Background: Metabolic imbalance is the common basis of many diseases. As natural isoquinoline alkaloid, berberine (BBR) has shown great promise in regulating glucose and lipids metabolism and treating metabolic disorders. However, the related mechanism still lacks systematic research. Aim: To discuss the role of BBR in the whole body\'s systemic metabolic regulation and further explore its therapeutic potential and targets. Method: Based on animal and cell experiments, the mechanism of BBR regulating systemic metabolic processes is reviewed. Potential metabolism-related targets were summarized using Therapeutic Target Database (TTD), DrugBank, GeneCards, and cutting-edge literature. Molecular modeling was applied to explore BBR binding to the potential targets. Results: BBR regulates the whole-body metabolic response including digestive, circulatory, immune, endocrine, and motor systems through adenosine 5\'-monophosphate (AMP)-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR), sirtuin (SIRT)1/forkhead box O (FOXO)1/sterol regulatory element-binding protein (SREBP)2, nuclear factor erythroid 2-related factor (Nrf) 2/heme oxygenase (HO)-1, and other signaling pathways. Through these reactions, BBR exerts hypoglycemic, lipid-regulating, anti-inflammatory, anti-oxidation, and immune regulation. Molecular docking results showed that BBR could regulate metabolism targeting FOXO3, Nrf2, NAD(P)H quinone oxidoreductase 1 (NQO1), glutathione peroxidase (Gpx) 4 and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA). Evaluating the target clinical effects, we found that BBR has the therapeutic potential of anti-aging, anti-cancer, relieving kidney disease, regulating the nervous system, and alleviating other chronic diseases. Conclusion: This review elucidates the interaction between potential targets and small molecular metabolites by exploring the mechanism of BBR regulating metabolism. That will help pharmacologists to identify new promising metabolites interacting with these targets.

Breast cancer is the most frequently diagnosed disease causing most deaths in women worldwide. Chemotherapy and neo-adjuvant therapy are the standard method of treatment in early stages of breast cancer. However drug resistance in breast cancer limit the use of these methods for treatment. Research focus is now shifted towards identifying natural phytochemicals with lower toxicity. This review illustrates the NF κB interaction with different signaling pathways in normal condition, breast cancer and other cancer and thus represent a potential target for treatment. No reports are available on the action of picrosides on NFκB and its associated proteins for anticancer activity. In the present review, potential interaction of picrosides with NF-κB and its associated proteins is reviewed for anticancer action. Further, an important facet of this review entails the ADMET analysis of Picroside, elucidating key ADMET properties which serves to underscore the crucial characteristics of Picroside as a potential drug for treating breast cancer. Furthermore, in silico analysis of Picrosides was executed in order to get potential binding modes between ligand (Picrosides II) and NFκB.

Natural plant sources are essential in the development of several anticancer drugs, such as vincristine, vinblastine, vinorelbine, docetaxel, paclitaxel, camptothecin, etoposide, and teniposide. However, various chemotherapies fail due to adverse reactions, drug resistance, and target specificity. Researchers are now focusing on developing drugs that use natural compounds to overcome these issues. These drugs can affect multiple targets, have reduced adverse effects, and are effective against several cancer types. Developing a new drug is a highly complex, expensive, and time-consuming process. Traditional drug discovery methods take up to 15 years for a new medicine to enter the market and cost more than one billion USD. However, recent Computer Aided Drug Discovery (CADD) advancements have changed this situation. This paper aims to comprehensively describe the different CADD approaches in identifying anticancer drugs from natural products. Data from various sources, including Science Direct, Elsevier, NCBI, and Web of Science, are used in this review. In-silico techniques and optimization algorithms can provide versatile solutions in drug discovery ventures. The structure-based drug design technique is widely used to understand chemical constituents\' molecular-level interactions and identify hit leads. This review will discuss the concept of CADD, in-silico tools, virtual screening in drug discovery, and the concept of natural products as anticancer therapies. Representative examples of molecules identified will also be provided.

Gigantol, a bibenzyl compound extracted from various medicinal plants, has shown a number of biological activities, making it an attractive candidate for potential medical applications. This systematic review aims to shed light on gigantol\'s promising role in inflammation treatment and its underlying mechanisms. Gigantol exhibits potential anti-inflammatory properties in pre-clinical pharmacological test systems. It effectively reduced the levels of pro-inflammatory markers and arachidonic acid metabolites through various pathways, such as NF-κB, AKT, PI3K, and JNK/cPLA2/12-LOX. The in-silico investigations demonstrated that the MMP-13 enzyme served as the most promising target for gigantol with highest binding affinity (docking score = -8.8 kcal/mol). Encouragingly, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of gigantol confirmed its compatibility with the necessary physiochemical, pharmacokinetic, and toxicity properties, bolstering its potential as a drug candidate. Gigantol, with its well-documented anti-inflammatory properties, could be a promising agent for treating inflammation in the near future.

Due to the high prevalence of cancer, progress in the management of cancer is the need of the hour. Most cancer patients develop chemotherapeutic drug resistance, and many remain insidious due to overexpression of Multidrug Resistance Protein 1 (MDR1), also known as Permeability-glycoprotein (P-gp) or ABCB1 transporter (ATP-binding cassette subfamily B member 1). P-gp, a transmembrane protein that protects vital organs from outside chemicals, expels medications from malignant cells. The blood-brain barrier (BBB), gastrointestinal tract (GIT), kidneys, liver, pancreas, and cancer cells overexpress P-gp on their apical surfaces, making treatment inefficient and resistant. Compounds that compete with anticancer medicines for transportation or directly inhibit P-gp may overcome biological barriers. Developing nanotechnology-based formulations may help overcome P-gp-mediated efflux and improve bioavailability and cell chemotherapeutic agent accumulation. Nanocarriers transport pharmaceuticals via receptor-mediated endocytosis, unlike passive diffusion, which bypasses ABCB1. Anticancer drugs and P-gp inhibitors in nanocarriers may synergistically increase drug accumulation and chemotherapeutic agent toxicity. The projection of desirable binding and effect may be procured initially by molecular docking of the inhibitor with P-gp, enabling the reduction of preliminary trials in formulation development. Here, P-gp-mediated efflux and several possible outcomes to overcome the problems associated with currently prevalent cancer treatments are highlighted.

UNASSIGNED: Cervical cancer poses a considerable worldwide health issue, where infection with the human papillomavirus (HPV) plays a vital role as a risk factor. Photodynamic therapy (PDT) is a minimally invasive treatment for HPV-related cervical lesions, which uses photosensitizers and light to selectively destroy abnormal cells.
UNASSIGNED: Our objective is to present a comprehensive overview of the different types of molecules employed in PDT to reduce the occurrence and fatality rates associated with cervical cancer.
UNASSIGNED: Scoping review and bibliometric analysis.
UNASSIGNED: The article explores clinical trials investigating the efficacy of PDT in treating low-grade squamous intraepithelial lesion and high-grade squamous intraepithelial lesion, as well as preclinical approaches utilizing various molecules for PDT in cervical cancer. Furthermore, the article sheds light on potential molecules for PDT enhancement, examining their properties through computer modeling simulations, molecular docking, and assessing their advantages and disadvantages.
UNASSIGNED: Our findings demonstrate that PDT holds promise as a therapeutic approach for treating cervical lesions associated with HPV and cervical cancer. Additionally, we observe that the utilization of diverse dye classes enhances the anticancer effects of PDT.
UNASSIGNED: Among the various molecules employed in PDT, functionalized fullerene exhibits a notable inclination toward overexpressed receptors in cervical cancer cells, making it a potential candidate for intensified use in PDT. However, further research is needed to evaluate its long-term effectiveness and safety.
Using light to treat cervical cancer: what you need to know Cervical cancer is a significant global health concern, often linked to the human papillomavirus (HPV). There is a less invasive treatment called photodynamic therapy (PDT), which employs light and special substances to target and destroy abnormal cells related to HPV. In this review, we aim to give you a comprehensive look at the different substances used in PDT to reduce the occurrence and severity of cervical cancer. We have examined clinical trials focusing on treating specific types of cervical lesions and explored preclinical approaches using various substances. We have also delved into computer simulations and molecular docking to understand the strengths and weaknesses of these substances. Our findings show that PDT has potential as a treatment for HPV-related cervical lesions and cancer. Different dye classes used in this therapy enhance its effectiveness against cancer. Notably, a substance called functionalized fullerene stands out for its tendency to target receptors overexpressed in cervical cancer cells. It looks promising, but more research is necessary to ensure its long-term effectiveness and safety.

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) have significantly impacted the HIV-1 wild-type due to their high specificity and superior potency. As well as different combinations of NNRTIs have been used on clinically approved combining highly active antiretroviral therapy (HAART) to resist the growth of HIV-1 and decrease the mortality rate of HIV/AIDS. Although the feeble strength against the drug-resistant mutant strains and the long-term damaging effects have been reducing the effectiveness of HAART, it could be a crucial challenge to develop novel Anti-HIV leads with a vital mode of action and the least side effects. The extensive chemical reactivity and the diverse chemotherapeutic applications of the 1,3,5-triazine have provided a wide scope of research in medicinal chemistry via a structural modification. In this review, we focused on the Anti-HIV profile of the tri-substituted s-triazine derivatives with structure-based features and also discussed the active mode of action to evaluate the significant findings. The tri-substituted 1,3,5-triazine derivatives have been found more promising to inhibit the growth of the drug-sensitive and drug-resistant variants of HIV-1, especially HIV-1 wild-type, HIV-1 K103N/Y181C, and HIV-1 Tyr181Cys. It has been observed that these derivatives have interacted with the enzyme protein residues via a significant π $\\pi $ - π $\\pi $ interaction and hydrogen bonding to resist the proliferation of the viral genomes. Further, the SAR and the active binding modes are critically described and highlight the role of structural variations with functional groups along with the binding affinity of targeted enzymes, which may be beneficial for rational drug discovery to develop highly dynamic Anti-HIV agents.

Rice bran is a valuable byproduct from the food processing industry, which contains abundant protein, essential unsaturated fatty acids, and numerous bioactive compounds. However, its susceptibility to rancidity greatly restricts its wide utilization. Many strategies have been proposed to delay the rancidity of rice bran, but most of them have their respective limitations. Here, we proposed that developing rice ban lipase peptide inhibitors represents an alternative and promising prescription for impeding the rancidity of rice bran, in contrast to the conventional stabilization approaches for rice bran. For this reason, the rancidity mechanisms of rice bran and the research progress of rice bran lipases were discussed. In addition, the feasibility of utilizing in silico screening and phage display, two state-of-the-art technologies, in the design of the related peptide inhibitors was also highlighted. This knowledge is expected to provide a theoretical basis for opening a new avenue for stabilizing rice bran.

In recent years, investigations on molecular interaction mechanisms between food proteins and ligands have attracted much interest. The interaction mechanisms can supply much useful information for many fields in the food industry, including nutrient delivery, food processing, auxiliary detection, and others. Molecular simulation has offered extraordinary insights into the interaction mechanisms. It can reflect binding conformation, interaction forces, binding affinity, key residues, and other information that physicochemical experiments cannot reveal in a fast and detailed manner. The simulation results have proven to be consistent with the results of physicochemical experiments. Molecular simulation holds great potential for future applications in the field of food protein-ligand interactions. This review elaborates on the principles of molecular docking and molecular dynamics simulation. Besides, their applications in food protein-ligand interactions are summarized. Furthermore, challenges, perspectives, and trends in molecular simulation of food protein-ligand interactions are proposed. Based on the results of molecular simulation, the mechanisms of interfacial behavior, enzyme-substrate binding, and structural changes during food processing can be reflected, and strategies for hazardous substance detection and food flavor adjustment can be generated. Moreover, molecular simulation can accelerate food development and reduce animal experiments. However, there are still several challenges to applying molecular simulation to food protein-ligand interaction research. The future trends will be a combination of international cooperation and data sharing, quantum mechanics/molecular mechanics, advanced computational techniques, and machine learning, which contribute to promoting food protein-ligand interaction simulation. Overall, the use of molecular simulation to study food protein-ligand interactions has a promising prospect.

Lysine-specific demethylase 1 (LSD1/KDM1A) has emerged as a promising therapeutic target for treating various cancers (such as breast cancer, liver cancer, etc.) and other diseases (blood diseases, cardiovascular diseases, etc.), owing to its observed overexpression, thereby presenting significant opportunities in drug development. Since its discovery in 2004, extensive research has been conducted on LSD1 inhibitors, with notable contributions from computational approaches. This review systematically summarizes LSD1 inhibitors investigated through computer-aided drug design (CADD) technologies since 2010, showcasing a diverse range of chemical scaffolds, including phenelzine derivatives, tranylcypromine (abbreviated as TCP or 2-PCPA) derivatives, nitrogen-containing heterocyclic (pyridine, pyrimidine, azole, thieno[3,2-b]pyrrole, indole, quinoline and benzoxazole) derivatives, natural products (including sanguinarine, phenolic compounds and resveratrol derivatives, flavonoids and other natural products) and others (including thiourea compounds, Fenoldopam and Raloxifene, (4-cyanophenyl)glycine derivatives, propargylamine and benzohydrazide derivatives and inhibitors discovered through AI techniques). Computational techniques, such as virtual screening, molecular docking and 3D-QSAR models, have played a pivotal role in elucidating the interactions between these inhibitors and LSD1. Moreover, the integration of cutting-edge technologies such as artificial intelligence holds promise in facilitating the discovery of novel LSD1 inhibitors. The comprehensive insights presented in this review aim to provide valuable information for advancing further research on LSD1 inhibitors.