3D structure prediction of human β1-adrenergic receptor via threading-based homology modeling for implications in structure-based drug designing

Tricarboxylate Citrate Transporter of an Oleaginous Fungus Mucor circinelloides WJ11: From Function to Structure and Role in Lipid Production

The citrate transporter protein (CTP) plays an important role in citrate efflux from the mitochondrial matrix to cytosol that has great importance in oleaginous fungi. The cytoplasmic citrate produced after citrate efflux serves as the primary carbon source for the triacylglycerol and cholesterol biosynthetic pathways. Because of the CTP's importance, our laboratory has extensively studied its structure/function relationships in Mucor circinelloides to comprehend its molecular mechanism. In the present study, the tricarboxylate citrate transporter (Tct) of M. circinelloides WJ11 has been cloned, overexpressed, purified, kinetically, and structurally characterized. The Tct protein of WJ11 was expressed in Escherichia coli, isolated, and functionally reconstituted in a liposomal system for kinetic studies. Our results showed that Tct has a high affinity for citrate with Km 0.018 mM. Furthermore, the tct overexpression and knockout plasmids were created and transformed into M. circinelloides WJ11. The mitochondria of the tct-overexpressing transformant of M. circinelloides WJ11 showed a 49% increase in citrate efflux, whereas the mitochondria of the tct-knockout transformant showed a 39% decrease in citrate efflux compared to the mitochondria of wild-type WJ11. To elucidate the structure-function relationship of this biologically important transporter a 3D model of the mitochondrial Tct protein was constructed using homology modeling. The overall structure of the protein is V-shaped and its 3D structure is dimeric. The transport stability of the structure was also assessed by molecular dynamics simulation studies. The activity domain was identified to form hydrogen bond and stacking interaction with citrate and malate upon docking. Tricarboxylate citrate transporter has shown high binding energy of −4.87 kcal/mol to citric acid, while −3.80 kcal/mol to malic acid. This is the first report of unraveling the structural characteristics of WJ11 mitochondrial Tct protein and understanding the approach of the transporting toward its substrate. In conclusion, the present findings support our efforts to combine functional and structural data to better understand the Tct of M. circinelloides at the molecular level and its role in lipid accumulation.

Comparative analyses of site-directed mutagenesis of human melatonin MTNR1A and MTNR1B receptors using a yeast fluorescent biosensor

Melatonin is an indoleamine neurohormone made by the pineal gland. Its receptors, MTNR1A and MTNR1B, are members of the G-protein-coupled receptor (GPCR) family and are involved in sleep, circadian rhythm, and mood disorders, and in the inhibition of cancer growth. These receptors, therefore, represent significant molecular targets for insomnia, circadian sleep disorders, and cancer. The yeast Saccharomyces cerevisiae is an attractive host for assaying agonistic activity for human GPCR. We previously constructed a GPCR-based biosensor employing a high-sensitivity yeast strain that incorporated both a chimeric yeast-human Gα protein and a bright fluorescent reporter gene (ZsGreen). Similar approaches have been used for simple and convenient measurements of various GPCR activities. In the current study, we constructed a fluorescence-based yeast biosensor for monitoring the signaling activation of human melatonin receptors. We used this system to analyze point mutations, including previously unreported mutations of the consensus sequences of MTNR1A and MTNR1B melatonin receptors and compared their effects. Most mutations in the consensus sequences significantly affected the signaling capacities of both receptors, but several mutations showed differences between these subtype receptors. Thus, this yeast biosensor holds promise for revealing the functions of melatonin receptors.

Recent advance on PTP1B inhibitors and their biomedical applications

Protein Tyrosine Phosphatase 1B (PTP1B), as one of the most important members in PTP superfamily, plays a vital role in conducting various cellular functions. So far, PTP1B has been reported to be involved in the development of many diseases including obesity, diabetes, cancers and cardiovascular diseases. Development of potent and specific PTP1B inhibitors and studies on the structure-activity relationship (SAR) between their chemical structures and their biological activity have drawn increasing attention as they could not only modulate the PTP1B functions inside the cells but also provide useful lead compounds for the treatment of various PTP1B-associated diseases. To this end, we herein summarized the recent developments of PTP1B inhibitors, and different kinds of high-throughput screening strategies for the identification of potential PTP1B inhibitors as well as their potential biomedical applications, and we also provided some perspectives in the concluding remarks in this work.

Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets

The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures of some proteins (the so-called undruggable targets) are known, their targeted drugs are still absent. As increasing crystal/cryogenic electron microscopy structures are deposited in Protein Data Bank, it is much more possible to discover the targeted drugs. Moreover, it is also highly probable to turn previous undruggable targets into druggable ones when we identify their hidden allosteric sites. In this review, we focus on the currently available advanced methods for the discovery of novel compounds targeting proteins without 3D structure and how to turn undruggable targets into druggable ones.

In Silico Modeling of Crimean Congo Hemorrhagic Fever Virus Glycoprotein-N and Screening of Anti Viral Hits by Virtual Screening

Crimean-Congo hemorrhagic fever (CCHF) is a widespread zoonotic viral disease, caused by a tick-born virus Crimean-Congo hemorrhagic fever virus (CCHFV). This disease is endemic in Middle East, Asia, Africa and South-Eastern Europe with the mortality rate of 5–30%. CCHFV genome is composed of three segments: large, medium and small segments. M segment encodes a polyprotein (glycoprotein) so called glycoprotein N (Gn) which is considered as a potential druggable target for the effective therapy of CCHF. The complete structure of Gn is still not characterized. The aim of the current study is to predict the complete three-dimensional (3D-) structure of CCHFV Gn protein via threading-based modeling and investigate the residues crucial for binding with CCHFV envelop. The developed model displayed excellent stereo-chemical and geometrical properties. Subsequently structure based virtual screening (SBVS) was applied to discover novel inhibitors of Gn protein. A library of > 1300 anti-virals was selected from PubChem database and directed to the predicted binding site of Gn. The SBVS results led to the identification of thirty-seven compounds that inhibit the protein in computational analysis. Those 37 hits were subject to pharmacokinetic profiling which demonstrated that 30/37 compound possess safer pharmacokinetic properties. Thus, by specifically targeting Gn, less toxic and more potent inhibitors of CCHFV were identified in silico.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify novel fungicides.