Computational molecular interaction between SARS-CoV-2 main protease and theaflavin digallate using free energy perturbation and molecular dynamics

Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from -8.0 to -9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07-0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25-0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity.

Reinvestigation of diphenylmethylpiperazine analogues of pyrazine as new class of Plasmodial cysteine protease inhibitors for the treatment of malaria

Malaria eradication is still a global challenge due to the lack of a broadly effective vaccine and the emergence of drug resistance to most of the currently available drugs as part of the mainline artemisinin-based combination therapy. A variety of experimental approaches are quite successful in identifying and synthesizing new promising pharmacophore hybrids with distinct mechanisms of action. Based on our recent findings, the current study demonstrates the reinvestigation of a series of diphenylmethylpiperazine and pyrazine-derived molecular hybrids. Pyrazine-derived molecular hybrids were screened to investigate the antiplasmodial activity on drug-susceptible Pf3D7 and drug-resistant PfW2 strains. The selected compounds were shown to be potent dual inhibitors of cysteine protease PfFP2 and PfFP3. Time-course parasitic development study demonstrated that compounds were able to arrest the growth of the parasite at the early trophozoite stage. The compounds did not show hemolysis of red blood cells and showed selectivity to the parasite compared with the mammalian Vero and A5489 cell lines. The study underlined HR5 and HR15 as a new class of Plasmodial falcipain inhibitors with an IC50 of 6.2 μM and 5.9 μM for PfFP2 and 6.8 μM and 6.4 μM for PfFP3, respectively. Both compounds have antimalarial efficacy with IC50 values of 3.05 μM and 2.80 μM for the Pf3D7 strain, and 4.35 μM and 3.39 μM for the PfW2 strain, respectively. Further structural optimization may turn them into potential Plasmodial falcipain inhibitors for malaria therapeutics.

Construction of recombinant fluorescent LSDV for high-throughput screening of antiviral drugs

Lumpy skin disease virus (LSDV) infection is a major socio-economic issue that seriously threatens the global cattle-farming industry. Here, a recombinant virus LSDV-ΔTK/EGFP, expressing enhanced green fluorescent protein (EGFP), was constructed with a homologous recombination system and applied to the high-throughput screening of antiviral drugs. LSDV-ΔTK/EGFP replicates in various kidney cell lines, consistent with wild-type LSDV. The cytopathic effect, viral particle morphology, and growth performance of LSDV-ΔTK/EGFP are consistent with those of wild-type LSDV. High-throughput screening allowed to identify several molecules that inhibit LSDV-ΔTK/EGFP replication. The strong inhibitory effect of theaflavin on LSDV was identified when 100 antiviral drugs were screened in vitro. An infection time analysis showed that theaflavin plays a role in the entry of LSDV into cells and in subsequent viral replication stages. The development of this recombinant virus will contribute to the development of LSDV-directed antiviral drugs and the study of viral replication and mechanisms of action.

Investigation of a set of flavonoid compounds as Helicobacter pylori urease inhibitors: insights from in silico studies

Helicobacter pylori (H. pylori) is a spiral, microaerophilic gram-negative bacterium, which is associated with the destruction of the lining of the stomach, leads to chronic inflammation of the stomach, which can cause stomach and duodenal ulcers. The problems caused by the treatment with antibiotics have caused researchers to use new approaches to treat infections caused by H. pylori, among them specific treatments with flavonoids. Urease enzyme, as one of the most important pathogenic and antigenic factors of this bacterium, is a suitable target for this purpose. In this study, the inhibitory effect of flavonoid compounds compared to acetohydroxamic acid on H. pylori urease enzyme was evaluated using molecular modeling methods. First, the interaction of flavonoids with urease enzyme compared with acetohydroxamic acid was investigated by molecular docking method to produce efficient docking poses. Then the physicochemical properties and toxicity of the best flavonoid compounds were analyzed using the swissadme server. Also, molecular dynamics calculations were performed to precisely understand the interactions between ligands and protein. The results of this study show that all the investigated flavonoid compounds are capable of inhibiting H. pylori urease. Among these compounds, six compounds chrysin, galangin, kaempferol, luteolin, morin and quercetin showed a greater tendency to bind to urease, compared to the acetohydroxamic acid inhibitor. These compounds are desirable in terms of physicochemical properties. This study also revealed that the flavonoids with their hydroxyl groups (-OH) play an important role during bond formation with amino acids Ala278, Ala169, His314, Asp362 and Asn168. Therefore, flavonoid compounds, due to their suitable location in the active site of the urease, create a more effective inhibition than the chemical drug acetohydroxamic acid and can be suitable candidates for the treatment of Helicobacter pylori under in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

In silico identification of colchicine derivatives as novel and potential inhibitors based on molecular docking and dynamic simulations targeting multifactorial drug targets involved in Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease's onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our in-silico study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer's and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer's drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer's treatment. Further in vitro and in vivo studies are warranted to explore these findings.Communicated by Ramaswamy H. Sarma.

Exploring the therapeutic mechanisms of Gleditsiae Spina acting on pancreatic cancer via network pharmacology, molecular docking and molecular dynamics simulation

Pancreatic cancer is one of the most aggressive tumors and also has a low survival rate. The dried spines of Gleditsia sinensis Lam are known as "Gleditsiae Spina" and they mostly contain flavonoids, phenolic acids, terpenoids, steroids, and other chemical components. In this study, the potential active components and molecular mechanisms of Gleditsiae Spina for treating pancreatic cancer were systematically revealed by network pharmacology, molecular docking and molecular dynamics simulations (MDs). RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53), tumor necrosis factor α (TNFα), interleukin-6 (IL6) and vascular endothelial growth factor A (VEGFA) were common targets of Gleditsiae Spina, human cytomegalovirus infection signaling pathway, AGE-RAGE signaling pathway in diabetic complications, and MAPK signaling pathway were critical pathways of fisetin, eriodyctiol, kaempferol and quercetin in the treatment of pancreatic cancer. Molecular dynamics simulations (MDs) results showed that eriodyctiol and kaempferol have long-term stable hydrogen bonds and high binding free energy for TP53 (-23.64 ± 0.03 kcal mol-1 and -30.54 ± 0.02 kcal mol-1, respectively). Collectively, our findings identify active components and potential targets in Gleditsiae Spina for the treatment of pancreatic cancer, which may help to explore leading compounds and potential drugs for pancreatic cancer.

Application of Molecular Simulation Methods in Food Science: Status and Prospects

Molecular simulation methods, such as molecular docking, molecular dynamic (MD) simulation, and quantum chemical (QC) calculation, have become popular as characterization and/or virtual screening tools because they can visually display interaction details that in vitro experiments can not capture and quickly screen bioactive compounds from large databases with millions of molecules. Currently, interdisciplinary research has expanded molecular simulation technology from computer aided drug design (CADD) to food science. More food scientists are supporting their hypotheses/results with this technology. To understand better the use of molecular simulation methods, it is necessary to systematically summarize the latest applications and usage trends of molecular simulation methods in the research field of food science. However, this type of review article is rare. To bridge this gap, we have comprehensively summarized the principle, combination usage, and application of molecular simulation methods in food science. We also analyzed the limitations and future trends and offered valuable strategies with the latest technologies to help food scientists use molecular simulation methods.