Miracle-dz/UniFAR-FTUs huggingface dataset:
In-silico comparative modeling and interaction studies of PRSV proteins - Accelerated towards dissection of structure based evolutionary divergence and functional interaction of virus within the host

Function based structure analysis of viral proteins reinforce their distinctive and unanticipated role within the host. The interaction dynamics of virus protein and host which is prerequisite for complete infectivity as well as systemic spread of invading virus demands to explore viral proteins in framework of their interacting partners. Papaya ringspot virus strain from Pakistan (PRSV-PK) spreading as atypical variant and causes drastic reduction in papaya production. The in-depth knowledge of the virus variant and effective management is obligatory. The desired objective is achievable once the evolutionary dynamics, molecular characterization and physicochemical structural properties conceived from the 3D protein structures are comprehended. Although the diversity studies on PRSV-PK strain been established but still there is a niche regarding structural based evolutionary dynamics of virus proteins and their probable interaction mode inside the host. The present investigations provided insights into the in-silico analysis of the functionally significant genes Coat protein (CP), Helper component proteinase (HC-Pro) and Nuclear Inclusion b protein (NIb) of PRSV-PK. The protein structure has been modeled using Phyre2, Swiss-Model and i-TASSER. Phyre2 built model showed 100% confidence for 67%, 63% and 20% sequence identity residues for PRSV CP, HC-Pro and NIb proteins respectively. The Swiss model showed identity values of 63.40%, 62.42% and 16.49% for CP, HC-Pro and NIb protein. whereas, i-TASSER server exhibited identity values of 67%, 63% and 19% for CP, HC-Pro and NIb proteins respectively. These structures provided a base line for functional analysis of experimentally derived crystal structures. The predicted models were validated using protein structure checking tools PROCHECK. Further the PRSV-PK-CP structures were compared with the PRSV-CP structures of representative isolates from different geographical regions. Nevertheless, the comparative modeling provides the insight into the evolutionary characteristics and proposed genetic diversity of PRSV based on protein structures. In addition, the conserved functional motifs have been mapped on aligned protein sequences of CP, HC-Pro and NIb, and their critical function within the host has been highlighted. Eventually, the interaction of papaya protein with the invading PRSV-CP has been predicted through in-silico protein-protein docking to elucidate their possible role in virus inhibition. The established structural-functional relation provided a basis to propose probable host-virus interactions in terms of virus infectivity, resultant host adaptability, and host defense response activation to counteract the virus invasion.
Natural variation in codon bias and mRNA folding strength interact synergistically to modify protein expression in Saccharomyces cerevisiae

Codon bias and mRNA folding strength (mF) are hypothesized molecular mechanisms by which polymorphisms in genes modify protein expression. Natural patterns of codon bias and mF across genes as well as effects of altering codon bias and mF suggest the influence of these two mechanisms may vary depending on the specific location of polymorphisms within a transcript. Despite the central role codon bias and mF may play in natural trait variation within populations, systematic studies of how polymorphic codon bias and mF relate to protein expression variation are lacking. To address this need, we analyzed genomic, transcriptomic, and proteomic data for 22 Saccharomyces cerevisiae isolates, estimated protein accumulation for each allele of 1620 genes as the log of protein molecules per RNA molecule (logPPR), and built linear mixed effects models associating allelic variation in codon bias and mF with allelic variation in logPPR. We found codon bias and mF interact synergistically in a positive association with logPPR and this interaction explains almost all the effect of codon bias and mF. We examined how the locations of polymorphisms within transcripts influence their effects and found that codon bias primarily acts through polymorphisms in domain encoding and 3’ coding sequences while mF acts most significantly through coding sequences with weaker effects from UTRs. Our results present the most comprehensive characterization to date of how polymorphisms in transcripts influence protein expression.
Histone deacetylase 3 regulates microglial function through histone deacetylation

ABSTRACT As the primary innate immune cells of the brain, microglia respond to damage and disease through pro-inflammatory release of cytokines and neuroinflammatory molecules. Histone acetylation is an activating transcriptional mark that regulates inflammatory gene expression. Inhibition of histone deacetylase 3 (Hdac3) has been utilized in pre-clinical models of depression, stroke, and spinal cord injury to improve recovery following injury, but the molecular mechanisms underlying Hdac3’s regulation of inflammatory gene expression in microglia is not well understood. To address this lack of knowledge, we examined how pharmacological inhibition of Hdac3 in an immortalized microglial cell line (BV2) impacted histone acetylation and gene expression of pro- and anti-inflammatory genes in response to immune challenge with lipopolysaccharide (LPS). Flow cytometry and cleavage under tags & release using nuclease (CUT & RUN) revealed that Hdac3 inhibition increases global and promoter-specific histone acetylation, resulting in the release of gene repression at baseline and enhanced responses to LPS. Hdac3 inhibition enhanced neuroprotective functions of microglia in response to LPS through reduced nitric oxide release and increased phagocytosis. The findings suggest Hdac3 serves as a regulator of microglial inflammation, and that inhibition of Hdac3 facilitates the microglial response to inflammation and its subsequent clearing of debris or damaged cells. Together, this work provides new mechanistic insights into therapeutic applications of Hdac3 inhibition which mediate reduced neuroinflammatory insults through microglial response.
DipM controls multiple autolysins and mediates two regulatory feedback loops promoting cell constriction in C. crescentus

Proteins containing a catalytically inactive LytM-type endopeptidase domain have emerged as important regulators of cell wall-degrading enzymes in bacteria. Although these so-called LytM factors are wide-spread among species, the range of functions they fulfill and their precise modes of action are still incompletely understood. In this work, we study the LytM factor DipM, a protein required for proper cell division in the model species C. crescentus. We show that the LytM domain of DipM interacts directly with multiple autolysins, including the lytic transglycosylases SdpA and SdpB, the amidase AmiC and the putative carboxypeptidase CrbA, and stimulates the activities of SdpA and AmiC. The crystal structure of the LytM domain of DipM reveals conserved features, including a distinctive groove. Modeling studies suggest that this groove could represent the docking site of AmiC. The architecture of the binding interface in the DipM-AmiC complex is very similar to that observed for the LytM domain of EnvC in complex with its autoinhibitory restraining arm, suggesting a conserved role of the groove in the interaction of LytM factors with their (auto-)regulatory targets. In line with this hypothesis, a mutation in the groove abolishes DipM function. Interestingly, single-molecule tracking studies reveal that the recruitment of DipM and its regulatory targets SdpA and SdpB to the division site is mutually interdependent, with DipM establishing a self-reinforcing cycle that gradually increases lytic transglycosylase activity at the cell center as division progresses. At the same time, the DipM-dependent activation of AmiC leads to the production of denuded peptidoglycan, generating a spatial cue that attracts FtsN to the division site and thus, in turn, again promotes the recruitment of DipM. Collectively, these findings show that DipM is a central regulator that acts at the intersection of different peptidoglycan remodeling pathways and coordinates the activities of various classes of autolysins to promote cell constriction and daughter cell separation.
Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS

Cyclic peptides naturally occur as antibiotics, fungicides, and immunosuppressants, and have been adapted for use as potential therapeutics. Scaffolded cyclic peptide antigens have many protein characteristics such as reduced toxicity, increased stability over linear peptides, and conformational selectivity, but with fewer amino acids than whole proteins. The profile of shapes presented by a cyclic peptide modulates its therapeutic efficacy, and is represented by the ensemble of its sampled conformations. Although some algorithms excel in creating a diverse ensemble of cyclic peptide conformations, they seldom address the entropic contribution of flexible conformations, and they often have significant practical difficulty producing an ensemble with converged and reliable thermodynamic properties. In this study, an accelerated molecular dynamics (MD) method, reservoir replica exchange MD (R-REMD or Res-REMD), was implemented in GROMACS-4.6. 7, and benchmarked on three small cyclic peptide model systems: a cyclized segment of Aβ (cyclo-(CGHHQKLVG)), a cyclized furin cleavage site of SARS-CoV-2 spike (cyclo-(CGPRRARSG)), and oxytocin (disulfide bonded CY-IQNCPLG). Additionally, we also benchmarked Res-REMD on Alanine dipeptide and Trpzip2 to demonstrate its validity and efficiency over REMD. Compared to REMD, Res-REMD significantly accelerated the ensemble generation of cyclo-(CGHHQKLVG), but not cyclo-(CGPRRARSG) or oxytocin. This difference is due to the longer auto-correlation time of torsional angles in cyclo-(CGHHQKLVG) v s. the latter two cyclic peptide systems; The randomly seeded reservoir in Res-REMD thus accelerates sampling and convergence. The auto-correlation time of the torsional angles can thus be used to determine whether Res-REMD is preferable to REMD for cyclic peptides. We provide a github page with modified GROMACS source code for running Res-REMD at https://github.com/PlotkinLab/Reservoir-REMD.
Identifying Pathogen and Allele Type Simultaneously (IPATS) in a single well using droplet digital PCR

A combined host biomarker and pathogen diagnosis provides insight into disease progression risk and contributes to appropriate clinical decision-making regarding prevention and treatment. In preventive veterinary medicine, such combined diagnosis could improve risk-based livestock herd management. We developed a single-well based test for combined diagnosis of bovine leukemia virus (BLV) and bovine MHC (BoLA)-DRB3 alleles. A fourplex droplet digital PCR method targeting the BLV pol gene, BLV-susceptible DRB3*016:01 allele, resistant DRB3*009:02 allele, and housekeeping RPP30 gene (IPATS-BLV) successfully measured the percentage of BLV-infected cells and determined allele types precisely. Furthermore, it discriminated homozygous from heterozygous carriers. Using this method to determine the impact of carrying these alleles on the BLV proviral load (PVL), we found DRB3*009:02-carrying cattle could suppress the PVL to a low or undetectable level, even with the presence of a susceptible allele. Although the population of DRB3*016:01-carrying cattle showed significantly higher PVLs when compared with cattle carrying other alleles, their individual PVLs were highly variable. Because of the simplicity and speed of this single-well assay, IPATS could be a suitable platform for the combined diagnosis of host biomarkers and pathogens in a wide range of other systems.
Invariance of object detection in untrained deep neural networks

The ability to perceive visual objects with various types of transformations, such as rotation, translation, and scaling, is crucial for consistent object recognition. In machine learning, invariant object detection for a network is often implemented by augmentation with a massive number of training images, but the mechanism of invariant object detection in biological brains — how invariance arises initially and whether it requires visual experience — remains elusive. Here, using a model neural network of the hierarchical visual pathway of the brain, we show that invariance of object detection can emerge spontaneously in the complete absence of learning. First, we found that units selective to a particular object class arise in randomly initialized networks even before visual training. Intriguingly, these units show robust tuning to images of each object class under a wide range of image transformation types, such as viewpoint rotation. We confirmed that this “innate” invariance of object selectivity enables untrained networks to perform an object-detection task robustly, even with images that have been significantly modulated. Our computational model predicts that invariant object tuning originates from combinations of non-invariant units via random feedforward projections, and we confirmed that the predicted profile of feedforward projections is observed in untrained networks. Our results suggest that invariance of object detection is an innate characteristic that can emerge spontaneously in random feedforward networks. Highlights Object-selective units spontaneously emerge in untrained deep neural networks Object selectivity maintains robustly in a wide range of image transformations Feedforward model can explain spontaneous emergence of the invariance Innate invariance enables invariant object detection without learning to variations
Scaling protein-water interactions in the Martini 3 coarse-grained force field to simulate transmembrane helix dimers in different lipid environments

Martini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the non-bonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or bilayer structure.
Dynamic fluctuations in ascending heart-to-brain communication under mental stress

Dynamical information exchange between central and autonomic nervous systems, as referred to functional brain–heart interplay, occurs during emotional and physical arousal. It is well documented that physical and mental stress lead to sympathetic activation. Nevertheless, the role of autonomic inputs in nervous-system-wise communication under mental stress is yet unknown. In this study, we estimated the causal and bidirectional neural modulations between EEG oscillations and peripheral sympathetic and parasympathetic activities using a recently proposed computational framework for a functional brain–heart interplay assessment, namely the sympathovagal synthetic data generation model. Mental stress was elicited in 37 healthy volunteers by increasing their cognitive demands throughout three tasks associated with increased stress levels. Stress elicitation induced an increased variability in sympathovagal markers, as well as increased variability in the directional brain–heart interplay. The observed heart–to–brain interplay was primarily from sympathetic activity targeting a wide range of EEG oscillations, whereas variability in the efferent direction seemed mainly related to EEG oscillations in the gamma band. These findings extend current knowledge on stress physiology, which mainly referred to top-down neural dynamics. Our results suggest that mental stress may not cause an increase in sympathetic activity exclusively as it initiates a dynamic fluctuation within brain-body networks including bidirectional interactions at a brain–heart level. We conclude that directional brain–heart interplay measurements may provide suitable biomarkers for a quantitative stress assessment and bodily feedback may modulate the perceived stress caused by increased cognitive demand.
Stimulating microtubule growth is not the essential function of the microtubule polymerase Stu2

TOG family proteins, including the budding yeast Stu2, are essential for the formation of a functional mitotic spindle. Across all eukaryotes, the described functions of this family depend on two microtubule binding elements: TOG domain arrays, and a basic linker domain important for binding the microtubule lattice. Consistently, we find here that Stu2’s basic linker is required for its ability to regulate microtubules in vitro, including stimulating microtubule growth, shrinkage, and catastrophe. We furthermore define a region contained within Stu2’s basic linker domain as its nuclear localization sequence, and identify phospho-regulation that promotes mitosis-specific nuclear import. Surprisingly, directing nuclear localization is the only function contained within Stu2’s basic linker that is required for cell viability, indicating that microtubule lattice binding is not required for Stu2’s essential function. Considering that lattice binding is required to stimulate microtubule polymerization and depolymerization in vitro, these established activities are unlikely to be the essential functions carried out by Stu2 in the cell’s nucleus. SUMMARY Stu2 is a TOG family protein that performs numerous microtubule regulatory functions in the cell. Here we show that Stu2’s nuclear localization is essential for cell viability. Surprisingly, its required nuclear function is distinct from its canonical activities regulating microtubules.
A new and highly effective method for predicting T-cell response targets implemented on SARS-CoV-2 data

Computational T-cell epitope prediction is essential in many immunological projects, including the development of vaccines. T-cells of immunocompetent vertebrate hosts can recognize as non-self only peptides which are present in the parasite’s proteins and absent in the host’s proteins. This basic principle allows us to predict which peptides can elicit T-cells’ response. We built on the fact that the specificity of T-cells reacting to SARS-CoV-2 antigens has been recently mapped in detail. Using Monte Carlo tests, we found that empirically confirmed peptides that stimulate T-cells contain an increased fraction of pentapeptides, hexapeptides, and heptapeptides which are not found in the human proteome (p < 0.0001). Similarly, hexapeptides absent in human proteins were overrepresented in peptides that elicited T-cell response in a published empirical study (p = 0.027). The new theory-based method predicted T-cell immunogenicity of SARS-CoV-2 peptides four times more effectively than current empirically based methods.
Oculomotor, vestibular, reaction time, and cognitive tests as objective measures of neural deficits in patients post COVID-19 infection

Objective An alarming proportion (>30%) of patients affected by SARS-CoV-2 (COVID-19) continue to experience neurological symptoms, including headache, dizziness, smell and/or taste abnormalities, and impaired consciousness (brain fog), after recovery from the acute infection. These symptoms are self-reported and vary from patient to patient, making it difficult to accurately diagnose and initiate a proper treatment course. Objective measures to identify and quantify neural deficits underlying the symptom profiles are lacking. This study tested the hypothesis that oculomotor, vestibular, reaction time, and cognitive (OVRT-C) testing using eye-tracking can objectively identify and measure functional neural deficits post COVID-19 infection. Methods Subjects diagnosed with COVID-19 (n = 77) were tested post-infection with a battery of 20 OVRT-C tests delivered on a portable eye-tracking device (Neurolign Dx100). Data from 14 tests were compared to previously collected normative data from subjects with similar demographics. Post-COVID subjects were also administered the Neurobehavioral Symptom Inventory (NSI) for symptom evaluation. Results A significant percentage of post COVID-19 patients (up to 86%) scored outside the norms in 12 out of 14 tests, with smooth pursuit and optokinetic responses being most severely affected. A multivariate model constructed using stepwise logistic regression identified 6 metrics as significant indicators of post-COVID patients. The area under the receiver operating characteristic curve (AUC) was 0.89, the estimated specificity was 98% (with cutoff value of 0.5) and the sensitivity was 88%. There were moderate but significant correlations between NSI domain key variables and OVRT-C tests. Conclusions This study demonstrates the feasibility of OVRT-C testing to provide objective measures of neural deficits in people recovering from COVID-19 infection. Such testing may serve as an efficient tool for identifying hidden neurological deficits post COVID-19, screening patients at risk of developing long COVID, and may help guide rehabilitation and treatment strategies.
Low prevalence of influenza A strains with resistance markers in Brazil during 2017–2019 seasons

The influenza A virus (IAV) is of a major public health concern as it causes annual epidemics and has the potential to cause pandemics. At present, the neuraminidase inhibitors (NAIs) are the most widely used anti-influenza drugs, but, more recently, the drug baloxavir marboxil (BXM), a polymerase inhibitor, has also been licensed in some countries. Mutations in the viral genes that encode the antiviral targets can lead to treatment resistance. Worldwide, a low prevalence of antiviral resistant strains has been reported. Despite that, this situation can change rapidly, and resistant strain surveillance is a priority. Thus, the aim of this was to evaluate Brazilian IAVs antiviral resistance from 2017 to 2019 through the identification of viral mutations associated with reduced inhibition of the drugs and by testing the susceptibility of IAV isolates to oseltamivir (OST), the most widely used NAI drug in the country. Initially, we analyzed 282 influenza A(H1N1)pdm09 and 455 A(H3N2) genetic sequences available on GISAID. The amino acid substitution (AAS) NA:S247N was detected in one A(H1N1)pdm09 strain. We also identified NA:I222V (n = 6) and NA:N329K (n = 1) in A(H3N2) strains. In addition, we performed a molecular screening for NA:H275Y in 437 A(H1N1)pdm09 samples, by pyrosequencing, which revealed a single virus harboring this mutation. Furthermore, the determination of OST IC50 values for 222 A(H1N1)pdm09 and 83 A(H3N2) isolates revealed that all isolates presented a normal susceptibility profile to the drug. Interestingly, we detected one A(H3N2) virus presenting with PA:E119D AAS. Moreover, the majority of the IAV sequences had the M2:S31N adamantanes resistant marker. In conclusion, we show a low prevalence of Brazilian IAV strains with NAI resistance markers, in accordance with what is reported worldwide, indicating that NAIs still remain an option for the treatment of influenza infections in Brazil. However, surveillance of influenza resistance should be strengthened in the country for improving the representativeness of investigated viruses and the robustness of the analysis.