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Intrinsically disordered proteins (IDPs) are central to many physiological functions and to various pathologies that include neurodegeneration. They can interact with numerous partner proteins. Here, we introduce the Sherpa hypothesis, according to which a subset of stable IDPs, which we term Phenotype-Preserving Disordered Proteins (PPDP), play a central role in protecting cell phenotypes from perturbations. To illustrate and test this hypothesis, we computer-simulate some salient features of how cells evolve and differentiate in the presence of either a single PPDP or two incompatible PPDPs. We relate this virtual experiment to the pathological interactions between two PPDPs, α-synuclein and Tubulin Polymerization Promoting Protein/p25, in neurodegenerative disorders. Finally, we discuss the implications of the Sherpa hypothesis for aptamer-based therapies of such disorders.

Despite the wealth of knowledge gained about intrinsically disordered proteins (IDPs) since their discovery, there are several aspects that remain unexplored and, hence, poorly understood. A living cell is a complex adaptive system that can be described as a wetware─a metaphor used to describe the cell as a computer comprising both hardware and software and attuned to logic gates─capable of "making" decisions. In this focused Review, we discuss how IDPs, as critical components of the wetware, influence cell-fate decisions by wiring protein interaction networks to keep them minimally frustrated. Because IDPs lie between order and chaos, we explore the possibility that they can be modeled as attractors. Further, we discuss how the conformational dynamics of IDPs manifests itself as conformational noise, which can potentially amplify transcriptional noise to stochastically switch cellular phenotypes. Finally, we explore the potential role of IDPs in prebiotic evolution, in forming proteinaceous membrane-less organelles, in the origin of multicellularity, and in protein conformation-based transgenerational inheritance of acquired characteristics. Together, these ideas provide a new conceptual framework to discern how IDPs may perform critical biological functions despite their lack of structure.

Proteomic analysis revealed the preservation of many proteins in the Heslington brain (which is at least 2600-year-old brain tissue uncovered within the skull excavated in 2008 from a pit in Heslington, Yorkshire, England). Five of these proteins—“main proteins”: heavy, medium, and light neurofilament proteins (NFH, NFM, and NFL), glial fibrillary acidic protein (GFAP), and myelin basic (MBP) protein—are engaged in the formation of non-amyloid protein aggregates, such as intermediate filaments and myelin sheath. We used a wide spectrum of bioinformatics tools to evaluate the prevalence of functional disorder in several related sets of proteins, such as the main proteins and their 44 interactors, all other proteins identified in the Heslington brain, as well as the entire human proteome (20,317 manually curated proteins), and 10,611 brain proteins. These analyses revealed that all five main proteins, half of their interactors and almost one third of the Heslington brain proteins are expected to be mostly disordered. Furthermore, most of the remaining Heslington brain proteins are expected to contain sizable levels of disorder. This is contrary to the expected substantial (if not complete) elimination of the disordered proteins from the Heslington brain. Therefore, it seems that the intrinsic disorder of NFH, NFM, NFL, GFAP, and MBP, their interactors, and many other proteins might play a crucial role in preserving the Heslington brain by forming tightly folded brain protein aggregates, in which different parts are glued together via the disorder-to-order transitions.

Before the SARS-CoV-2 Omicron variant emergence, Shell Disorder Models (SDM) suggested that an attenuated precursor from pangolins may have entered humans in 2017 or earlier. This was based on a shell-disorder analysis of SARS-CoV-1/2 and pangolin-Cov-2017. SDM suggests that Omicron is attenuated with almost identical N (inner shell) disorder as pangolin-CoV-2017 (N-PID (percentage of intrinsic disorder): 44.8% vs. 44.9% - lower than other variants). The outer shell disorder (M-PID) of Omicron is lower than that of other variants (5.4% vs. 5.9%). COVID-19-related CoVs have the lowest M-PIDs (hardest outer-shell) among all CoVs. This is likely to be responsible for higher contagiousness of SARS-CoV-2 and Omicron, since the hard outer-shell protects the virion from salivary/mucosal anti-microbial enzymes. Phylogenetic study using M reveals that Omicron branched off from an ancestor of the Wuhan strain closely related to pangolin-CoVs. M, being evolutionarily conserved in COVID-19, is most ideal for COVID-19 phylogenetic study. Omicron may have been hiding among burrowing animals (e.g. pangolins) that provide optimal evolutionary environments for attenuation and increase shell hardness, which is essential for fecal-oral-respiratory transmission via buried feces. Incoming data support SDM showing the presence of fewer infectious particles in the lungs than in the bronchi upon infection.

The liquid-liquid phase separation (LLPS) of biological macromolecules has emerged as a foundational mechanism underlying the formation of a myriad of membraneless organelles (MLOs), such as stress granules, transcription factor condensates, and chromatin compartments. A molecular grammar of sequences, which would enable a quantitative prediction and understanding of protein phase separation from first principles is currently missing. A major challenge in the field is the sparsity of bioinformatics data and the lack of computational, data-driven tools for biophysical and statistical analysis of proteins capable of phase separation. Here we present the utility of web applications framed within a novel open-source platform for BioInformatic Analysis of liquid-liquid Phase-Separating protein Sequences, https://biapss.chem.iastate.edu/. BIAPSS combines high-throughput interactive data analytics of physicochemical and evolutionary features with a comprehensive repository of bioinformatic data for on-the-fly research of the sequence-dependent properties of proteins with known LLPS behavior. To facilitate exploration of the services and provide the interpretation guideline, we present two attention-getting case studies of FUS and hnRNPDL. This should help the LLPS community uncover the nature of interactions driving the formation of membraneless organelles.

Experimenters face challenges and limitations while analyzing glycoproteins due to their high flexibility, stereochemistry, anisotropic effects, and hydration phenomena. Computational studies complement experiments and have been used in characterization of the structural properties of glycoproteins. However, recent investigations revealed that computational studies face significant challenges as well. Here, we introduce and discuss some of these challenges and weaknesses in the investigations of glycoproteins. We also present requirements of future developments in computational biochemistry and computational biology areas that could be necessary for providing more accurate structural property analyses of glycopro-teins using computational tools. Further theoretical strategies that need to be and can be developed are discussed herein.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent of the coronavirus disease (CoVID-19), is a part of the β-coronaviridae family. In comparison with two other members of this family of coronaviruses infecting humans (SARS-CoV and Middle East Respiratory Syndrome (MERS) CoV), SARS-CoV-2 showed the most severe effects on the entire Earth population causing world-wide CoVID-19 pandemic. SARS-CoV-2 contains five major protein classes, such as four structural proteins (Nucleocapsid (N), Membrane (M), Envelop (E), and Spike Glycoprotein (S)) and Replicase polyproteins (R), which are synthesized as two polyproteins (ORF1a and ORF1ab) that are subsequently processed into 12 nonstructural proteins by three viral proteases. All these proteins share high sequence similarity with their SARS-CoV counterparts. Due to the severity of the current situation, most of the SARS-CoV-2-related research is focused on finding therapeutic solutions and the analysis of comorbidities during infection. However, studies on the peculiarities of the amino acid sequences of viral protein classes and their structure space analysis throughout the evolutionary time-frame are limited. At the same time, due to their structural malleability, viral proteins can be directly or indirectly associated with the dysfunctionality of the host cell proteins, which may lead to comorbidities during the infection and at the post infection stage. To fill these gaps, we conducted the evolutionary sequence-structure analysis of the viral protein classes to evaluate the rate of their evolutionary malleability. We also looked at the intrinsic disorder propensities of these viral proteins and confirmed that although they typically do not have long intrinsically disordered regions (IDRs), all of them have at least some levels of intrinsic disorder. Furthermore, short IDRs found in viral proteins are extremely effective and prioritize the proteins for host cell interactions, which may lead to host cell dysfunction. Next, the associations of viral proteins with the host cell proteins were studied, and a list of diseases which are associated with such host cell proteins was developed. Other than the usual set of diseases, we have identified some maladies, which may happen after the recovery from the infections. Comparison of the expression rates of the host cell proteins during the diseases suggested the existence of two distinct classes. First class includes proteins, which are directly associated with certain sets of diseases, where they have shared similar activities. Second class is related to the cytokine storm-mediated pro-inflammation (already known for its role in acute respiratory distress syndrome, ARDS), and neuroinflammation may trigger some of the neurological malignancies and neurodegenerative and neuropsychiatric diseases. Finally, since the transmembrane serine protease 2 (TMPRSS2), which is one of the leading proteins associated with the viral uptake, is an androgen-mediated protein, our study suggested that males and postmenopausal females can be more susceptible to the SARS-CoV-2 infection.

The microtubule-associated protein tau pathologically accumulates and aggregates in Alzheimer’s disease (AD) and other tauopathies, leading to cognitive dysfunction and neuronal loss. Molecular chaperones, like small heat-shock proteins (sHsps), can help deter the accumulation of misfolded proteins, such as tau. Here, we tested the hypothesis that the overexpression of wild-type Hsp22 (wtHsp22) and its phosphomimetic (S24,57D) Hsp22 mutant (mtHsp22) could slow tau accumulation and preserve memory in a murine model of tauopathy, rTg4510. Our results show that Hsp22 protected against deficits in synaptic plasticity and cognition in the tauopathic brain. However, we did not detect a significant change in tau phosphorylation or levels in these mice. This led us to hypothesize that the functional benefit was realized through the restoration of dysfunctional pathways in hippocampi of tau transgenic mice since no significant benefit was measured in non-transgenic mice expressing wtHsp22 or mtHsp22. To identify these pathways, we performed mass spectrometry of tissue lysates from the injection site. Overall, our data reveal that Hsp22 overexpression in neurons promotes synaptic plasticity by regulating canonical pathways and upstream regulators that have been characterized as potential AD markers and synaptogenesis regulators, like EIF4E and NFKBIA.

Compromised PTEN function is associated with multiple cancers. As per the continuum model, variable degree of PTEN inactivation drives distinct cancer phenotypes. Loss of PTEN activity, via genomic/non-genomic mechanisms, leads to enhanced oncogenic PI3K signaling. While kinase inhibitors have proved effective in the clinic, they are increasingly met with off-target effects and therapy-resistance due to compensatory feedback mechanisms. Although PTEN restoration therapy has proved promising in experimental models; implementation of these therapies in the clinic remains challenging. To fill this therapy gap, we have targeted endogenous PTEN for activation via peptidomimetics, mitigating PI3K signaling. Our selected peptidomimetics reduced cell proliferation, migration and cell cycle activity after treatment of non-small cell lung cancer cells expressing endogenous PTEN. Computational studies utilizing PTEN crystal structures revealed a binding site at the interface of the Phosphatase Domain (PD) and C2 Domain (C2D). Induced fit docking indicated that a unique functional group is responsible for peptidomimetic-mediated enhancement of PTEN activity. Molecular dynamics analysis revealed energetically favorable binding of our lead peptidomimetic at the PD/C2D interface, which allosterically modulated the conformation of the active site. Binding of our peptidomimetic altered the active site orientation of PIP3, increasing its binding affinity. In summary, we have developed the first-known direct PTEN activators and analyzed their effects in suppressing oncogenic activities in lung cancer. Refinement of our peptidomimetics, complemented with in vivo studies, will provide a novel clinical rationale to reduce doses of standard therapy and their associated toxicities, decreasing morbidity and mortality observed in the clinic. Citation Format: Emily Palumbo, Peng Teng, Prerna Malaney, Jacob Wilson, Fiona Kearns, Michael T. Kemp, Zhi Tian, Vladimir Uversky, Diane Allen-Gipson, Yu Chen, H. Lee Woodcock, Jianfeng Cai, Vrushank Dave. Enhancement of PTEN activity via peptidomimetics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4826.

This paper addresses the polar profile of ancient proteins using a comparative study of amino acids found in 25,000,000-year-old shells as described in Abelson's work. We simulated the polar profile with a computer platform that represented an evolutionary computational toy model that mimics the generation of small proteins starting from a pool of amino acid monomers and that included several dynamic properties such as self-replication and fragmentation-recombination of the proteins. The simulations were taken up to 15 generations and produced a considerable number of proteins of 25 amino acids in length. The computational model included the amino acids found in the ancient shells, the thermal degradation factor and the relative abundance of the amino acids observed in the Miller-Urey experimental simulation on prebiotic amino acid formation. We found that the amino acid polar profiles of the ancient shells and those simulated and extrapolated from the Miller-Urey abundances are coincident.

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Intrinsically disordered proteins (IDPs) are either entirely disordered or contain disordered regions in their native state. IDPs were found to be abundant across all kingdoms of life, particularly in eukaryotes, and are implicated in numerous cellular processes. Experimental annotation of disorder lags behind the rapidly growing sizes of the protein databases and thus computational methods are used to close this gap and to investigate the disorder. MFDp2 is a novel webserver for accurate sequence-based prediction of protein disorder which also outputs well-described sequence-derived information that allows profiling the predicted disorder. We conveniently visualize sequence conservation, predicted secondary structure, relative solvent accessibility, and alignments to chains with annotated disorder. The webserver allows predictions for multiple proteins at the same time, includes help pages and tutorial, and the results can be downloaded as text-based (parsable) file. MFDp2 is freely available at http://biomine.ece.ualberta.ca/MFDp2/.

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