Antimicrobial Drug Repurposing Through Molecular Modelling: Acquisition, Analyis and Prediction

Antimicrobial resistance has sparked unprecedented medical crises around the world, not only increasing the mortality rate but also impacting nosocomial resources. Methicillin-resistant Staphylococcus aureus (MRSA) has consistently evaded the available range of antibiotics and is a typical case study for new generation drugs. Drug development has been conventionally suffering from exceedingly high costs and overdrawn timelines. Drug Repurposing can be a solution to alleviate those burdens. Put simply, DR is a mechanism to identify new usages of existing drugs, typically targeted to treat diseases different to the ones that these were initially intended for. This inherently interdisciplinary research targets to identify the best MRSA drug candidates analysing protein (BIG) data, in the process developing a combination of techniques from stochastic mathematics, statistics and data analytics that can generically identify drug targets from the databank. Structure-based virtual screening was used to repurpose an extensive range of marketed drugs and Phase I/II/III trials. Molecular docking methods were used for virtual screening against MRSA targets based on sequence alignment to match gene sequences against proteins in the Protein Data Bank (PDB). Ligands from the Database of Useful Decoys - Enhanced were docked against MRSA-oriented target proteins using 10 open-source docking programmes for benchmark. The novel consensus scoring methods prove superior to other reported consensus scores in terms of discrimination between decoys and active ligands concerning MRSA drug target identification. The consensus scoring predictions are then applied to docking data between MRSA targets and compounds from the Repurposing Hub to identify a list of potential drug candidates for anti-MRSA treatment. MRSA is currently an apocalypse across the world with limited prevention and medications. This study provided more potential candidates to help fight against MRSA. The consensus scoring developed in this study can be generically implemented to unlock other antimicrobial drug candidates

Towards Effective Consensus Scoring in Structure-Based Virtual Screening

Virtual screening (VS) is a computational strategy that uses in silico automated protein docking inter alia to rank potential ligands, or by extension rank protein–ligand pairs, identifying potential drug candidates. Most docking methods use preferred sets of physicochemical descriptors (PCDs) to model the interactions between host and guest molecules. Thus, conventional VS is often data-specific, method-dependent and with demonstrably differing utility in identifying candidate drugs. This study proposes four universality classes of novel consensus scoring (CS) algorithms that combine docking scores, derived from ten docking programs (ADFR, DOCK, Gemdock, Ledock, PLANTS, PSOVina, QuickVina2, Smina, Autodock Vina and VinaXB), using decoys from the DUD-E repository (http://dude.docking.org/) against 29 MRSA-oriented targets to create a general VS formulation that can identify active ligands for any suitable protein target. Our results demonstrate that CS provides improved ligand–protein docking fidelity when compared to individual docking platforms. This approach requires only a small number of docking combinations and can serve as a viable and parsimonious alternative to more computationally expensive docking approaches. Predictions from our CS algorithm are compared against independent machine learning evaluations using the same docking data, complementing the CS outcomes. Our method is a reliable approach for identifying protein targets and high-affinity ligands that can be tested as high-probability candidates for drug repositioning. Graphical Abstract

Female Germline Stem Cells: A Source for Applications in Reproductive and Regenerative Medicine

One of the most significant findings in stem cell biology is the establishment of female germline stem cells (FGSCs) in the early 21st century. Besides the massive contribution of FGSCs to support ovarian function and fertility of females, the ability to create transgenic animals from FGSCs have high efficiency. Whether FGSCs can differentiate into mature oocytes for fertilization and complete embryonic development is a significant question for scientists. FGSCs were shown to produce oocytes, and the fertilized oocytes could generate offspring in mice and rats. This discovery has opened a new direction in human FGSCs research. Recently, cryopreservation of ovarian cortical tissue was already developed for women with cancer. Thus, isolation and expansion of FGSCs from this tissue before or after cryopreservation may be helpful for clinical fertility therapies. Scientists have suggested that the ability to produce transgenic animals using FGSCs would be a great tool for biological reproduction. Research on FGSCs opened a new direction in reproductive biotechnology to treat infertility and produce biological drugs supported in pre-menopausal syndrome in women. The applicability of FGSCs is enormous in the basic science of stem cell models for studying the development and maturation of oocytes, especially applications in treating human disease

Isolation and selection of Bacillus strains with high potential probiotic that used in catfish farming (Pangasianodon hypophthalmus)

In this study, we isolated 28 strains of Bacillus spp. from water samples, catfish pond mud samples and earthworm manure (Perionyx excavates). By the cross-streak agar methods, 22 Bacillus strains showed the inhibition ability to Edwardsiella ictaluri, which caused Bacillary Necrosis Pangasius (BNP) in catfish (Pangasianodon hypophthalmus). Both Bacillus sp. Q16 and Q111 strains showed the highest inhibition to E. ictaluri by the double-layer agar methods. Finally, two Bacillus strains (Q16, Q111) were selected as a source of potential probiotic because of the ability of extracellular enzyme secretion (protease, amylase, cellulose) strong growth at 0,1-1% salt concentrations, survival within the pH range 6-8, resistance to low pH and low bile salts, inability to produce haemolysin enzyme, sensitivity to eight antibiotics in the three impacting groups (inhibition of wall synthesis, inhibition mechanism of protein synthesis, inhibition of nucleic acid synthesis). Two Bacillus strains (Q16, Q111) were identified that they belong to Bacillus subtilis by biochemical method and 16S rRNA gene sequencing method. This study indicated that two Bacillus strains (Q16, Q111) isolated from catfish pond can be applied as high potential probiotics that used to farm catfish

Short Tandem Repeats Used in Preimplantation Genetic Testing of Î’-Thalassemia: Genetic Polymorphisms For 15 Linked Loci in the Vietnamese Population

BACKGROUND: β-thalassemia is one of the most common monogenic diseases worldwide. Preimplantation genetic testing (PGT) of β-thalassemia is performed to avoid affected pregnancies has become increasingly popular worldwide. In which, the indirect analysis using short tandem repeat (STRs) linking with HBB gene to detect different β-globin (HBB) gene mutation is a simple, accurate, economical and also provides additional control of contamination and allele-drop-out ADO. AIM: This study established microsatellite markers for PGT of Vietnamese β-thalassemia patient. METHODS: Fifteen (15) STRs gathered from 5 populations were identified by in silico tools within 1 Mb flanking the HBB gene. The multiplex PCR reaction was optimized and performed on 106 DNA samples from at-risk families. RESULTS: After estimating, PIC values were ≥ 0.7 for all markers, with expected heterozygosity and observed heterozygosity values ranged from 0.81 to 0.92 and 0.53 to 0.86, respectively. One hundred percent of individuals had at least seven heterozygous markers and were found to be heterozygous for at least two markers on either side of the HBB gene. The STRs panel was successfully performed on one at-risk family. CONCLUSION: In general, a pentadecaplex marker (all < 1 Mb from the HBB gene) assay was constituted for β-thalassemia PGT on Vietnamese population

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Extracting Prime Protein Targets As Possible Drug Candidates: Machine Learning Evaluation

Extracting ‘high ranking’ or ‘Prime Protein Targets’ (PPTs) as potent MRSA drug candidates from a given set of ligands is a key challenge in efficient molecular DOCKING. This study combines protein-versus-ligand matching Molecular Docking (MD) data extracted from 10 independent Molecular Docking (MD) evaluations - ADFR; DOCK; Gemdock; Ledock; Plants; Psovina; Quickvina2; smina; vina; and vinaxb to identify top MRSA drug candidates. 29 Active Protein Targets (APT) from the Enhanced DUD-E repository (http://DUD-E.decoys.org) are matched against 1040 ligands using ‘Forward modeling’ Machine Learning for initial ‘Data Mining & Modeling’ (DDM) to extract PPTs and the corresponding High Affinity Ligands (HALs). K-Means Clustering (KMC) is then performed on 400 ligands matched against 29 PTs, with each cluster accommodating HALs, and the corresponding PPTs. Performance of KMC is then validated against randomly chosen head, tail, and middle Active Ligands (ALs). KMC outcomes have been validated against two other clustering methods, namely Gaussian Mixture Model (GMM) and Density Based Spatial Clustering of Applications with Noise (DBSCAN). While GMM shows similar results as with KMC, DBSCAN has failed to yield more than one cluster and handle the noise (outliers), thus affirming the choice of KMC or GMM. Databases obtained from ADFR to mine PPTs are then ranked according to the number of the corresponding HAL-PPT Combinations (HPC) inside the derived clusters, an approach called ‘Reverse Modeling’ (RM). From the set of 29 PTs studied, RM predicts high fidelity of 5 PPTs (17%) that bind with 76 out of 400 i.e., 19% ligands leading to a prediction of next generation MRSA drug candidates: PPT2 (average HPC is 41.1%) is the top choice, followed by PPT14 (average HPC 25.46%), and then PPT15 (average HPC 23.12%). This algorithm can be generically implemented irrespective of pathogenic forms and is particularly effective for sparse data

Green synthesis of nano-silver and its antibacterial activity against methicillin-resistant Staphylococcus aureus

Superbugs resistant to antimicrobials are swiftly expanding worldwide. One of these superbugs for which effective antibiotics are urgently needed is methicillin-resistant Staphylococcus aureus (MRSA). Thus, the creation of novel antimicrobial substances is necessary, one of the appealing antibacterial inorganic materials is silver nanoparticles (AgNPs) for application of treating bacterial infectious illnesses. In order to investigate novel, potent, and economically feasible therapeutic approaches, the current study presents a cost-effective and environmentally friendly technique for synthesizing AgNPs using Citrus maxima peel (CMP) extract as a reducing agent. UV–Vis Spectroscopy confirmed the formation of AgNPs in the 400–––500 nm wavelength range. The Powder X-ray diffr action (PXRD) and high-resolution transmission electron microscopy (HRTEM) results at the optimized synthesis conditions revealed highly crystalline AgNPs (face-centered cubic structure) with particles the size of 10–––20 nm. The Fourier transform infrared spectroscopy (FT-IR) revealed the presence of flavonoids, terpenoids, phenolics, and glycosides in the phytochemical compositions of the CMP extract, which can serve as reducing agents for the formation of the spherical AgNPs. Minimum inhibitory concentration (MIC) values of 8.27 µg/mL, minimum bactericidal concentration (MBC) values of 16.54 µg/mL, and an inhibition zone of 11.7 mm were indicative of the potent antibacterial activity of as-prepared AgNPs against MRSA. The findings suggest biogenic silver nanoparticles could be an effective antimicrobial agent against nosocomial infections

Wide-Band-Gap Semiconductors for Biointegrated Electronics: Recent Advances and Future Directions

Wearable and implantable bioelectronics have experienced remarkable progress over the last decades. Bioelectronic devices provide seamless integration between electronics and biological tissue, offering unique functions for healthcare applications such as real-time and online monitoring and stimulation. Organic semiconductors and silicon-based flexible electronics have been dominantly used as materials for wearable and implantable devices. However, inherent drawbacks such as low electronic mobility, particularly in organic materials, instability, and narrow band gaps mainly limit their full potential for optogenetics and implantable applications. In this context, wide-band-gap (WBG) materials with excellent electrical and mechanical properties have emerged as promising candidates for flexible electronics. With a significant piezoelectric effect, direct band gap and optical transparency, and chemical inertness, these materials are expected to have practical applications in many sectors such as energy harvesting, optoelectronics, or electronic devices, where lasting and stable operation is highly desired. Recent advances in micro/nanomachining processes and synthesis methods for WBG materials led to their possible use in soft electronics. Considering the importance of WBG materials in this fast-growing field, the present paper provides a comprehensive Review on the most common WBG materials, including zinc oxide (ZnO) for II–VI compounds, gallium nitride (GaN) for III–V compounds, and silicon carbide (SiC) for IV–IV compounds. We first discuss the fundamental physical and chemical characteristics of these materials and their advantages for biosensing applications. We then summarize the fabrication techniques of wide-band-gap semiconductors, including how these materials can be transferred from rigid to stretchable and flexible substrates. Next, we provide a snapshot of the recent development of flexible WBG materials-based wearable and implantable devices. Finally, we conclude with perspectives on future research direction

Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data

The under-representation of several ethnic groups in existing genetic databases and studies have undermined our understanding of the genetic variations and associated traits or diseases in many populations. Cost and technology limitations remain the challenges in performing large-scale genome sequencing projects in many developing countries, including Vietnam. As one of the most rapidly adopted genetic tests, non-invasive prenatal testing (NIPT) data offers an alternative untapped resource for genetic studies. Here we performed a large-scale genomic analysis of 2683 pregnant Vietnamese women using their NIPT data and identified a comprehensive set of 8,054,515 single-nucleotide polymorphisms, among which 8.2% were new to the Vietnamese population. Our study also revealed 24,487 disease-associated genetic variants and their allele frequency distribution, especially 5 pathogenic variants for prevalent genetic disorders in Vietnam. We also observed major discrepancies in the allele frequency distribution of disease-associated genetic variants between the Vietnamese and other populations, thus highlighting a need for genome-wide association studies dedicated to the Vietnamese population. The resulted database of Vietnamese genetic variants, their allele frequency distribution, and their associated diseases presents a valuable resource for future genetic studies