SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming ...process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.
Twenty structures including 19 SARS-CoV-2 targets and one human target were built by homology modeling. Library of ZINC drug database, natural products, 78 anti-viral drugs were screened against these targets plus human ACE2. This study provides drug repositioning candidates and targets for further in vitro and in vivo studies of SARS-CoV-2. Display omitted
In December 2019, COVID-19 epidemic was described in Wuhan, China, and the infection has spread widely affecting hundreds of thousands. Herein, an effort was made to identify commercially available ...drugs in order to repurpose them against coronavirus by the means of structure-based virtual screening. In addition, ZINC15 library was used to identify novel leads against main proteases. Human TMPRSS2 3D structure was first generated using homology modeling approach. Our molecular docking study showed four potential inhibitors against Mpro enzyme, two available drugs (Talampicillin and Lurasidone) and two novel drug-like compounds (ZINC000000702323 and ZINC000012481889). Moreover, four promising inhibitors were identified against TMPRSS2; Rubitecan and Loprazolam drugs, and compounds ZINC000015988935 and ZINC000103558522. ADMET profile showed that the hits from our study are safe and drug-like compounds. Furthermore, molecular dynamic (MD) simulation and binding free energy calculation using the MM-PBSA method was performed to calculate the interaction energy of the top-ranked drugs.
Communicated by Ramaswamy H. Sarma
Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab‐based ...open‐source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin‐labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small‐angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples.
Predicting RNA three-dimensional structures from sequence could accelerate understanding of the growing number of RNA molecules being discovered across biology. Rosetta's Fragment Assembly of RNA ...with Full-Atom Refinement (FARFAR) has shown promise in community-wide blind RNA-Puzzle trials, but lack of a systematic and automated benchmark has left unclear what limits FARFAR performance. Here, we benchmark FARFAR2, an algorithm integrating RNA-Puzzle-inspired innovations with updated fragment libraries and helix modeling. In 16 of 21 RNA-Puzzles revisited without experimental data or expert intervention, FARFAR2 recovers native-like structures more accurate than models submitted during the RNA-Puzzles trials. Remaining bottlenecks include conformational sampling for >80-nucleotide problems and scoring function limitations more generally. Supporting these conclusions, preregistered blind models for adenovirus VA-I RNA and five riboswitch complexes predicted native-like folds with 3- to 14 Å root-mean-square deviation accuracies. We present a FARFAR2 webserver and three large model archives (FARFAR2-Classics, FARFAR2-Motifs, and FARFAR2-Puzzles) to guide future applications and advances.
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•A new RNA fragment assembly method, FARFAR2, uses RNA-Puzzle-inspired innovations•FARFAR2 recovers native-like structures on six new blind challenges•A FARFAR2 webserver is available at https://rosie.rosettacommons.org/farfar2•A dataset of millions of FARFAR2-predicted models is available for further study
Watkins et al. benchmark FARFAR2, an algorithm for RNA structure prediction that consolidates a decade of ad hoc strategies. FARFAR2 recovers native-like structures more accurately than original challenge submissions for 16 of 21 RNA-Puzzles and achieves native-like preregistered blind predictions for adenovirus VA-I RNA and five riboswitch complexes.
Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of ...the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.
The need for the development of new fast computational 3D structure methods is to close the widening gap between the number of sequences available and experimentally determined 3D structures. Recent applications of homology modeling in drug discovery are summarized. The variety of the homology modeling tools needs a careful inspection to make a good choice. Knowledge and experience about the steps of the modeling process are crucial in getting high‐accuracy modeling. The accuracy determines the functionality of the model.
The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One ...extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising
techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.
Adipose tissue is the primary site of storage for excess energy as triglyceride and it helps in synthesizing a number of biologically active compounds that regulate metabolic homeostasis. Consumption ...of high dietary fat increases stored fat mass and is considered as a main risk factor for metabolic diseases. Beta-sitosterol (β-sitosterol) is a plant sterol. It has the similar chemical structure like cholesterol. Clinical and experimental studies have shown that β-sitosterol has anti-diabetic, hypolipidemic, anti-cancer, anti-arthritic, and hepatoprotective role. However, effect of β-sitosterol on insulin signaling molecules and glucose oxidation has not been explored. Hence in the present study we aimed to discover the protective role of β-sitosterol on the expression of insulin signaling molecules in the adipose tissue of high-fat diet and sucrose-induced type-2 diabetic experimental rats. Effect dose of β-sitosterol (20 mg/kg b.wt, orally for 30 days) was given to high fat diet and sucrose-induced type-2 diabetic rats to study its anti-diabetic activity. Results of the study showed that the treatment with β-sitosterol to diabetes-induced rats normalized the altered levels of blood glucose, serum insulin and testosterone, lipid profile, oxidative stress markers, antioxidant enzymes, insulin receptor (IR), and glucose transporter 4 (GLUT4) proteins. Our present findings indicate that β-sitosterol improves glycemic control through activation of IR and GLUT4 in the adipose tissue of high fat and sucrose-induced type-2 diabetic rats. Insilico analysis also coincides with invivo results. Hence it is very clear that β-sitosterol can act as potent antidiabetic agent.
Zinc (Zn) is an essential micronutrient for plants and humans. Nearly 50% of the agriculture soils of world are Zn-deficient. The low availability of Zn reduces the yield and quality of the crops. ...The zinc-regulated, iron-regulated transporter-like proteins (ZIP) family and iron-regulated transporters (IRTs) are involved in cellular uptake of Zn, its intracellular trafficking and detoxification in plants. In addition to Zn, ZIP family transporters also transport other divalent metal cations (such as Cd2+, Fe2+, and Cu2+). ZIP transporters play a crucial role in biofortification of grains with Zn. Only a very limited information is available on structural features and mechanism of Zn transport of plant ZIP family transporters. In this article, we present a detailed account on structure, function, regulations and phylogenetic relationships of plant ZIP transporters. We give an insight to structure of plant ZIPs through homology modeling and multiple sequence alignment with Bordetella bronchiseptica ZIP (BbZIP) protein whose crystal structure has been solved recently. We also provide details on ZIP transporter genes identified and characterized in rice and other plants till date. Functional characterization of plant ZIP transporters will help for the better crop yield and human health in future.
To improve the availability of three-dimensional (3D) structures of HLA molecules, we created the pHLA3D database. In its first version, we modeled and published 106 3D structures of HLA class I ...molecules from the HLA-A, HLA-B, and HLA-C loci. This paper presents an update of this database, providing more 127 3D structures of HLA class II molecules (41 DR, 42 DQ, and 44 DP), predicted via homology modeling with MODELLER and SWISS-MODEL. These new 3D structures of HLA class II molecules are now freely available at pHLA3D (www.phla3d.com.br) for immunologists and other researchers working with HLA molecules.
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