GC-MS analysis, molecular docking, and pharmacokinetic studies of Multidentia crassa extracts' compounds for analgesic and anti-inflammatory activities in dentistry.

Plant extracts have been useful for oral health or dentistry. However, only a few evidence-based justifications exist. This study evaluated Multidentia crassa (Hiern) Bridson & Verdc, one of the oral health-used plants in Malawi. Gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared (FT-IR) identified the extracts' compounds. The pharmacokinetics of the identified compounds were studied using pkCSM and SwissADME, and molecular docking studies were used to identify potential drug candidates for oral health by predicting the binding affinity of the compounds to cyclooxygenases, interleukin-1 beta receptors, odontoblast cold sensor proteins, and purinergic receptor P2X3. FT-IR analysis showed characteristic peaks of phenols, carboxylic acids, alkenes, alkyl halides, amines, esters, ethers, aromatics, and lipids. GC-MS results showed the presence of 58 bioactive phytocompounds, some of which have various pharmacological activities relevant to oral health. Molecular docking further validated stigmastan-3,5-diene's potency for analgesic and anti-inflammatory purposes. Based on a literature review, this is the first report on the bioactive compounds of M. crassa extracts showing analgesic and anti-inflammatory effects. This study's results can lead to new herbal and conventional medicines. Therefore, we recommend in vivo and in vitro studies to elucidate the pharmacological effects of the plant extracts.

Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors.

The COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, and transmembrane protease serine 2 (TMPRSS2). In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat Mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of the drug candidates to target receptors, providing insight into their potential efficacy. This study is aimed at assessing the useful contributions of the application of computational instruments in the discovery of receptors targeted in SARS-CoV-2. It further highlights some identified advantages and limitations of these studies, thereby revealing some complementary experimental validation to ensure the efficacy and safety of identified drug candidates.