KULLBACK-LEIBER DIVERGENCE MEASURE IN CORRELATION OF GRAY-SCALE OBJECTS

Kullback-Leiber divergence measure is one of the commonly used distance measure that is used for computing the dissimilarity score between histograms. In this paper we show that it produces biased results when correlation is computed between gray scale images or sections of images using their histograms. The biased is explored and demonstrated through numerous experiments with different sizes of objects and different kind of movements between the pairs of images i.e., slow moving, fast moving, rotating bodies etc, in cluttered and less cluttered environments. The performance of the Kullback-Leiber divergence measure is compared with a pixel based spatial matching criterion

Identification of Phytochemicals from Arabian Peninsula Medicinal Plants as Strong Binders to SARS-CoV-2 Proteases (3CL^Pro and PL^Pro) by Molecular Docking and Dynamic Simulation Studies

We provide promising computational (in silico) data on phytochemicals (compounds 1–10) from Arabian Peninsula medicinal plants as strong binders, targeting 3-chymotrypsin-like protease (3CLPro) and papain-like proteases (PLPro) of SARS-CoV-2. Compounds 1–10 followed the Lipinski rules of five (RO5) and ADMET analysis, exhibiting drug-like characters. Non-covalent (reversible) docking of compounds 1–10 demonstrated their binding with the catalytic dyad (CYS145 and HIS41) of 3CLPro and catalytic triad (CYS111, HIS272, and ASP286) of PLPro. Moreover, the implementation of the covalent (irreversible) docking protocol revealed that only compounds 7, 8, and 9 possess covalent warheads, which allowed the formation of the covalent bond with the catalytic dyad (CYS145) in 3CLPro and the catalytic triad (CYS111) in PLPro. Root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and radius of gyration (Rg) analysis from molecular dynamic (MD) simulations revealed that complexation between ligands (compounds 7, 8, and 9) and 3CLPro and PLPro was stable, and there was less deviation of ligands. Overall, the in silico data on the inherent properties of the above phytochemicals unravel the fact that they can act as reversible inhibitors for 3CLPro and PLPro. Moreover, compounds 7, 8, and 9 also showed their novel properties to inhibit dual targets by irreversible inhibition, indicating their effectiveness for possibly developing future drugs against SARS-CoV-2. Nonetheless, to confirm the theoretical findings here, the effectiveness of the above compounds as inhibitors of 3CLPro and PLPro warrants future investigations using suitable in vitro and in vivo tests

Covalent Inhibitors from Saudi Medicinal Plants Target RNA-Dependent RNA Polymerase (RdRp) of SARS-CoV-2

COVID-19, a disease caused by SARS-CoV-2, has caused a huge loss of human life, and the number of deaths is still continuing. Despite the lack of repurposed drugs and vaccines, the search for potential small molecules to inhibit SARS-CoV-2 is in demand. Hence, we relied on the drug-like characters of ten phytochemicals (compounds 1–10) that were previously isolated and purified by our research team from Saudi medicinal plants. We computationally evaluated the inhibition of RNA-dependent RNA polymerase (RdRp) by compounds 1–10. Non-covalent (reversible) docking of compounds 1–10 with RdRp led to the formation of a hydrogen bond with template primer nucleotides (A and U) and key amino acid residues (ASP623, LYS545, ARG555, ASN691, SER682, and ARG553) in its active pocket. Covalent (irreversible) docking revealed that compounds 7, 8, and 9 exhibited their irreversible nature of binding with CYS813, a crucial amino acid in the palm domain of RdRP. Molecular dynamic (MD) simulation analysis by RMSD, RMSF, and Rg parameters affirmed that RdRP complexes with compounds 7, 8, and 9 were stable and showed less deviation. Our data provide novel information on compounds 7, 8, and 9 that demonstrated their non-nucleoside and irreversible interaction capabilities to inhibit RdRp and shed new scaffolds as antivirals against SARS-CoV-2

Novel Approach to Manufacture an AUV Propeller by Additive Manufacturing and Error Analysis

Autonomous underwater vehicle (AUV) is an unmanned tether-free vehicle which is powered by battery or fuel cell. The weight of the AUV is a major issue to be decided when considering its performance. To manufacture a propeller that is lighter in weight and able to carry the pressure applied to the blades is an involving process. The present study investigates the performance of the propeller of an AUV, manufactured by additive manufacturing, using ABS plastic material. The propeller blade designed in SolidWorks was transferred to the CUBPRO (DUO), followed by setting the parameters for a 3D printing machine. A comparative study was carried out for ABS (Acrylonitrile Butadiene Styrene) material between the required dimensions and a 3D printed model dimension propeller blade. An error analysis was carried out and we observed that ABS material is the most suitable for an AUV propeller. A stress-strain analysis for the propeller was carried out using the Finite Element Method