(PS)2: protein structure prediction server version 3.0

Epitope delimitation: A new method for defining epitopes of human IgG-reactive antigenic peptides based on rabbit-recognized epitope motifs

The use of precise epitope peptides as antigens is essential for accurate serological diagnosis of viral-infected individuals, but now it remains an unsolvable problem for mapping precise B cell epitopes (BCEs) recognized by human serum. To address this challenge, we propose a novel epitope delimitation (ED) method to uncover BCEs in the delineated human IgG-reactive (HR) antigenic peptides (APs). Specifically, the method based on the rationale of similarities in humoral immune responses between mammalian species consists of a pair of elements: experimentally delineated HR-AP and rabbit-recognized (RR) BCE motif and corresponding pair of sequence alignment analysis. As a result of using the ED approach, after decoding four RR-epitomes of human papillomavirus types 16/18-E6 and E7 proteins utilizing rabbit serum against each recombinant protein and sequence alignment analysis of HR-APs and RR-BCEs, 19 fine BCEs in 17 of 22 known HR-APs were defined based on each corresponding RR-BCE motifs, including the type-specificity of each delimited BCE in homologous proteins. The test with 22 known 16/20mer HR-APs demonstrated that the ED method is effective and efficient, indicating that it can be used as an alternative method to the conventional identification of fine BCEs using overlapping 8mer peptides.

An immunoinformatic approach employing molecular docking and molecular dynamics simulation for evaluation of l-asparaginase produced by Bacillus velezensis

l-Asparaginase is one of the most important treatments for acute lymphoblastic leukemia. In this study, l-asparaginase-producing bacteria were isolated from the effluent and soil of the Isfahan slaughterhouse using M9 specific medium. Isolates were identified by 16SrRNA phylogenetic analysis. The immune characteristics were predicted. Molecular docking was performed between l-asparaginase and l-asparagine substrate using AutoDock tools 4.2 and AutoDock Vina. Molecular dynamics simulation studies were fulfilled using GROMACS. Five l-asparaginase-producing bacteria isolated that belonging to Stenotrophomonas maltophilia, Chryseobacterium sp. Chryseobacterium indologenes, Bacillus velezensis and Bacillus safensis. Predictions showed B. velezensis has better immune characteristics than B. safensis. The binding energies of the docked complex were calculated to be -4.34 and -4.9 kcal/mol. Molecular docking confirmed the interaction of l-asparaginase with its substrate. It was observed that the residues Thr36, Tyr50, Ala47, Thr116, Asp117, Met142, Thr193 and Thr192 were fundamental in protein-ligand complexation. Also, RMSD, RMSF, Rg, DSSP, SASA and MM-PBSA analysis showed that when l-asparaginase is bound to l-asparagine, it did not lose stability, secondary structure and compactness. Slaughterhouse soils and effluents are a potential source of l-asparaginase-producing bacteria that probably can probably produce l-asparaginase with more favorable immune properties than commercial enzymes.Communicated by Ramaswamy H. Sarma.

Indole-based LpxC (UDP-3-O-(R-3-hydroxyacyl)-N-acetylglucosaminedeacetylase) inhibitors for Salmonella typhi: rational drug discovery through in silico screening

Salmonella typhi is an infectious bacteria that causes typhoid fever and poses a significant risk to human health. The emergence of antibiotic resistance has become a growing concern in the management of this disease. In this work, a structure-based drug design approach was used to identify inhibitors for zinc-dependent metalloamidase LpxC, the enzyme responsible for the biosynthesis of lipid A. Using an in silico approach (virtual screening, docking, and molecular dynamics (MD) simulations), from a library of 59,000 indole derivatives, we were able to identify promising lead molecules with high binding affinity to the LpxC. Of these, five molecules (compound 435 (CID: 12253558), compound 436 (CID: 122514279), compound 1812 (CID: 90797680), compound 2584 (CID: 57056726), and compound 2545 (CID: 59897361)) have passed all the filtering criteria. This finding was verified by molecular dynamics (MD) simulation as well as post-dynamics free energy calculations. The five compounds that have been identified have shown the most promise compared to other compounds that are already recognized. To further validate the positive outcome of this study, experimental validation and optimization are necessary. These lead compounds may help to develop new antibiotics for antibiotic-resistant Salmonella typhi and improve typhoid fever treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03699-5.

Computer-Aided Drug Design and Synthesis of Rhenium Clotrimazole Antimicrobial Agents

In the context of the global health issue caused by the growing occurrence of antimicrobial resistance (AMR), the need for novel antimicrobial agents is becoming alarming. Inorganic and organometallic complexes represent a relatively untapped source of antibiotics. Here, we report a computer-aided drug design (CADD) based on a 'scaffold-hopping' approach for the synthesis and antibacterial evaluation of fac-Re(I) tricarbonyl complexes bearing clotrimazole (ctz) as a monodentate ligand. The prepared molecules were selected following a pre-screening in silico analysis according to modification of the 2,2'-bipyridine (bpy) ligand in the coordination sphere of the complexes. CADD pointed to chiral 4,5-pinene and 5,6-pinene bipyridine derivatives as the most promising candidates. The corresponding complexes were synthesized, tested toward methicillin-sensitive and -resistant S. aureus strains, and the obtained results evaluated with regard to their binding affinity with a homology model of the S. aureus MurG enzyme. Overall, the title species revealed very similar minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values as those of the reference compound used as the scaffold in our approach. The obtained docking scores advocate the viability of 'scaffold-hopping' for de novo design, a potential strategy for more cost- and time-efficient discovery of new antibiotics.

SeqCP: A sequence-based algorithm for searching circularly permuted proteins

Circular permutation (CP) is a protein sequence rearrangement in which the amino- and carboxyl-termini of a protein can be created in different positions along the imaginary circularized sequence. Circularly permutated proteins usually exhibit conserved three-dimensional structures and functions. By comparing the structures of circular permutants (CPMs), protein research and bioengineering applications can be approached in ways that are difficult to achieve by traditional mutagenesis. Most current CP detection algorithms depend on structural information. Because there is a vast number of proteins with unknown structures, many CP pairs may remain unidentified. An efficient sequence-based CP detector will help identify more CP pairs and advance many protein studies. For instance, some hypothetical proteins may have CPMs with known functions and structures that are informative for functional annotation, but existing structure-based CP search methods cannot be applied when those hypothetical proteins lack structural information. Despite the considerable potential for applications, sequence-based CP search methods have not been well developed. We present a sequence-based method, SeqCP, which analyzes normal and duplicated sequence alignments to identify CPMs and determine candidate CP sites for proteins. SeqCP was trained by data obtained from the Circular Permutation Database and tested with nonredundant datasets from the Protein Data Bank. It shows high reliability in CP identification and achieves an AUC of 0.9. SeqCP has been implemented into a web server available at: http://pcnas.life.nthu.edu.tw/SeqCP/.

In Silico Methods for Identification of Potential Active Sites of Therapeutic Targets

Target identification is an important step in drug discovery, and computer-aided drug target identification methods are attracting more attention compared with traditional drug target identification methods, which are time-consuming and costly. Computer-aided drug target identification methods can greatly reduce the searching scope of experimental targets and associated costs by identifying the diseases-related targets and their binding sites and evaluating the druggability of the predicted active sites for clinical trials. In this review, we introduce the principles of computer-based active site identification methods, including the identification of binding sites and assessment of druggability. We provide some guidelines for selecting methods for the identification of binding sites and assessment of druggability. In addition, we list the databases and tools commonly used with these methods, present examples of individual and combined applications, and compare the methods and tools. Finally, we discuss the challenges and limitations of binding site identification and druggability assessment at the current stage and provide some recommendations and future perspectives.

Peimine inhibits variants of SARS-CoV-2 cell entry via blocking the interaction between viral spike protein and ACE2

Coronavirus disease 2019 (COVID-19) is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several vaccines against SARS-CoV-2 have been approved; however, variants of concern (VOCs) can evade vaccine protection. Therefore, developing small compound drugs that directly block the interaction between the viral spike glycoprotein and ACE2 is urgently needed to provide a complementary or alternative treatment for COVID-19 patients. We developed a viral infection assay to screen a library of approximately 126 small molecules and showed that peimine inhibits VOCs viral infections. In addition, a fluorescence resonance energy transfer (FRET) assay showed that peimine suppresses the interaction of spike and ACE2. Molecular docking analysis revealed that peimine exhibits a higher binding affinity for variant spike proteins and is able to form hydrogen bonds with N501Y in the spike protein. These results suggest that peimine, a compound isolated from Fritillaria, may be a potent inhibitor of SARS-CoV-2 variant infection. PRACTICAL APPLICATIONS: In this study, we identified a naturally derived compound of peimine, a major bioactive alkaloid extracted from Fritillaria, that could inhibit SARS-CoV-2 variants of concern (VOCs) viral infection in 293T/ACE2 and Calu-3 lung cells. In addition, peimine blocks viral entry through interruption of spike and ACE2 interaction. Moreover, molecular docking analysis demonstrates that peimine has a higher binding affinity on N501Y in the spike protein. Furthermore, we found that Fritillaria significantly inhibits SARS-CoV-2 viral infection. These results suggested that peimine and Fritillaria could be a potential functional drug and food for COVID-19 patients.

Disulfiram blocked cell entry of SARS-CoV-2 via inhibiting the interaction of spike protein and ACE2

Disulfiram is an FDA-approved drug that has been used to treat alcoholism and has demonstrated a wide range of anti-cancer, anti-bacterial, and anti-viral effects. In the global COVID-19 pandemic, there is an urgent need for effective therapeutics and vaccine development. According to recent studies, disulfiram can act as a potent SARS-CoV-2 replication inhibitor by targeting multiple SARS-CoV-2 non-structural proteins to inhibit viral polyprotein cleavage and RNA replication. Currently, disulfiram is under evaluation in phase II clinical trials to treat COVID-19. With more and more variants of the SARS-CoV-2 worldwide, it becomes critical to know whether disulfiram can also inhibit viral entry into host cells for various variants and replication inhibition. Here, molecular and cellular biology assays demonstrated that disulfiram could interrupt viral spike protein binding with its receptor ACE2. By using the viral pseudo-particles (Vpps) of SARS-CoV-2, disulfiram also showed the potent activity to block viral entry in a cell-based assay against Vpps of different SARS-CoV-2 variants. We further established a live virus model system to support the anti-viral entry activity of disulfiram with the SARS-CoV-2 virus. Molecular docking revealed how disulfiram hindered the binding between the ACE2 and wild-type or mutated spike proteins. Thus, our results indicate that disulfiram has the capability to block viral entry activity of different SARS-CoV-2 variants. Together with its known anti-replication of SARS-CoV-2, disulfiram may serve as an effective therapy against different SARS-CoV-2 variants.

Kunitz-Type Peptides from Sea Anemones Protect Neuronal Cells against Parkinson's Disease Inductors via Inhibition of ROS Production and ATP-Induced P2X7 Receptor Activation

Parkinson’s disease (PD) is a socially significant disease, during the development of which oxidative stress and inflammation play a significant role. Here, we studied the neuroprotective effects of four Kunitz-type peptides from Heteractis crispa and Heteractis magnifica sea anemones against PD inductors. The peptide HCIQ1c9, which was obtained for the first time, inhibited trypsin less than other peptides due to unfavorable interactions of Arg17 with Lys43 in the enzyme. Its activity was reduced by up to 70% over the temperature range of 60–100 °C, while HCIQ2c1, HCIQ4c7, and HMIQ3c1 retained their conformation and stayed active up to 90–100 °C. All studied peptides inhibited paraquat- and rotenone-induced intracellular ROS formation, in particular NO, and scavenged free radicals outside the cells. The peptides did not modulate the TRPV1 channels but they affected the P2X7R, both of which are considered therapeutic targets in Parkinson’s disease. HMIQ3c1 and HCIQ4c7 almost completely inhibited the ATP-induced uptake of YO-PRO-1 dye in Neuro-2a cells through P2X7 ion channels and significantly reduced the stable calcium response in these cells. The complex formation of the peptides with the P2X7R extracellular domain was determined via SPR analysis. Thus, these peptides may be considered promising compounds to protect neuronal cells against PD inductors, which act as ROS production inhibitors and partially act as ATP-induced P2X7R activation inhibitors.

Structural model of human PORCN illuminates disease-associated variants and drug-binding sites

Wnt signaling is essential for normal development and is a therapeutic target in cancer. The enzyme PORCN, or porcupine, is a membrane-bound O-acyltransferase (MBOAT) that is required for the post-translational modification of all Wnts, adding an essential mono-unsaturated palmitoleic acid to a serine on the tip of Wnt hairpin 2. Inherited mutations in PORCN cause focal dermal hypoplasia, and therapeutic inhibition of PORCN slows the growth of Wnt-dependent cancers. Based on homology to mammalian MBOAT proteins, we developed and validated a structural model of human PORCN. The model accommodates palmitoleoyl-CoA and Wnt hairpin 2 in two tunnels in the conserved catalytic core, shedding light on the catalytic mechanism. The model predicts how previously uncharacterized human variants of uncertain significance can alter PORCN function. Drugs including ETC-159, IWP-L6 and LGK-974 dock in the PORCN catalytic site, providing insights into PORCN pharmacologic inhibition. This structural model enhances our mechanistic understanding of PORCN substrate recognition and catalysis, as well as the inhibition of its enzymatic activity, and can facilitate the development of improved inhibitors and the understanding of disease-relevant PORCN mutants. This article has an associated First Person interview with the joint first authors of the paper.

Functionalized Protein Nanotubes Based on the Bacteriophage vB_KleM-RaK2 Tail Sheath Protein

We report on the construction of functionalized nanotubes based on tail sheath protein 041 from vB_KleM-RaK2 bacteriophage. The truncated 041 protein (041Δ200) was fused with fluorescent proteins GFP and mCherry or amidohydrolase YqfB. The generated chimeric proteins were successfully synthesized in E. coli BL21 (DE3) cells and self-assembled into tubular structures. We detected the fluorescence of the structures, which was confirmed by stimulated emission depletion microscopy. When 041Δ200GFP and 041Δ200mCherry were coexpressed in E. coli BL21 (DE3) cells, the formed nanotubes generated Förster resonance energy transfer, indicating that both fluorescent proteins assemble into a single nanotube. Chimeric 041Δ200YqfB nanotubes possessed an enzymatic activity, which was confirmed by hydrolysis of N⁴-acetyl-2′-deoxycytidine. The enzymatic properties of 041Δ200YqfB were similar to those of a free wild-type YqfB. Hence, we conclude that 041-based chimeric nanotubes have the potential for the development of delivery vehicles and targeted imaging and are applicable as scaffolds for biocatalysts.

Effects of Distal Mutations on Ligand-Binding Affinity in E. coli Dihydrofolate Reductase

Mutations far from the center of chemical activity in dihydrofolate reductase (DHFR) can affect several steps in the catalytic cycle. Mutations at highly conserved positions and the distal distance of the catalytic center (Met-42, Thr-113, and Gly-121) were designed, including single-point and double-point mutations. Upon ligand binding, the fluorescence of the intrinsic optical probe, tryptophan, decreases due to either fluorescence quenching or energy transfer. We demonstrated an optical approach in measuring the equilibrium dissociation constant for enzyme-cofactor, enzyme-substrate, and enzyme-product complexes in wildtype ecDHFR and each mutant. We propose that the effects of these distal mutations on ligand-binding affinity stem from the spatial steric hindrance, the disturbance on the hydrogen network, or the modification of the protein flexibility. The modified N-terminus tag in DHFR acts as a cap on the entrance of the substrate-binding cavity, squeezes the adenosine binding subdomain, and influences the binding of NADPH in some mutants. If the mutation positions are away from the N-terminus tag and the adenosine binding subdomain, the additive effects due to the N-terminus tag were not observed. In the double-mutant-cycle analysis, double mutations show nonadditive properties upon either cofactor or substrate binding. Also, in general, the first point mutation strongly affects the ligand binding compared to the second one.

CirPred, the first structure modeling and linker design system for circularly permuted proteins

Background

This work aims to help develop new protein engineering techniques based on a structural rearrangement phenomenon called circular permutation (CP), equivalent to connecting the native termini of a protein followed by creating new termini at another site. Although CP has been applied in many fields, its implementation is still costly because of inevitable trials and errors.

Results

Here we present CirPred, a structure modeling and termini linker design method for circularly permuted proteins. Compared with state-of-the-art protein structure modeling methods, CirPred is the only one fully capable of both circularly-permuted modeling and traditional co-linear modeling. CirPred performs well when the permutant shares low sequence identity with the native protein and even when the permutant adopts a different conformation from the native protein because of three-dimensional (3D) domain swapping. Linker redesign experiments demonstrated that the linker design algorithm of CirPred achieved subangstrom accuracy.

Conclusions

The CirPred system is capable of (1) predicting the structure of circular permutants, (2) designing termini linkers, (3) performing traditional co-linear protein structure modeling, and (4) identifying the CP-induced occurrence of 3D domain swapping. This method is supposed helpful for broadening the application of CP, and its web server is available at http://10.life.nctu.edu.tw/CirPred/ and http://lo.life.nctu.edu.tw/CirPred/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04403-1.

Role of juvenile hormone receptor Methoprene-tolerant 1 in silkworm larval brain development and domestication

The insect brain is the central part of the neurosecretory system, which controls morphology, physiology, and behavior during the insect's lifecycle. Lepidoptera are holometabolous insects, and their brains develop during the larval period and metamorphosis into the adult form. As the only fully domesticated insect, the Lepidoptera silkworm Bombyx mori experienced changes in larval brain morphology and certain behaviors during the domestication process. Hormonal regulation in insects is a key factor in multiple processes. However, how juvenile hormone (JH) signals regulate brain development in Lepidoptera species, especially in the larval stage, remains elusive. We recently identified the JH receptor Methoprene tolerant 1 ( Met1) as a putative domestication gene. How artificial selection on Met1 impacts brain and behavioral domestication is another important issue addressing Darwin's theory on domestication. Here, CRISPR/Cas9-mediated knockout of Bombyx Met1 caused developmental retardation in the brain, unlike precocious pupation of the cuticle. At the whole transcriptome level, the ecdysteroid (20-hydroxyecdysone, 20E) signaling and downstream pathways were overactivated in the mutant cuticle but not in the brain. Pathways related to cell proliferation and specialization processes, such as extracellular matrix (ECM)-receptor interaction and tyrosine metabolism pathways, were suppressed in the brain. Molecular evolutionary analysis and in vitro assay identified an amino acid replacement located in a novel motif under positive selection in B. mori, which decreased transcriptional binding activity. The B. mori MET1 protein showed a changed structure and dynamic features, as well as a weakened co-expression gene network, compared with B. mandarina. Based on comparative transcriptomic analyses, we proposed a pathway downstream of JH signaling (i.e., tyrosine metabolism pathway) that likely contributed to silkworm larval brain development and domestication and highlighted the importance of the biogenic amine system in larval evolution during silkworm domestication.

A secondary structure-based position-specific scoring matrix applied to the improvement in protein secondary structure prediction

Protein secondary structure prediction (SSP) has a variety of applications; however, there has been relatively limited improvement in accuracy for years. With a vision of moving forward all related fields, we aimed to make a fundamental advance in SSP. There have been many admirable efforts made to improve the machine learning algorithm for SSP. This work thus took a step back by manipulating the input features. A secondary structure element-based position-specific scoring matrix (SSE-PSSM) is proposed, based on which a new set of machine learning features can be established. The feasibility of this new PSSM was evaluated by rigid independent tests with training and testing datasets sharing <25% sequence identities. In all experiments, the proposed PSSM outperformed the traditional amino acid PSSM. This new PSSM can be easily combined with the amino acid PSSM, and the improvement in accuracy was remarkable. Preliminary tests made by combining the SSE-PSSM and well-known SSP methods showed 2.0% and 5.2% average improvements in three- and eight-state SSP accuracies, respectively. If this PSSM can be integrated into state-of-the-art SSP methods, the overall accuracy of SSP may break the current restriction and eventually bring benefit to all research and applications where secondary structure prediction plays a vital role during development. To facilitate the application and integration of the SSE-PSSM with modern SSP methods, we have established a web server and standalone programs for generating SSE-PSSM available at http://10.life.nctu.edu.tw/SSE-PSSM.

The influence of dataset homology and a rigorous evaluation strategy on protein secondary structure prediction

The secondary structure prediction (SSP) of proteins has long been an essential structural biology technique with various applications. Despite its vital role in many research and industrial fields, in recent years, as the accuracy of state-of-the-art secondary structure predictors approaches the theoretical upper limit, SSP has been considered no longer challenging or too challenging to make advances. With the belief that the substantial improvement of SSP will move forward many fields depending on it, we conducted this study, which focused on three issues that have not been noticed or thoroughly examined yet but may have affected the reliability of the evaluation of previous SSP algorithms. These issues are all about the sequence homology between or within the developmental and evaluation datasets. We thus designed many different homology layouts of datasets to train and evaluate SSP prediction models. Multiple repeats were performed in each experiment by random sampling. The conclusions obtained with small experimental datasets were verified with large-scale datasets using state-of-the-art SSP algorithms. Very different from the long-established assumption, we discover that the sequence homology between query datasets for training, testing, and independent tests exerts little influence on SSP accuracy. Besides, the sequence homology redundancy between or within most datasets would make the accuracy of an SSP algorithm overestimated, while the redundancy within the reference dataset for extracting predictive features would make the accuracy underestimated. Since the overestimating effects are more significant than the underestimating effect, the accuracy of some SSP methods might have been overestimated. Based on the discoveries, we propose a rigorous procedure for developing SSP algorithms and making reliable evaluations, hoping to bring substantial improvements to future SSP methods and benefit all research and application fields relying on accurate prediction of protein secondary structures.

Characterization of the Bubblegum acyl-CoA synthetase of Microchloropsis gaditana

The metabolic pathways of glycerolipids are well described in cells containing chloroplasts limited by a two-membrane envelope but not in cells containing plastids limited by four membranes, including heterokonts. Fatty acids (FAs) produced in the plastid, palmitic and palmitoleic acids (16:0 and 16:1), are used in the cytosol for the synthesis of glycerolipids via various routes, requiring multiple acyl-Coenzyme A (CoA) synthetases (ACS). Here, we characterized an ACS of the Bubblegum subfamily in the photosynthetic eukaryote Microchloropsis gaditana, an oleaginous heterokont used for the production of lipids for multiple applications. Genome engineering with TALE-N allowed the generation of MgACSBG point mutations, but no knockout was obtained. Point mutations triggered an overall decrease of 16:1 in lipids, a specific increase of unsaturated 18-carbon acyls in phosphatidylcholine and decrease of 20-carbon acyls in the betaine lipid diacylglyceryl-trimethyl-homoserine. The profile of acyl-CoAs highlighted a decrease in 16:1-CoA and 18:3-CoA. Structural modeling supported that mutations affect accessibility of FA to the MgACSBG reaction site. Expression in yeast defective in acyl-CoA biosynthesis further confirmed that point mutations affect ACSBG activity. Altogether, this study supports a critical role of heterokont MgACSBG in the production of 16:1-CoA and 18:3-CoA. In M. gaditana mutants, the excess saturated and monounsaturated FAs were diverted to triacylglycerol, thus suggesting strategies to improve the oil content in this microalga.

Pathogenicity and immunogenicity of Edwardsiella piscicida ferric uptake regulator (fur) mutations in zebrafish

Edwardsiella piscicida is the etiological agent of edwardsiellosis in fish and causes severe economic losses in global aquaculture. Vaccination would be the most effective method to prevent infectious diseases and their associated economic losses. The ferric uptake regulator (Fur) is an important transcriptional global regulator of Gram-negative bacteria. In this study, we examined the regulatory function of Fur in E. piscicida. We designed a strain that displays features of the wild-type virulent strain of E. piscicida at the time of immunization to enable strains first to effectively colonize lymphoid tissues and then to exhibit a regulated delayed attenuation in vivo to preclude inducing disease symptoms. Regulated delayed attenuation in vivo is based on the substitution of a tightly regulated araC P_araBAD cassette for the promoter of the fur gene such that expression of this gene is dependent on arabinose provided during growth. Thus, following E. piscicida mutant colonization of lymphoid tissues, the Fur protein ceases to be synthesized due to the absence of arabinose such that attenuation is gradually manifest in vivo to preclude induction of diseases symptoms. We deleted the promoter, including all sequences that interact with activator or repressor proteins, for the fur gene, and substituted the improved araC P_araBAD cassette to yield an E. piscicida strain with the ΔP_fur170:TT araC P_araBADfur deletion-insertion mutation (χ16012). Compared to the wild-type strain J118, χ16012 exhibited retarded growth and enhanced siderophore production in the absence of arabinose. mRNA levels of Fur-regulated genes were analyzed in iron deplete or replete condition in wild-type and fur mutant strains. We observed zebrafish immunized with χ16012 showed better colonization and protection compared to the Δfur (χ16001). Studies showed that E. piscicida strain χ16012 is attenuated and induces systemic and mucosal IgM titer in zebrafish. In addition, we found an increase in transcript levels of tnf-α, il-1β, il-8 and ifn-γ in different tissues of zebrafish immunized with χ16012 compared to the unimmunized group. We conclude that, E. piscicida with regulated delayed attenuation could be an effective immersion vaccine for the aquaculture industry.

High-performance FRET biosensors for single-cell and in vivo lead detection

Forms of lead (Pb) have been insidiously invading human life for thousands of years without obvious signs of their considerable danger to human health. Blood lead level (BLL) is the routine measure used for diagnosing the degree of lead intoxication, although it is unclear whether there is any safe range of BLL. To develop a practical detection tool for living organisms, we engineered a genetically encoded fluorescence resonance energy transfer (FRET)-based Pb²⁺ biosensor, 'Met-lead 1.44 M1', with excellent performance. Met-lead 1.44 M1 has an apparent dissociation constant (K_d) of 25.97 nM, a detection limit (LOD) of 10 nM (2.0 ppb/0.2 μg/dL), and an enhancement dynamic ratio of nearly ~ 5-fold upon Pb²⁺ binding. The 10 nM sensitivity of Met-lead 1.44 M1 is five times below the World Health Organization-permitted level of lead in tap water (10 ppb; WHO, 2017), and fifteen times lower than the maximum BLL for children (3 μg/dL). We deployed Met-lead 1.44 M1 to measure Pb²⁺ concentrations in different living models, including two general human cell lines and one specific line, induced pluripotent stem cell (iPSC)-derived cardiomyocytes, as well as in widely used model species in plant (Arabidopsis thaliana) and animal (Drosophila melanogaster) research. Our results suggest that this new biosensor is suitable for lead toxicological research in vitro and in vivo, and will pave the way toward potential applications for both low BLL measures and rapid detection of environmental lead in its divalent form.

A simple strategy to enhance the speed of protein secondary structure prediction without sacrificing accuracy

The secondary structure prediction of proteins is a classic topic of computational structural biology with a variety of applications. During the past decade, the accuracy of prediction achieved by state-of-the-art algorithms has been >80%; meanwhile, the time cost of prediction increased rapidly because of the exponential growth of fundamental protein sequence data. Based on literature studies and preliminary observations on the relationships between the size/homology of the fundamental protein dataset and the speed/accuracy of predictions, we raised two hypotheses that might be helpful to determine the main influence factors of the efficiency of secondary structure prediction. Experimental results of size and homology reductions of the fundamental protein dataset supported those hypotheses. They revealed that shrinking the size of the dataset could substantially cut down the time cost of prediction with a slight decrease of accuracy, which could be increased on the contrary by homology reduction of the dataset. Moreover, the Shannon information entropy could be applied to explain how accuracy was influenced by the size and homology of the dataset. Based on these findings, we proposed that a proper combination of size and homology reductions of the protein dataset could speed up the secondary structure prediction while preserving the high accuracy of state-of-the-art algorithms. Testing the proposed strategy with the fundamental protein dataset of the year 2018 provided by the Universal Protein Resource, the speed of prediction was enhanced over 20 folds while all accuracy measures remained equivalently high. These findings are supposed helpful for improving the efficiency of researches and applications depending on the secondary structure prediction of proteins. To make future implementations of the proposed strategy easy, we have established a database of size and homology reduced protein datasets at http://10.life.nctu.edu.tw/UniRefNR.

Increased APOE glycosylation plays a key role in the atherogenicity of L5 low-density lipoprotein

Low-density lipoprotein (LDL) is heterogeneous, composed of particles with variable atherogenicity. Electronegative L5 LDL exhibits atherogenic properties in vitro and in vivo, and its levels are elevated in patients with increased cardiovascular risk. Apolipoprotein E (APOE) content is increased in L5, but what role APOE plays in L5 function remains unclear. Here, we characterized the contributions of APOE posttranslational modification to L5's atherogenicity. Using two-dimensional electrophoresis and liquid chromatography-mass spectrometry, we studied APOE's posttranslational modification in L5 from human plasma. APOE structures with various glycan residues were predicted. Molecular docking and molecular dynamics simulation were performed to examine the functional changes of APOE resulting from glycosylation. We also examined the effects of L5 deglycosylation on endothelial cell apoptosis. The glycan sequence N-acetylgalactosamine, galactose, and sialic acid was consistently expressed on serine 94, threonine 194, and threonine 289 of APOE in L5 and was predicted to contribute to L5's negative surface charge and hydrophilicity. The electrostatic force between the negatively charged sialic acid-containing glycan residue of APOE and positively charged amino acids at the receptor-binding area suggested that glycosylation interferes with APOE's attraction to receptors, lipid-binding ability, and lipid transportation and metabolism functions. Importantly, L5 containing glycosylated APOE induced apoptosis in cultured endothelial cells through lectin-like oxidized LDL receptor-1 (LOX-1) signaling, and glycosylation removal from L5 attenuated L5-induced apoptosis. APOE glycosylation may contribute to the atherogenicity of L5 and be a useful biomarker for rapidly quantifying L5.

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas

Introduction:

The emergence of new omics approaches, such as genomic algorithms to identify tumor mutations and molecular modeling tools to predict the three-dimensional structure of proteins, has facilitated the understanding of the dynamic mechanisms involved in the pathogenesis of low-grade gliomas including oligodendrogliomas and astrocytomas.

Methods:

In this study, we targeted known mutations involved in low-grade gliomas, starting with the sequencing of genomic regions encompassing exon 4 of isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) and the four exons (5-6 and 7-8) of TP53 from 32 samples, followed by computational analysis to study the impact of these mutations on the structure and function of 3 proteins IDH1, IDH2, and p53.

Results:

We obtain a mutation that has an effect on the catalytic site of the protein IDH1 as R132H and on the catalytic site of the protein IDH2 as R172M. Other mutations at p53 have been identified as K305N, which is a pathogenic mutation; R175 H, which is a benign mutation; and R158G, which disrupts the structural conformation of the tumor suppressor protein.

Conclusion:

In low-grade gliomas, mutations in IDH1, IDH2, and TP53 may be the key to tumor progression because they have an effect on the function of the protein such as mutations R132H in IDH1 and R172M in IDH2, which change the function of the enzyme alpha-ketoglutarate, or R158G in TP53, which affects the structure of the generated protein, thus their importance in understanding gliomagenesis and for more accurate diagnosis complementary to the anatomical pathology tests.

Monitoring the Heavy Metal Lead Inside Living Drosophila with a FRET-Based Biosensor

The harmful impact of the heavy metal lead on human health has been known for years. However, materials that contain lead remain in the environment. Measuring the blood lead level (BLL) is the only way to officially evaluate the degree of exposure to lead. The so-called "safe value" of the BLL seems to unreliably represent the secure threshold for children. In general, lead's underlying toxicological mechanism remains unclear and needs to be elucidated. Therefore, we developed a novel genetically encoded fluorescence resonance energy transfer (FRET)-based lead biosensor, Met-lead, and applied it to transgenic Drosophila to perform further investigations. We combined Met-lead with the UAS-GAL4 system to the sensor protein specifically expressed within certain regions of fly brains. Using a suitable imaging platform, including a fast epifluorescent or confocal laser-scanning/two-photon microscope with high resolution, we recorded the changes in lead content inside fly brains ex vivo and in vivo and at different life stages. The blood-brain barrier was found to play an important role in the protection of neurons in the brain against damage due to the heavy metal lead, either through food or microinjection into the abdomen. Met-lead has the potential to be a powerful tool for the sensing of lead within living organisms by employing either a fast epi-FRET microscope or high-resolution brain imaging.

Amino-acid inserts of HIV-1 capsid (CA) induce CA degradation and abrogate viral infectivity: Insights for the dynamics and mechanisms of HIV-1 CA decomposition

Accumulation of amino acid (AA) insertions/substitutions are observed in the Gag-protein of HIV-1 variants resistant to HIV-1 protease inhibitors. Here, we found that HIV-1 carrying AA insertions in capsid protein (CA) undergoes aberrant CA degradation. When we generated recombinant HIV-1s (rHIV-1s) containing 19-AAs in Gag, such insertions caused significant CA degradation, which initiated in CA's C-terminal. Such rHIV-1s had remarkable morphological abnormality, decreased infectivity, and no replicative ability, which correlated with levels of CA degradation. The CA degradation observed was energy-independent and had no association with cellular/viral proteolytic mechanisms, suggesting that the CA degradation occurs due to conformational/structural incompatibility caused by the 19-AA insertions. The incorporation of degradation-prone CA into the wild-type CA resulted in significant disruption of replication competence in "chimeric" virions. The data should allow better understanding of the dynamics and mechanisms of CA decomposition/degradation and retroviral uncoating, which may lead to new approach for antiretroviral modalities.

Identification of a novel variant of Golli myelin basic protein BG21 in the uniquely neuroprotective white-footed mouse

The myelin basic protein (MBP) gene is a complex gene which codes for several distinct forms of MBP. The various forms of MBP are functionally involved in the development of the nervous system, T-cell regulation, and myelination. Several neurological disorders have been linked to MBP abnormality, further demonstrating its functional significance in the nervous system. The white-footed mouse (Peromyscus leucopus) exhibits profound neuroprotective characteristics, is asymptomatic to various disease-states, and has a lifespan twice that of the house mouse (Mus musculus). We used M. musculus mouse MBP as a reference to explore MBP in P. leucopus mice. Through genetic and downstream proteomic data analysis, we identified a novel variant of the BG21 isoform of MBP in P. leucopus mice. Variation in this isoform is present at the genetic level between the two species of mice. Our results show differences within the open reading frame of the transcripts accompanied by corresponding differences in protein structure prediction. These data introduce the potential of MBP variation as one of many causal variables contributing to the unique presentation of enhanced neuroprotection and longevity in P. leucopus mice.

Ensembles generated from crystal structures of single distant homologues solve challenging molecular-replacement cases in AMPLE

Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Although routine in many cases, it becomes more effortful and often impossible when the available experimental structures typically used as search models are only distantly homologous to the target. Nevertheless, with current powerful MR software, relatively small core structures shared between the target and known structure, of 20-40% of the overall structure for example, can succeed as search models where they can be isolated. Manual sculpting of such small structural cores is rarely attempted and is dependent on the crystallographer's expertise and understanding of the protein family in question. Automated search-model editing has previously been performed on the basis of sequence alignment, in order to eliminate, for example, side chains or loops that are not present in the target, or on the basis of structural features (e.g. solvent accessibility) or crystallographic parameters (e.g. B factors). Here, based on recent work demonstrating a correlation between evolutionary conservation and protein rigidity/packing, novel automated ways to derive edited search models from a given distant homologue over a range of sizes are presented. A variety of structure-based metrics, many readily obtained from online webservers, can be fed to the MR pipeline AMPLE to produce search models that succeed with a set of test cases where expertly manually edited comparators, further processed in diverse ways with MrBUMP, fail. Further significant performance gains result when the structure-based distance geometry method CONCOORD is used to generate ensembles from the distant homologue. To our knowledge, this is the first such approach whereby a single structure is meaningfully transformed into an ensemble for the purposes of MR. Additional cases further demonstrate the advantages of the approach. CONCOORD is freely available and computationally inexpensive, so these novel methods offer readily available new routes to solve difficult MR cases.

A new mitofusin topology places the redox-regulated C terminus in the mitochondrial intermembrane space

Mitochondrial fusion occurs in many eukaryotes, including animals, plants, and fungi. It is essential for cellular homeostasis, and yet the underlying mechanisms remain elusive. Comparative analyses and phylogenetic reconstructions revealed that fungal Fzo1 and animal Mitofusin proteins are highly diverged from one another and lack strong sequence similarity. Bioinformatic analysis showed that fungal Fzo1 proteins exhibit two predicted transmembrane domains, whereas metazoan Mitofusins contain only a single transmembrane domain. This prediction contradicts the current models, suggesting that both animal and fungal proteins share one topology. This newly predicted topology of Mfn1 and Mfn2 was demonstrated biochemically, confirming that the C-terminal, redox-sensitive cysteine residues reside within the intermembrane space (IMS). Functional experiments established that redox-mediated disulfide modifications within the IMS domain are key modulators of reversible Mfn oligomerization that drives fusion. Together, these results lead to a revised understanding of Mfns as single-spanning outer membrane proteins with an N_out-C_in orientation, providing functional insight into the IMS contribution to redox-regulated fusion events.

Annotation of Peptide Structures Using SMILES and Other Chemical Codes-Practical Solutions

Contemporary peptide science exploits methods and tools of bioinformatics, and cheminformatics. These approaches use different languages to describe peptide structures—amino acid sequences and chemical codes (especially SMILES), respectively. The latter may be applied, e.g., in comparative studies involving structures and properties of peptides and peptidomimetics. Progress in peptide science “in silico” may be achieved via better communication between biologists and chemists, involving the translation of peptide representation from amino acid sequence into SMILES code. Recent recommendations concerning good practice in chemical information include careful verification of data and their annotation. This publication discusses the generation of SMILES representations of peptides using existing software. Construction of peptide structures containing unnatural and modified amino acids (with special attention paid on glycosylated peptides) is also included. Special attention is paid to the detection and correction of typical errors occurring in SMILES representations of peptides and their correction using molecular editors. Brief recommendations for training of staff working on peptide annotations, are discussed as well.

Structural insights into a high affinity nanobody:antigen complex by homology modelling

Porphyromonas gingivalis is a major periodontitis-causing pathogens. P. gingivalis secrete a cysteine protease termed RgpB, which is specific for Arg-Xaa bonds in substrates. Recently, a nanobody-based assay was used to demonstrate that RgpB could represent a novel diagnostic target, thereby simplifying. P. gingivalis detection. The nanobody, VHH7, had a high binding affinity and was specific for RgpB, when tested towards the highly identical RgpA. In this study a homology model of VHH7 was build. The complementarity determining regions (CDR) comprising the paratope residues responsible for RgpB binding were identified and used as input to the docking. Furthermore, residues likely involved in the RgpB epitope was identified based upon RgpB:RgpA alignment and analysis of residue surface accessibility. CDR residues and putitative RgpB epitope residues were used as input to an information-driven flexible docking approach using the HADDOCK server. Analysis of the VHH7:RgpB model demonstrated that the epitope was found in the immunoglobulin-like domain and residue pairs located at the molecular paratope:epitope interface important for complex stability was identified. Collectively, the VHH7 homology model and VHH7:RgpB docking supplies knowledge of the residues involved in the high affinity interaction. This information could prove valuable in the design of an antibody-drug conjugate for specific RgpB targeting.

BECN2 interacts with ATG14 through a metastable coiled-coil to mediate autophagy

ATG14 binding to BECN/Beclin homologs is essential for autophagy, a critical catabolic homeostasis pathway. Here, we show that the α-helical, coiled-coil domain (CCD) of BECN2, a recently identified mammalian BECN1 paralog, forms an antiparallel, curved homodimer with seven pairs of nonideal packing interactions, while the BECN2 CCD and ATG14 CCD form a parallel, curved heterodimer stabilized by multiple, conserved polar interactions. Compared to BECN1, the BECN2 CCD forms a weaker homodimer, but binds more tightly to the ATG14 CCD. Mutation of nonideal BECN2 interface residues to more ideal pairs improves homodimer self-association and thermal stability. Unlike BECN1, all BECN2 CCD mutants bind ATG14, although more weakly than wild type. Thus, polar BECN2 CCD interface residues result in a metastable homodimer, facilitating dissociation, but enable better interactions with polar ATG14 residues stabilizing the BECN2:ATG14 heterodimer. These structure-based mechanistic differences in BECN1 and BECN2 homodimerization and heterodimerization likely dictate competitive ATG14 recruitment.

Protein-Protein Docking

Protein-protein docking algorithms are powerful computational tools, capable of analyzing the protein-protein interactions at the atomic-level. In this chapter, we will review the theoretical concepts behind different protein-protein docking algorithms, highlighting their strengths as well as their limitations and pointing to important case studies for each method. The methods we intend to cover in this chapter include various search strategies and scoring techniques. This includes exhaustive global search, fast Fourier transform search, spherical Fourier transform-based search, direct search in Cartesian space, local shape feature matching, geometric hashing, genetic algorithm, randomized search, and Monte Carlo search. We will also discuss the different ways that have been used to incorporate protein flexibility within the docking procedure and some other future directions in this field, suggesting possible ways to improve the different methods.

Computational analysis, structural modeling and ligand binding site prediction of Plasmodium falciparum 1-deoxy-d-xylulose-5-phosphate synthase

Malaria remains one of the most serious infectious diseases in the world. There are five human species of the Plasmodium genus, of which Plasmodium falciparum is the most virulent and responsible for the vast majority of malaria related deaths. The unique biochemical processes that exist in Plasmodium falciparum provide a useful way to develop novel inhibitors. One such biochemical pathway is the methyl erythritol phosphate pathway (MEP), required to synthesize isoprenoid precursors. In the present study, a detailed computational analysis has been performed for 1-deoxy-d-xylulose-5-phosphate synthase, a key enzyme in MEP. The protein is found to be stable and residues from 825 to 971 are highly conserved across species. The homology model of the enzyme is developed using three web-based servers and Modeller software. It has twelve disordered regions indicating its druggability. Virtual screening of ZINC database identifies ten potential compounds in thiamine diphosphate binding region of the enzyme.

HOMCOS: an updated server to search and model complex 3D structures

The HOMCOS server (http://homcos.pdbj.org) was updated for both searching and modeling the 3D complexes for all molecules in the PDB. As compared to the previous HOMCOS server, the current server targets all of the molecules in the PDB including proteins, nucleic acids, small compounds and metal ions. Their binding relationships are stored in the database. Five services are available for users. For the services “Modeling a Homo Protein Multimer” and “Modeling a Hetero Protein Multimer”, a user can input one or two proteins as the queries, while for the service “Protein-Compound Complex”, a user can input one chemical compound and one protein. The server searches similar molecules by BLAST and KCOMBU. Based on each similar complex found, a simple sequence-replaced model is quickly generated by replacing the residue names and numbers with those of the query protein. A target compound is flexibly superimposed onto the template compound using the program fkcombu. If monomeric 3D structures are input as the query, then template-based docking can be performed. For the service “Searching Contact Molecules for a Query Protein”, a user inputs one protein sequence as the query, and then the server searches for its homologous proteins in PDB and summarizes their contacting molecules as the predicted contacting molecules. The results are summarized in “Summary Bars” or “Site Table”display. The latter shows the results as a one-site-one-row table, which is useful for annotating the effects of mutations. The service “Searching Contact Molecules for a Query Compound” is also available.

Identification of BECN1 and ATG14 Coiled-Coil Interface Residues That Are Important for Starvation-Induced Autophagy

Autophagy, an essential eukaryotic homeostasis pathway, allows the sequestration of unwanted, damaged, or harmful cytoplasmic components in vesicles called autophagosomes, permitting subsequent lysosomal degradation and nutrient recycling. Autophagosome nucleation is mediated by class III phosphatidylinositol-3-kinase complexes that include two key autophagy proteins, BECN1/Beclin 1 and ATG14/BARKOR, which form parallel heterodimers via their coiled-coil domains (CCDs). Here we present the 1.46 Å X-ray crystal structure of the antiparallel, human BECN1 CCD homodimer, which represents BECN1 oligomerization outside the autophagosome nucleation complex. We use circular dichroism and small-angle X-ray scattering (SAXS) to show that the ATG14 CCD is significantly disordered but becomes more helical in the BECN1:ATG14 heterodimer, although it is less well-folded than the BECN1 CCD homodimer. SAXS also indicates that the BECN1:ATG14 heterodimer is more curved than other BECN1-containing CCD dimers, which has important implications for the structure of the autophagosome nucleation complex. A model of the BECN1:ATG14 CCD heterodimer that agrees well with the SAXS data shows that BECN1 residues at the homodimer interface are also responsible for heterodimerization, allowing us to identify ATG14 interface residues. Finally, we verify the role of BECN1 and ATG14 interface residues in binding by assessing the impact of point mutations of these residues on co-immunoprecipitation of the partner and demonstrate that these mutations abrogate starvation-induced upregulation of autophagy but do not impact basal autophagy. Thus, this research provides insights into structures of the BECN1 CCD homodimer and the BECN1:ATG14 CCD heterodimer and identifies interface residues that are important for BECN1:ATG14 heterodimerization and for autophagy.

Amyotrophic Lateral Sclerosis Type 20 - In Silico Analysis and Molecular Dynamics Simulation of hnRNPA1

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease that affects the upper and lower motor neurons. 5-10% of cases are genetically inherited, including ALS type 20, which is caused by mutations in the hnRNPA1 gene. The goals of this work are to analyze the effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on hnRNPA1 protein function, to model the complete tridimensional structure of the protein using computational methods and to assess structural and functional differences between the wild type and its variants through Molecular Dynamics simulations. nsSNP, PhD-SNP, Polyphen2, SIFT, SNAP, SNPs&GO, SNPeffect and PROVEAN were used to predict the functional effects of nsSNPs. Ab initio modeling of hnRNPA1 was made using Rosetta and refined using KoBaMIN. The structure was validated by PROCHECK, Rampage, ERRAT, Verify3D, ProSA and Qmean. TM-align was used for the structural alignment. FoldIndex, DICHOT, ELM, D2P2, Disopred and DisEMBL were used to predict disordered regions within the protein. Amino acid conservation analysis was assessed by Consurf, and the molecular dynamics simulations were performed using GROMACS. Mutations D314V and D314N were predicted to increase amyloid propensity, and predicted as deleterious by at least three algorithms, while mutation N73S was predicted as neutral by all the algorithms. D314N and D314V occur in a highly conserved amino acid. The Molecular Dynamics results indicate that all mutations increase protein stability when compared to the wild type. Mutants D314N and N319S showed higher overall dimensions and accessible surface when compared to the wild type. The flexibility level of the C-terminal residues of hnRNPA1 is affected by all mutations, which may affect protein function, especially regarding the protein ability to interact with other proteins.