Search

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/8102883. This review arose out of a course for graduate students in the life sciences at UCSF, "Peer Review in the Life Sciences," which aims to introduce junior scientists to peer review in a critical yet constructive way. The students selected preprints to review, led discussions of them, drafted reviews, and revised them based on feedback from peers and instructors. Summary The major goal of this paper is to functionally characterize ginsentides, a recently discovered class of cysteine-rich pseudocyclic peptides isolated from the herb ginseng. The authors point out broad reported beneficial effects of ginseng and highlight the knowledge gap regarding mechanisms, and posit that bioactive ginsentides could provide an explanation. This paper aims to close this knowledge gap by linking a previously structurally characterized ginsentide, TP1 (Tam et al. 2018 Sci. Rep.), to a broad variety of beneficial physiological effects such as vasorelaxation and potentially reduced inflammation and stress. The major strength of this paper is that the authors perform experiments probing the relationship between ginsentides and a variety of pathways linked to positive physiological effects. The major weakness of this paper is that, despite the individual experiments, there is a lack of a final coherent mechanistic model for ginsentide action. For example: Fig. 2 demonstrates TP1 cell entry, but does not show intracellular persistence or colocalization with the potential targets suggested in Fig. 3. In Fig. 4 and 7, where TP1 would be acting (intra- or extracellularly) in these pathways is unclear. Fig. 6, however, strongly suggests extracellular binding activity of TP1. The authors do not suggest a model for TP1 activity that suitably integrates the variety and types of effects observed and reconciles potentially contradictory details. Overall, this paper provides a promising roadmap for how phytochemicals may impact medicine, especially cardiovascular health, but requires further elaboration to conclusively demonstrate ginsentide's role in the entirety of the purported effects. Major Points We found it difficult to synthesize the data into an overall consistent model of ginsentide action. The paper begins with data emphasizing the constrained, cysteine-rich cyclic nature of ginsentides in their entrance into cells. However, how structure contributes to this effect is not examined. Indeed, because much of the other data presented suggests extracellular activity, we are unclear how the purported cell penetrating properties play a role. Such a claim would require a structural control (eg. a reduced or denatured TP1 peptide) to demonstrate structure-based cell entry in Fig 2. Could the authors speculate on the persistence of the unique disulfide-rich structure during uptake and inside the cell, as well? Are these data consistent with observed putative extracellular effects in Fig. 5-7? The interpretation of NO production data (Fig. 4) could be clearer by demonstrating or speculating as to whether TP1 needs to enter cells to activate this pathway or if extracellular binding is sufficient. We question the conclusions about ginsentide selectivity for the adrenergic receptor (Fig. 5) based on data that show ginsentides reduce aortic contractions. It is difficult to see a mechanistic link between the two, and no speculation is provided. Fig. 6-7 suggest TP1 is binding extracellular targets, which is difficult to reconcile with the internalization mechanism of the earlier figures. Is this on a faster timescale than the uptake? The overall model suggested is that TP1 is a promiscuous binding peptide that inhibits various protein functions but it is unclear how and whether this depends on the native, disulfide-rich structure of the protein. We are unable to properly evaluate the proteomics results from the material presented. In the proteomic interaction experiment (Fig. 3), how were background proteins determined? This is a key aspect that is not explained. What exactly were the "control" experimental conditions? The lack of sufficient detail here renders the meaning of these results impossible to determine. The provided data do not directly support the textual claim that the level of TP1-induced NO production by endothelial cells is sufficient to cause vasorelaxation. It is unclear how much of the vasorelaxation in Fig. 5 is attributable specifically to the produced NO in Fig 4. To establish a causal link, one would need to demonstrate that TP1 does not induce vasorelaxation in a NO-producing-deficient background. We suggest altering the claim (lines 21-22) to allow for a correlative interpretation given that Fig. 4 and Fig. 5 are different sets of experiments. We also suggest adding context that discusses if observed effect sizes have been observed elsewhere (eg. Wang et al. Exp. Ther. Med. 2016). Given that only behavioral data is given for the mice experiments (Fig. 8-9), we suggest altering the claim that ginsentides can reduce stress and depressive behavior (lines 26-27, 302). The behavioral tests used are thought to be measures of depression-like behavior and it is unclear if it is appropriate to conflate stress and depression. To support the current claim about stress, we suggest measuring corticosterone levels in TP1-treated mice exposed to stressful situations. With the limited set of experiments performed, consider alternative or more parsimonious interpretations of the results, such as inducing changes to general mobility, hyperactivity, pain, etc. To support the current claim about depression, mobility should be controlled for as a potential confound to determine if TP1 increases mobility absent stressful situations. Minor Points Technical questions: The authors argue that ginsentides can act as a therapeutic because they would be less prone to degradation and heat sensitivity, and a large concern regarding the field of therapeutics is cell delivery. Given the evidenced contribution of energy-dependent endocytosis in cell uptake of TP1 in Fig. 2, we do not believe "cell-penetrating" is the best phrasing as this invokes diffusion/permeability. We suggest rephrasing for precision, potentially to "Cy3-TP1 is uptaken by cells". We do however also appreciate that endocytosis inhibition does not completely abrogate cell uptake, potentially pointing to other contributing processes. Consider adding Fig. 2B's experimental rationale to the main text for clarity since it is a main figure. We understood it to be a control for the addition of Trypan blue to cells to quench extracellular Cy3-TP1 fluorescence after reading the methods. Additionally, explaining what the "control" treatments were will improve clarity for Fig. 2 overall. To support the claim that the inhibitors decrease uptake, statistical tests should be between the treated conditions and the Cy3-TP1 condition instead of between the treated conditions and the control (Fig. 2E). Are there any explanatory interpretations of the data showing a decrease in upstream activators over time (Fig. 4G, p-eNOS; Fig. S3A, p-Akt)? We were somewhat confused by Fig. S4-6 because it does not seem that the controls (treatment-, TP1-) are set to 100% which we understood them to be from the caption. The text could be improved by an explicit explanation of what targets Fig. S4-8 show TP1 is not acting on. Fig. 5-7 include adjacent bar graphs with varying y-axis boundaries. Doing this exaggerates the effects of the ginsentides mentioned and can mislead the reader. There seems to be some discordance regarding the order of events (initial pre-incubation with treatment of monocytes vs. endothelial cells) between the text and caption for Fig. 6. We suggest including an explanation for using the lung coefficient as a measurement for pulmonary embolisms (Fig. 7). We suggest including the ginsentide-related patents of the authors in the competing interests (eg. US patent US20200277343A1: "Preparation and use of ginsentides and ginsentide-like peptides"). Stylistic/typographic suggestions: Typo in line 78. Should be "adaptogens". We suggest improving the confocal image in Fig. 1 by nicely cropping one representative cell image, including a colored coded legend of stains, and marking the cell membrane to orient the reader. The nature of line 434's "Cy3-rT1" is unexplained. This may be a typo. Competing interests The author declares that they have no competing interests.

The incorporation of pseudoallylic strain by N-methylation at the solvent exposed loop in proteins leads to a stark increase in their thermodynamic stability that can be tuned by altering the amino acid composition., Reverse turns are solvent-exposed motifs in proteins that are crucial in nucleating β-sheets and drive the protein folding. The solvent-exposed nature makes reverse turns more amenable to chemical modifications than α-helices or β-sheets towards modulating the stability of re-engineered proteins. Here, we utilize van der Waals repulsive forces in tuning the steric restraint at the reverse turn. The steric restraint induced upon N-methylation of the i+1–i+2 amide bond at the reverse turn results in well-folded and stable β-sheets in aqueous solution at room temperature. The developed superactive turn inducing motif is tolerant to a wide variety of functional groups present on coded amino acids making the designed turn fully compatible with bioactive loops in proteins. We demonstrate that the steric restraint and the functional groups at the reverse turn act in synergy to modulate the folding of re-engineered β-sheets. Introduction of the turn motifs onto a three-stranded β-sheet protein, Pin 1 WW domain, resulted in various analogs showing a cooperative two-state transition with thermal stability (TM) ranging from 62 °C to 82 °C. Despite modulating the stability of Pin 1 variants by ∼2.8 kcal mol–1 (ΔΔGf), the native fold in all the protein variants was found to be unperturbed. This structural stability is brought about by conformational preorganization at the engineered reverse turn that results in strong intramolecular hydrogen bonds along the three dimensional structure of the protein. Thus, this simple loop engineering strategy via two amino acid substitution provides us a “toolkit” to modulate the stability of β-sheet containing peptides and proteins in aqueous solution that will greatly expand the scope of de novo protein and foldamer design.

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift towards modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior R f r e e and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g. Coot) and fit can be further improved by refinement using standard pipelines (e.g. Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.