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Background: Cancer remains a significant global health challenge, with ongoing research focused on identifying effective therapeutic targets. Human agmatinase (AGMAT), a binuclear manganese enzyme, has been associated with cancer progression through its role in polyamine production and its involvement in the NO/MAPK/PI3K signaling pathway in lung tissue. Objective: This study aimed to identify potential inhibitors of AGMAT from a library of FDA-approved drugs using computational methods, intending to find novel therapeutic agents for cancer treatment. Methods: The three-dimensional structure of AGMAT was determined using homology modeling, with Pseudomonas guanidinobutyrase (GbuA) serving as the template due to its 74% sequence similarity to AGMAT. The model was validated using PROCHECK, Verify3D, ProSA and ERRAT software. High-throughput virtual screening was conducted on a chemical library of approximately 7922 FDA-approved drugs to identify potential AGMAT inhibitors. Molecular docking simulations assessed the binding affinities of these drugs. Results: The virtual screening identified ten lead FDA-approved molecules: Nemifitidum, Examorelin, Pralmorelin hydrochloride, Nonathymulin, Ebiratide, Lypressin, Histrelin, Agripressin, Cetrorelix and Ornipressin that exhibited significant binding affinities to AGMAT. Conclusion: The identified lead compounds represent promising candidates for further investigation as potential cancer therapeutics targeting AGMAT. These findings provide a basis for future experimental validation and the development of new drugs toward cancer treatments.

Gout is an extremely painful form of inflammatory arthritis, caused by the formation of monosodium urate (MSU) crystals in the joints. MSU crystals are one of the triggers for the activation of nucleotide-binding domain (NOD)-like receptor protein 3 (NLRP3) inflammasome (NACHT, LRR and PYD domains-containing protein), which in turn induces caspase-1 activation and a nonspecific immune responses that cause inflammation. Further structural studies and ligand designs are needed to block the interaction of NLRP3 with MSU or allow the interaction without activating caspase-1. This would facilitate the screening of new drugs for the treatment of gout. Using computational methods for homology modeling and molecular dynamics simulations, the structural model of mouse NLRP3 protein with its domains, three potential structural models were consistently constructed and tested to find the most stable structural model. Adenosine triphosphate (ATP) — an activator of NACHT (the central domain of mouse NLRP3 protein) — was docked and simulated. Ligand effects to activate as well as limit this protein were analyzed. This study provides insights to deeper understanding about gout development pathway via the NLRP3 protein.

Predicting 3D structure of protein from its amino acid sequence is one of the most important unsolved problems in biophysics and computational biology. This paper attempts to give a comprehensive introduction of the most recent effort and progress on protein structure prediction. Following the general flowchart of structure prediction, related concepts and methods are presented and discussed. Moreover, brief introductions are made to several widely-used prediction methods and the community-wide critical assessment of protein structure prediction (CASP) experiments.

Novel bioinformatic procedures and computational methods have been used to analyze, characterize and provide more detailed description of some selected fish antifreeze proteins (AFPs) retrieved from Swiss–Prot database. Analysis shows that AFPs are rich in non-polar residues and that the AFPs Q01758 and P05140 contain SS bonds. The aliphatic index computed by ExPasy's ProtParam infers that AFPs may be stable for a wide range of temperatures and the AFP P80961 is classified as an unstable protein. The very low GRAVY index of AFP P80961 infers its higher hydrosolubility. Secondary structure analysis shows that the flounder and sculpin fish AFPs are found to be of predominant ∝–helical structures and the rest of them are with mixed secondary structures. The average molecular weight of AFPs computed is 9584 Da. SOSUI server predicts one transmembrane region in P04002 (winter flounder fish) and two regions in P09031 (yellowtail flounder fish). The predicted transmembrane regions were visualized and analyzed using helical wheel plots generated by EMBOSS pepwheel tool. The residues A, L, G and N are identified as the antigenic sites by EMBOSS antigenic program. The presence of 11 Cys residues in AFPs Q01758 (rainbow smelt fish) and P05140 (sea raven fish) indicates the presence of disulfide bridges (SS bonds) in these AFPs, and it is also recognized by CYS_REC tool and well documented from the three dimensional structure using Rasmol tool.

The interaction of ladder polyethers of marine origin, like ciguatoxin 3C and brevenal, as well as hypothetic ent-brevenal, with the human voltage-gated Kv1.5 potassium ion channel is investigated in this work using homology modeling, automated docking, and energy scoring from molecular dynamics (MD) simulations. A 3D homology model of the pore region of the Kv1.5 channel, previously developed from the 2.9 Å resolution crystal structure of the mammalian Kv1.2 channel — which has a very similar pore sequence — is used here. While ciguatoxin 3C did not enter the pore, both brevenal and ent-brevenal were found into the pore, the latter one with the best score. Binding is attended by notable strain in the ligands, and the corresponding energy increase was evaluated for ent-brevenal by self consistent field (SCF) and density functional theory (DFT) procedures. Egress of ent-brevenal from the pore, as a microscopical reversal of the ingress, was investigated by a smart form of biased MD simulations. While this study indicates ample room and attractive interactions for both brevenal and its enantiomer into the pore, whether these molecules will be found to inhibit voltage-gated potassium ion currents depends upon the barriers in the real system to access the pore, with their thermodynamic and kinetic requirements.

The interaction of the K⁺-sparing agent amiloride — a synthetic chlorinated pyrimidine derivative — with the hASIC1a ion channel is investigated here along homology modeling of the pore region (using the crystal structure of the cASIC1 channel as a template and the known sequence of hASIC1a), automated docking (using the NMR solution structure of amiloride and its conjugated acid, refined by computations), and molecular dynamics simulations. This represents the first modeling and computational chemistry of the pore region of ASIC/DEG/ENaCs/FaNaCh channels. The results agree with the putative amiloride binding site for alphaENaC channel chimeras once the amiloride free base is considered, while its conjugated acid — in contrast with literature beliefs — is poorly scored on a nearby protein pocket. Different protonation conditions of the pore region are irrelevant because histidine residues are far from the binding sites. Mapping the amino acids of the homology model closest to amiloride can have heuristic value in stimulating in silico search of new pore-blocking agents, experimental studies of ASIC channels themselves, and development of code for constant-pH MD simulations.

Kynurenine aminotransferase III (KAT III) is a novel member of the kynurenine aminotransferase enzyme family. Its active site topology and structure characteristics have not been established. In this study, with extensive computational simulations, including homology modeling and molecular dynamics simulations, a 3D structure model of human KAT III dimer was created and refined. Furthermore, CDOCKER approach was employed to dock two ligands (L-methionine and L-tryptophan) into the active sites of human KAT III dimer and uncover the ligand-binding modes. The complexes were subjected to 5 ns MD simulation, and the results indicate that TYR119 and TRP13 might be the key residues as they have the large contributions to the binding affinity, which is in good agreement with the experimental results. Moreover, another two residues (ASP120 and TYR57) are also found that their strong interactions stabilize the whole system. The structural and biochemical insights obtained from the present study will be helpful for designing the specific inhibitors of human KAT III.

Through a reductive dimerization of two farnesyl diphosphate (FPP) molecules, Squalene synthase from Panax ginseng (P. ginseng) (PgSS) catalyzes the biosynthesis of squalene, a key cholesterol precutsor, and hence is an attractive site of therapeutic intervention. Thus, the 3D structure of PgSS has been firmly established by homology modeling and was used to relax by MD simulation to get the reliable structure. It is well known that Mg²⁺ plays an important role in substrate binding. Understanding how PgSS recruits the FPP substrate through Mg²⁺ is the first and foremost step toward further mechanistic investigations and the design of effective PgSS inhibitors. Quantum mechanical calculation method is used to determine the Mg²⁺ binding mode. In the first binding motif, the Mg²⁺ ion is coordinated to D77, D81, and one oxygen atom from the α- and β-phosphates of FPP. In order to determine the important residue of the substrate (FPP) binding, we dock the one FPP to the protein. Arg113 may be an important residue because they form a salt bridge with PgSS. After virtual screening technique of PgSS, a novel natural compound (8002215) has been found with the lowest affinity energy. Then we identify that His266 is the most important anchoring residue for binding with 8002215 because it has strong edge-to-face interaction with inhibitor. Leu205 and Gln206 are important residues for they make hydrogen bonds with inhibitor. Our results may be helpful for further experimental investigations.

Aspalathin and nothofagin are the major dihydrochalcones found in rooibos (Aspalathus linearis), which display anti-diabetic activities, but the mechanism is still unclear. In this paper, hSGLT2 (human sodium dependent glucose co-transporter 2), a target for diabetes mellitus, was built using homology modeling method. Molecular docking and dynamics simulations were carried out on aspalathin, nothofagin and SGLT2 complexes with dapagliflozin as positive control. The results show that both the binding energies and binding modes of aspalathin and nothofagin are similar to dapagliflozin, indicating that either component of rooibos may exhibit anti-diabetic effects through inhibiting SGLT2 receptor. However, the predicted permeability value of aspalathin and nothofagin is low, which may cause poor absorption, resulting in weak SGLT2 inhibition. Calculation results elucidate the possible inhibiting mechanism of aspalathin and nothofagin against SGLT2, and therefore enhance our understanding of anti-diabetic activities of rooibos.

In this study, we address the issue of performing meaningful pK_a calculations using homology modeled three-dimensional (3D) structures and analyze the possibility of using the calculated pK_a values to detect structural defects in the models. For this purpose, the 3D structure of each member of five large protein families of a bacterial nucleoside monophosphate kinases (NMPK) have been modeled by means of homology-based approach. Further, we performed pK_a calculations for the each model and for the template X-ray structures. Each bacterial NMPK family used in the study comprised on average 100 members providing a pool of sequences and 3D models large enough for reliable statistical analysis. It was shown that pK_a values of titratable groups, which are highly conserved within a family, tend to be conserved among the models too. We demonstrated that homology modeled structures with sequence identity larger than 35% and gap percentile smaller than 10% can be used for meaningful pK_a calculations. In addition, it was found that some highly conserved titratable groups either exhibit large pK_a fluctuations among the models or have pK_a values shifted by several pH units with respect to the pK_a calculated for the X-ray structure. We demonstrated that such case usually indicates structural errors associated with the model. Thus, we argue that pK_a calculations can be used for assessing the quality of the 3D models by monitoring fluctuations of the pK_a values for highly conserved titratable residues within large sets of homologous proteins.

Rich information on point mutation studies is scattered across heterogeneous data sources. This paper presents an automated workflow for mining mutation annotations from full-text biomedical literature using natural language processing (NLP) techniques as well as for their subsequent reuse in protein structure annotation and visualization. This system, called mSTRAP (Mutation extraction and STRucture Annotation Pipeline), is designed for both information aggregation and subsequent brokerage of the mutation annotations. It facilitates the coordination of semantically related information from a series of text mining and sequence analysis steps into a formal OWL-DL ontology. The ontology is designed to support application-specific data management of sequence, structure, and literature annotations that are populated as instances of object and data type properties. mSTRAPviz is a subsystem that facilitates the brokerage of structure information and the associated mutations for visualization. For mutated sequences without any corresponding structure available in the Protein Data Bank (PDB), an automated pipeline for homology modeling is developed to generate the theoretical model. With mSTRAP, we demonstrate a workable system that can facilitate automation of the workflow for the retrieval, extraction, processing, and visualization of mutation annotations — tasks which are well known to be tedious, time-consuming, complex, and error-prone. The ontology and visualization tool are available at .

The Vascular Endothelial Growth Factor receptors (VEGF-Rs) play a significant role in tumor development and tumor angiogenesis and are therefore interesting targets in cancer therapy. Targeting the VEGF-R is of special importance as the feed of the tumor has to be reduced. In general, this can be carried out by inhibiting the tyrosine kinase function of the VEGF-R. Nevertheless, there arise some problems with the specificity of known kinase inhibitors: they bind to the ATP-binding site and inhibit a number of kinases, moreover the so far most specific inhibitors act at least on these three major types of VEGF-Rs: Flt-1, Flk-1/KDR, Flt-4. The goal is a selective VEGF-R-2 (Flk-1/KDR) inhibitor, because this receptor triggers rather unspecific signals from VEGF-A, -C, -D and -E. Here, we describe a protocol starting from an established inhibitor (Vatalanib) with 2D-/3D-searching and property filtering of the in silico screening hits and the "negative docking approach". With this approach we were able to identify a compound, which shows a fourfold higher reduction of the proliferation rate of endothelial cells compared to the reduction effect of the lead structure.

The P0 protein is a structural glycoprotein that accounts for more than 50% of the peripheral nervous system myelin membrane protein and is associated with human Charcot-Marie-Tooth disease. The P0 glycoprotein consists of three parts: the extracellular domain, the single helix transmembrane region, and the intracellular domain. The three-dimensional atomic structure of the full sequence P0 glyprotein has not yet been solved. Using homology modeling with secondary and tertiary structure prediction, it is possible to construct in silico a three-dimensional model of this protein embedded in the lipid bilayer. Further detailed analyses of such a model allow one to distinguish theoretical autoimmune epitopes and to visualize molecular effects and chemical changes in the molecule. For example, breaking a disulfide bridge can cause the opening of the P0_Ex part of the protein, leading to a decrease in migration speed of the “opened” protein in the SDS-PAGE.