Utilization of Cassava Wastewater for Low-Cost Production of Prodigiosin via Serratia marcescens TNU01 Fermentation and Its Novel Potent α-Glucosidase Inhibitory Effect

The purpose of this study was to reuse cassava wastewater (CW) for scaled-up production, via the fermentation of prodigiosin (PG), and to conduct an evaluation of its bioactivities. PG was produced at the yield of high 6150 mg/L in a 14 L-bioreactor system, when the designed novel medium (7 L), containing CW and supplemented with 0.25% casein, 0.05% MgSO4, and 0.1% K2HPO4, was fermented with Serratia marcescens TNU01 at 28 °C in 8 h. The PG produced and purified in this study was assayed for some medical effects and showed moderate antioxidant, high anti-NO (anti-nitric oxide), and potential α-glucosidase inhibitory activities. Notably, PG was first reported as a novel effective α-glucosidase inhibitor with a low IC50 value of 0.0183 µg/mL. The commercial anti-diabetic drug acarbose was tested for comparison and had a lesser effect with a high IC50 value of 328.4 µg/mL, respectively. In a docking study, the cation form of PG (cation-PG) was found to bind to the enzyme α-glucosidase by interacting with two prominent amino acids, ASP568 and PHE601, at the binding site on the target enzyme, creating six linkages and showing a better binding energy score (−14.6 kcal/mol) than acarbose (−10.5 kcal/mol). The results of this work suggest that cassava wastewater can serve as a low-cost raw material for the effective production of PG, a potential antidiabetic drug candidate.

Antioxidant Activity and In-Silico Study of Anthraquinone Glycosides Extracted from Cassia Fistula Against the Main Protease (7BUY) In SARS-COV2

With the spreading of Covid-19 and seeking for a drug that helps people around the world to cure this disease.In this article, we used a plant(Cassia fistula) which is rich in anthraquinone glycosides to control the causative agent. Anthraquinone was extracted from Cassia fistula pods using alcohol method.Antioxidant activity of the extracted anthraquinone was analysed by using hydrogen peroxide scavenging assay.The best inhibition assay was 70% at100mg/mlconcentration. The docking study introduced atheoretical explanation for an interaction between two types of anthraquinone glycosides (rhein and aloe-emodin) in Cassia fistula against the main protease (7BZ5) in SARS-COV-2 virus, which gave a good binding energy score as -5.36491489 and -5.48040009 for rhein and aloe-emodin, respectively.

APPLICATION OF MULTI-TRAIT BAYESIAN DECISION THEORY FOR PARENTAL GENOMIC SELECTION

In all breeding programs, the decision about which individuals to select and intermate to form the next selection cycle is crucial. The improvement of genetic stocks requires considering multiple traits simultaneously, given that economic value and net genetic merits depend on many traits; therefore, with the advance of computational and statistical tools and genomic selection (GS), researchers are focusing on multi-trait selection. Selection of the best individuals is difficult, especially in traits that are antagonistically correlated, where improvement in one trait might imply a reduction in other(s). There are approaches that facilitate multi-trait selection, and recently a Bayesian decision theory (BDT) has been proposed. Parental selection using BDT has the potential to be effective in multi-trait selection given that it summarizes all relevant quantitative genetic concepts such as heritability, response to selection and the structure of dependence between traits (correlation). In this study, we applied BDT to provide a treatment for the complexity of multi-trait parental selection using three multivariate loss functions (LF), Kullback-Leibler (KL), Energy Score, and Multivariate Asymmetric Loss (MALF), to select the best performing parents for the next breeding cycle in two extensive real wheat data sets. Results show that the high ranking lines in genomic estimated breeding value (GEBV) for certain traits did not always have low values for PEL. For both data sets, the KL loss function gave similar importance to all traits including grain yield. In contrast, the Energy Score and MALF gave better performance in 3 of 4 traits that were different than grain yield. The BDT approach should help breeders to decide based not only on the GEBV per se of the parent to be selected, but also on the level of uncertainty according to the Bayesian paradigm.

Molecular Docking Studies on the Anti-viral Effects of Compounds From Kabasura Kudineer on SARS-CoV-2 3CLpro

The COVID-19 has now been declared a global pandemic by the World Health Organization. No approved drug is currently available; therefore, an urgent need has been developed for any antiviral therapy for COVID-19. Main protease 3CLpro of this novel Coronavirus (SARS-CoV-2) play a critical role in the disease propagation, and hence represent a crucial target for the drug discovery. Herein, we have applied a bioinformatics approach for drug repurposing to identify the possible potent inhibitors of SARS-CoV-2 main proteases 3CLpro (6LU7). In search of the anti-COVID-19 compound, we selected 145 phyto-compounds from Kabasura kudineer (KK), a poly-herbal formulation recommended by AYUSH for COVID-19 which are effective against fever, cough, sore throat, shortness of breath (similar to SARS-CoV2-like symptoms). The present study aims to identify molecules from natural products which may inhibit COVID-19 by acting on the main protease (3CLpro). Obtained results by molecular docking showed that Acetoside (−153.06), Luteolin 7 -rutinoside (−134.6) rutin (−133.06), Chebulagic acid (−124.3), Syrigaresinol (−120.03), Acanthoside (−122.21), Violanthin (−114.9), Andrographidine C (−101.8), myricetin (−99.96), Gingerenone -A (−93.9), Tinosporinone (−83.42), Geraniol (−62.87), Nootkatone (−62.4), Asarianin (−79.94), and Gamma sitosterol (−81.94) are main compounds from KK plants which may inhibit COVID-19 giving the better energy score compared to synthetic drugs. Based on the binding energy score, we suggest that these compounds can be tested against Coronavirus and used to develop effective antiviral drugs.

Insights Studies for Certain Natural FDA Approved Polyphenolics and Repurposing for COVID-19

Natural polyphenolic drugs were approved for treatment of various diseases. Diosmin, rutin, quercetin, aesculin, genistein, hesperidin and silybin are known for their safety and have been applied for several human disorders including cancer, cardiovascular disorders, atherosclerosis, oxidative stress, capillary fragility, liver and pancreatic disorders and others. As the structures of the selected polyphenolic compounds possess variable chemical moieties with diverse chemical and electronic characters, these properties have been employed for further insights studies to predict new applications concerning the newly occurred pandemic. COVID-19 is a terrible disease that attacked millions of human populations at the end of year 2019. As the number of death cases has increased to exceed one million of humans, the early discovery of new treatment from previously approved and safe drugs is the main target of this study. Employing the putative docking studies for the selected polyphenolic drugs were done and the results were promising, all tested drugs exhibited high affinity with the selected five proteins of protease enzyme, the docking score ranged from -8.4461 to -26.1691 kcal/mol with 3-7 variable interaction bonds. Among the tested drugs, diosmin appeared as the most promising drug as it exhibited the highest energy score and interaction bonds with the most of proteins.

Metrics of Phenotypic Aging From the Energetics Perspective

Identifying the most critical metrics of aging is an ongoing challenge due to a lack of comprehensive measurements and heterogeneity of the aging process. Using the Baltimore Longitudinal Study of Aging, we developed a conceptual framework to identify metrics of aging that capture the hierarchical and temporal relationships between functional aging, phenotypic aging, and biological aging based on four hypothesized domains: energy regulation, body composition, homeostatic mechanisms, and neurodegeneration. Focusing on the energetics domain, we examined trajectories of eight phenotypes using more than 10 years of longitudinal data. The standardized Cronbach’s alpha for these variables was 0.80, providing construct validity of our concept. We further implemented item response theory to integrate these phenotypes into a summarized energy score. Linear mixed models were used to assess the cross-sectional and longitudinal associations between the summarized energy score and physical functioning as measured by gait speed and time to walk 400m as quickly as possible (number of participants ~ 811, number of observations ~ 1700). After adjusting for age, sex, weight, and height, a higher summarized energy score was independently associated with faster baseline gait speed (0.13 m/s, p<0.001 ) and faster 400m time (-35.3 seconds, p<0.001), and longitudinally associated with slower gait speed decline (0.08 m/s/decade, p<0.001) and slower 400m time increase (-37.8 secs/decade, p<0.001). This work demonstrates the utility of our energetics domain-based summarized score. Moving forward, it will be important to clarify relationships between this summarized score and other functional metrics and assess its generalizability to the other cohorts.

Using in-silica Analysis and Reverse Vaccinology Approach for COVID-19 Vaccine Development

Background: The recent pandemic of COVID19 that has struck the world is yet to be battled by a potential cure. Countless lives have been claimed due to the existing pandemic and the societal normalcy has been damaged permanently. As a result, it becomes crucial for academic researchers in the field of bioinformatics to combat the existing pandemic. Materials and Methods: The study involved collecting the virulent strain sequence of SARS-nCoV19 for the country USA against human host through publically available bioinformatics databases. Using in-silica analysis, reverse vaccinology, and 3-D modelling, two leader proteins were identified to be potential vaccine candidates for development of a multi-epitope drug. Results: It was revealed that the two leader proteins ORF1ab MT326102 and MT326715 had the highest extinction coefficient and the lowest score on the GRAVY. Along with the given parameters, these leader proteins were highly stable and were also antigenic in nature. The two selected epitopes were then docked against their respective alleles to obtain the global energy scores, which was the lowest of all possible pairs. Conclusion: The epitopes which displayed the lowest global energy score on docking with the alleles were selected and proposed as successful and potential vaccine candidates for multi-epitope vaccine development. Doi: 10.28991/SciMedJ-2020-02-SI-9 Full Text: PDF

Dependence uncertainty bounds for the energy score and the multivariate Gini mean difference

The energy distance and energy scores became important tools in multivariate statistics and multivariate probabilistic forecasting in recent years. They are both based on the expected distance of two independent samples. In this paper we study dependence uncertainty bounds for these quantities under the assumption that we know the marginals but do not know the dependence structure. We find some interesting sharp analytic bounds, where one of them is obtained for an unusual spherically symmetric copula. These results should help to better understand the sensitivity of these measures to misspecifications in the copula.

Simulasi Docking Molekuler Senyawa Potensial Tanaman Justicia Gendarussa Burm.f. Sebagai Antidiabetes

Indonesia has various natural compounds that are potential as antidiabetics but the mechanism of action was not yet known in detail, one of them is Justicia gendarussa. Justicia gendarussa is known as Gandarusa contains kaempferol and naringenin. In this study, the two compounds were simulated with glucokinase enzyme using a glibenclamide as a standard reference drug to determine their potential action as an antidiabetic. The research method was carried out using molecular docking computation simulation (in silico). The results showed the binding energy scores of glibenclamide, naringenin, and kaempferol to glucokinase enzymes are -22.0917; -22,1866; and -22,6328 kcal/mol, respectively. The hydrogen bonding plays in binding the enzyme. These results showed the binding energy score was not different significantly. Thus, naringenin and kaempferol had the same antidiabetic potential as glibenclamide. Keywords: Justicia gendarussa, antidiabetes, molecular docking, naringenin, kaempferol Abstrak Berbagai senyawa alam Indonesia berpotensi sebagai antidiabetes namun belum diketahui mekanisme aksinya secara rinci, salah satu contohnya Justicia gendarussa Burm.f.. Tanaman Justicia gendarussa yang dikenal baik dengan nama Gandarusa, mengandung kaempferol dan naringenin. Pada penelitian ini, kedua senyawa disimulasikan terhadap enzim glukokinase menggunakan senyawa pembanding glibenklamid yang merupakan obat referensi untuk mengetahui potensinya sebagai antidiabetes. Metode penelitian dilakukan menggunakan simulasi komputasi docking molekuler (in silico). Hasil docking molekuler menunjukkan skor energi ikatan glibenklamid, naringenin dan kaempferol terhadap enzim glukokinase masing-masing sebesar -22,0917; -22,1866 ; dan -22,6328 kkal/mol. Ikatan yang berperan adalah ikatan hydrogen. Hasil penelitian menunjukkan nilai skor energi ikatan yang tidak berbeda signifikan. Dengan demikian naringenin dan kaempferol memiliki potensi sebagai antidiabetes yang sama dengan glibenklamid. Kata kunci: Justicia gendarussa, antidiabetes, docking molekuler, naringenin, kaempfero