Humans have relied on nature throughout their ages to cater for their basic needs including medicines to cure a wide spectrum of diseases. Plants have formed the basis for sophisticated systems of traditional medicines. For therapeutic agents many of the presently known lead compounds are natural products or their derivatives. Ethnomedicinal studies play a vital role to discover new drugs from indigenous medicinal plants. Green pharmaceuticals are getting popularity and extraordinary importance because vast opportunities for new drug discoveries are provided by the unmatched availability of chemical diversity and natural products either as pure compounds or as homogenous plant extracts. Therefore, in recent years the demand for herbal medicines and several natural products from a variety of plant species is consistently increasing. In spite of being an agricultural country and having different ecological regions, the medicinal plants of Pakistan have not been explored for their secondary metabolites which are responsible for treating different diseases. Although, huge importance of different extracts of medicinal plants from Pakistan have been reported for their different activities such as antimicrobial, anti-cancerouse, antiviral and antioxidant but complete biochemical profiling of these medicinal plants is lacking. LC-MS and GC-MS techniques have been applied in the field of drug discovery from medicinal plants but in Pakistan its success rate is very low in the subject of biochemical profiling. Therefore, such techniques should be used in Pakistan to explore active constituents from medicinal plants which could be used as medicines in future.

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Secreted frizzled-related protein 4 (SFRP4) is a member of secreted protein family with sequence similarity to frizzled receptors of wingless-related integration site (Wnt) signaling pathways. These proteins control diverse functions from embryonic development to adults in many organisms including humans. Initially, SFRPs were recognized as antagonists of Wnt signaling and supposed to interact with Wnts. Further research demonstrated their interactions to frizzled receptors and a functional diversity was related to these proteins, Wnt signaling potentiation in addition to modulation. SFRP4 is the largest member of SFRP family and is implicated in many diseases including obesity, type 2 diabetes (T2D), and cancer. SFRP4 acts as a biomarker for T2D and was expressed several years before clinical diagnosis of disease. This review mainly focusses on the role of SFRP4 in obesity and how it can lead to β-cell failure and ultimately to T2D. The role of SFRP4 in adipose tissues causing increased production of adipokines lead to the oxidative stress in pancreas that particularly have low amount of antioxidant enzymes in pancreatic β-cells leading to failure in exocytosis of insulin containing granules causing T2D. Obesityinduced inflammation is a principal factor in pathogenesis of insulin resistance as well as metabolic syndrome. Pro-inflammatory cytokines have potential to cause insulin resistance in skeletal muscles, adipose tissue, and liver via inhibition of insulin signal transduction. Secretion of SFRP4 is mediated by interleukin 1-β (IL1-β). This review highlights the molecular mechanisms by which SFRP4 leads to T2D.Understanding of molecular mechanism and targeting SFRP4 could help to eradicate or reduce chances of developing T2D. K E Y W O R D S adipokines, obesity, SFRP4, type-2 diabetes, Wnt signaling 1 | INTRODUCTION Cellular activities and functions are coordinated through processing of biological information and communication between cells via different signaling molecules. These signaling molecules regulate gene expression in nucleus and in Abbreviations: C/EBP, CAAT/enhancer-binding protein; CRD, cystein rich domain; DKK, dickkopfs; FZD, frizzled receptors; IL, interleukin; LRP, low density lipoprotein receptor related protein; MCP1, monocyte chemotactic protein-1; MG, methylglyoxal; NLD, netrin-like domain; PKB, protein kinase B; Pparγ, peroxisome proliferator-activated receptor γ; SFRP4, secreted frizzled-related protein 4; T2D, type 2 diabetes; WIF, Wnt inhibitory factors; Wnt, wingless-related integration site.

The novel coronavirus disease 2019 (COVID-19) was firstly reported from Wuhan city of China and found as a highly contagious, transmittable and pathogenic viral infection. The World Health Organization declared COVID-19 as a pandemic since its emergence from China. The RNA-dependent RNA polymerase (nsp-12) is a complex with nsp-7 and nsp-8 cofactors and is a major constituent of viral replication and RNA synthesis machinery. In the current study, the RdRp of the virus was selected as a receptor protein for computational drug discovery. Computational homology modelling was done in order to find the hidden secondary structures and structural assessment of the viral protein to target them via antiviral drugs. The study was based on molecular docking of different phytochemicals to check their potentials against viral replicative proteins. Out of 200 ligands used in this study from different plants, the best ten were selected based on drug discovery parameters such as S-score, ligand interactions, hydrophobic interactions and druglikeness. The ten best selected ligands were found to be verbenalin, epigallocatechin, swertisin, nobiletin, pinoresinol, caftaric acid, hesperetin, islandicin, neochlorogenic acid and sesamin that exploit the potency as antagonists of viral protein. Among binding interactions of all ligands, Arg339 centred as the main interacting residue among almost all the ligands. Till now, many antiviral agents have shown potency in only mild cases of SARS-CoV-2, but no effective drug has been found for critical pulmonary cases. In clinical trials, many broad-spectrum antiviral agents have been still in trial periods of testing against SARS-CoV-2. Till date, no effective drug or vaccine has been validated with significant efficacy and potency against the SARS-CoV-2; therefore, there is an urgent need to design effective vaccine against nCoV-19 infection.

Diabetes mellitus termed as metabolic disorder is a collection of interlinked diseases and mainly body’s inability to manage glucose level which leads to cardiovascular diseases, renal failure, neurological disorders, and many others. The drugs contemporarily used for diabetes have many inevitable side effects, and many of them have become less responsive to this multifactorial disorder. Momordica charantia commonly known as bitter gourd has many bioactive compounds with antidiabetic properties. The current study was designed to use computational methods to discover the best antidiabetic peptides devised from hypoglycemic polypeptide-P of M. charantia. The binding affinity and interaction patterns of peptides were evaluated against four receptor proteins (i.e., as agonists of insulin receptor and inhibitors of sodium-glucose cotransporter 1, dipeptidyl peptidase-IV, and glucose transporter 2) using molecular docking approach. A total of thirty-seven peptides were docked against these receptors. Out of which, top five peptides against each receptor were shortlisted based on their S-scores and binding affinities. Finally, the eight best ligands (i.e., LIVA, TSEP, EKAI, LKHA, EALF, VAEK, DFGAS, and EPGGGG) were selected as these ligands strictly followed Lipinski’s rule of five and exhibited good ADMET profiling. One peptide EPGGGG showed activity towards insulin and SGLT1 receptor proteins. The top complex for both these targets was subjected to 50 ns of molecular dynamics simulations and MM-GBSA binding energy test that concluded both complexes as highly stable, and the intermolecular interactions were dominated by van der Waals and electrostatic energies. Overall, the selected ligands strongly fulfilled the drug-like evaluation criterion and proved to have good antidiabetic properties.