Effect of Sec62 on the conformation of the Sec61 channel in yeast.

Most eukaryotic secretory and membrane proteins are funneled by the Sec61 complex into the secretory pathway. Furthermore, some substrate peptides rely on two essential accessory proteins, Sec62 and Sec63, being present to assist with their translocation via the Sec61 channel in post-translational translocation. Cryo-electron microscopy (cryo-EM) recently succeeded in determining atomistic structures of unbound and signal sequence-engaged Sec complexes from Saccharomyces cerevisiae, involving the Sec61 channel and the proteins Sec62, Sec63, Sec71 and Sec72. In this study, we investigated the conformational effects of Sec62 on Sec61. Indeed, we observed in molecular dynamics simulations that the conformational dynamics of lateral gate, plug and pore region of Sec61 are altered by the presence/absence of Sec62. In molecular dynamics simulations that were started from the cryo-EM structures of Sec61 coordinated to Sec62 or of apo Sec61, we observed that the luminal side of the lateral gate gradually adopts a closed conformation similar to the apo state during unbound state simulations. In contrast, it adopts a wider conformation in the bound state. Furthermore, we demonstrate that the conformation of the active (substrate-bound) state of the Sec61 channel shifts toward an alternative conformation in the absence of the substrate. We suggest that the signal peptide holds/stabilizes the active state conformation of Sec61 during post-translational translocation. Thus, our study explains the effect of Sec62 on the conformation of the Sec61 channel and describes the conformational transitions of Sec61 channel.

Synthesis, Biological Evaluation and Docking Studies of Ring-Opened Analogues of Ipomoeassin F.

The plant-derived macrocyclic resin glycoside ipomoeassin F (Ipom-F) binds to Sec61α and significantly disrupts multiple aspects of Sec61-mediated protein biogenesis at the endoplasmic reticulum, ultimately leading to cell death. However, extensive assessment of Ipom-F as a molecular tool and a therapeutic lead is hampered by its limited production scale, largely caused by intramolecular assembly of the macrocyclic ring. Here, using in vitro and/or in cellula biological assays to explore the first series of ring-opened analogues for the ipomoeassins, and indeed all resin glycosides, we provide clear evidence that macrocyclic integrity is not required for the cytotoxic inhibition of Sec61-dependent protein translocation by Ipom-F. Furthermore, our modeling suggests that open-chain analogues of Ipom-F can interact with multiple sites on the Sec61α subunit, most likely located at a previously identified binding site for mycolactone and/or the so-called lateral gate. Subsequent in silico-aided design led to the discovery of the stereochemically simplified analogue 3 as a potent, alternative lead compound that could be synthesized much more efficiently than Ipom-F and will accelerate future ipomoeassin research in chemical biology and drug discovery. Our work may also inspire further exploration of ring-opened analogues of other resin glycosides.

Signal Peptide Features Determining the Substrate Specificities of Targeting and Translocation Components in Human ER Protein Import.

In human cells, approximately 30% of all polypeptides enter the secretory pathway at the level of the endoplasmic reticulum (ER). This process involves cleavable amino-terminal signal peptides (SPs) or more or less amino-terminal transmembrane helices (TMHs), which serve as targeting determinants, at the level of the precursor polypeptides and a multitude of cytosolic and ER proteins, which facilitate their ER import. Alone or in combination SPs and TMHs guarantee the initial ER targeting as well as the subsequent membrane integration or translocation. Cytosolic SRP and SR, its receptor in the ER membrane, mediate cotranslational targeting of most nascent precursor polypeptide chains to the polypeptide-conducting Sec61 complex in the ER membrane. Alternatively, fully-synthesized precursor polypeptides and certain nascent precursor polypeptides are targeted to the ER membrane by either the PEX-, SND-, or TRC-pathway. Although these targeting pathways may have overlapping functions, the question arises how relevant this is under cellular conditions and which features of SPs and precursor polypeptides determine preference for a certain pathway. Irrespective of their targeting pathway(s), most precursor polypeptides are integrated into or translocated across the ER membrane via the Sec61 channel. For some precursor polypeptides specific Sec61 interaction partners have to support the gating of the channel to the open state, again raising the question why and when this is the case. Recent progress shed light on the client spectrum and specificities of some auxiliary components, including Sec62/Sec63, TRAM1 protein, and TRAP. To address the question which precursors use a certain pathway or component in intact human cells, i.e., under conditions of fast translation rates and molecular crowding, in the presence of competing precursors, different targeting organelles, and relevant stoichiometries of the involved components, siRNA-mediated depletion of single targeting or transport components in HeLa cells was combined with label-free quantitative proteomics and differential protein abundance analysis. Here, we present a summary of the experimental approach as well as the resulting differential protein abundance analyses and discuss their mechanistic implications in light of the available structural data.

Phenylbutyrate rescues the transport defect of the Sec61α mutations V67G and T185A for renin.

The human Sec61 complex is a widely distributed and abundant molecular machine. It resides in the membrane of the endoplasmic reticulum to channel two types of cargo: protein substrates and calcium ions. The SEC61A1 gene encodes for the pore-forming Sec61α subunit of the Sec61 complex. Despite their ubiquitous expression, the idiopathic SEC61A1 missense mutations p.V67G and p.T185A trigger a localized disease pattern diagnosed as autosomal dominant tubulointerstitial kidney disease (ADTKD-SEC61A1). Using cellular disease models for ADTKD-SEC61A1, we identified an impaired protein transport of the renal secretory protein renin and a reduced abundance of regulatory calcium transporters, including SERCA2. Treatment with the molecular chaperone phenylbutyrate reversed the defective protein transport of renin and the imbalanced calcium homeostasis. Signal peptide substitution experiments pointed at targeting sequences as the cause for the substrate-specific impairment of protein transport in the presence of the V67G or T185A mutations. Similarly, dominant mutations in the signal peptide of renin also cause ADTKD and point to impaired transport of this renal hormone as important pathogenic feature for ADTKD-SEC61A1 patients as well.

Mycolactone enhances the Ca2+ leak from endoplasmic reticulum by trapping Sec61 translocons in a Ca2+ permeable state.

The Mycobacterium ulcerans exotoxin, mycolactone, is an inhibitor of co-translational translocation via the Sec61 complex. Mycolactone has previously been shown to bind to, and alter the structure of the major translocon subunit Sec61α, and change its interaction with ribosome nascent chain complexes. In addition to its function in protein translocation into the ER, Sec61 also plays a key role in cellular Ca2+ homeostasis, acting as a leak channel between the endoplasmic reticulum (ER) and cytosol. Here, we have analysed the effect of mycolactone on cytosolic and ER Ca2+ levels using compartment-specific sensors. We also used molecular docking analysis to explore potential interaction sites for mycolactone on translocons in various states. These results show that mycolactone enhances the leak of Ca2+ ions via the Sec61 translocon, resulting in a slow but substantial depletion of ER Ca2+. This leak was dependent on mycolactone binding to Sec61α because resistance mutations in this protein completely ablated the increase. Molecular docking supports the existence of a mycolactone-binding transient inhibited state preceding translocation and suggests mycolactone may also bind Sec61α in its idle state. We propose that delayed ribosomal release after translation termination and/or translocon 'breathing' during rapid transitions between the idle and intermediate-inhibited states allow for transient Ca2+ leak, and mycolactone's stabilisation of the latter underpins the phenotype observed.

Molecular Modeling of Signal Peptide Recognition by Eukaryotic Sec Complexes.

Here, we review recent molecular modelling and simulation studies of the Sec translocon, the primary component/channel of protein translocation into the endoplasmic reticulum (ER) and bacterial periplasm, respectively. Our focus is placed on the eukaryotic Sec61, but we also mention modelling studies on prokaryotic SecY since both systems operate in related ways. Cryo-EM structures are now available for different conformational states of the Sec61 complex, ranging from the idle or closed state over an inhibited state with the inhibitor mycolactone bound near the lateral gate, up to a translocating state with bound substrate peptide in the translocation pore. For all these states, computational studies have addressed the conformational dynamics of the translocon with respect to the pore ring, the plug region, and the lateral gate. Also, molecular simulations are addressing mechanistic issues of insertion into the ER membrane vs. translocation into the ER, how signal-peptides are recognised at all in the translocation pore, and how accessory proteins affect the Sec61 conformation in the co- and post-translational pathways.

Quantitative Proteomics and Differential Protein Abundance Analysis after Depletion of Putative mRNA Receptors in the ER Membrane of Human Cells Identifies Novel Aspects of mRNA Targeting to the ER.

In human cells, one-third of all polypeptides enter the secretory pathway at the endoplasmic reticulum (ER). The specificity and efficiency of this process are guaranteed by targeting of mRNAs and/or polypeptides to the ER membrane. Cytosolic SRP and its receptor in the ER membrane facilitate the cotranslational targeting of most ribosome-nascent precursor polypeptide chain (RNC) complexes together with the respective mRNAs to the Sec61 complex in the ER membrane. Alternatively, fully synthesized precursor polypeptides are targeted to the ER membrane post-translationally by either the TRC, SND, or PEX19/3 pathway. Furthermore, there is targeting of mRNAs to the ER membrane, which does not involve SRP but involves mRNA- or RNC-binding proteins on the ER surface, such as RRBP1 or KTN1. Traditionally, the targeting reactions were studied in cell-free or cellular assays, which focus on a single precursor polypeptide and allow the conclusion of whether a certain precursor can use a certain pathway. Recently, cellular approaches such as proximity-based ribosome profiling or quantitative proteomics were employed to address the question of which precursors use certain pathways under physiological conditions. Here, we combined siRNA-mediated depletion of putative mRNA receptors in HeLa cells with label-free quantitative proteomics and differential protein abundance analysis to characterize RRBP1- or KTN1-involving precursors and to identify possible genetic interactions between the various targeting pathways. Furthermore, we discuss the possible implications on the so-called TIGER domains and critically discuss the pros and cons of this experimental approach.

How does Sec63 affect the conformation of Sec61 in yeast?

The Sec complex catalyzes the translocation of proteins of the secretory pathway into the endoplasmic reticulum and the integration of membrane proteins into the endoplasmic reticulum membrane. Some substrate peptides require the presence and involvement of accessory proteins such as Sec63. Recently, a structure of the Sec complex from Saccharomyces cerevisiae, consisting of the Sec61 channel and the Sec62, Sec63, Sec71 and Sec72 proteins was determined by cryo-electron microscopy (cryo-EM). Here, we show by co-precipitation that the Sec61 channel subunit Sbh1 is not required for formation of stable Sec63-Sec61 contacts. Molecular dynamics simulations started from the cryo-EM conformation of Sec61 bound to Sec63 and of unbound Sec61 revealed how Sec63 affects the conformation of Sec61 lateral gate, plug, pore region and pore ring diameter via three intermolecular contact regions. Molecular docking of SRP-dependent vs. SRP-independent signal peptide chains into the Sec61 channel showed that the pore regions affected by presence/absence of Sec63 play a crucial role in positioning the signal anchors of SRP-dependent substrates nearby the lateral gate.

Effect of Concentration, Chain Length, Hydrophobicity, and an External Electric Field on the Growth of Mixed Alkanethiol Self-Assembled Monolayers: A Molecular Dynamics Study.

Growing functionalized self-assembled monolayers (SAMs) with fewer defects and lower cost is the focus of ongoing investigations. In the present study, molecular dynamics simulations were performed to investigate the process of SAM formation on a gold substrate from mixed alkanethiolates in ethanol solution. Using the mixed-SAM system of 11-mercaptoundecanoic acid (MUA) with either 1-decanethiol (C9CH3) or 6-mercaptohexanol (C6OH) in a 3:7 ratio as the standard SAM model, we systematically investigated the effects of the concentration, chain length, functional group, and an external electric field on SAM growth. The results showed that the initial growth rate and surface coverage of the SAM are dependent on the ligand concentration. At a certain high concentration (about 1.2-1.5 times the minimum concentration), the final surface coverage is optimal. Reducing the chain length and increasing the proportion of hydrophobic diluting molecules are effective ways to improve the surface coverage, but the compositional ligands have to be changed, which may not be desirable for the functional requirements of SAMs. Furthermore, by investigating the behavior of the alkanethiolates and ethanol solvent under an applied external field, we find that a strong electric field with a proper field direction can facilitate the generation of defect-free monolayers. These findings will contribute to the understanding of mixed-SAM formation and provide insight into experimental design for efficient and effective SAM formation.

Deep-AmPEP30: Improve Short Antimicrobial Peptides Prediction with Deep Learning.

Antimicrobial peptides (AMPs) are a valuable source of antimicrobial agents and a potential solution to the multi-drug resistance problem. In particular, short-length AMPs have been shown to have enhanced antimicrobial activities, higher stability, and lower toxicity to human cells. We present a short-length (≤30 aa) AMP prediction method, Deep-AmPEP30, developed based on an optimal feature set of PseKRAAC reduced amino acids composition and convolutional neural network. On a balanced benchmark dataset of 188 samples, Deep-AmPEP30 yields an improved performance of 77% in accuracy, 85% in the area under the receiver operating characteristic curve (AUC-ROC), and 85% in area under the precision-recall curve (AUC-PR) over existing machine learning-based methods. To demonstrate its power, we screened the genome sequence of Candida glabrata-a gut commensal fungus expected to interact with and/or inhibit other microbes in the gut-for potential AMPs and identified a peptide of 20 aa (P3, FWELWKFLKSLWSIFPRRRP) with strong anti-bacteria activity against Bacillus subtilis and Vibrio parahaemolyticus. The potency of the peptide is remarkably comparable to that of ampicillin. Therefore, Deep-AmPEP30 is a promising prediction tool to identify short-length AMPs from genomic sequences for drug discovery. Our method is available at https://cbbio.cis.um.edu.mo/AxPEP for both individual sequence prediction and genome screening for AMPs.

Refined Empirical Force Field to Model Protein-Self-Assembled Monolayer Interactions Based on AMBER14 and GAFF.

Understanding protein interaction with material surfaces is important for the development of nanotechnological devices. The structures and dynamics of proteins can be studied via molecular dynamics (MD) if the protein-surface interactions can be accurately modeled. To answer this question, we computed the adsorption free energies of peptides (representing eleven different amino acids) on a hydrophobic self-assembled monolayer (CH3-SAM) and compared them to the benchmark experimental data set. Our result revealed that existing biomolecular force fields, GAFF and AMBER ff14sb, cannot reproduce the experimental peptide adsorption free energies by Wei and Latour (Langmuir, 2009, 25, 5637-5646). To obtain the improved force fields, we systematically tuned the Lennard-Jones parameters of selected amino acid sidechains and the functional group of SAM with repeated metadynamics and umbrella sampling simulations. The final parameter set has yielded a significant improvement in the free energy values with R = 0.83 and MSE = 0.65 kcal/mol. We applied the refined force field to predict the initial adsorption orientation of lysozyme on CH3-SAM. Two major orientations-face-down and face-up-were predicted. Our analysis on the protein structure, solvent accessible surface area, and binding of native ligand NAG3 suggested that lysozyme in the face-up orientation can remain active after initial adsorption. However, because of its weaker affinity (ΔΔG = 7.86 kcal/mol) for the ligand, the bioactivity of the protein is expected to reduce. Our work facilitates the use of MD for the study of protein-SAM systems. The refined force field compatible with GROMACS is available at https://cbbio.cis.um.edu.mo/software/SAMFF .

TNF Receptor Type II as an Emerging Drug Target for the Treatment of Cancer, Autoimmune Diseases, and Graft-Versus-Host Disease: Current Perspectives and In Silico Search for Small Molecule Binders.

There is now compelling evidence that TNF receptor type II (TNFR2) is predominantly expressed on CD4+Foxp3+ regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), and plays a major role in the expansion and function of Tregs and MDSCs. Consequently, targeting of TNFR2 by either antagonists or agonists may represent a novel strategy in the treatment of cancer and autoimmune diseases, by downregulating or upregulating suppressor cell activity. The advance in the understanding of complex structure of TNFR2 and its binding with TNF at molecular levels offers opportunity for structure-guided drug discovery. This article reviews the current evidences regarding the decisive role of TNFR2 in immunosuppressive function of Tregs and MDSCs, and the current effort to develop novel TNFR2-targeting therapeutic agents in the treatment of cancer, autoimmune diseases, and graft-versus-host disease. To shed light on the potential TNFR2-targeting small molecules, we for the first time performed virtual screening of 400,000 natural compounds against the two TNF-binding sites, regions 3 and 4, of TNFR2. Our result showed that the top hits at region 4 had slightly higher docking energies than those at region 3. Nevertheless, free energy calculation from the TNF-TNFR2 molecular dynamics simulation revealed that the binding strength of TNF in region 3 is only one-tenth of that in region 4. This suggests that region 3 is a potentially more viable binding site to be targeted by small molecules than region 4. Therefore, the effectiveness in targeting region 3 of TNFR2 deserves further investigation.

AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest.

Antimicrobial peptides (AMPs) are promising candidates in the fight against multidrug-resistant pathogens owing to AMPs' broad range of activities and low toxicity. Nonetheless, identification of AMPs through wet-lab experiments is still expensive and time consuming. Here, we propose an accurate computational method for AMP prediction by the random forest algorithm. The prediction model is based on the distribution patterns of amino acid properties along the sequence. Using our collection of large and diverse sets of AMP and non-AMP data (3268 and 166791 sequences, respectively), we evaluated 19 random forest classifiers with different positive:negative data ratios by 10-fold cross-validation. Our optimal model, AmPEP with the 1:3 data ratio, showed high accuracy (96%), Matthew's correlation coefficient (MCC) of 0.9, area under the receiver operating characteristic curve (AUC-ROC) of 0.99, and the Kappa statistic of 0.9. Descriptor analysis of AMP/non-AMP distributions by means of Pearson correlation coefficients revealed that reduced feature sets (from a full-featured set of 105 to a minimal-feature set of 23) can result in comparable performance in all respects except for some reductions in precision. Furthermore, AmPEP outperformed existing methods in terms of accuracy, MCC, and AUC-ROC when tested on benchmark datasets.

Molecular Dynamics Information Improves cis-Peptide-Based Function Annotation of Proteins.

cis-Peptide bonds, whose occurrence in proteins is rare but evolutionarily conserved, are implicated to play an important role in protein function. This has led to their previous use in a homology-independent, fragment-match-based protein function annotation method. However, proteins are not static molecules; dynamics is integral to their activity. This is nicely epitomized by the geometric isomerization of cis-peptide to trans form for molecular activity. Hence we have incorporated both static (cis-peptide) and dynamics information to improve the prediction of protein molecular function. Our results show that cis-peptide information alone cannot detect functional matches in cases where cis-trans isomerization exists but 3D coordinates have been obtained for only the trans isomer or when the cis-peptide bond is incorrectly assigned as trans. On the contrary, use of dynamics information alone includes false-positive matches for cases where fragments with similar secondary structure show similar dynamics, but the proteins do not share a common function. Combining the two methods reduces errors while detecting the true matches, thereby enhancing the utility of our method in function annotation. A combined approach, therefore, opens up new avenues of improving existing automated function annotation methodologies.

Pipeline for inferring protein function from dynamics using coarse-grained molecular mechanics forcefield.

Dynamics is integral to the function of proteins, yet the use of molecular dynamics (MD) simulation as a technique remains under-explored for molecular function inference. This is more important in the context of genomics projects where novel proteins are determined with limited evolutionary information. Recently we developed a method to match the query protein's flexible segments to infer function using a novel approach combining analysis of residue fluctuation-graphs and auto-correlation vectors derived from coarse-grained (CG) MD trajectory. The method was validated on a diverse dataset with sequence identity between proteins as low as 3%, with high function-recall rates. Here we share its implementation as a publicly accessible web service, named DynFunc (Dynamics Match for Function) to query protein function from ≥1 µs long CG dynamics trajectory information of protein subunits. Users are provided with the custom-developed coarse-grained molecular mechanics (CGMM) forcefield to generate the MD trajectories for their protein of interest. On upload of trajectory information, the DynFunc web server identifies specific flexible regions of the protein linked to putative molecular function. Our unique application does not use evolutionary information to infer molecular function from MD information and can, therefore, work for all proteins, including moonlighting and the novel ones, whenever structural information is available. Our pipeline is expected to be of utility to all structural biologists working with novel proteins and interested in moonlighting functions.

De novo inference of protein function from coarse-grained dynamics.

Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 µs coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all.