Protein Homology Modeling Research Articles

The anti-fouling activity of solvothermally synthesized Nb2O5-coated Fe ship strip on optimal interactions at the targeted interfaces of barnacle attachments - An Insilico study

Abstract Fouling is a major issue occurring in water-going vessels, such as ships that cause increased surface roughness and drag resistance. The fouling organisms produce extracellular polymeric substances (EPS), which negatively impact water-going vessels. The settlement-inducing protein complex (SIPC) is a contact pheromone that promotes the gregarious settling of barnacle larvae (cyprids). The SIPC can be found in both adult barnacle cuticles and cyprids as transient adhesive secretions (footprints). The presence of SIPC in the footprints plays a critical role during the initial adhesion, which facilitates further settlement. The adsorption of of SIPC on Iron/Fe ship strip(FSS) surface was often found to be irreversible even after physical treatements. For the antifouling studies, Nb2O5 coated FSS were constructed and simulated to analyze the interaction of barnacles Aacp20K protein. For simulation studies, the homology model of barnacles Aacp20K protein is fabricated using the SWISS automated comparative modeling platform. The result of homology model showed a good 3D secondary structure of Aacp20K protein, especially 7q1y template protein. Adsorption location analysis results illustrate that the surface of the FSS coated with Nb2O5 film disfavour the binding of SIPC inhibiting the binding of barnacle cuticles and cyprids. For validating the simulation results, Nb2O5 nanostructure film was synthesized using a solvothermal process and characterized using XRD,SEM and EDS. Furthermore, the wetting behaviour was studied experimentally. The simulations and experimental results indicate Nb2O5-coated FSS as potent anti-fouling surfaces.

Drug repositioning identifies potential autophagy inhibitors for the LIR motif p62/SQSTM1 protein

Autophagy is a critical cellular process for degrading damaged organelles and proteins under stressful conditions and has casually been shown to contribute to tumor survival and drug resistance. Sequestosome-1 (SQSTM1/p62) is an autophagy receptor that interacts with its binding partners via the LC3-interacting region (LIR). The p62 protein has been a highly researched target for its critical role in selective autophagy. In this study, we aimed to identify FDA-approved drugs that bind to the LIR motif of p62 and inhibit its LIR function, which could be useful targets for modulating autophagy. To this, the homology model of the p62 protein was predicted using biological data, and docking analysis was performed using Molegro Virtual Docker and PyRx softwares. We further assessed the toxicity profile of the drugs using the ProTox-II server and performed dynamics simulations on the effective candidate drugs identified. The results revealed that the kanamycin, velpatasvir, verteporfin, and temoporfin significantly decreased the binding of LIR to the p62 protein. Finally, we experimentally confirmed that Kanamycin can inhibit autophagy-associated acidic vesicular formation in breast cancer MCF-7 and MDA-MB 231 cells. These repositioned drugs may represent novel autophagy modulators in clinical management, warranting further investigation.

Characterization of the immunodominant regions of Senecavirus A-VP1 structural protein via ELISA epitope mapping

Senecavirus A (SVA) is an RNA virus in the family Picornaviridae that has been detected in swine-production systems and is associated with vesicular disease and neonate mortality. The viral capsid is composed of four structural proteins: VP1–VP4. Although the VP1 protein has been reported to be the most immunogenic protein in vivo, no information on the immunodominant regions of the SVA polyprotein is available. The objective of this study was to identify the immunodominant regions of SVA polyprotein using an enzyme-linked immunosorbent assay (ELISA) epitope-mapping approach. The binding effect of SVA polyclonal antibody (SVA-pAb), SVA-VP1 monoclonal antibodies (SVA-mAb), and SVA-positive sera from clinically affected animals were characterized using a set of 18 overlapping SVA VP1-derived peptides by indirect and blocking ELISAs. All VP1 peptides yielded significant signal against SVA-pAb and SVA-VP1-mAb upon indirect ELISA. One peptide (aa 1–20) showed significantly high optical density on SVA recombinant VP1 protein (rVP1) and whole-virus-based indirect ELISAs. The blocking ELISA results demonstrated that peptides spanning aa 165–185 and 225–245 had a 50 % or greater inhibitory effect on SVA-pAb, while six groups of overlapping peptides spanning aa 1–35, 45–80, 90–140, 150–170, 195–230, and 240–264 and two groups of overlapping peptides spanning aa 1–50 and 60–264 showed a 50 % inhibitory effect or greater on swine VP1-mAb and SVA-seropositive swine serum, respectively, against SVA rVP1. Three-dimensional protein homology modeling showed that the peptides binding SVA-pAb are located on the outer surface of the viral capsid, while SVA mAbs and swine-positive sere can bind to epitopes located in both the inner and outer surfaces of the capsid. These linear epitopes showed differential binding and inhibitory activity on mAb and pAb; however, further studies will be necessary to evaluate whether they can act as decoy or neutralizing epitopes. Because mAb antibodies demonstrated a high binding affinity for this set of peptides, this information could lay the foundation for generating and screening specific antibodies for therapeutic potential.

Molecular study of a case with variant of RHCE*ce allele in haplotype dce resulting in weakened e antigen

To explore the Rh genotype for a female with RhD(-) blood type and its molecular basis. A 26-year-old female who had attended the outpatient clinic of the First Affiliated Hospital of Zhengzhou University in August 2019 was selected as the study subject. Peripheral blood samples were collected from the proband and her parents for Rh phenotyping with gel card method. PCR-sequence-based typing (PCR-SBT) and DNA sequencing were used to determine the RHD zygosity and Rh genotype of the proband and her parents. Homology modeling of Rh proteins was performed with bioinformatic software, and protein structural alterations caused by the variant was simulated by molecular dynamics. Serological tests showed that the proband and her father both had weakened e antigen of the Rh phenotype. PCR-SBT and DNA sequencing showed that the genotypes of the proband and her parents were dce/dCE, dce/DcE and dCE/DcE, respectively. And the genotypes of the RHD and RHCE of the proband were RHD*01N.01/RHD*01N.16, RHCE*01.01/RHCE*04, respectively. Protein simulation and molecular dynamics analysis revealed that the ce_16C variant resulted from RHCE*ce (c.48G>C) may alter the structure of intracellular and extracellular loops, mainly affecting the mobility of extracellular loops 2, 6 and intracellular loops 3, 4. Variant of the RHCE*ce allele c.48G>C probably underlay the weakened e antigen in this proband.

Genomic analysis of secondary metabolite biosynthesis gene clusters and structural characterization of terpene synthase and cytochrome P450 enzymes in Zingiber officinale Roscoe

This study uses bioinformatics approaches to elucidate the genetic basis of secondary metabolite biosynthesis in Zingiber officinale (Z. officinale). To this end, it identifies 44 secondary metabolite biosynthetic gene clusters and maps onto individual chromosomes, with chromosomes 1A and 8A exhibiting higher concentrations. Here, protein homology modeling provided insights into the structural characteristics of terpene synthases and Cytochrome P450 enzymes, shedding light on their potential roles in stress response and secondary metabolite production. Moreover, the identification of enzymes, such as (-)-kolavenyl diphosphate synthase TPS28 and cytochrome P450 93A3-like, opens up new possibilities for investigating the intricate pathways involved in terpene diversity and stress response mechanisms within Z. officinale. This study highlights the importance of understanding the molecular mechanisms underlying plant-derived bioactive compounds for pharmaceutical applications.

Engineering erucic acid biosynthesis in camelina (Camelina sativa) via FAE1 gene cloning and antisense technology.

Oil seeds now make up the world's second-largest food source after cereals. In recent years, the medicinal- oil plant Camelina sativa has attracted much attention for its high levels of unsaturated fatty acids and low levels of saturated fatty acids as well as its resistanceto abiotic stresses. Improvement of oil quality is considered an important trait in this plant. Erucic acid is one of the fatty acids affecting the quality of camelina oil. Altering the fatty acid composition in camelina oil through genetic manipulation requires the identification, isolation, and cloning of genes involved in fatty acid biosynthesis. The Fatty Acid Elongase 1 (FAE1) gene encodes the enzyme β-ketoacyl CoA synthase (KCS), a crucial enzyme in the biosynthesis of erucic acid. In this study, the isolation and cloning of the FAE1 gene from Camelina sativa were conducted to construct an antisense structure. The molecular homology modeling of DFAE1 proteins using the SWISS-MODEL server on ExPASy led to the generation of the 3D structures of FAE1 and DFAE1 proteins. The GMQE values of 0.44 for FAE1 and 0.08 for DFAE1 suggest high accuracy in the structural estimation of these genes. The fragments were isolated from the DNA source of the genomic Soheil cultivar with an erucic acid content of about 3% (in matured seeds) using PCR. After cloning the FAE1 gene into the Bluescript II SK+ vector and sequencing, the resulting fragments were utilized to construct the antisense structure in the pBI121 plant expression vector. The approved antisense structure was introduced into the Camelina plant using the Agrobacterium-mediated method, with optimization of tissue culture and gene transfer conditions. This approach holds potential to advance our knowledge of fat biosynthesis, leading to potential improvements in oil quality in Camelina sativa.

UPC2 mutations and development of azole resistance in Candida albicans hospital isolates from Lebanon

ObjectivesThis study evaluated the role of Upc2 in the development of azole resistance in Candida albicans isolates from Lebanese hospitalized patients and determined a correlation between resistance and virulence. MethodsThe UPC2 gene which codes for an ergosterol biosynthesis regulator was sequenced and analysed in two azole-resistant and one azole-susceptible C. albicans isolates. An amino acid substitution screening was carried out on Upc2 with a focus on its ligand binding domain (LBD) known to interact with ergosterol. Then, Upc2 protein secondary structure prediction and homology modelling were conducted, followed by total plasma membrane ergosterol and cell wall chitin quantifications. For virulence, mouse models of systemic infection were generated and an agar adhesion and invasion test was performed. ResultsAzole-resistant isolates harboured novel amino acid substitutions in the LBD of Upc2 and changes in protein secondary structures were observed. In addition, these isolates exhibited a significant increase in plasma membrane ergosterol content. Resistance and virulence were inversely correlated while increased cell wall chitin concentration does not seem to be linked to resistance since even though we observed an increase in chitin concentration, it was not statistically significant. ConclusionsThe azole-resistant C. albicans isolates harboured novel amino acid substitutions in the LBD of Upc2 which are speculated to induce an increase in plasma membrane ergosterol content, preventing the binding of azoles to their target, resulting in resistance.

In silico characterization, homology modeling and structure-based functional annotation of Nile tilapia (Oreochromis niloticus) HSP70 and HSC70 proteins

In silico characterization, homology modeling and structure-based functional annotation of Nile tilapia (Oreochromis niloticus) HSP70 and HSC70 proteins

Protein Homology Modeling in the Low Sequence Similarity Regime

Predicting the 3-D structure of a protein from its sequence based on a template protein structure is still one of the most exact modeling techniques present today. However, template-based modeling is heavily dependent on the selection of a single template structure and the sequence alignment between target and template. Mainly when the target and template sequence identity is low, the error from the alignment introduces larger errors to the model structure. An iterative method to correct such alignment mistakes is used in this study with a benchmark set from CASP in the extremely low sequence-identity regime. This is a protocol developed and tested before and it evaluates the alignment quality by building rough 3-D models for each alignment. Then by using a genetic algorithm it iteratively creates a new set of alignments. Since the method evaluates models, not sequence alignments, structural features are automatically incorporated into the alignment protocol. In the current study, models from structural alignment have been built by Modeller program to show the maximum possible quality of the model that can be obtained from that template structure with the iterative modeling protocol. Then the results and correctly aligned segments from the iterative modeling protocol are analyzed. Finally, it has been shown that if a good local fragment assessment scoring function is developed, the correctly aligned segments exist in the pool of alignments created by the protocol. Thus, the improvement of modeling in the low sequence identity regime is conceivable.

Cyp51A mutations, protein modeling, and efflux pump gene expression reveals multifactorial complexity towards understanding Aspergillus section Nigri azole resistance mechanism

Black Aspergillus species are the most common etiological agents of otomycosis, and pulmonary aspergillosis. However, limited data is available on their antifungal susceptibility profiles and associated resistance mechanisms. Here, we determined the azole susceptibility profiles of black Aspergillus species isolated from the Indian environment and explored the potential resistance mechanisms through cyp51A gene sequencing, protein homology modeling, and expression analysis of selected genes cyp51A, cyp51B, mdr1, and mfs based on their role in imparting resistance against antifungal drugs. In this study, we have isolated a total of 161 black aspergilli isolates from 174 agricultural soil samples. Isolates had variable resistance towards medical azoles; approximately 11.80%, 3.10%, and 1.24% of isolates were resistant to itraconazole (ITC), posaconazole (POS), and voriconazole (VRC), respectively. Further, cyp51A sequence analysis showed that non-synonymous mutations were present in 20 azole-resistant Aspergillus section Nigri and 10 susceptible isolates. However, Cyp51A homology modeling indicated insignificant protein structural variations because of these mutations. Most of the isolates showed the overexpression of mdr1, and mfs genes. Hence, the study concluded that azole-resistance in section Nigri cannot be attributed exclusively to the cyp51A gene mutation or its overexpression. However, overexpression of mdr1 and mfs genes may have a potential role in drug resistance.

A Tool to Teach Evolution of Protein Sequences and Structures

Computer modeling and protein structure visualization tools are effective and engaging ways of presenting various molecular biology concepts to high school and college students. Here, we describe a series of activities and exercises that use online bioinformatics databases and programs to search for and obtain protein sequence and structure data and use it to build homology models of proteins. Exercises in homology modeling can serve the pedagogical purpose of introducing and illustrating the concept of homology within gene and protein families, which results in conservation of the 3D structures of proteins and allows us to predict structures when experimental data are not available.

In silico evaluation of outer membrane protein S2 as a suitable vaccine candidate against Edwardsiella tarda infection of fish

AbstractObjectiveEdwardsiella tarda, the agent responsible for edwardsiellosis, is one of the primary emerging pathogens in fish aquaculture. The disease leads to significant economic loss for the farmers. Development of effective vaccines can minimize the disease burden.MethodsThe types of vaccinations that are currently at the center of the most significant research are subunit vaccines. Outer membrane proteins, which are a component of the bacteria, are very well known to be effective at stimulating immune responses in the host. In this study, the gene encoding for outer membrane protein S2 (OmpS2) of E. tarda was identified, cloned, and sequenced, followed by in silico analysis.ResultThe structure and subcellular localization of the protein were first confirmed. Homology modeling of the whole protein was performed, and the protein was checked for its eligibility as a vaccine candidate. This was followed by identifying antigenic sites, B‐cell epitopes, and cytotoxic T‐lymphocyte epitopes on OmpS2. We obtained a few distinct vaccine peptides from OmpS2. The complete genome of E. tarda was subjected to genome analysis to identify potential epitopes that would bind to the fish major histocompatibility complex molecule and elicit both humoral and cell‐mediated immune responses.ConclusionThis study provides valuable insights for consideration of OmpS2 as a potential vaccine candidate against E. tarda infection.

In silico identification of quorum sensing inhibitors against LasR protein in a clinical isolate of multidrug resistant Pseudomonas aeruginosa DMC-27b

Background: Pseudomonas aeruginosa is an opportunistic pathogen that uses quorum-sensing (QS) and biofilm formation to subvert antibiotic therapy. Antibiotic resistance has led to a demand for alternative methods of treatment, and destabilizing the LasR-OdDHL binding with inhibitors offers a potential solution. Methods: This study aimed to construct a homology model of the LasR protein using the genetic sequence of the P. aeruginosa DMC-27b strain (GenBank: SMRY00000000.2). Molecular docking, molecular mechanics-based binding free energy calculation, and pharmacokinetic analysis were performed on 1900 3D structures collected from synthetic and natural compound databases to identify three potential lead molecules. These compounds were evaluated using ADMET (absorption, distribution, metabolism, excretion, toxicity) analysis, and molecular dynamics protocols were used to refine the results. Results: The three lead compounds showed higher binding capability with the LasR receptor than the native ligand and passed the ADMET evaluation stage. In total, 44 properties remained within the range of 95% of known drugs, indicating their potential efficacy as drugs against P. aeruginosa and other bacteria that use a similar QS system. Conclusions: This study provides insights into potential drug designing and development against clinical isolates of emerging P. aeruginosa strains and other bacteria that use a similar QS system.

In silico studies on Epicoccum spp. Secondary metabolites as potential drugs for mucormycosis

Mucormycosis is a rare and severe form of fungal infection caused by some fungal species belonged to mucormycetes that mainly infects skin but also eyes and other organs of the human body. The COVID-19 pandemic has demonstrated the rise in mucormycosis cases due to usage of industrial grade oxygen and overuse of steroids particularly in developing nations, where the pandemic has stressed the medical system to its limit. The major aim of this study was to screen potential antifungal compounds produced by Epicoccum spp. against target enzyme lanosterol 1,4-alpha demethylase of Rhizopus arrhizus var. delemar (strain RA 99–880 / ATCC MYA-4621 / FGSC 9543 / NRRL 43880), to evaluate potential drug candidates using in silico approach, compounds that may be explored further for the treatment of mucormycosis. Sequence of enzyme was retrieved from the UniProtKB database and ligands from PubChem database. 3D structure was obtained using protein homology modelling (SWISS-MODEL server). The target enzyme was prepared along with ligands using ADT software and then subjected to molecular docking using Autodock Vina. The results and protein-target interactions were studied using the BIOVIA Discovery studio. After virtual screening of secondary metabolites produced by Epicoccum spp. and after comparing them with the results of control drugs, the compound curvularin specifically showed potential interactions with amino acid residues of target enzymes. It is also exclusively binding to the iron atom of the hemoglobin (HEME) group with binding affinity of −12.3 kcal/mol, where the hemoglobin is the main target of current existing drugs used for treating patients. The stability of molecular complexes can be measured through molecular dynamic simulation and root mean square fluctuation (RMSF) values. In this study, stable complexes were formed with curvularin and rostratin A having the highest RMSF values of 4.3 Å and 4.5 Å, respectively. Lower RMSF values indicate stability, while higher values indicate flexibility. The ADMET score gave an outlook about the absorption, distribution, metabolism, excretion and toxicity of the ligands. All the drug candidates used in this study passed the basic Lipinski rule of five except orevactaene. Curvularin and rostratin A were predicted as enzyme inhibitors by a bioactivity prediction tool (Molinspiration). In vitro and in vivo studies will be a way to go further.

In silico characterization, homology modelling and structure-based functional annotation of Labeo rohita TLR4 protein

In silico characterization, homology modelling and structure-based functional annotation of Labeo rohita TLR4 protein

Homology modeling and molecular docking studies of INF1 protein of Phytophthora infestans in Potato

Homology modeling and molecular docking studies of INF1 protein of Phytophthora infestans in Potato

AI-Based Homology Modelling of Fatty Acid Transport Protein 1 Using AlphaFold: Structural Elucidation and Molecular Dynamics Exploration.

Fatty acid transport protein 1 (FATP1) is an integral transmembrane protein that is involved in facilitating the translocation of long-chain fatty acids (LCFA) across the plasma membrane, thereby orchestrating the importation of LCFA into the cell. FATP1 also functions as an acyl-CoA ligase, catalyzing the ATP-dependent formation of fatty acyl-CoA using LCFA and VLCFA (very-long-chain fatty acids) as substrates. It is expressed in various types of tissues and is involved in the regulation of crucial signalling pathways, thus playing a vital role in numerous physiological and pathological conditions. Structural insight about FATP1 is, thus, extremely important for understanding the mechanism of action of this protein and developing efficient treatments against its anomalous expression and dysregulation, which are often associated with pathological conditions such as breast cancer. As of now, there has been no prior prediction or evaluation of the 3D configuration of the human FATP1 protein, hindering a comprehensive understanding of the distinct functional roles of its individual domains. In our pursuit to unravel the structure of the most commonly expressed isoforms of FATP1, we employed the cutting-edge ALPHAFOLD 2 model for an initial prediction of the entire protein's structure. This prediction was complemented by molecular dynamics simulations, focusing on the most promising model. We predicted the structure of FATP1 in silico and thoroughly refined and validated it using coarse and molecular dynamics in the absence of the complete crystal structure. Their relative dynamics revealed the different properties of the characteristic FATP1.

NGS Analysis to Detect Mutation in Brain Tumor Diagnostic

Abstract: This study presents an integrated computational approach for analyzing protein sequences and their 3D structures. By leveraging the MMDB Macromolecular database, homologs of a protein sequence of interest are identified, and interactive visualization of their structural properties is provided. The computational alignment method, using BLASTP, allows for efficient determination of sequence similarities and identification of conserved regions among multiple protein sequences. COBALT is employed to refine sequence alignments and facilitate graphical analysis of sequence relationships. RASMOL, a computational analysis program, generates 2-D representations of protein-ligand complexes, enabling visual exploration of their interactions. ORF finder is used to identify coding regions in mRNA sequences, aiding in the prediction of protein-coding regions. The approach is applied to brain tumor diagnostics using human biological samples, exploring the structural properties of brain tumor-related proteins with the help of the 2RHU protein structure and PYMOL visualization software. Overall, this integrated computational framework offers a comprehensive toolkit for protein sequence analysis, structure visualization, and homology modeling, with potential applications in drug discovery, molecular biology, and medical diagnostics

Exploring and targeting potential druggable antimicrobial resistance targets ArgS, SecY, and MurA in Staphylococcus sciuri with TCM inhibitors through a subtractive genomics strategy.

Staphylococcus sciuri (also currently Mammaliicoccus sciuri) are anaerobic facultative and non-motile bacteria that cause significant human pathogenesis such as endocarditis, wound infections, peritonitis, UTI, and septic shock. Methicillin-resistant S. sciuri (MRSS) strains also infects animals that include healthy broilers, cattle, dogs, and pigs. The emergence of MRSS strains thereby poses a serious health threat and thrives the scientific community towards novel treatment options. Herein, we investigated the druggable genome of S. sciuri by employing subtractive genomics that resulted in seven genes/proteins where only three of them were predicted as final targets. Further mining the literature showed that the ArgS (WP_058610923), SecY (WP_058611897), and MurA (WP_058612677) are involved in the multi-drug resistance phenomenon. After constructing and verifying the 3D protein homology models, a screening process was carried out using a library of Traditional Chinese Medicine compounds (consisting of 36,043 compounds). The molecular docking and simulation studies revealed the physicochemical stability parameters of the docked TCM inhibitors in the druggable cavities of each protein target by identifying their druggability potential and maximum hydrogen bonding interactions. The simulated receptor-ligand complexes showed the conformational changes and stability index of the secondary structure elements. The root mean square deviation (RMSD) graph showed fluctuations due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points where the pattern of the RMSD and root mean square fluctuation (RMSF) (< 1.0Å) support any major domain shifts within the structural framework of the protein-ligand complex and placement of ligand was well complemented within the binding site. The β-factor values demonstrated instability at few points while the radius of gyration for structural compactness as a time function for the 100-ns simulation of protein-ligand complexes showed favorable average values and denoted the stability of all complexes. It is assumed that such findings might facilitate researchers to robustly discover and develop effective therapeutics against S. sciuri alongside other enteric infections.

Construction of a HIV-1 subtype C 3D model using homology modeling and in-silico docking, molecular dynamics simulation, and MM-GBSA calculation of second-generation HIV-1 maturation inhibitor(s)

Maturation inhibitors (MIs) efficiently block HIV-1 maturation by inhibiting the cleavage of the capsid protein and spacer peptide 1 (CA-SP1) leading to the production of immature and non-infectious virus particles. We have previously reported that second-generation MIs were more potent than bevirimat (BVM) against HIV-1 subtype C. In-silico studies on interaction of with BVM and their analogs have been limited to HIV-1 subtype B(5I4T) due to lack of an available 3D structure for HIV-1 subtype C virus. In our current study, we have developed a 3D model of HIV-1C Gag CA-SP1 region using protein homology modeling with HIV-1 subtype B(514T) as a template. The HIV-1 C homology model generated was extensively validated using several online tools and served as a template to perform molecular docking studies with eight well-characterized MIs. The docked complex of HIV-1C and all nine MIs was subjected to molecular dynamics simulation for 100 ns using AMBER and binding free energy calculations were done using MM-GBSA. Based on our data, CV8611 exhibited highest binding energy of −6.5 Kcal/mol among all BVM analogs. CV8611 formed strong interactions with Gly222 and Met235 of HIV-1C Gag CA-SP1 during MD simulation and remained intact. The root mean square deviation and root mean square fluctuation values of the complex were stable during the simulations. Our study is the first to report construction and validation of 3D model for the HIV-1C Gag CA-SP1, which could serve as a crucial tool in the structure-aided design of novel and broadly acting maturation inhibitors. Communicated by Ramaswamy H. Sarma