, respectively. The calculated results showed that raltegravir and hesperidin had high binding affinities and stabilities to Omicron with ΔGbinding of - 75.7304 ± 0.98324 and - 42.693536 ± 0.979056 kJ/mol, respectively. Further clinical studies should be performed for the two best compounds from this study.