Amino acid substitution scoring matrices specific to intrinsically disordered regions in proteins

Engineering G protein-coupled receptors for stabilization

G protein-coupled receptors (GPCRs) are one of the most important families of targets for drug discovery. One of the limiting steps in the study of GPCRs has been their stability, with significant and time-consuming protein engineering often used to stabilize GPCRs for structural characterization and drug screening. Unfortunately, computational methods developed using globular soluble proteins have translated poorly to the rational engineering of GPCRs. To fill this gap, we propose GPCR-tm, a novel and personalized structurally driven web-based machine learning tool to study the impacts of mutations on GPCR stability. We show that GPCR-tm performs as well as or better than alternative methods, and that it can accurately rank the stability changes of a wide range of mutations occurring in various types of class A GPCRs. GPCR-tm achieved Pearson's correlation coefficients of 0.74 and 0.46 on 10-fold cross-validation and blind test sets, respectively. We observed that the (structural) graph-based signatures were the most important set of features for predicting destabilizing mutations, which points out that these signatures properly describe the changes in the environment where the mutations occur. More specifically, GPCR-tm was able to accurately rank mutations based on their effect on protein stability, guiding their rational stabilization. GPCR-tm is available through a user-friendly web server at https://biosig.lab.uq.edu.au/gpcr_tm/.

The Evolution of Temperature and Desiccation-Related Protein Families in Tardigrada Reveals a Complex Acquisition of Extremotolerance

Tardigrada is an ecdysozoan lineage famed for its resilience. Tardigrades can tolerate high doses of radiation, low-oxygen environments, desiccation, and both high and low temperatures under a dormant state called "anhydrobiosis", which is a reversible halt of metabolism upon almost complete desiccation. A large amount of research has focused on the genetic pathways related to these capabilities, and a number of genes have been identified and linked to the extremotolerant response of tardigrades. However, the history of these genes is unclear, and the origins and history of extremotolerant genes within Tardigrada remain a mystery. Here, we generate the first phylogenies of six separate protein families linked with desiccation and radiation tolerance in Tardigrada: cytosolic abundant heat-soluble protein, mitochondrial abundant heat-soluble protein, secretory abundant heat-soluble protein, meiotic recombination 11 homolog, and the newly discovered Echiniscus testudo abundant heat-soluble proteins (alpha and beta). The high number of independent gene duplications found amongst the six gene families studied suggests that tardigrades have a complex history with numerous independent adaptations to cope with aridity within the limnoterrestrial environment. Our results suggest that tardigrades likely transitioned from a marine environment to a limnoterrestrial environment only twice, once in stem Eutardigrada and once in Heterotardigrada, which explains the unique adaptations to anhydrobiosis present in both classes.

New alignment method for remote protein sequences by the direct use of pairwise sequence correlations and substitutions

Understanding protein sequences and how they relate to the functions of proteins is extremely important. One of the most basic operations in bioinformatics is sequence alignment and usually the first things learned from these are which positions are the most conserved and often these are critical parts of the structure, such as enzyme active site residues. In addition, the contact pairs in a protein usually correspond closely to the correlations between residue positions in the multiple sequence alignment, and these usually change in a systematic and coordinated way, if one position changes then the other member of the pair also changes to compensate. In the present work, these correlated pairs are taken as anchor points for a new type of sequence alignment. The main advantage of the method here is its combining the remote homolog detection from our method PROST with pairwise sequence substitutions in the rigorous method from Kleinjung et al. We show a few examples of some resulting sequence alignments, and how they can lead to improvements in alignments for function, even for a disordered protein.

CapsNet-MHC predicts peptide-MHC class I binding based on capsule neural networks

The Major Histocompatibility Complex (MHC) binds to the derived peptides from pathogens to present them to killer T cells on the cell surface. Developing computational methods for accurate, fast, and explainable peptide-MHC binding prediction can facilitate immunotherapies and vaccine development. Various deep learning-based methods rely on separate feature extraction from the peptide and MHC sequences and ignore their pairwise binding information. This paper develops a capsule neural network-based method to efficiently capture the peptide-MHC complex features to predict the peptide-MHC class I binding. Various evaluations confirmed our method outperformance over the alternative methods, while it can provide accurate prediction over less available data. Moreover, for providing precise insights into the results, we explored the essential features that contributed to the prediction. Since the simulation results demonstrated consistency with the experimental studies, we concluded that our method can be utilized for the accurate, rapid, and interpretable peptide-MHC binding prediction to assist biological therapies.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

Insights from analyses of low complexity regions with canonical methods for protein sequence comparison

Low complexity regions are fragments of protein sequences composed of only a few types of amino acids. These regions frequently occur in proteins and can play an important role in their functions. However, scientists are mainly focused on regions characterized by high diversity of amino acid composition. Similarity between regions of protein sequences frequently reflect functional similarity between them. In this article, we discuss strengths and weaknesses of the similarity analysis of low complexity regions using BLAST, HHblits and CD-HIT. These methods are considered to be the gold standard in protein similarity analysis and were designed for comparison of high complexity regions. However, we lack specialized methods that could be used to compare the similarity of low complexity regions. Therefore, we investigated the existing methods in order to understand how they can be applied to compare such regions. Our results are supported by exploratory study, discussion of amino acid composition and biological roles of selected examples. We show that existing methods need improvements to efficiently search for similar low complexity regions. We suggest features that have to be re-designed specifically for comparing low complexity regions: scoring matrix, multiple sequence alignment, e-value, local alignment and clustering based on a set of representative sequences. Results of this analysis can either be used to improve existing methods or to create new methods for the similarity analysis of low complexity regions.

In Silico Studies Reveal Peramivir and Zanamivir as an Optimal Drug Treatment Even If H7N9 Avian Type Influenza Virus Acquires Further Resistance

An epidemic of avian type H7N9 influenza virus, which took place in China in 2013, was enhanced by a naturally occurring R294K mutation resistant against Oseltamivir at the catalytic site of the neuraminidase. To cope with such drug-resistant neuraminidase mutations, we applied the molecular docking technique to evaluate the fitness of the available drugs such as Oseltamivir, Zanamivir, Peramivir, Laninamivir, L-Arginine and Benserazide hydrochloride concerning the N9 enzyme with single (R294K, R119K, R372K), double (R119_294K, R119_372K, R294_372K) and triple (R119_294_372K) mutations in the pocket. We found that the drugs Peramivir and Zanamivir score best amongst the studied compounds, demonstrating their high binding potential towards the pockets with the considered mutations. Despite the fact that mutations changed the shape of the pocket and reduced the binding strength for all drugs, Peramivir was the only drug that formed interactions with the key residues at positions 119, 294 and 372 in the pocket of the triple N9 mutant, while Zanamivir demonstrated the lowest RMSD value (0.7 Å) with respect to the reference structure.

IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States

The power of structural information for informing biological mechanisms is clear for stable folded macromolecules, but similar structure–function insight is more difficult to obtain for highly dynamic systems such as intrinsically disordered proteins (IDPs) which must be described as structural ensembles. Here, we present IDPConformerGenerator, a flexible, modular open-source software platform for generating large and diverse ensembles of disordered protein states that builds conformers that obey geometric, steric, and other physical restraints on the input sequence. IDPConformerGenerator samples backbone phi (φ), psi (ψ), and omega (ω) torsion angles of relevant sequence fragments from loops and secondary structure elements extracted from folded protein structures in the RCSB Protein Data Bank and builds side chains from robust Monte Carlo algorithms using expanded rotamer libraries. IDPConformerGenerator has many user-defined options enabling variable fractional sampling of secondary structures, supports Bayesian models for assessing the agreement of IDP ensembles for consistency with experimental data, and introduces a machine learning approach to transform between internal and Cartesian coordinates with reduced error. IDPConformerGenerator will facilitate the characterization of disordered proteins to ultimately provide structural insights into these states that have key biological functions.

Evolution of short linear motifs and disordered proteins Topic: yeast as model system to study evolution

Evolutionary preservation of protein structure had a major influence on the field of molecular evolution: changes in individual amino acids that did not disrupt protein folding would either have no effect or subtly change the 'lock' so that it could fit a new 'key'. Homology of individual amino acids could be confidently assigned through sequence alignments, and models of evolution could be tested. This view of molecular evolution excluded large regions of proteins that could not be confidently aligned, such as intrinsically disordered regions (IDRs) that do not fold into stable structures. In the last decade, major progress has been made in understanding the evolution of IDRs, much of it facilitated by new experimental and computational approaches in yeast. Here, we review this progress as well as several still outstanding questions.

idpr: A package for profiling and analyzing Intrinsically Disordered Proteins in R

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are proteins or protein-domains that do not have a single native structure, rather, they are a class of flexible peptides that can rapidly adopt multiple conformations. IDPs are quite abundant, and their dynamic characteristics provide unique advantages for various biological processes. The field of “unstructured biology” has emerged, in part, because of numerous computational studies that had identified the unique characteristics of IDPs and IDRs. The package ‘idpr’, short for Intrinsically Disordered Proteins in R, implements several R functions that match the established characteristics of IDPs to protein sequences of interest. This includes calculations of residue composition, charge-hydropathy relationships, and predictions of intrinsic disorder. Additionally, idpr integrates several amino acid substitution matrices and calculators to supplement IDP-based workflows. Overall, idpr aims to integrate tools for the computational analysis of IDPs within R, facilitating the analysis of these important, yet under-characterized, proteins. The idpr package can be downloaded from Bioconductor (https://bioconductor.org/packages/idpr/).

Examples of Extreme Survival: Tardigrade Genomics and Molecular Anhydrobiology

Tardigrades are ubiquitous meiofauna that are especially renowned for their exceptional extremotolerance to various adverse environments, including pressure, temperature, and even ionizing radiation. This is achieved through a reversible halt of metabolism triggered by desiccation, a phenomenon called anhydrobiosis. Recent establishment of genome resources for two tardigrades, Hypsibius exemplaris and Ramazzottius varieornatus, accelerated research to uncover the molecular mechanisms behind anhydrobiosis, leading to the discovery of many tardigrade-unique proteins. This review focuses on the history, methods, discoveries, and current state and challenges regarding tardigrade genomics, with an emphasis on molecular anhydrobiology. Remaining questions and future perspectives regarding prospective approaches to fully elucidate the molecular machinery of this complex phenomenon are discussed.

Functions of intrinsically disordered proteins through evolutionary lenses

Protein sequences are the result of an evolutionary process that involves the balancing act of experimenting with novel mutations and selecting out those that have an undesirable functional outcome. In the case of globular proteins, the function relies on a well-defined conformation, therefore, there is a strong evolutionary pressure to preserve the structure. However, different evolutionary rules might apply for the group of intrinsically disordered regions and proteins (IDR/IDPs) that exist as an ensemble of fluctuating conformations. The function of IDRs can directly originate from their disordered state or arise through different types of molecular recognition processes. There is an amazing variety of ways IDRs can carry out their functions, and this is also reflected in their evolutionary properties. In this chapter we give an overview of the different types of evolutionary behavior of disordered proteins and associated functions in normal and disease settings.

A Novel Core Effector Vp1 Promotes Fungal Colonization and Virulence of Ustilago maydis

The biotrophic fungus Ustilago maydis secretes a plethora of uncharacterized effector proteins and causes smut disease in maize. Among the effector genes that are up-regulated during the biotrophic growth in maize, we identified vp1 (virulence promoting 1), which has an expression that was up-regulated and maintained at a high level throughout the life cycle of the fungus. We characterized Vp1 by applying in silico analysis, reverse genetics, phenotypic assessment, microscopy, and protein localization and provided a fundamental understanding of the Vp1 protein in U. maydis. The reduction in fungal virulence and colonization in the vp1 mutant suggests the virulence-promoting function of Vp1. The deletion studies on the NLS (nuclear localization signal) sequence and the protein localization study revealed that the C-terminus of Vp1 is processed after secretion in plant apoplast and could localize to the plant nucleus. The Ustilago hordei ortholog UhVp1 lacks NLS localized in the plant cytoplasm, suggesting that the orthologs might have a distinct subcellular localization. Further complementation studies of the Vp1 orthologs in related smut fungi revealed that none of them could complement the virulence function of U. maydis Vp1, suggesting that UmVp1 could acquire a specialized function via sequence divergence.

Suppression of aggregate and amyloid formation by a novel intrinsically disordered region in metazoan Hsp110 chaperones

Molecular chaperones maintain proteostasis by ensuring the proper folding of polypeptides. Loss of proteostasis has been linked to numerous neurodegenerative disorders including Alzheimer's, Parkinson's, and Huntington's disease. Hsp110 is related to the canonical Hsp70 class of protein-folding molecular chaperones and interacts with Hsp70 as a nucleotide exchange factor (NEF). In addition to its NEF activity, Hsp110 possesses an Hsp70-like substrate-binding domain (SBD) whose biological roles remain undefined. Previous work in Drosophila melanogaster has implicated the sole Hsp110 gene (Hsc70cb) in proteinopathic neurodegeneration. We hypothesize that in addition to its role as an Hsp70 NEF, Drosophila Hsp110 may function as a protective protein "holdase," preventing the aggregation of unfolded polypeptides via the SBD-β subdomain. We demonstrate for the first time that Drosophila Hsp110 effectively prevents aggregation of the model substrate citrate synthase. We also report the discovery of a redundant and heretofore unknown potent holdase capacity in a 138-amino-acid region of Hsp110 carboxyl terminal to both SBD-β and SBD-α (henceforth called the C-terminal extension). This sequence is highly conserved in metazoan Hsp110 genes, completely absent from fungal representatives, and is computationally predicted to contain an intrinsically disordered region (IDR). We demonstrate that this IDR sequence within the human Hsp110s, Apg-1 and Hsp105α, inhibits the formation of amyloid Aβ-42 and α-synuclein fibrils in vitro but cannot mediate fibril disassembly. Together these findings establish capacity for metazoan Hsp110 chaperones to suppress both general protein aggregation and amyloidogenesis, raising the possibility of exploitation of this IDR for therapeutic benefit.

New Pathways of Mutational Change in SARS-CoV-2 Proteomes Involve Regions of Intrinsic Disorder Important for Virus Replication and Release

The massive worldwide spread of the SARS-CoV-2 virus is fueling the COVID-19 pandemic. Since the first whole-genome sequence was published in January 2020, a growing database of tens of thousands of viral genomes has been constructed. This offers opportunities to study pathways of molecular change in the expanding viral population that can help identify molecular culprits of virulence and virus spread. Here we investigate the genomic accumulation of mutations at various time points of the early pandemic to identify changes in mutationally highly active genomic regions that are occurring worldwide. We used the Wuhan NC_045512.2 sequence as a reference and sampled 15 342 indexed sequences from GISAID, translating them into proteins and grouping them by month of deposition. The per-position amino acid frequencies and Shannon entropies of the coding sequences were calculated for each month, and a map of intrinsic disorder regions and binding sites was generated. The analysis revealed dominant variants, most of which were located in loop regions and on the surface of the proteins. Mutation entropy decreased between March and April of 2020 after steady increases at several sites, including the D614G mutation site of the spike (S) protein that was previously found associated with higher case fatality rates and at sites of the NSP12 polymerase and the NSP13 helicase proteins. Notable expanding mutations include R203K and G204R of the nucleocapsid (N) protein inter-domain linker region and G251V of the viroporin encoded by ORF3a between March and April. The regions spanning these mutations exhibited significant intrinsic disorder, which was enhanced and decreased by the N-protein and viroporin 3a protein mutations, respectively. These results predict an ongoing mutational shift from the spike and replication complex to other regions, especially to encoded molecules known to represent major β-interferon antagonists. The study provides valuable information for therapeutics and vaccine design, as well as insight into mutation tendencies that could facilitate preventive control.

Substitution scoring matrices for proteins - An overview

Sequence analysis is the primary and simplest approach to discover structural, functional and evolutionary details of related proteins. All the alignment based approaches of sequence analysis make use of amino acid substitution matrices, and the accuracy of the results largely depends on the type of scoring matrices used to perform alignment tasks. An amino acid substitution matrix is a 20 × 20 matrix in which the individual elements encapsulate the rates at which each of the 20 amino acid residues in proteins are substituted by other amino acid residues over time. In contrast to most globular/ordered proteins whose amino acids composition is considered as standard, there are several classes of proteins (e.g., transmembrane proteins) in which certain types of amino acid (e.g., hydrophobic residues) are enriched. These compositional differences among various classes of proteins are manifested in their underlying residue substitution frequencies. Therefore, each of the compositionally distinct class of proteins or protein segments should be studied using specific scoring matrices that reflect their distinct residue substitution pattern. In this review, we describe the development and application of various substitution scoring matrices peculiar to proteins with standard and biased compositions. Along with most commonly used standard matrices (PAM, BLOSUM, MD and VTML) that act as default parameters in various homologs search and alignment tools, different substitution scoring matrices specific to compositionally distinct class of proteins are discussed in detail.