Abstract
The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the ...dissociation constant (pKa) of charged groups of seven amino acids and NH+ and COO− groups at polypeptide termini. Information regarding isoelectric point and pKa is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pKa values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pKa values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pKa using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org
Graphical Abstract
Graphical Abstract
Isoelectric Point Calculator 2.0 - prediction of IEP with deep learning.
In the era of increasing bacterial resistance to antibiotics, new bactericidal substances are sought, and lysins derived from extremophilic organisms have the undoubted advantage of being stable ...under harsh environmental conditions. The PhiKo endolysin is derived from the phiKo bacteriophage infecting Gram-negative extremophilic bacterium
HB27. This enzyme shows similarity to two previously investigated thermostable type-2 amidases, the Ts2631 and Ph2119 from
bacteriophages, that revealed high lytic activity not only against thermophiles but also against Gram-negative mesophilic bacteria. Therefore, antibacterial potential of the PhiKo endolysin was investigated in the study presented here.
Enzyme activity was assessed using turbidity reduction assays (TRAs) and antibacterial tests. Differential scanning calorimetry was applied to evaluate protein stability. The Collection of Anti-Microbial Peptides (CAMP) and Antimicrobial Peptide Calculator and Predictor (APD3) were used to predict regions with antimicrobial potential in the PhiKo primary sequence. The minimum inhibitory concentration (MIC) of the RAP-29 synthetic peptide was determined against Gram-positive and Gram-negative selected strains, and mechanism of action was investigated with use of membrane potential sensitive fluorescent dye 3,3'-Dipropylthiacarbocyanine iodide (DiSC
(5)).
The PhiKo endolysin is highly thermostable with melting temperature of 91.70°C. However, despite its lytic effect against such extremophiles as:
,
,
,
, and
, PhiKo showed moderate antibacterial activity against mesophiles. Consequently, its protein sequence was searched for regions with potential antibacterial activity. A highly positively charged region was identified and synthetized (PhiKo
). The novel RAP-29 peptide lysed mesophilic strains of staphylococci and Gram-negative bacteria, reducing the number of cells by 3.7-7.1 log units and reaching the minimum inhibitory concentration values in the range of 2-31 μM. This peptide is unstructured in an aqueous solution but forms an α-helix in the presence of detergents. Moreover, it binds lipoteichoic acid and lipopolysaccharide, and causes depolarization of bacterial membranes. The RAP-29 peptide is a promising candidate for combating bacterial pathogens. The existence of this cryptic peptide testifies to a much wider panel of antimicrobial peptides than thought previously.
Abstract
Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point—the pH at which a ...particular molecule carries no net electrical charge—is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides’ isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.
Graphical Abstract
Graphical Abstract
Proteome-pI 2.0 database: 61,329,034 proteins from 20,115 proteomes with isoelectric point predicted using 21 methods; 5.38B dissociation constant (pKa) predictions; 9.58B in silico digested peptides (Trypsin, Chymotrypsin, Trypsin+LysC, LysN, ArgC).
Abstract
The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the ...dissociation constant (pKa) of charged groups of seven amino acids and NH+ and COO− groups at polypeptide termini. Information regarding isoelectric point and pKa is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pKa values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pKa values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pKa using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org
Abstract
Bacterial gene regulatory networks orchestrate responses to environmental challenges. Horizontal gene transfer can bring in genes with regulatory potential, such as new transcription factors ...(TFs), and this can disrupt existing networks. Serious regulatory perturbations may even result in cell death. Here, we show the impact on Escherichia coli of importing a promiscuous TF that has adventitious transcriptional effects within the cryptic Rac prophage. A cascade of regulatory network perturbations occurred on a global level. The TF, a C regulatory protein, normally controls a Type II restriction-modification system, but in E. coli K-12 interferes with expression of the RacR repressor gene, resulting in de-repression of the normally-silent Rac ydaT gene. YdaT is a prophage-encoded TF with pleiotropic effects on E. coli physiology. In turn, YdaT alters expression of a variety of bacterial regulons normally controlled by the RcsA TF, resulting in deficient lipopolysaccharide biosynthesis and cell division. At the same time, insufficient RacR repressor results in Rac DNA excision, halting Rac gene expression due to loss of the replication-defective Rac prophage. Overall, Rac induction appears to counteract the lethal toxicity of YdaT. We show here that E. coli rewires its regulatory network, so as to minimize the adverse regulatory effects of the imported C TF. This complex set of interactions may reflect the ability of bacteria to protect themselves by having robust mechanisms to maintain their regulatory networks, and/or suggest that regulatory C proteins from mobile operons are under selection to manipulate their host's regulatory networks for their own benefit.
Graphical Abstract
Graphical Abstract
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