Fazlin Mohd Fauzi

Diversity Selection of Compounds Based on ‘Protein Affinity Fingerprints’ Improves Sampling of Bioactive Chemical Space

Diversity selection is a frequently applied strategy for assembling high‐throughput screening libraries, making the assumption that a diverse compound set increases chances of finding bioactive molecules. Based on previous work on experimental ‘affinity fingerprints’, in this study, a novel diversity selection method is benchmarked that utilizes predicted bioactivity profiles as descriptors. Compounds were selected based on their predicted activity against half of the targets (training set), and diversity was assessed based on coverage of the remaining (test set) targets. Simultaneously, fingerprint‐based diversity selection was performed. An original version of the method exhibited on average 5% and an improved version on average 10% increase in target space coverage compared with the fingerprint‐based methods. As a typical case, bioactivity‐based selection of 231 compounds (2%) from a particular data set (‘Cutoff‐40’) resulted in 47.0% and 50.1% coverage, while fingerprint‐based selection only achieved 38.4% target coverage for the same subset size. In conclusion, the novel bioactivity‐based selection method outperformed the fingerprint‐based method in sampling bioactive chemical space on the data sets considered. The structures retrieved were structurally more acceptable to medicinal chemists while at the same time being more lipophilic, hence bioactivity‐based diversity selection of compounds would best be combined with physicochemical property filters in practice.

Understanding the mode-of-action of Cassia auriculata via in silico and in vivo studies towards validating it as a long term therapy for type II diabetes.

ETHNOPHARMACOLOGICAL RELEVANCE Cassia auriculata (CA) is used as an antidiabetic therapy in Ayurvedic and Siddha practice. This study aimed to understand the mode-of-action of CA via combined cheminformatics and in vivo biological analysis. In particular, the effect of 10 polyphenolic constituents of CA in modulating insulin and immunoprotective pathways were studied. MATERIALS AND METHODS In silico target prediction was first employed to predict the probability of the polyphenols interacting with key protein targets related to insulin signalling, based on a model trained on known bioactivity data and chemical similarity considerations. Next, CA was investigated in in vivo studies where induced type 2 diabetic rats were treated with CA for 28 days and the expression levels of genes regulating insulin signalling pathway, glucose transporters of hepatic (GLUT2) and muscular (GLUT4) tissue, insulin receptor substrate (IRS), phosphorylated insulin receptor (AKT), gluconeogenesis (G6PC and PCK-1), along with inflammatory mediators genes (NF-κB, IL-6, IFN-γ and TNF-α) and peroxisome proliferators-activated receptor gamma (PPAR-γ) were determined by qPCR. RESULTS In silico analysis shows that several of the top 20 enriched targets predicted for the constituents of CA are involved in insulin signalling pathways e.g. PTPN1, PCK-α, AKT2, PI3K-γ. Some of the predictions were supported by scientific literature such as the prediction of PI3K for epigallocatechin gallate. Based on the in silico and in vivo findings, we hypothesized that CA may enhance glucose uptake and glucose transporter expressions via the IRS signalling pathway. This is based on AKT2 and PI3K-γ being listed in the top 20 enriched targets. In vivo analysis shows significant increase in the expression of IRS, AKT, GLUT2 and GLUT4. CA may also affect the PPAR-γ signalling pathway. This is based on the CA-treated groups showing significant activation of PPAR-γ in the liver compared to control. PPAR-γ was predicted by the in silico target prediction with high normalisation rate although it was not in the top 20 most enriched targets. CA may also be involved in the gluconeogenesis and glycogenolysis in the liver based on the downregulation of G6PC and PCK-1 genes seen in CA-treated groups. In addition, CA-treated groups also showed decreased cholesterol, triglyceride, glucose, CRP and Hb1Ac levels, and increased insulin and C-peptide levels. These findings demonstrate the insulin secretagogue and sensitizer effect of CA. CONCLUSION Based on both an in silico and in vivo analysis, we propose here that CA mediates glucose/lipid metabolism via the PI3K signalling pathway, and influence AKT thereby causing insulin secretion and insulin sensitivity in peripheral tissues. CA enhances glucose uptake and expression of glucose transporters in particular via the upregulation of GLUT2 and GLUT4. Thus, based on its ability to modulate immunometabolic pathways, CA appears as an attractive long term therapy for T2DM even at relatively low doses.

Global Mapping of Traditional Chinese Medicine into Bioactivity Space and Pathways Annotation Improves Mechanistic Understanding and Discovers Relationships between Therapeutic Action (Sub)classes

Traditional Chinese medicine (TCM) still needs more scientific rationale to be proven for it to be accepted further in the West. We are now in the position to propose computational hypotheses for the mode-of-actions (MOAs) of 45 TCM therapeutic action (sub)classes from in silico target prediction algorithms, whose target was later annotated with Kyoto Encyclopedia of Genes and Genomes pathway, and to discover the relationship between them by generating a hierarchical clustering. The results of 10,749 TCM compounds showed 183 enriched targets and 99 enriched pathways from Estimation Score ≤ 0 and ≥ 5% of compounds/targets in a (sub)class. The MOA of a (sub)class was established from supporting literature. Overall, the most frequent top three enriched targets/pathways were immune-related targets such as tyrosine-protein phosphatase nonreceptor type 2 (PTPN2) and digestive system such as mineral absorption. We found two major protein families, G-protein coupled receptor (GPCR), and protein kinase family contributed to the diversity of the bioactivity space, while digestive system was consistently annotated pathway motif, which agreed with the important treatment principle of TCM, “the foundation of acquired constitution” that includes spleen and stomach. In short, the TCM (sub)classes, in many cases share similar targets/pathways despite having different indications.

Linking Ayurveda and Western medicine by integrative analysis.

In this article, we discuss our recent work in elucidating the mode-of-action of compounds used in traditional medicine including Ayurvedic medicine. Using computational (‘in silico’) approach, we predict potential targets for Ayurvedic anti-cancer compounds, obtained from the Indian Plant Anticancer Database given its chemical structure. In our analysis, we observed that: (i) the targets predicted can be connected to cancer pathogenesis i.e. steroid-5-alpha reductase 1 and 2 and estrogen receptor-β, and (ii) predominantly hormone-dependent cancer targets were predicted for the anti-cancer compounds. Through the use of our in silico target prediction, we conclude that understanding how traditional medicine such as Ayurveda work through linking with the ‘western’ understanding of chemistry and protein targets can be a fruitful avenue in addition to bridging the gap between the two different schools of thinking. Given that compounds used in Ayurveda have been tested and used for thousands of years (although not in the same approach as Western medicine), they can potentially be developed into potential new drugs. Hence, to further advance the case of Ayurvedic medicine, we put forward some suggestions namely: (a) employing and integrating novel analytical methods given the advancements of ‘omics’ and (b) sharing experimental data and clinical results on studies done on Ayurvedic compounds in an easy and accessible way.

Computer-aided (in silico) approaches in the mode-of-action analysis and safety assessment of Ostarine and 4-methylamphetamine

This study exemplifies computer‐aided (in silico) approaches in assessing the risks of new psychoactive substances emerging in the European Union. In this work, we (i) consider the potential of Ostarine exhibiting psychoactivity and (ii) anticipate potential activities and toxicities of 4‐methylamphetamine.

Animal Model of Gestational Diabetes Mellitus with Pathophysiological Resemblance to the Human Condition Induced by Multiple Factors (Nutritional, Pharmacological, and Stress) in Rats

This study attempts to develop an experimental gestational diabetes mellitus (GDM) animal model in female Sprague-Dawley rats. Rats were fed with high fat sucrose diet, impregnated, and induced with Streptozotocin and Nicotinamide on gestational day 0 (D0). Sleeping patterns of the rats were also manipulated to induce stress, a lifestyle factor that contributes to GDM. Rats were tested for glycemic parameters (glucose, C-peptide, and insulin), lipid profiles (total cholesterol, triglycerides, HDL, and LDL), genes affecting insulin signaling (IRS-2, AKT-1, and PCK-1), glucose transporters (GLUT-2 and GLUT-4), proinflammatory cytokines (IL-6, TNF-α), and antioxidants (SOD, CAT, and GPX) on D6 and D21. GDM rats showed possible insulin resistance as evidenced by high expression of proinflammatory cytokines, PCK-1 and CRP. Furthermore, low levels of IRS-2 and AKT-1 genes and downregulation of GLUT-4 from the initial to final phases indicate possible defect of insulin signaling. GDM rats also showed an impairment of antioxidant status and a hyperlipidemic state. Additionally, GDM rats exhibited significantly higher body weight and blood glucose and lower plasma insulin level and C-peptide than control. Based on the findings outlined, the current GDM animal model closely replicates the disease state in human and can serve as a reference for future investigations.

Antibacterial and Antibiofilm Activities of Nonpolar Extracts of Allium stipitatum Regel. against Multidrug Resistant Bacteria

The present study assessed the in vitro antibacterial and antibiofilm potential of hexane (ASHE) and dichloromethane (ASDE) extracts of Allium stipitatum (Persian shallot) against planktonic cells and biofilm structures of clinically significant antibiotic resistant pathogens, with a special emphasis on methicillin-sensitive Staphylococcus aureus (MSSA), methicillin-resistant S. aureus (MRSA), and emerging pathogens, Acinetobacter baumannii and Stenotrophomonas maltophilia. Antibacterial activities were determined through disk diffusion, minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), time-kill kinetics, and electron microscopy. Antibiofilm activity was assessed by XTT [2,3-bis(2-methoxy-4-nitro-5-sulfo-phenyl)-2H-tetrazolium-5-carboxanilide] reduction assay and by confocal laser scanning microscopy (CLSM). The zone of inhibition ranged from 13 to 33 mm, while the MICs and MBCs ranged from 16 to 1024 μg mL−1. Both ASHE and ASDE completely eradicated overnight cultures of the test microorganisms, including antibiotic resistant strains. Time-kill studies showed that the extracts were strongly bactericidal against planktonic cultures of S. aureus, MRSA, Acinetobacter baumannii, and S. maltophilia as early as 4 hours postinoculation (hpi). ASHE and ASDE were shown to inhibit preformed biofilms of the four biofilm phenotypes tested. Our results demonstrate the potential therapeutic application of ASHE and ASDE to inhibit the growth of gram-positive and gram-negative biofilms of clinical significance and warrant further investigation of the potential of A. stipitatum bulbs against biofilm-related drug resistance.

Whole-Exome Sequencing of ETV6/RUNX1 in Four Childhood Acute Lymphoblastic Leukaemia Cases

Background: ETV6/RUNX1 gene fusion is the most frequently seen chromosomal abnormality in childhood acute lymphobastic leukamia (ALL). However, additional genetic changes are known to be required for the development of this type of leukaemia. Therefore, we here aimed to assess the somatic mutational profile of four ALL cases carrying the ETV6/RUNX1 fusion gene using whole-exome sequencing. Methods: DNA was isolated from bone marrow samples using a QIAmp DNA Blood Mini kit and subsequently sequenced using the Illumina MiSeq system. Results: We identified 12,960 to17,601 mutations in each sample, with a total of 16,466 somatic mutations in total. Some 15,533 variants were single nucleotide polymorphisms (SNPs), 129 were substitutions, 415 were insertions and 389 were deletions. When taking into account the coding region and protein impact, 1,875 variants were synonymous and 1,956 were non-synonymous SNPs. Among non-synonymous SNPs, 1,862 were missense, 13 nonsense, 35 frameshifts, 11 nonstop, 3 misstart, 15 splices disrupt and 17 in-frame indels. A total of 86 variants were located in leukaemia-related genes of which 32 variants were located in the coding regions of GLI2, SP140, GATA2, SMAD5, KMT2C, CDH17, CDX2, FLT3, PML and MOV10L1. Conclusions: Detection and identification of secondary genetic alterations are important in identifying new therapeutic targets and developing rationally designed treatment regimens with less toxicity in ALL patients.