Dual core photonic crystal fiber based plasmonic refractive index sensor with ultra-wide detection range.

In this study, an ultra-wide range plasmonic refractive index sensor based on dual core photonic crystal fiber is suggested and analyzed numerically. The proposed design achieves fabrication feasibility by employing external sensing mechanism in which silver is deposited onto the flat outer surface of the fiber as plasmonic material. A thin layer of titanium oxide (TiO2) is considered on top of the silver layer for preventing its oxidation problem. The sensor attains identification of a vast array of analytes consisting a wide range of refractive indices of 1.10 - 1.45. It achieves a maximum spectral sensitivity of 24300 nm/RIU along with its corresponding resolution of 4.12 × 10-6 RIU. The maximum figure of merit of the sensor is 120 RIU-1. The sensor also supports amplitude interrogation approach and exhibits a maximum amplitude sensitivity of 172 RIU-1. The impact of the design parameters such as radius of air holes, polishing distance, thickness of silver and titanium oxide layers are investigated thoroughly. An ultra-wide detection range with high sensitivity, fabrication feasibility, and easy application make the sensor a potential candidate for detection of a wide array of bio-originated materials, chemicals, and other analytes.

MPDB 2.0: a large scale and integrated medicinal plant database of Bangladesh.

OBJECTIVE: MPDB 2.0 is built to be the continuation of MPDB 1.0, to serve as a more comprehensive data repertoire for Bangladeshi medicinal plants, and to provide a user-friendly interface for researchers, health practitioners, drug developers, and students who wish to study the various medicinal & nutritive plants scattered around Bangladesh and the underlying phytochemicals contributing to their efficacy in Bangladeshi folk medicine. RESULTS: MPDB 2.0 database ( https://www.medicinalplantbd.com/ ) comprises a collection of more than five hundred Bangladeshi medicinal plants, alongside a record of their corresponding scientific, family, and local names together with their utilized parts, information regarding ailments, active compounds, and PubMed ID of related publications. While medicinal plants are not limited to the borders of any country, Bangladesh and its Southeast Asian neighbors do boast a huge collection of potent medicinal plants with considerable folk-medicinal history compared to most other countries in the world. Development of MPDB 2.0 has been highly focused upon human diseases, albeit many of the plants indexed here can serve in developing biofuel (e.g.: Jatropha curcas used in biofuel) or bioremediation technologies (e.g.: Amaranthus cruentus helps to reduce cadmium level in soil) or nutritive diets (Terminalia chebula can be used in nutritive diets) or cosmetics (Aloe vera used in cosmetics), etc.

Energetic and structural basis for the differences in infectivity between the wild-type and mutant spike proteins of SARS-CoV-2 in the Mexican population.

SARS-CoV-2 is the causative agent of the ongoing viral pandemic of COVID-19. After the emergence of this virus, it became a global public health concern and quickly evolved into a pandemic. Mexico is currently in the third position in the number of deaths due to SARS-CoV-2. To date, there have been several lineages of SARS-CoV-2 worldwide; in the Mexican population, two variants of the spike protein (S-protein) are found, localized at H49Y and D614G, which have been related to increased infectivity with respect to the wild-type S-protein. To understand how these differences impact the structural behavior of the S-protein of SARS-CoV-2, as well as binding with ACE2, we performed MD simulations combined with the molecular mechanics generalized Born/Poisson-Boltzmann surface area (MMGB(PB)SA) approach starting from X-ray crystallography data. Energetic and structural analysis showed that the differences in infectivity can be explained by differences in affinity of the protein-protein interface between the wild-type and mutant S-protein with ACE2. Conformational analysis showed that molecular recognition between the S-protein and ACE2 is linked to a decrease in the conformational flexibility of wild-type and mutant S-protein; however, an increase in the conformational mobility of ACE2 could also contribute to the binding affinity observed using the MMGB(PB)SA method.

Structural analogues of existing anti-viral drugs inhibit SARS-CoV-2 RNA dependent RNA polymerase: A computational hierarchical investigation.

The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic, resulting in an exponentially increased mortality globally and scientists all over the world are struggling to find suitable solutions to combat it. Multiple repurposed drugs have already been in several clinical trials or recently completed. However, none of them shows any promising effect in combating COVID-19. Therefore, developing an effective drug is an unmet global need. RdRp (RNA dependent RNA polymerase) plays a pivotal role in viral replication. Therefore, it is considered as a prime target of drugs that may treat COVID-19. In this study, we have screened a library of compounds, containing approved RdRp inhibitor drugs that were or in use to treat other viruses (favipiravir, sofosbuvir, ribavirin, lopinavir, tenofovir, ritonavir, galidesivir and remdesivir) and their structural analogues, in order to identify potential inhibitors of SARS-CoV-2 RdRp. Extensive screening, molecular docking and molecular dynamics show that five structural analogues have notable inhibitory effects against RdRp of SARS-CoV-2. Importantly, comparative protein-antagonists interaction revealed that these compounds fit well in the pocket of RdRp. ADMET analysis of these compounds suggests their potency as drug candidates. Our identified compounds may serve as potential therapeutics for COVID-19.