Silver nanoparticles (AgNPs) were synthesized using hydroalcoholic extracts of dittany (Origanum dictamnus), sage (Salvia officinalis), sea buckthorn (Elaeagnus rhamnoides, syn. Hippophae rhamnoides), and calendula (Calendula officinalis) as reducing agents. AgNPs synthesized using NaBH4 and citric acid were used as control. The impact of the origin of the extract and preparation conditions (light, temperature, reaction time) on the properties of the synthesized AgNPs was investigated. The structure, morphology, composition, physicochemical characteristics, and colloidal stability were characterized using dynamic laser scattering (DLS), ultraviolet-visible spectrophotometry (UV–/Vis), XRD, X-ray fluorescence (XRF), TEM, and FTΙR. The reduction of total phenolic and flavonoid content of the extracts after the reaction of AgNPs synthesis was also determined. Low IC50 values for all types of AgNPs revealed good antioxidant activity, attributable to the phenolic and flavonoid content of their surface. The results suggest that plant extract selection is important to the green synthesis of AgNPs because it affects the kinetics of their synthesis as well as their morphology, physicochemical characteristics, and colloidal stability. In vitro permeation studies on porcine skin revealed that AgNPs remained at the upper layers of stratum corneum and did not penetrate the skin barrier after 4 h of cutaneous application suggesting the safety of their application on intact skin for a relatively short time.

Warfarin sodium is a low-dose pharmaceutical blood thinner that exists in two forms: the clathrate form and the amorphous form. In commercially available warfarin sodium oral suspension, the active pharmaceutical ingredient (API) is added in the amorphous state. This study investigates the apparent instability of the commercially available warfarin liquid oral formulation using Raman and IR spectroscopy, X-ray diffraction, differential scanning calorimetry, UV spectroscopy, and optical microscopy. Warfarin, not its sodium salt, was identified as the undissolved solid existing in the suspension. This was found to be due to the dissociation of sodium salt and the protonation of the warfarin ion in the liquid phase, which triggered the crystallization of the sparingly soluble unsalted form. The coexistence of protonated and unprotonated warfarin ions in the supernatant, as detected by Raman and UV spectroscopy, confirmed this assumption. Study of the dissolution of warfarin sodium amorphous salt and crystalline sodium clathrate in the placebo and pure water verified the results. The effect of pH and temperature on warfarin precipitation was also explored.

Macro domains are conserved protein domains found in eukaryotic organisms, bacteria, and archaea as well as in certain viruses. They consist of 130-190 amino acids and can bind ADP-ribose. Although the exact role of these domains is not fully understood, the conserved binding affinity for ADP-ribose indicates that this ligand is important for the function of the domain. Such a macro domain is also present in the non-structural protein 3 (nsP3) of Chikungunya Alphavirus (CHIKV) and consists of 160 amino acids. In this study we describe the high yield expression of the macro domain from CHIKV and its preliminary structural analysis via solution NMR spectroscopy. The macro domain seems to be folded in solution and an almost complete backbone assignment was achieved. In addition, the α/β/α sandwich topology with 4 α-helices and 6 β-strands was predicted by TALOS+.

Determination of the polymorphic form of an active pharmaceutical ingredient (API) in a suspension could be really challenging because of the water phase and the low concentration of the API in this formulation. Posaconazole is an antifungal drug available also as an oral suspension. The aim of this study was to develop a sample-preparation method for polymorphic identification of the dispersed API by increasing the concentration of the API but with no compromise of polymorph stability. For this purpose, filtration, drying and centrifugation were tested for separating the API from the suspending medium. Centrifugation was selected because it succeeded in separating Posaconazole API with no polymorph transformation during the process. During this study, it was found that Posaconazole in oral suspensions is Form-S. However, when slower scanning rates were used for acquiring an XRPD pattern with better signal/noise ratio, Posaconazole was converted to Form I due to water loss. In order to protect the sample from conversion, different approaches were tested to secure an airtight sample including a commercially available XRPD sample holder with a dome-like transparent cap, standard polymethylmethacrylate (PMMA) sample holders covered with Mylar film, transparent pressure-sensitive tape and a transparent food membrane. Only usage of the transparent food membrane was found to protect the API from conversion for a period of at least two weeks and resulted in a Posaconazole Form-S XRPD pattern with no artificial peaks.

In the field of computational drug design, the identification and characterisation of the biological target of interest is a major step. Despite the growing number of such resolved protein structures every year, there are still many drug targets, especially membrane proteins, for which structural determination is very difficult. In these cases, experimental knowledge on already determined bioactive molecules may be used successfully for computational ligand‐based drug‐design methods. However, for the past three decades, most drug discovery efforts have been driven by the structure of the target biomolecule. Advances in structural biology methods have provided structural information of many molecules, giving rise to the structure‐based drug‐design process as a powerful tool for drug discovery in research academia and pharmaceutical industry. Both fields in the in silico drug‐design field are commonly used, each one depending on background experimental information and relevant computational methodologies. Key Concepts The main computer‐aided drug‐design approaches are either ligand or structure based. Main ligand‐based methods for identifying bioactive compounds are chemical similarity, pharmacophore mapping and QSAR. Advances in structural biology methodologies have greatly assisted structure‐based drug design. Structure‐based methods in computational drug design are mostly molecular docking, molecular dynamics, fragment‐based drug‐design and pharmacophore modelling. Docking and pharmacophore methodologies are most commonly used for virtual screening in drug design.