In this review, a timeline starting at the willow bark and ending in the latest discoveries of analgesic and anti-inflammatory drugs will be discussed. Furthermore, the chemical features of the different small organic molecules that have been used in pain management will be studied. Then, the mechanism of different types of pain will be assessed, including neuropathic pain, inflammatory pain, and the relationship found between oxidative stress and pain. This will include obtaining insights into the cyclooxygenase action mechanism of nonsteroidal anti-inflammatory drugs (NSAID) such as ibuprofen and etoricoxib and the structural difference between the two cyclooxygenase isoforms leading to a selective inhibition, the action mechanism of pregabalin and its use in chronic neuropathic pain, new theories and studies on the analgesic action mechanism of paracetamol and how changes in its structure can lead to better characteristics of this drug, and cannabinoid action mechanism in managing pain through a cannabinoid receptor mechanism. Finally, an overview of the different approaches science is taking to develop more efficient molecules for pain treatment will be presented.

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Silver nanoparticles are recognized for numerous physical, biological, and pharmaceutical applications. eir main uses in the medical field comprise diagnostic and therapeutic applications. In this project, the interaction between silver nanoparticles and the lipid layer of the skin was studied in order to know how nanoparticles behave when they are in contact with the skin. Energies of the silver nanoparticles were calculated through the optimization of silver clusters using density functional theory implemented in the Gaussian program 09W. Biological molecules such as glucose, stearic acid, palmitic acid, and quercetin present in coated nanoparticles and in the skin were also optimized. e silver clusters containing 6 atoms were proven to be the most stable complexes. Moreover, a study of molecular orbital describing HOMO interactions of the clusters was performed showing that the electronic density was around the silver cluster. Molecular dynamics simulation was performed using Abalone program. Silver nanoparticles seemed to have very good clearance properties in our molecular dynamics simulation because over a certain period of time, the silver cluster got far away from the biological molecules.

Free fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic β-cells. An advantage of therapies that target FFA1 is their reduced risk of hypoglycemia relative to common type 2 diabetes treatments. In this work, quantitative structure–activity relationship (QSAR) approach was used to construct models to identify possible FFA1 agonists by applying four different machine-learning algorithms. The best model (M2) meets the Tropsha’s test requirements and has the statistics parameters R2 = 0.843, Q2CV = 0.785, and Q2ext = 0.855. Also, coverage of 100% of the test set based on the applicability domain analysis was obtained. Furthermore, a deep analysis based on the ADME predictions, molecular docking, and molecular dynamics simulations was performed. The lipophilicity and the residue interactions were used as relevant criteria for selecting a candidate from the screening of the DiaNat and DrugBank databases. Finally, the FDA-approved drugs bilastine, bromfenac, and fenofibric acid are suggested as potential and lead FFA1 agonists.