Experimental and clinical trial investigations of phyto-extracts, phyto-chemicals and phyto-formulations against oral lichen planus: A systematic review

Antidiabetic potency and molecular insights of natural products bearing indole moiety: A systematic bioinformatics investigation targeting AKT1

Diabetic mellitus (DM) is a chronic disorder, and type 2 DM (T2DM) is the most prevalent among all categories (nearly 90%) across the globe every year. With the availability of potential drugs, the prevalence rate has remained uncontrollable, while natural resources showed a promising potency, and exploring such potential candidates at the preclinical stage is essential. An extensive literature search selected 89 marine and plant-derived indole derivatives with anti-inflammatory, antioxidant, lipid-lowering, etc., activities. However, as we know, drugs have not been able to convert from 'lead' to 'mainstream' due to inadequate drug-ability profiles, as our systematic investigation proved and selected herdmanine_A (HERD_A) and penerpene_D (PENE_D) as the most potential antidiabetic candidates from the library of indole derivatives. Based on our previous network pharmacology study, we selected three new target enzymes: Acetyl-CoA carboxylase 2 (ACACB; PDB ID: 3JRX), cyclin-dependent kinase 4 (CDK4; PDB ID: 3G33), and alpha serine/threonine-protein kinase 1 (AKT1; PDB ID: 3O96) to assess the antidiabetic potency of selected indole derivatives through binding energy or docking score. To conduct molecular docking studies with these enzymes, we used the PyRx-AutoDock platform. Furthermore, molecular dynamic simulation at 100 ns, physicochemical analysis, pharmacokinetics, toxicity assessment, and drug-likeness evaluation suggested that HERD_A and penerpene PENE_D were the most potent inhibitors against AKT1 compared to koenimbine (most potential based on the recorded IC50 value) and murrayakonine_A (most potential based on the docking score). In summary, HERD_A and/or PENE_D have the potential to be used as alternative therapeutic agent for the treatment of diabetes after some pharmacological investigation.

Efficacy of Topical Treatments for the Management of Symptomatic Oral Lichen Planus: A Systematic Review

Oral lichen planus (OLP) is a chronic mucosal inflammatory disease associated with T-cell-mediated immunological dysfunction. Symptomatic OLP is a painful condition, and complete healing is often not achieved. The aim of this systematic review was to assess the effectiveness of topical drugs, medications, and other interventions compared to placebo or to other treatments in pain reduction and clinical resolution in adult patients with symptomatic OLP. A detailed electronic literature search was performed through the MEDLINE (PubMed) database between 1 January 2005 and 30 September 2022. Eligible studies were selected based on the inclusion criteria, and a quality assessment was conducted. From 649 titles, 121 articles were selected as abstracts, 75 papers were assessed as full text, along with 15 other papers obtained through a manual search. A total of 15 RCTs were finally included in the review process. Because of the significant heterogeneity in the study design of the included studies, no meta-analysis of the data could be performed. Topical corticosteroids represent the first-line treatment in the management of symptomatic OLP due to their efficacy and minimal adverse effects. Calcineurin inhibitors seem to be equally effective and are indicated in recalcitrant cases, extensive lesions, patients susceptible to oral candidiasis, or cases unresponsive to corticosteroids. Other treatments, such as aloe vera, chamomile, isotretinoin, ozone, and laser therapy, could be beneficial as adjunct therapies in association with first-line treatments.

Combined Bioinformatics and Combinatorial Chemistry Tools to Locate Drug-Able Anti-TB Phytochemicals: A Cost-Effective Platform for Natural Product-Based Drug Discovery

Based on extensive experimental studies, a huge number of phytochemicals showed potential activity against tuberculosis (TB) at a lower minimum inhibitory concentration (MIC) and fewer toxicity profiles. However, these promising drugs have not been able to convert from 'lead' to 'mainstream' due to inadequate drug-ability profiles. Thus, early drug-prospective analyses are required at the primary stage to accelerate natural-product-based drug discovery with limited resources and time. In the present study, we have selected seventy-three potential anti-TB phytochemicals (MIC value ≤10 μg/mL) and assessed the drug-ability profiles using bioinformatics and combinatorial chemistry tools, systematically. Primarily, the molecular docking study was done against two putative drug targets, catalase-peroxidase enzyme (katG) and RNA polymerase subunit-β (rpoB) of Mycobacterium tuberculosis (Mtb) using AutoDock 4.2 software. Further, assessed the drug-ability score from Molsoft, toxicity profiles from ProTox, pharmacokinetics from SwisADME, hierarchical cluster analysis (HCA) by ChemMine tools and frontier molecular orbitals (FMOs) with Avogadro and structural activity relationships (SAR) analysis with ChemDraw 18.0 software. Above analyses indicated that, lower MIC exhibited anti-TB phytochemicals, abietane, 12-demethylmulticaulin exhibited poor docking and drug-ability scores, while tiliacorinine, 2-nortiliacorinine showed higher binding energy and drug-ability profiles. Overall, tiliacorinine, 2-nortiliacorinine, 7α-acetoxy-6β-hydroxyroyleanone (AHR), (2S)-naringenin and isovachhalcone were found as the most active and drug-able anti-TB candidates from 73 candidates. Phytochemicals are always a vital source of mainstream drugs, but the MIC value of a phytochemical is not sufficient for it to be promoted. An ideal drug-ability profile is therefore essential for achieving clinical success, where advanced bioinformatics tools help to assess and analyse that profile. Additionally, several natural pharmacophores found in existing anti-TB drugs in SAR analyses also provide crucial information for developing potential anti-TB drug. As a conclusion, combined bioinformatics and combinatorial chemistry are the most effective strategies to locate potent-cum-drug-able candidates in the current drug-development module.