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The study aims to classify the eyes with proliferative diabetic retinopathy (PDR) and non-proliferative diabetic retinopathy (NPDR) based on the optical coherence tomography angiography (OCTA) vascular density maps using a supervised machine learning algorithm.OCTA vascular density maps (at superficial capillary plexus (SCP), deep capillary plexus (DCP), and total retina (R) levels) of 148 eyes from 78 patients with diabetic retinopathy (45 PDR and 103 NPDR) was used to classify the images to NPDR and PDR groups based on a supervised machine learning algorithm known as the support vector machine (SVM) classifier optimized by a genetic evolutionary algorithm.The implemented algorithm in three different models reached up to 85% accuracy in classifying PDR and NPDR in all three levels of vascular density maps. The deep retinal layer vascular density map demonstrated the best performance with a 90% accuracy in discriminating between PDR and NPDR.The current study on a limited number of patients with diabetic retinopathy demonstrated that a supervised machine learning-based method known as SVM can be used to differentiate PDR and NPDR patients using OCTA vascular density maps.

Introduction: Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 293,241 deaths worldwide since its emergence in late 2019 (updated May 13, 2020). COVID-19 is caused by a novel emerged coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. Methods: In this study, we have targeted spike (S) glycoprotein, as an important surface antigen to identify its B- and T-cell immunodominant regions. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover the most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). Results: The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531–N711; T717–C877; and V883–E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. Conclusion: These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in preclinical studies.

Background: The ecto-nucleoside triphosphate diphosphohydrolases (NTPDases) terminate nucleotide signaling via the hydrolysis of extracellular nucleoside-5'-triphosphate and nucleoside- 5'-diphosphate, to nucleoside-5'-monophosphate and composed of eight Ca2+/Mg2+ dependent ectonucleotidases (NTPDase1-8). Extracellular nucleotides are involved in a variety of physiological mechanisms. However, they are rapidly inactivated by ectonucleotidases that are involved in the sequential removal of phosphate group from nucleotides with the release of inorganic phosphate and their respective nucleoside. Ectonucleoside triphosphate diphosphohydrolases (NTPDases) represent the key enzymes responsible for nucleotides hydrolysis and their overexpression has been related to certain pathological conditions. Therefore, the inhibitors of NTPDases are of particular importance in order to investigate their potential to treat various diseases e.g., cancer, ischemia and other disorders of the cardiovascular and immune system. Methods: Keeping in view the importance of NTPDase inhibitors, a series of thiadiazolopyrimidones were evaluated for their potential inhibitory activity towards NTPDases by the malachite green assay. Results: The results suggested that some of the compounds were found as non-selective inhibitors of isozyme of NTPDases, however, most of the compounds act as potent and selective inhibitors. In case of substituted amino derivatives (4c-m), the compounds 4m (IC50 = 1.13 ± 0.09 μM) and 4g (IC50 = 1.72 ± 0.08 μM) were found to be the most potent inhibitors of h-NTPDase1 and 2, respectively. Whereas, compound 4d showed the best inhibitory potential for both h-NTPDase3 (IC50 = 1.25 ± 0.06 μM) and h-NTPDase8 (0.21 ± 0.02 μM). Among 5a-t derivatives, compounds 5e (IC50 = 2.52 ± 0.15 μM), 5p (IC50 = 3.17 ± 0.05 μM), 5n (IC50 = 1.22 ± 0.06 μM) and 5b (IC50 = 0.35 ± 0.001 μM) were found to be the most potent inhibitors of h-NTPDase1, 2, 3 and 8, respectively. Interestingly, the inhibitory concentration values of above-mentioned inhibitors were several folds greater than suramin, a reference control. In order to determine the binding interactions, molecular docking studies of the most potent inhibitors were conducted into the homology models of NTPDases and the putative binding analysis further confirmed that selective and potent compounds bind deep inside the active pocket of the respective enzymes. Conclusions: The docking analysis proposed that the inhibitory activity correlates with the hydrogen bonds inside the binding pocket. Thus, these derivatives are of interest and may further be investigated for their importance in medicinal chemistry.

Fibroblast growth factor 10 functions as a paracrine mesenchymal molecule to initiate signalling pathways regarding to cellular development and health. However, the low thermal stability restricts it's functionality in the human body and the shelf-life of FGF10-based formulations. The current study aimed to employ rational design and bioinformatics approaches to identify some point mutations which may improve the thermal stability of FGF10. Bioinformatics analyses resulted in N105D, C106F, K144R, K153M and I156R as the potential stability conferring mutations. The identified mutants were subjected to MD simulation indicating that all mutations are both structurally and energetically favoured. Finally, the effects of the identified mutations on receptor binding of FGF10 were predicted and the results showed that K144R and K153M mutations may increase the binding affinity relative to the wild type. The findings of the current study propose potentially improved FGF10 analogues for further experimental investigations.

A convenient catalyst-free synthesis of hitherto unknown pentacyclic benzosultam-annulated thiopyranoindole derivatives is reported which proceeds via domino Knoevenagel / intramolecular hetero-Diels–Alder reactions of (E)-N-alkyl-2-aryl-N-(2-formylphenyl)ethene-1-sulfonamides with indoline-2-thiones in water. The products were obtained regioselectively in high yields.

Malaria is one of the life-threatening parasitic diseases that is endemic in tropical areas. The increased prevalence of malaria due to drug resistance leads to a high incidence of mortality. Drug discovery based on natural products and secondary metabolites is considered as alternative approaches for antimalarial therapy. Herbal medicines have advantages over modern medicines, including fewer side effects, cost-effectiveness, and affordability encouraging the herbal-based drug discovery. Several naturally occurring, semisynthetic, and synthetic antimalarial medications are on the market. For example, chloroquine is a synthetic medication for antimalarial therapy derived from quinine. Moreover, artemisinin, and its derivative, artesunate with sesquiterpene lactone backbone, is an antimalarial agent originated from Artemisia annua L. A. annua traditionally has been used to detoxify blood and eliminate fever in China. Although the artemisinin-based combination therapy against malaria has shown exceptional responses, the limited medicinal options demand novel therapeutics. Furthermore, drug resistance is the cause in most cases, and new medications are proposed to overcome the resistance. In addition to conventional therapeutics, this review covers some important genera in this area, including Artemisia, Cinchona, Cryptolepis, and Tabebuia, whose antimalarial activities are finely verified.

Protein-peptide interactions have attracted the attention of many drug discovery scientists due to their possible druggability features on most key biological activities such as regulating disease-related signaling pathways and enhancing the immune system's responses. Different studies have utilized some protein-peptide-specific docking algorithms/methods to predict protein-peptide interactions. However, the existing algorithms/methods suffer from two serious limitations which make them unsuitable for protein-peptide docking problems. First, it seems that the prevalent approaches require to be modified and remodeled for weighting the unbounded forces between a protein and a peptide. Second, they do not employ state-of-the-art search algorithms for detecting the 3D pose of a peptide relative to a protein. To address these restrictions, the present study aims to introduce a novel multi-objective algorithm, which first generates some potential 3D poses of a peptide, and then, improves them through its operators. The candidate solutions are further evaluated using Multi-Objective Pareto Front (MOPF) optimization concepts. To this end, van der Waals, electrostatic, solvation, and hydrogen bond energies between the atoms of a protein and designated peptide are computed. To evaluate the algorithm, it is first applied to the LEADS-PEP dataset containing 53 protein-peptide complexes with up to 53 rotatable branches/bonds and then compared with three popular/efficient algorithms. The obtained results indicate that the MOPF-based approaches which reduce the backbone RMSD between the original and predicted states, achieve significantly better results in terms of the success rate in predicting the near-native conditions. Besides, a comparison between the different types of search algorithms reveals that efficient ones like the multi-objective Trader/differential evolution algorithm can predict protein-peptide interactions better than the popular algorithms such as the multi-objective genetic/particle swarm optimization algorithms.

A regio- and diastereoselective synthesis of 2,3-dihydro-10b′H-spiro[indeno[1,2-b]quinoxaline-11,1′-pyrrolo[2,1-a]isoquinoline]-2′,3′-diylbis(phenylmethanone) derivatives containing four contiguous chiral stereocenters was achieved through 1,3-dipolar cycloaddition of isoquinolinium N-ylides in a one-pot three-component reaction. The desired products were obtained in short reaction times and in moderate to high yields (up to 92%) under relatively mild reaction conditions. The structure and relative stereochemistry of the desired product was confirmed by X-ray diffraction analysis.

An efficient Lewis acid mediated domino Knoevenagel/hetero Diels–Alder (DKHDA) reaction of pyrazolone derivatives with N-acrylated anthranilic aldehydes was developed, which afforded functionalized tetracyclic tetrahydropyrazolo[4',3':5,6]pyrano[3,4-c]quinolones. The products were formed in good yields and with excellent regio- and stereoselectivity in favor of the cis-configured isomer.

Hitherto unknown thiadiazolo[2′,3′:2,3]imidazo[4,5-b]indoles were synthesized for the first time by base-mediated cyclocondensation, bromination, and subsequent cyclization by two-fold Buchwald–Hartwig reactions.

Modified Fe3O4 magnetic nanoparticles (magnetic nanocarrier) technology have found the proper place in separation and purification techniques, such as protein and enzyme purification, mostly due to its easy and fast operational procedure by using an external permanent magnet. Herein, Fe3O4 magnetic nanoparticles were prepared, and surface modification was performed with vanadate and phosphate salts to yield four various model of magnetic nanocarriers. Affinity ligands which are used for immobilization on the nanocarriers leading to the development of appropriative nanocarriers for the affinity separation of alkaline phosphatase from the bovine milk. The findings showed that the use of sodium hexametaphosphate affinity ligand attached to the carrier with an 18-atom linker leads to better separation of alkaline phosphatase from the bovine milk with 14.1-fold purification efficiency. All results confirmed that our designed nanocarriers can purify alkaline phosphatase using a fast and low-cost approach.

Objective Osteoarthritis causes severe pain and disability in joints, one of the most prevalent involved joints is the knee joint. There are several therapeutics ways to control pain and disability, but almost none of them are definite treatment. In this article, we tried to reveal the effect of weight loss on improving symptoms of knee osteoarthritis as an effective and permanent therapeutic approach. Methods We chose 62 patients with grade 1–2 (mild to moderate) knee osteoarthritis and divided them equally into case and control groups. Patients should not had used NSAIDs at least for 6 months before study initiation. Symptoms severity was measured by WOMAC and VAS questionnaires before and after 3 months follow up. Weight and BMI were recorded too. Case group was suggested to have weight loss diet of less fat and carbohydrates and control group did not have any limitation. Results Comparison of variables’ average of case and control groups was not logistically meaningful at the initiation and after the end of the study. But there was a meaningful correlation between variables’ changes and lifestyle change in both groups, especially in WOMAC and VAS scores. All variables in case group had statistically meaningful differences between their amounts at the beginning and after the end of the study, on the contrary of the control group. Conclusion In the comparison of our study with similar studies in the world. We deduced that weight loss can improve symptoms of knee osteoarthritis even in short time weight loss diet (3 months). Trial registration number ZUMS.REC.1394.94.

Rocks are formed from particles and the interaction between those particles controls the behaviour of a rock’s mechanical properties. Since it is very important to conduct extensive studies about the relationship between the micro-parameters and macro-parameters of rock, this paper investigates the effects of some micro-parameters on strength properties and the behaviour of cracks in rock. This is carried out by using numerical simulation of an extensive series of Uniaxial Compressive Strength (UCS) and Brazilian Tensile Strength (BTS) tests. The micro-parameters included the particles’ contact modulus, the contact stiff ness ratio, bond cohesion, bond tensile strength, the friction coefficient and the friction angle, and the mechanical properties of chromite rock have been considered as base values of the investigation. Based on the obtained results, it was found that the most important micro-parameters on the behaviour of rock in the compressive state are bond cohesion, bond tensile strength, and the friction coefficient. Also, the bond tensile strength showed the largest effect under tensile conditions. The micro-parameter of bond tensile strength increased the rock tensile strength (up to 5 times), minimized destructive cracks and increased the corresponding strain (almost 2.5 times) during critical stress., Svaka je stijena stvorena od čestica čijim se međudjelovanjem određuju njezina mehanička svojstva. Budući da je vrlo važno provesti opsežne studije o povezanosti mikroparametara i makroparametara stijene, u ovome su radu istraživani učinci nekih mikroparametara na svojstva čvrstoće i ponašanje pukotina stijene numeričkim simulacijama jednoosne tlačne čvrstoće (UCS) i brazilske vlačne čvrstoće (BTS). Ispitivani mikroparametri uključivali su kontakt čestica, omjer kontaktne krutosti, koheziju veze, vlačnu čvrstoću, koeficijent trenja i kut trenja, a mehanička svojstva stijene bogate kromitom bile su osnovne vrijednosti ispitivanih mikroparametara. Utvrđeno je kako su najvažniji mikroparametri na ponašanje stijene kod tlačenja kohezija veze, vlačna čvrstoća veze i koeficijent trenja. Također, vlačna čvrstoća ima najveći učinak u vlačnim uvjetima. Ovaj mikroparametar povećava vlačnu čvrstoću (do 5 puta), minimalizira destruktivne pukotine i povećava odgovarajuće naprezanje (gotovo 2,5 puta) pri kritičnome naprezanju.

Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 253,381 deaths worldwide since its emergence in late 2019 (updated May 6th, 2020). COVID-19 is caused by a novel emerged coronavirus named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. In this study, we have targeted spike (S) glycoprotein, as an important surface antigen of SARS-CoV-2, to identify its immunodominant B- and T-cell epitopes. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531–N711; T717–C877; and V883–E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in the animal studies.

Purpose: Receptor tyrosine kinase (RTK) inhibitors are widely used pharmaceuticals in cancer therapy. Fibroblast growth factor receptors (FGFRs) are members of RTK superfamily which are highly expressed on the surface of carcinoma associate fibroblasts (CAFs). The involvement of FGFRs in different types of cancer makes them promising target in cancer therapy and hence, the identification of novel FGFR inhibitors is of great interest. In the current study we aimed to develop an alignment independent three dimensional quantitative structure-activity relationship (3D-QSAR) model for a set of 26 FGFR2 kinase inhibitors allowing the prediction of activity and identification of important structural features for these inhibitors. Methods: Pentacle software was used to calculate grid independent descriptors (GRIND) for the active conformers generated by docking followed by the selection of significant variables using fractional factorial design (FFD). The partial least squares (PLS) model generated based on the remaining descriptors was assessed by internal and external validation methods. Results: Six variables were identified as the most important probes-interacting descriptors with high impact on the biological activity of the compounds. Internal and external validations were lead to good statistical parameters (r2 values of 0.93 and 0.665, respectively). Conclusion: The results showed that the model has good predictive power and may be used for designing novel FGFR2 inhibitors.

Various novel polycyclic thiopyranoindol annulated [3,4- c ]quinolone derivatives were synthesized via domino Knoevenagel-hetero-Diels–Alder reactions of indoline-2-thions and novel N -acrylated anthranilaldehydes in refluxing ethanol as a solvent in the presence of 20 mol% ZnBr 2 as a Lewis acid catalyst. All reactions proceed with high yields with excellent regio- and stereoselectivity.

Monoclonal antibodies and vaccines have widely been studied for the immunotherapy of cancer, while their large size appears to limit their functionality in solid tumors, in large part due to unique properties of tumor microenvironment such as high pressure of tumor interstitial fluid. To tackle such limitations, smaller formats of antibodies have been developed, including antigen-binding fragments, single-chain variable fragments, single variable domain of camelid antibody (so-called nanobody (Nb) or VHH). Of these, Nbs offer great immunotherapy potentials because of their advantageous physicochemical and pharmacological features, including small size, high stability, and excellent tissue penetration. Besides, the therapeutic impacts of Nbs can be improved by their modifications and functionalizations (e.g., PEGylation and conjugation to the Fc domain, peptide tags, drugs, toxins, aptamers, and radionuclides). This review aims to provide comprehensive insights into key signaling networks of colorectal cancer and discuss Nb-based precision immunotherapy of colorectal cancer.

Type 2 diabetes mellitus (T2DM) is one of the most widely prevalent metabolic disorders with no cure to date thus remains the most challenging task in the current drug discovery. Therefore, the only strategy to control diabetes prevalence is to develop novel efficacious therapeutics. Dipeptidyl Peptidase 4 (DPP-4) inhibitors are currently used as anti-diabetic drugs for the inhibition of incretins. This study aims to construct the chemical feature based on pharmacophore models for dipeptidyl peptidase IV. The structure-based pharmacophore modeling has been employed to evaluate new inhibitors of DPP-4. A four-featured pharmacophore model was developed from crystal structure of DPP-4 enzyme with 4-(2-aminoethyl) benzenesulfonyl fluoride in its active site via pharmacophore constructing tool of Molecular Operating Environment (MOE) consisting F1 Hyd (hydrophobic region), F2 Hyd|Cat|Don (hydrophobic cationic and donor region), F3 Acc (acceptor region) and F4 Hyd (hydrophobic region). The generated pharmacophore model was used for virtual screening of in-house compound library (the available compounds which were used for initial screening to get the few compounds for the current studies). The resultant selected compounds, after virtual screening were further validated using in vitro assay. Furthermore, structure-activity relationship was carried out for the compounds possessing significant inhibition potential after docking studies. The binding free energy of analogs was evaluated via molecular mechanics generalized Born surface area (MM-GBSA) and Poisson-Boltzmann surface area (MM-PBSA) methods using AMBER 16 as a molecular dynamics (MD) simulation package. Based on potential findings, we report that selected candidates are more likely to be used as DPP-4 inhibitors or as starting leads for the development of novel and potent DPP-4 inhibitors.

Sphingosine 1-phosphate type 1 (S1P1) receptors are expressed on lymphocytes and regulate immune cells trafficking. Sphingosine 1-phosphate and its analogues cause internalization and degradation of S1P1 receptors, preventing the auto reactivity of immune cells in the target tissues. It has been shown that S1P1 receptor agonists such as fingolimod can be suitable candidates for treatment of autoimmune diseases. The current study aimed to generate GRIND-based 3D-QSAR predictive models for agonistic activities of 2-imino-thiazolidin-4-one derivatives on S1P1 to be used in virtual screening of chemical libraries. The developed model for the S1P1 receptor agonists showed appropriate power of predictivity in internal (r2acc 0.93 and SDEC 0.18) and external (r2 0.75 and MAE (95% data), 0.28) validations. The generated model revealed the importance of variables DRY-N1 and DRY-O in the potency and selectivity of these compounds towards S1P1 receptor. To propose potential chemical entities with S1P1 agonistic activity, PubChem chemicals database was searched and the selected compounds were virtually tested for S1P1 receptor agonistic activity using the generated models, which resulted in four potential compounds with high potency and selectivity towards S1P1 receptor. Moreover, the affinities of the identified compounds towards S1P1 receptor were evaluated using molecular dynamics simulations. The results indicated that the binding energies of the compounds were in the range of −39.31 to −46.18 and −3.20 to −9.75 kcal mol−1, calculated by MM-GBSA and MM-PBSA algorithms, respectively. The findings in the current work may be useful for the identification of potent and selective S1P1 receptor agonists with potential use in diseases such as multiple sclerosis., Graphical abstract Image 1, Highlights • A set of S1P1 and S1P3 receptor agonists was used to develop 3D-QSAR predictive models. • The predictivity of the generated models were validated using external and internal validation methods. • PubChem chemicals database was searched for identification of selective S1P1 receptor agonists. • Molecular dynamics simulations were used to calculate ligands binding energies to S1P1 receptor.

Transportation of the nutrients and other substances from the blood to the brain is selectively controlled by the brain capillary endothelial cells that form a restrictive barrier, so-called blood-brain barrier (BBB). Currently, there is no unimpeachable approach to overcome the BBB obstructiveness because the existing options are either invasive or ineffective.This review delineates the biological impacts of BBB on brain drug delivery and targeting. The nanoscaled multifunctional shuttles armed with the targeting entities (e.g., antibodies and peptides) are discussed. Important insights are remarked into the combinatorial screening methodologies used for the identification of de novo peptides capable of crossing BBB and targeting the brain.Depending on the physicochemical properties of small molecules and macromolecules, they may cross the BBB and get into the brain either through passive diffusion or active/facilitated transportation and transcytosis in a very selectively controlled manner. Phage-derived shuttle peptides can specifically be selected against BBB endocytic machinery and used in engineering novel peptide-drug conjugates (PDCs). Nanoscaled multitargeting delivery systems encompassing PDCs can overcome the BBB obstructiveness and deliver drugs specifically to diseased cells in the brain with trivial side effects.

A tumor is defined as a group of cancer cells and 'surrounding' stromal bio-entities. Alongside the extracellular matrix (ECM) in the tumor microenvironment (TME), the stromal cells play key roles in cancer affliction and progression. Carcinoma-associated fibroblasts (CAFs) in the area of the tumor, whether activated or not, dictate the future of tumor cells. The CAFs and corresponding secreted growth factors (GFs), which mediate the crosstalk within the TME, can be targeted in therapies directed at the stroma. The impact of the fibroblast growth factor-fibroblast growth factor receptor (FGF-FGFR) signaling pathway in different kinds of tumors has been explored. Several tyrosine kinase inhibitors (TKIs), monoclonal antibodies (mAbs), and ligand traps targeting the formation of FGF-FGFR complex are in preclinical or early development phases. Moreover, there are numerous studies in the literature reporting the application of phage display technology for the development of peptides and proteins capable of functioning as FGF mimetics or traps, which are able to modulate FGF-related signaling pathways. In this review, prominent research in relation to phage display-assisted ligand identification for the FGF/FGFR system is discussed.

Over expression of nucleotide pyrophosphatase (NPPs) activity is associated with chondrocalcinosis, osteoarthritis, type 2 diabetes, neurodegenerative diseases, allergies and cancer metastasis. The potential of NPPs inhibitors as therapeutic agents, and the scarceness of their structure–activity relationship, encouraged us to develop new NPP inhibitors. Specifically, 2-bromo-7-methyl-5-oxo-5H-1,3,4-thiadiazolopyrimidine and its corresponding 6-fluoro derivatives were synthesized via a Suzuki–Miyaura reaction. The cross-coupling reaction with different arylboronic acids gave desired coupling products in good to excellent yields and showed wide functional group tolerance. Furthermore, all compounds were investigated for their potential to inhibit two families of ecto-nucleotidases, i.e. nucleoside triphosphate diphosphohydrolases (NTPDase) and NPPs. Interestingly, our compounds were identified as selective inhibitors of NPPs. Among derivatives 5a–5i, compound 5i (IC50 ± SEM = 0.39 ± 0.01 μM) was found to be the most potent inhibitor of h-NPP1 and compound 5h (IC50 ± SEM = 1.02 ± 0.05 μM) was found to be the most potent inhibitor of h-NPP3. Similarly, for fluorinated thiadiazolopyrimidones, derivative 6e (IC50 ± SEM = 0.31 ± 0.01 μM) exhibited the best inhibition of NPP1 and it was found that this compound exhibited ≈28 fold improvement in inhibitory potential as compared with the reference control i.e. Suramin (IC50 ± SEM = 8.67 ± 1.3 μM). Moreover, homology modelling and molecular docking studies of both inhibitors were carried out to suggest the putative binding mode of inhibitors with the respective enzyme i.e. h-NPP1 and h-NPP3.

Alkaline Phosphatases (APs) play a key role in maintaining a ratio of phosphate to inorganic pyrophosphate (Pi/PPi) and thus regulate extracellular matrix calcification during bone formation and growth. Among different isozymes of AP, aberrant increase in the level of tissue non-specific alkaline phosphatase (TNAP) is strongly associated with vascular calcification and end-stage renal diseases. In this context, we synthesized a novel series of fluorinated pyrimidone derivatives, i.e., 2-bromo-7-trifluoromethyl-5-oxo-5H-1,3,4-thiadiazolepyrimidones. The bromine functionality was further used for derivatisation by nucleophilic aromatic substitution using amines as nucleophiles as well as by Palladium catalysed Suzuki-Miyaura reactions. The synthesized derivatives were found potent but non-selective inhibitors of both isozymes of AP. Arylated thiadiazolopyrimidones exhibited stronger inhibitory activities than 2-amino-thiadiazolopyrimidones. The binding modes and possible interactions of the most active inhibitor within the active site of the enzyme were observed by molecular docking studies.

Fibroblast growth factor 7 (FGF7) is a member of the fibroblast growth factor (FGF) family of proteins. FGF7 is of stromal origin and produces a paracrine effect on epithelial cells. In the current investigation, we aimed to identify new single-domain antibodies (sdAbs) against FGF7 using phage display technology. The vector harboring the codon-optimized DNA sequence for FGF7 protein was transformed into Escherichia coli BL21 (DE3) pLysS, and then the protein was expressed at the optimized condition. Enzyme-linked immunosorbent assay, circular dichroism spectropolarimetry, and in vitro scratch assay experiments were used to confirm the proper folding and functionality of the purified FGF7 protein. The purity of the produced FGF7 was 92%, with production yield of 3.5 mg/L of culture. Panning against the purified FGF7 was performed, and the identified single-domain antibodies showed significant affinity. Further investigation on one of the selected sdAb displaying phage clones showed concentration-dependent binding to FGF7. The selected sdAb can be used for developing novel tumor-suppressing agents where inhibition of FGF7 is required.

Sphingosine 1-phosphate type 1 (S1P1) receptors are expressed on lymphocytes and regulate immune cells trafficking. Sphingosine 1-phosphate and its analogues cause internalization and degradation of S1P1 receptors, preventing the auto reactivity of immune cells in the target tissues. It has been shown that S1P1 receptor agonists such as fingolimod can be suitable candidates for treatment of autoimmune diseases. The current study aimed to generate GRIND-based 3D-QSAR predictive models for agonistic activities of 2-imino-thiazolidin-4-one derivatives on S1P1 to be used in virtual screening of chemical libraries. The developed model for the S1P1 receptor agonists showed appropriate power of predictivity in internal (r2acc 0.93 and SDEC 0.18) and external (r2 0.75 and MAE (95% data), 0.28) validations. The generated model revealed the importance of variables DRY-N1 and DRY-O in the potency and selectivity of these compounds towards S1P1 receptor. To propose potential chemical entities with S1P1 agonistic activity, PubChem chemicals database was searched and the selected compounds were virtually tested for S1P1 receptor agonistic activity using the generated models, which resulted in four potential compounds with high potency and selectivity towards S1P1 receptor. Moreover, the affinities of the identified compounds towards S1P1 receptor were evaluated using molecular dynamics simulations. The results indicated that the binding energies of the compounds were in the range of −39.31 to −46.18 and −3.20 to −9.75 kcal mol−1, calculated by MM-GBSA and MM-PBSA algorithms, respectively. The findings in the current work may be useful for the identification of potent and selective S1P1 receptor agonists with potential use in diseases such as multiple sclerosis.