Amino Acid Residues In Positions Research Articles

Sliding-attention transformer neural architecture for predicting T cell receptor–antigen–human leucocyte antigen binding

Neoantigens are promising targets for immunotherapy by eliciting immune response and removing cancer cells with high specificity, low toxicity and ease of personalization. However, identifying effective neoantigens remains difficult because of the complex interactions among T cell receptors, antigens and human leucocyte antigen sequences. In this study, we integrate important physical and biological priors with the Transformer model and propose the physics-inspired sliding transformer (PISTE). In PISTE, the conventional, data-driven attention mechanism is replaced with physics-driven dynamics that steers the positioning of amino acid residues along the gradient field of their interactions. This allows navigating the intricate landscape of biosequence interactions intelligently, leading to improved accuracy in T cell receptor–antigen–human leucocyte antigen binding prediction and robust generalization to rare sequences. Furthermore, PISTE effectively recovers residue-level contact relationships even in the absence of three-dimensional structure training data. We applied PISTE in a multitude of immunogenic tumour types to pinpoint neoantigens and discern neoantigen-reactive T cells. In a prospective study of prostate cancer, 75% of the patients elicited immune responses through PISTE-predicted neoantigens.

Sequence-Based Protein Design: A Review of Using Statistical Models to Characterize Coevolutionary Traits for Developing Hybrid Proteins as Genetic Sensors.

Statistical analyses of homologous protein sequences can identify amino acid residue positions that co-evolve to generate family members with different properties. Based on the hypothesis that the coevolution of residue positions is necessary for maintaining protein structure, coevolutionary traits revealed by statistical models provide insight into residue-residue interactions that are important for understanding protein mechanisms at the molecular level. With the rapid expansion of genome sequencing databases that facilitate statistical analyses, this sequence-based approach has been used to study a broad range of protein families. An emerging application of this approach is to design hybrid transcriptional regulators as modular genetic sensors for novel wiring between input signals and genetic elements to control outputs. Among many allosterically regulated regulator families, the members contain structurally conserved and functionally independent protein domains, including a DNA-binding module (DBM) for interacting with a specific genetic element and a ligand-binding module (LBM) for sensing an input signal. By hybridizing a DBM and an LBM from two different family members, a hybrid regulator can be created with a new combination of signal-detection and DNA-recognition properties not present in natural systems. In this review, we present recent advances in the development of hybrid regulators and their applications in cellular engineering, especially focusing on the use of statistical analyses for characterizing DBM-LBM interactions and hybrid regulator design. Based on these studies, we then discuss the current limitations and potential directions for enhancing the impact of this sequence-based design approach.

Predicting transcriptional activation domain function using Graph Neural Networks.

Analysis of factors that lead to the functionality of transcriptional activation domains remains a crucial and yet challenging task owing to the significant diversity in their sequences and their intrinsically disordered nature. Almost all existing methods that have aimed to predict activation domains have involved traditional machine learning approaches, such as logistic regression, that are unable to capture complex patterns in data or plain convolutional neural networks and have been limited in exploration of structural features. However, there is a tremendous potential in the inspection of the structural properties of activation domains, and an opportunity to investigate complex relationships between features of residues in the sequence. To address these, we have utilized the power of graph neural networks which can represent structural data in the form of nodes and edges, allowing nodes to exchange information among themselves. We have experimented with two kinds of graph formulations, one involving residues as nodes and the other assigning atoms to be the nodes. A logistic regression model was also developed to analyze feature importance. For all the models, several feature combinations were experimented with. The residue-level GNN model with amino acid type, residue position, acidic/basic/aromatic property and secondary structure feature combination gave the best performing model with accuracy, F1 score and AUROC of 97.9%, 71% and 97.1% respectively which outperformed other existing methods in the literature when applied on the dataset we used. Among the other structure-based features that were analyzed, the amphipathic property of helices also proved to be an important feature for classification. Logistic regression results showed that the most dominant feature that makes a sequence functional is the frequency of different types of amino acids in the sequence. Our results consistent have shown that functional sequences have more acidic and aromatic residues whereas basic residues are seen more in non-functional sequences.

Membrane-Active All-Hydrocarbon-Stapled α-Helical Amphiphilic Tat Peptides: Broad-Spectrum Antibacterial Activity and Low Incidence of Drug Resistance.

Multidrug resistance against conventional antibiotics has dramatically increased the difficulty of treatment and accelerated the need for novel antibacterial agents. The peptide Tat (47-57) is derived from the transactivating transcriptional activator of human immunodeficiency virus 1, which is well-known as a cell-penetrating peptide in mammalian cells. However, it is also reported that the Tat peptide (47-57) has antifungal activity. In this study, a series of membrane-active hydrocarbon-stapled α-helical amphiphilic peptides were synthesized and evaluated as antibacterial agents against Gram-positive and Gram-negative bacteria, including multidrug-resistant strains. The impact of hydrocarbon staple, the position of aromatic amino acid residue in the hydrophobic face, the various types of aromatic amino acids, and the hydrophobicity on bioactivity were also investigated and discussed in this study. Among those synthesized peptides, analogues P3 and P10 bearing a l-2-naphthylalanine (Φ) residue at the first position and a Tyr residue at the eighth position demonstrated the highest antimicrobial activity and negligible hemolytic toxicity. Notably, P3 and P10 showed obviously enhanced antimicrobial activity against multidrug-resistant bacteria, low drug resistance, high cell selectivity, extended half-life in plasma, and excellent performance against biofilm. The antibacterial mechanisms of P3 and P10 were also preliminarily investigated in this effort. In conclusion, P3 and P10 are promising antimicrobial alternatives for the treatment of the antimicrobial-resistance crisis.

Iso-mukaadial acetate and ursolic acid acetate bind to Plasmodium Falciparum heat shock protein 70: towards targeting parasite protein folding pathway.

Plasmodium falciparum is the most lethal malaria parasite. P. falciparum Hsp70 (PfHsp70) is an essential molecular chaperone (facilitates protein folding) and is deemed a prospective antimalarial drug target. The present study investigates the binding capabilities of select plant derivatives, iso-mukaadial acetate (IMA) and ursolic acid acetate (UAA), against P. falciparum using an in silico docking approach. The interaction between the ligands and PfHsp70 was evaluated using plasmon resonance (SPR) analysis. Molecular docking, binding free energy analysis and molecular dynamics simulations were conducted towards understanding the mechanisms by which the compounds bind to PfHsp70. The molecular docking results revealed ligand flexibilities, conformations and positions of key amino acid residues and protein-ligand interactions as crucial factors accounting for selective inhibition of Hsp70. The simulation results also suggest protein-ligand van der Waals forces as the driving force guiding the interaction of these compounds with PfHsp70. Of the two compounds, UAA and IMA bound to PfHsp70 within the micromolar range based on surface plasmon resonance (SPR) based binding assay. Our findings pave way for future rational design of new selective compounds targeting PfHsp70.

Engineered assemblies from isomeric pentapeptides augment dry eye treatment

Changing positions of amino acid residues in the peptide sequence alters the peptide’ s assembly behaviors, affording various nanostructures. However, it remains elusive that how subtle changes in the peptide sequence influence the in vivo bioactivity of peptide-based nanocarriers, further impacting the efficacy of the encapsulated drugs. We report here a class of isomeric pentapeptide amphiphiles that associate into filaments with different dimensions, which were further used as carriers of Diquafosol tetrasodium (DQS), for the treatment of dry eye disease. Our results suggest that subtle changes in peptide sequences resulted in dramatically different molecular packings and distinct morphologies, which were verified by molecular dynamics simulations. In vivo results show that the drug retention time could be prolonged by the peptidic nanostructures on the ocular surface but were highly morphological-dependent. The longer retention time promised better therapeutic efficacy. In terms of facile synthesis and good biocompatibility, we believe that these peptides could be used for eye disease treatments or other related areas.

Characterization of bovine immunodeficiency virus genes and proteins

The goal of the study was determining the effect of natural selection on the bovine immunodeficiency virus (BIV) through the identification of polymorphisms by comparing a number of genes, open reading frames and proteins and analyzing the effect of nonsynonymous substitutions in the Vif protein of BIV isolates on the Vif conformational parameters. The selection pressure on the genes was estimated by Tajima test, as well as the determination of the ratio of nonsynonymous substitutions (Ka) to synonymous (Ks) Ka/Ks. Ka and Ks coefficients, their ratio (Ka/Ks) were calculated on the basis of alignments of amino acid and nucleotide sequences of the vif gene of BIV isolates. The nonsynonymous (dN) to synonymous (dS) substitution rate ratio per nucleotide site dN/dS was calculated to estimate the effect of selection on the vif gene by SLAC method on Datamonkey server. The number of hydrogen bonds, α-helices, β-sheets, β-turns for the protein tertiary structures of proteins was determined by I-TASSER server. Genes, open reading frames (ORFs) and the U3 regulatory region of BIV genome which are under the influence of selection have been identified. Gag, pol, s, vif genes, ORF W and ORF Y are under the negative (purifying) selection pressure. Env gene and the U3 regulatory region are under positive selection. Shannon entropy analysis (peaks that are specific to the positions of amino acid residues), interpreted as polymorphisms, revealed 16, 8, and 4 nonsynonymous substitutions for Pol, Gag, and Vif BIV proteins, respectively. Significant changes in the number of hydrogen bonds, α-helices, β-layers, β-turns were determined by the analysis of the effect of four nonsynonymous substitutions in the Vif protein on the conformational parameters of Vif of two BIV isolates. The multidirectional effect of selection on BIV genes is shown

Rapid Determination of the Topology of Oligomeric α-Helical Membrane Proteins by Water- and Lipid-Edited Methyl NMR.

Single-span oligomeric α-helical transmembrane proteins are common in virus ion channels, which are targets of antiviral drugs. Knowledge about the high-resolution structures of these oligomeric α-helical bundles is so far scarce. Structure determination of these membrane proteins by solid-state NMR traditionally requires resolving and assigning protein chemical shifts and measuring many interhelical distances, which are time-consuming. To accelerate experimental structure determination, here we introduce a simple solid-state NMR approach that uses magnetization transfer from water and lipid protons to the protein. By detecting the water- and lipid-transferred intensities of the high-sensitivity methyl 13C signals of Leu, Val, and Ile residues, which are highly enriched in these membrane proteins, we can derive models of the topology of these homo-oligomeric helical bundles. The topology is specified by the positions of amino acid residues in heptad repeats and the orientations of residues relative to the channel pore, lipids, and the helical interface. We demonstrate this water- and lipid-edited methyl NMR approach on the envelope (E) protein of SARS-CoV-2, the causative agent of the COVID-19 pandemic. We show that water-edited and lipid-edited 2D 13C-13C correlation spectra can be measured with sufficient sensitivity. Even without resolving multiple residues of the same type in the NMR spectra, we can obtain the helical bundle topology. We apply these experiments to the structurally unknown E proteins of the MERS coronavirus and the human coronavirus NL63. The resulting structural topologies show interesting differences in the positions of the aromatic residues in these three E proteins, suggesting that these viroporins may have different mechanisms of activation and ion conduction.

ROS-Triggered Gel-Sol Transition and Kinetics-Controlled Cargo Release by Methionine-Containing Peptides.

The gel-sol transition of self-assembling peptides is a useful switch for environment-dependent drug release. For their applications, kinetics control of the responses is important for matching the velocity of release to the target biological events. Here we demonstrate the chemical control of redox-triggered gel-sol transition kinetics of self-assembling peptides by altering the amino acid sequence. Amphiphilic peptides were developed in which a methionine residue was located in the middle (JigSAP-IMI) or near the N terminus (JigSAP-MII). Both peptides formed hydrogels under physiological conditions-forming β-sheet-based supramolecular nanofibers. In contrast, the oxidized forms remained in the solution state under identical conditions-adopting α-helix-rich secondary structures. Upon oxidation with H2 O2 , a reactive oxygen species, JigSAP-MII showed a faster gel-to-sol transition and cargo-releasing than JigSAP-IMI, thus indicating that the phase-transition and releasing kinetics of self-assembling peptides can be rationally controlled by the position of the reactive amino acid residue.

Casein calcium-binding peptides: Preparation, characterization, and promotion of calcium uptake in Caco-2 cell monolayers

In this study, casein calcium-binding peptides were isolated from casein hydrolysate using calcium-peptide binding properties and their banding properties were characterized. Subsequently, the promoted calcium absorption abilities of casein calcium-binding peptides in the Caco-2 cells monolayers were investigated. Amino acid composition analysis showed that casein calcium-binding peptide-calcium chelate are rich in Glu, Ser, and Asp, with a significant increase in proportion compared to the casein hydrolysate. Molecular weight analysis showed that approximately 90 % of the casein calcium-binding peptides are oligopeptides. Thirty-seven peptide sequences were identified by mass spectrometry, and the presence, quantity, and position of some specific amino acid residues were found to correlate with calcium-binding ability. Additionally, calcium-peptide binding properties were characterized by using Ultraviolet-Visible spectroscopy, Fourier transform infrared spectroscopy, and scanning electron microscopy, which indicated that calcium ions were mainly chelated with the amino nitrogen atoms and oxygen atoms on the carboxyl group of casein calcium-binding peptides, thus forming chelate with porous microstructures. Compared with the control group, the casein calcium-binding peptides treatment group showed a significant increase in calcium transport at 30, 60, 120 and 180 min, respectively, by 44.25 %, 31.21 %, 20.67 % and 24.08 %. Therefore, casein calcium-binding peptides are expected to be used as dietary calcium supplements.

DFT-aided infrared and electronic circular dichroism spectroscopic study of cyclopeptide S-PK6 and the exploration of its antitumor potential by molecular docking

Cyclic peptides have been widely explored as new chemical modalities in drug design, yet the structural study of bioactive cyclic peptides is often difficult due to the irregular constrained structure. In this article, we reported the infrared (IR) and electronic circular dichroism (ECD) spectroscopic study of an isoindolinone-containing analog (S-PK6) of natural antitumor cyclopeptide Phakellistatin 6. The peak positions of various amino acid residues in the IR spectrum of S-PK6 were specified with the aid of DFT-calculations. To establish a feasible and accurate method for simulating the ECD of small cyclic peptides, we performed a comparison of experimental ECD of S-PK6 with the theoretical spectra calculated by different methods, which indicated that the simulation at the TDDFT/CAM-B3LTP/cc-pVDZ level could provide a decent match for the experimental ECD spectrum of cyclopeptide. Motivated by our previous finding that the isoindolinone-containing cyclopeptides could efficiently inhibit the proliferation of HepG2 cells by decreasing the murine double minute2 (MDM2) protein level, we have investigated the possible binding mode between S-PK6 and MDM2 by molecular docking. Finally, molecular docking of S-PK6 with different cancer-related proteins have been performed, which suggested that diverse intramolecular hydrogen bonding networks might be formed in S-PK6 upon binding to different target protein structures, revealing a target-induced conformational adaptation mechanism. This research provides critical insights into the structure of small cyclopeptides and hints towards the design of peptidyl drugs.

InSPIRE: An Open-Source Tool for Increased Mass Spectrometry Identification Rates Using Prosit Spectral Prediction

Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase peptide spectrum match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example, when dealing with nonspecific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines. inSPIRE allows large-scale rescoring with data from multiple MS search files, increases sensitivity to minor differences in amino acid residue position, and can be applied to various MS sample types, including tryptic proteome digestions and immunopeptidomes. inSPIRE boosts PSM identification rates in immunopeptidomics, leading to better performance than the original Prosit rescoring pipeline, as confirmed by benchmarking of inSPIRE performance on ground truth datasets. The integration of various features in the inSPIRE backbone further boosts the PSM identification in immunopeptidomics, with a potential benefit for the identification of noncanonical peptides.

DeepZF: improved DNA-binding prediction of C2H2-zinc-finger proteins by deep transfer learning.

Cys2His2 zinc-finger (C2H2-ZF) proteins are the largest class of human transcription factors and hence play central roles in gene regulation and cell function. C2H2-ZF proteins are characterized by a DNA-binding domain containing multiple ZFs. A subset of the ZFs bind diverse DNA triplets. Despite their central roles, little is known about which of their ZFs are binding and how the DNA-binding preferences are encoded in the amino acid sequence of each ZF. We present DeepZF, a deep-learning-based pipeline for predicting binding ZFs and their DNA-binding preferences given only the amino acid sequence of a C2H2-ZF protein. To the best of our knowledge, we compiled the first in vivo dataset of binding and non-binding ZFs for training the first ZF-binding classifier. Our classifier, which is based on a novel protein transformer, achieved an average AUROC of 0.71. Moreover, we took advantage of both in vivo and in vitro datasets to learn the recognition code of ZF-DNA binding through transfer learning. Our newly developed model, which is the first to utilize deep learning for the task, achieved an average Pearson correlation greater than 0.94 over each of the three DNA binding positions. Together, DeepZF outperformed extant methods in the task of C2H2-ZF protein DNA-binding preferences prediction: it achieved an average Pearson correlation of 0.42 in motif similarity compared with an average correlation smaller than 0.1 achieved by extant methods. By applying established interpretability techniques, we show that DeepZF inferred biologically relevant binding principles, such as the effect of amino acid residue positions on ZF DNA-binding potential. DeepZF code, model, and results are available via github.com/OrensteinLab/DeepZF. Supplementary data are available at Bioinformatics online.

Chemometrics and genome mining reveal an unprecedented family of sugar acid–containing fungal nonribosomal cyclodepsipeptides

Xylomyrocins, a unique group of nonribosomal peptide secondary metabolites, were discovered in Paramyrothecium and Colletotrichum spp. fungi by employing a combination of high-resolution tandem mass spectrometry (HRMS/MS)-based chemometrics, comparative genome mining, gene disruption, stable isotope feeding, and chemical complementation techniques. These polyol cyclodepsipeptides all feature an unprecedented d-xylonic acid moiety as part of their macrocyclic scaffold. This biosynthon is derived from d-xylose supplied by xylooligosaccharide catabolic enzymes encoded in the xylomyrocin biosynthetic gene cluster, revealing a novel link between carbohydrate catabolism and nonribosomal peptide biosynthesis. Xylomyrocins from different fungal isolates differ in the number and nature of their amino acid building blocks that are nevertheless incorporated by orthologous nonribosomal peptide synthetase (NRPS) enzymes. Another source of structural diversity is the variable choice of the nucleophile for intramolecular macrocyclic ester formation during xylomyrocin chain termination. This nucleophile is selected from the multiple available alcohol functionalities of the polyol moiety, revealing a surprising polyspecificity for the NRPS terminal condensation domain. Some xylomyrocin congeners also feature N-methylated amino acid residues in positions where the corresponding NRPS modules lack N-methyltransferase (M) domains, providing a rare example of promiscuous methylation in the context of an NRPS with an otherwise canonical, collinear biosynthetic program.

Comparative In-silico Analysis of Structural and Functional Attributes of Microbial Lipases

Lipase is the third most demanding enzyme group and is a major component of fat metabolism. It is omnipresent in nature. Microbial lipases are highly specific and economically efficient enzymes. They have applications in a variety of industries. In this study, the computational result elucidates structural and functional attributes of eight selected lipases from Uniprot. Primary, secondary, and tertiary structures obtained from Swiss and Profunc are analyzed. Further, they are validated with the help of Saves Server. COACH and COFACTOR is used for functional analysis. Lastly, phylogenetic tree is developed using MegaX software. Our in-silico analysis predicted lipases as alpha-beta-gamma protein with different ligand binding sites at different amino acid residue positions. Furthermore, they exhibited almost similar functional traits like catalytic activity and hydrolase activity. Overall, this study provides an insight into structural-functional characteristics of different lipases of microbial origin.

The Local Environment of Loop Switch 1 Modulates the Rate of ATP-Induced Dissociation of Human Cardiac Actomyosin.

Two isoforms of human cardiac myosin, alpha and beta, share significant sequence similarities but show different kinetics. The alpha isoform is a faster motor; it spends less time being strongly bound to actin during the actomyosin cycle. With alpha isoform, actomyosin dissociates faster upon ATP binding, and the affinity of ADP to actomyosin is weaker. One can suggest that the isoform-specific actomyosin kinetics is regulated at the nucleotide binding site of human cardiac myosin. Myosin is a P-loop ATPase; the nucleotide-binding site consists of P-loop and loops switch 1 and 2. All three loops position MgATP for successful hydrolysis. Loops sequence is conserved in both myosin isoforms, and we hypothesize that the isoform-specific structural element near the active site regulates the rate of nucleotide binding and release. Previously we ran molecular dynamics simulations and found that loop S291-E317 near loop switch 1 is more compact and exhibits larger fluctuations of the position of amino acid residues in beta isoform than in alpha. In alpha isoform, the loop forms a salt bridge with loop switch 1, the bridge is not present in beta isoform. Two isoleucines I303 and I313 of loop S291-E317 are replaced with valines in alpha isoform. We introduced a double mutation I303V:I313V in beta isoform background and studied how the mutation affects the rate of ATP binding and ADP dissociation from actomyosin. We found that ATP-induced actomyosin dissociation occurs faster in the mutant, but the rate of ADP release remains the same as in the wild-type beta isoform. Due to the proximity of loop S291-E317 and loop switch 1, a faster rate of ATP-induced actomyosin dissociation indicates that loop S291-E317 affects structural dynamics of loop switch 1, and that loop switch 1 controls ATP binding to the active site. A similar rate of ADP dissociation from actomyosin in the mutant and wild-type myosin constructs indicates that loop switch 1 does not control ADP release from actomyosin.

A Novel Insight into Screening for Antioxidant Peptides from Hazelnut Protein: Based on the Properties of Amino Acid Residues.

This study used the properties of amino acid residues to screen antioxidant peptides from hazelnut protein. It was confirmed that the type and position of amino acid residues, grand average of hydropathy, and molecular weight of a peptide could be comprehensively applied to obtain desirable antioxidants after analyzing the information of synthesized dipeptides and BIOPEP database. As a result, six peptides, FSEY, QIESW, SEGFEW, IDLGTTY, GEGFFEM, and NLNQCQRYM were identified from hazelnut protein hydrolysates with higher antioxidant capacity than reduced Glutathione (GSH) against linoleic acid oxidation. The peptides having Tyr residue at C-terminal were found to prohibit the oxidation of linoleic acid better than others. Among them, peptide FSEY inhibited the rancidity of hazelnut oil very well in an oil-in-water emulsion. Additionally, quantum chemical parameters proved Tyr-residue to act as the active site of FSEY are responsible for its antioxidation. This is the first presentation of a novel approach to excavating desired antioxidant peptides against lipid oxidation from hazelnut protein via the properties of amino acid residues.

Exploring proteins in living cells

<p indent="0mm">Proteins have been studied for over <sc>200 years,</sc> but much of that work has been performed <italic>in vitro</italic>. This article briefly summarized the current status of protein exploration in living cells, and then presented some of my own representative findings in this field. First, I summarized the major methodologies hitherto developed for studying proteins <italic>in vivo</italic>, including visualizing a target protein by fusing it with the green fluorescent protein; investigating the tertiary structure of the target protein via in-cell nuclear magnetic resonance spectroscopy; and exploring the behaviors of a target protein by genetically labeling it with different types of unnatural amino acids. Next, I described how my laboratory applied and modified an <italic>in vivo</italic> methodology in which the genetic introduction of a photoactivatable, unnatural amino acid at a selected residue position in a target protein then mediates crosslinking of that protein with other proteins when the cells are irradiated by UV light. By improving that method, my laboratory contributed the following: (1) The creation of a bacterial strain with a genome that has a gene that encodes the orthogonal aminoacyl-tRNA synthetase and one that encodes the tRNA that are both needed to incorporate an unnatural amino acid (i.e., Bpa) into any target protein. (2) The development of a system in which the unnatural amino acid is randomly introduced at each of the target protein’s amino acid residue positions and, after detecting a meaningful interaction, DNA sequencing subsequently identifies that unnatural amino acid’s exact position. (3) The incorporation of the unnatural amino acid into a target protein by directly modifying the endogenous target gene in the genomic DNA so that the variant protein is produced spatiotemporally identical to that of the wild-type protein. (4) The development of a high-throughput polyacrylamide gel electrophoresis system in which 384 protein samples can be analyzed in a single gel. Finally, I described a few representative results from my lab by using <italic>in vivo</italic> protein photocrosslinking analysis: (1) The serendipitous discovery of a reversible subcellular structure (regrowth-delay body) that forms when a highly selected group of important proteins assembles only in non-dividing bacterial cells, and then dissolves when the cells resume growth. Their presence thus marks dormant persister bacterial cells that are known to tolerate antibiotics. (2) A revelation of a “gear shifting” mechanism that modulates bacterial ATP synthase activity via adaptation of its ε-subunit to the “inserted” or “non-inserted” conformation as the cell responds to a variety of favorable to unfavorable cellular conditions. (3) The identification of a supramolecular protein complex that is composed of proteins present in the cytoplasm, inner membrane, periplasm and outer membrane of Gram-negative bacteria, and that mediates the biogenesis of a group of outer membrane proteins. (4) The unveiling of a unique way that the acid stress chaperone HdeA acts. It exhibits biological activity while its tertiary structure becomes largely disordered, and then it protects other chaperones under acidic conditions. (5) A clarification that the long-designated bifunctional protein DegP acts primarily as a proteinase with little chaperone activity. (6) The discovery that small heat shock proteins are activated in a temperature-responsive, cascade manner that allows them to significantly increase their biological activity at high temperatures. I then conclude with a list of unresolved issues regarding protein exploration in living cells.

The role of zinc finger linkers in zinc finger protein binding to DNA.

Zinc finger proteins (ZFP) play important roles in cellular processes. The DNA binding region of ZFP consists of 3 zinc finger DNA binding domains connected by amino acid linkers, the sequence TGQKP connects ZF1 and ZF2, and TGEKP connects ZF2 with ZF3. Linkers act to tune the zinc finger protein in the right position to bind its DNA target, the type of amino acid residues and length of linkers reflect on ZF1-ZF2-ZF3 interactions and contribute to the search and recognition process of ZF protein to its DNA target. Linker mutations and the affinity of the resulting mutants to specific and nonspecific DNA targets were studied by MD simulations and MM_GB(PB)SA. The affinity of mutants to DNA varied with type and position of amino acid residue. Mutation of K in TGQKP resulted in loss in affinity due to the loss of positive K interaction with phosphates, mutation of G showed loss in affinity to DNA, WT protein and all linker mutants showed loss in affinity to a nonspecific DNA target, this finding confirms previous reports which interpreted this loss in affinity as due to ZF1 having an anchoring role, and ZF3 playing an explorer role in the binding mechanism. The change in ZFP-DNA affinity with linker mutations is discussed in view of protein structure and role of linker residues in binding.

Non-canonical proline-tyrosine interactions with multiple host proteins regulate Ebola virus infection.

The Ebola virus VP30 protein interacts with the viral nucleoprotein and with host protein RBBP6 via PPxPxY motifs that adopt non-canonical orientations, as compared to other proline-rich motifs. An affinity tag-purification mass spectrometry approach identified additional PPxPxY-containing host proteins hnRNP L, hnRNPUL1, and PEG10, as VP30 interactors. hnRNP L and PEG10, like RBBP6, inhibit viral RNA synthesis and EBOV infection, whereas hnRNPUL1 enhances. RBBP6 and hnRNP L modulate VP30 phosphorylation, increase viral transcription, andexert additive effects on viral RNA synthesis. PEG10 has more modest inhibitory effects on EBOV replication. hnRNPUL1 positively affects viral RNA synthesis but in a VP30-independent manner. Binding studies demonstrate variable capacity of the PPxPxY motifs from these proteins to bind VP30, define PxPPPPxY as an optimal binding motif, and identify the fifth proline and the tyrosine as most critical for interaction. Competition binding and hydrogen-deuterium exchange mass spectrometry studies demonstrate that each protein binds a similar interface on VP30. VP30 therefore presents a novel proline recognition domain that is targeted by multiple host proteins to modulate viral transcription.