The present and the future of motif-mediated protein-protein interactions

Genome-wide identification of MATE and ALMT genes and their expression profiling in mungbean (Vigna radiata L.) under aluminium stress

The Multidrug and toxic compound extrusion (MATE) and aluminium activated malate transporter (ALMT) gene families are involved in response to aluminium (Al) stress. In this study, we identified 48 MATE and 14 ALMT gene families in Vigna radiata genome and classified into 5 (MATE) and 3 (ALMT) clades by phylogenetic analysis. All the VrMATE and VrALMT genes were distributed across mungbean chromosomes. Tandem duplication was the main driving force for evolution and expansion of MATE gene family. Collinearity of mungbean with soybean indicated that MATE gene family is closely linked to Glycine max. Eight MATE transporters in clade 2 were found to be associated with previously characterized Al tolerance related MATEs in various plant species. Citrate exuding motif (CEM) was present in seven VrMATEs of clade 2. Promoter analysis revealed abundant plant hormone and stress responsive cis-elements. Results from quantitative real time-polymerase chain reaction (qRT-PCR) revealed that VrMATE19, VrMATE30 and VrALMT13 genes were markedly up-regulated at different time points under Al stress. Overall, this study offers a new direction for further molecular characterization of the MATE and ALMT genes in mungbean for Al tolerance.

Assessing the functional impact of protein binding site definition

Many biomedical applications, such as classification of binding specificities or bioengineering, depend on the accurate definition of protein binding interfaces. Depending on the choice of method used, substantially different sets of residues can be classified as belonging to the interface of a protein. A typical approach used to verify these definitions is to mutate residues and measure the impact of these changes on binding. Besides the lack of exhaustive data, this approach also suffers from the fundamental problem that a mutation introduces an unknown amount of alteration into an interface, which potentially alters the binding characteristics of the interface. In this study we explore the impact of alternative binding site definitions on the ability of a protein to recognize its cognate ligand using a pharmacophore approach, which does not affect the interface. The study also shows that methods for protein binding interface predictions should perform above approximately F-score = 0.7 accuracy level to capture the biological function of a protein.

Proteome-wide assessment of human interactome as a source of capturing domain-motif and domain-domain interactions

Protein-protein interactions (PPIs) play a crucial role in various biological processes by establishing domain-motif (DMI) and domain-domain interactions (DDIs). While the existence of real DMIs/DDIs is generally assumed, it is rarely tested; therefore, this study extensively compared high-throughput methods and public PPI repositories as sources for DMI and DDI prediction based on the assumption that the human interactome provides sufficient data for the reliable identification of DMIs and DDIs. Different datasets from leading high-throughput methods (Yeast two-hybrid [Y2H], Affinity Purification coupled Mass Spectrometry [AP-MS], and Co-fractionation-coupled Mass Spectrometry) were assessed for their ability to capture DMIs and DDIs using known DMI/DDI information. High-throughput methods were not notably worse than PPI databases and, in some cases, appeared better. In conclusion, all PPI datasets demonstrated significant enrichment in DMIs and DDIs (p-value <0.001), establishing Y2H and AP-MS as reliable methods for predicting these interactions. This study provides valuable insights for biologists in selecting appropriate methods for predicting DMIs, ultimately aiding in SLiM discovery.

Computational Evaluation of Peptide-Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains

Many biological functions are mediated by protein-protein interactions (PPIs), often involving specific structural modules, such as SH2 domains. Inhibition of PPIs is a pharmaceutical strategy of growing importance. However, a major challenge in the design of PPI inhibitors is the large interface involved in these interactions, which, in many cases, makes inhibition by small organic molecules ineffective. Peptides, which cover a wide range of dimensions and can be opportunely designed to mimic protein sequences at PPI interfaces, represent a valuable alternative to small molecules. Computational techniques able to predict the binding affinity of peptides for the target domain or protein represent a crucial stage in the workflow for the design of peptide-based drugs. This chapter describes a protocol to obtain the potential of mean force (PMF) for peptide-SH2 domain binding, starting from umbrella sampling (US) molecular dynamics (MD) simulations. The PMF profiles can be effectively used to predict the relative standard binding free energies of different peptide sequences.

Quantitative fragmentomics allow affinity mapping of interactomes

Human protein networks have been widely explored but most binding affinities remain unknown, hindering quantitative interactome-function studies. Yet interactomes rely on minimal interacting fragments displaying quantifiable affinities. Here, we measure the affinities of 65,000 interactions involving PDZ domains and their target PDZ-binding motifs (PBM) within a human interactome region particularly relevant for viral infection and cancer. We calculate interactomic distances, identify hot spots for viral interference, generate binding profiles and specificity logos, and explain selected cases by crystallographic studies. Mass spectrometry experiments on cell extracts and literature surveys show that quantitative fragmentomics effectively complements protein interactomics by providing affinities and completeness of coverage, putting a full human interactome affinity survey within reach. Finally, we show that interactome hijacking by the viral PBM of human papillomavirus E6 oncoprotein substantially impacts the host cell proteome beyond immediate E6 binders, illustrating the complex system-wide relationship between interactome and function.

Protein networks have been widely explored but most binding affinities remain unknown, limiting the quantitative interpretation of interactomes. Here the authors measure affinities of 65,000 interactions involving human PDZ domains and target sequence motifs relevant for viral infection and cancer.

Topological frustration leading to backtracking in a coupled folding-binding process

Intrinsically disordered proteins (IDPs) are abundant in all species. Their discovery challenges the traditional "sequence-structure-function" paradigm of protein science because IDPs play important roles in various biological processes without preformed folded structures. Bioinformatic analysis reveals that the intrinsically conformational disorder of IDPs as well as their conformational transition upon binding to their targets is encoded by their amino acid sequences. The rRNase domain of colicin E3 and the immunity protein Im3 are a pair of proteins involved in bacterial survival. While the N-terminal segment and the central segment of E3 make comparable intermolecular contacts with Im3 in the bound state, binding of E3 with Im3 is dominantly triggered by the central segment of E3. In this work, to further investigate the binding mechanism of disordered E3 with Im3, we performed systematic free energy and transition path analysis through coarse-grained molecular dynamics simulations. We observed backtracking of the N-terminal segment of E3 in the binding process, whose occurrence depends on salt concentration. Conformational analysis revealed that initial binding of the N-terminal segment of E3 to Im3 usually leads to misorientation of a central hairpin of E3 on Im3, which generates topological frustration and results in backtracking of the N-terminal segment. Our results not only provide deeper mechanistic insights into the coupled folding-binding process of the E3/Im3 complex, but also suggest that topological frustration could be present in the coupled folding-binding process of IDPs and play an important role in regulating the binding transition pathways.

The Eukaryotic Linear Motif resource: 2022 release

Almost twenty years after its initial release, the Eukaryotic Linear Motif (ELM) resource remains an invaluable source of information for the study of motif-mediated protein-protein interactions. ELM provides a comprehensive, regularly updated and well-organised repository of manually curated, experimentally validated short linear motifs (SLiMs). An increasing number of SLiM-mediated interactions are discovered each year and keeping the resource up-to-date continues to be a great challenge. In the current update, 30 novel motif classes have been added and five existing classes have undergone major revisions. The update includes 411 new motif instances mostly focused on cell-cycle regulation, control of the actin cytoskeleton, membrane remodelling and vesicle trafficking pathways, liquid-liquid phase separation and integrin signalling. Many of the newly annotated motif-mediated interactions are targets of pathogenic motif mimicry by viral, bacterial or eukaryotic pathogens, providing invaluable insights into the molecular mechanisms underlying infectious diseases. The current ELM release includes 317 motif classes incorporating 3934 individual motif instances manually curated from 3867 scientific publications. ELM is available at: http://elm.eu.org.

Genome-Wide Identification of MATE Gene Family in Potato (Solanum tuberosum L.) and Expression Analysis in Heavy Metal Stress

A genome-wide identification and expression analysis of multidrug and toxic compound extrusion (MATE) gene family in potato was carried out to explore the response of MATE proteins to heavy meta stress. In this study, we identified 64 MATE genes from potato genome, which are located on 12 chromosomes, and are divided into I–IV subfamilies based on phylogenetic analysis. According to their order of appearance on the chromosomes, they were named from StMATE1–64. Subcellular location prediction showed that 98% of them are located on the plasma membrane as transporters. Synteny analysis showed that five pairs of collinearity gene pairs belonged to members of subfamily I and subfamily II had two pairs indicating that the duplication is of great significance to the evolution of genes in subfamilies I and II. Gene exon–intron structures and motif composition are more similar in the same subfamily. Every StMATE gene contained at least one cis-acting element associated with regulation of hormone transport. The relative expression levels of eight StMATE genes were significantly upregulated under Cu²⁺ stress compared with the non-stress condition (0 h). After Cd²⁺ stress for 24 h, the expression levels of StMATE33 in leaf tissue were significantly increased, indicating its crucial role in the process of Cd²⁺ stress. Additionally, StMATE18/60/40/33/5 were significantly induced by Cu²⁺ stress, while StMATE59 (II) was significantly induced by Ni²⁺ stress. Our study initially explores the biological functions of StMATE genes in the regulation of heavy metal stress, further providing a theoretical basis for studying the subsequent molecular mechanisms in detail.

Drug design targeting active posttranslational modification protein isoforms

Modern drug design aims to discover novel lead compounds with attractable chemical profiles to enable further exploration of the intersection of chemical space and biological space. Identification of small molecules with good ligand efficiency, high activity, and selectivity is crucial toward developing effective and safe drugs. However, the intersection is one of the most challenging tasks in the pharmaceutical industry, as chemical space is almost infinity and continuous, whereas the biological space is very limited and discrete. This bottleneck potentially limits the discovery of molecules with desirable properties for lead optimization. Herein, we present a new direction leveraging posttranslational modification (PTM) protein isoforms target space to inspire drug design termed as "Post-translational Modification Inspired Drug Design (PTMI-DD)." PTMI-DD aims to extend the intersections of chemical space and biological space. We further rationalized and highlighted the importance of PTM protein isoforms and their roles in various diseases and biological functions. We then laid out a few directions to elaborate the PTMI-DD in drug design including discovering covalent binding inhibitors mimicking PTMs, targeting PTM protein isoforms with distinctive binding sites from that of wild-type counterpart, targeting protein-protein interactions involving PTMs, and hijacking protein degeneration by ubiquitination for PTM protein isoforms. These directions will lead to a significant expansion of the biological space and/or increase the tractability of compounds, primarily due to precisely targeting PTM protein isoforms or complexes which are highly relevant to biological functions. Importantly, this new avenue will further enrich the personalized treatment opportunity through precision medicine targeting PTM isoforms.

Programmed Trade-offs in Protein Folding Networks

Molecular chaperones as specialized protein quality control enzymes form the core of cellular protein homeostasis. How chaperones selectively interact with their substrate proteins thus allocate their overall limited capacity remains poorly understood. Here, I present an integrated analysis of sequence and structural determinants that define interactions of protein domains as the basic protein folding unit with the Saccharomyces cerevisiae Hsp70 Ssb. Structural homologs of single-domain proteins that differentially interact with Ssb for de novo folding were found to systematically differ in complexity of their folding landscapes, selective use of nonoptimal codons, and presence of short discriminative sequences, thus highlighting pervasive trade-offs in chaperone-assisted protein folding landscapes. However, short discriminative sequences were found to contribute by far the strongest signal toward explaining Ssb interactions. This observation suggested that some chaperone interactions may be directly programmed in the amino acid sequences rather than responding to folding challenges, possibly for regulatory advantages.

Learning peptide recognition rules for a low-specificity protein

Many proteins interact with short linear regions of target proteins. For some proteins, however, it is difficult to identify a well-defined sequence motif that defines its target peptides. To overcome this difficulty, we used supervised machine learning to train a model that treats each peptide as a collection of easily-calculated biochemical features rather than as an amino acid sequence. As a test case, we dissected the peptide-recognition rules for human S100A5 (hA5), a low-specificity calcium binding protein. We trained a Random Forest model against a recently released, high-throughput phage display dataset collected for hA5. The model identifies hydrophobicity and shape complementarity, rather than polar contacts, as the primary determinants of peptide binding specificity in hA5. We tested this hypothesis by solving a crystal structure of hA5 and through computational docking studies of diverse peptides onto hA5. These structural studies revealed that peptides exhibit multiple binding modes at the hA5 peptide interface-all of which have few polar contacts with hA5. Finally, we used our trained model to predict new, plausible binding targets in the human proteome. This revealed a fragment of the protein α-1-syntrophin that binds to hA5. Our work helps better understand the biochemistry and biology of hA5, as well as demonstrating how high-throughput experiments coupled with machine learning of biochemical features can reveal the determinants of binding specificity in low-specificity proteins.

Motifs and interface amino acid-mediated regulation of amyloid biogenesis in microbes to humans: potential targets for intervention

Amyloids are linked to many debilitating diseases in mammals. Some organisms produce amyloids that have a functional role in the maintenance of their biological processes. Microbes utilize functional bacterial amyloids (FuBA) for pathogenicity and infections. Amyloid biogenesis is regulated differentially in various systems to avoid its toxic accumulation. A familiar feature in the process of amyloid biogenesis from humans to microbes is its regulation by protein-protein interactions (PPI). The spatial arrangement of amino acid residues in proteins generates topologies like flat interface and linear motif, which participate in protein interactions. Motifs and interface residue-mediated interactions have a direct or an indirect impact on amyloid secretion and assembly. Some motifs undergo post-translational modifications (PTM), which effects interactions and dynamics of the amyloid biogenesis cascade. Interaction-induced local changes stimulate global conformational transitions in the PPI complex, which indirectly affects amyloid formation. Perturbation of such motifs and interface residues results in amyloid abolishment. Interface residues, motifs and their respective interactive protein partners could serve as potential targets for intervention to inhibit amyloid biogenesis.

Protein-Protein Interactions Mediated by Intrinsically Disordered Protein Regions Are Enriched in Missense Mutations

Because proteins are fundamental to most biological processes, many genetic diseases can be traced back to single nucleotide variants (SNVs) that cause changes in protein sequences. However, not all SNVs that result in amino acid substitutions cause disease as each residue is under different structural and functional constraints. Influential studies have shown that protein–protein interaction interfaces are enriched in disease-associated SNVs and depleted in SNVs that are common in the general population. These studies focus primarily on folded (globular) protein domains and overlook the prevalent class of protein interactions mediated by intrinsically disordered regions (IDRs). Therefore, we investigated the enrichment patterns of missense mutation-causing SNVs that are associated with disease and cancer, as well as those present in the healthy population, in structures of IDR-mediated interactions with comparisons to classical globular interactions. When comparing the different categories of interaction interfaces, division of the interface regions into solvent-exposed rim residues and buried core residues reveal distinctive enrichment patterns for the various types of missense mutations. Most notably, we demonstrate a strong enrichment at the interface core of interacting IDRs in disease mutations and its depletion in neutral ones, which supports the view that the disruption of IDR interactions is a mechanism underlying many diseases. Intriguingly, we also found an asymmetry across the IDR interaction interface in the enrichment of certain missense mutation types, which may hint at an increased variant tolerance and urges further investigations of IDR interactions.

Degradation of proteins by PROTACs and other strategies

Blocking the biological functions of scaffold proteins and aggregated proteins is a challenging goal. PROTAC proteolysis-targeting chimaera (PROTAC) technology may be the solution, considering its ability to selectively degrade target proteins. Recent progress in the PROTAC strategy include identification of the structure of the first ternary eutectic complex, extra-terminal domain-4-PROTAC-Von-Hippel-Lindau (BRD4-PROTAC-VHL), and PROTAC ARV-110 has entered clinical trials for the treatment of prostate cancer in 2019. These discoveries strongly proved the value of the PROTAC strategy. In this perspective, we summarized recent meaningful research of PROTAC, including the types of degradation proteins, preliminary biological data in vitro and in vivo, and new E3 ubiquitin ligases. Importantly, the molecular design, optimization strategy and clinical application of candidate molecules are highlighted in detail. Future perspectives for development of advanced PROTAC in medical fields have also been discussed systematically.

Resources to Discover and Use Short Linear Motifs in Viral Proteins

Viral proteins evade host immune function by molecular mimicry, often achieved by short linear motifs (SLiMs) of three to ten consecutive amino acids (AAs). Motif mimicry tolerates mutations, evolves quickly to modify interactions with the host, and enables modular interactions with protein complexes. Host cells cannot easily coordinate changes to conserved motif recognition and binding interfaces under selective pressure to maintain critical signaling pathways. SLiMs offer potential for use in synthetic biology, such as better immunogens and therapies, but may also present biosecurity challenges. We survey viral uses of SLiMs to mimic host proteins, and information resources available for motif discovery. As the number of examples continues to grow, knowledge management tools are essential to help organize and compare new findings.

Features of molecular recognition of intrinsically disordered proteins via coupled folding and binding

The sequence-structure-function paradigm of proteins has been revolutionized by the discovery of intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). In contrast to traditional ordered proteins, IDPs/IDRs are unstructured under physiological conditions. The absence of well-defined three-dimensional structures in the free state of IDPs/IDRs is fundamental to their function. Folding upon binding is an important mode of molecular recognition for IDPs/IDRs. While great efforts have been devoted to investigating the complex structures and binding kinetics and affinities, our knowledge on the binding mechanisms of IDPs/IDRs remains very limited. Here, we review recent advances on the binding mechanisms of IDPs/IDRs. The structures and kinetic parameters of IDPs/IDRs can vary greatly, and the binding mechanisms can be highly dependent on the structural properties of IDPs/IDRs. IDPs/IDRs can employ various combinations of conformational selection and induced fit in a binding process, which can be templated by the target and/or encoded by the IDP/IDR. Further studies should provide deeper insights into the molecular recognition of IDPs/IDRs and enable the rational design of IDP/IDR binding mechanisms in the future.

Applications of in Silico Methods for Design and Development of Drugs Targeting Protein-Protein Interactions

BACKGROUND

Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.

OBJECTIVE

Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, when deregulated. Multiplicity and great amount of PPIs structures offer a huge number of new and potential targets for the treatment of different diseases.

METHODS

Computational techniques are becoming predominant in PPIs studies for their effectiveness, flexibility, accuracy and cost. As a matter of fact, there are effective in silico approaches which are able to identify PPIs and PPI site. Such methods for computational target prediction have been developed through molecular descriptors and data-mining procedures.

RESULTS

In this review, we present different types of interactions between protein-protein and the application of in silico methods for design and development of drugs targeting PPIs. We described computational approaches for the identification of possible targets on protein surface and to detect of stimulator/ inhibitor molecules.

CONCLUSION

A deeper study of the most recent bioinformatics methodologies for PPIs studies is vital for a better understanding of protein complexes and for discover new potential PPI modulators in therapeutic intervention.

Predicting Protein-Protein Interfaces that Bind Intrinsically Disordered Protein Regions

A long-standing goal in biology is the complete annotation of function and structure on all protein-protein interactions, a large fraction of which is mediated by intrinsically disordered protein regions (IDRs). However, knowledge derived from experimental structures of such protein complexes is disproportionately small due, in part, to challenges in studying interactions of IDRs. Here, we introduce IDRBind, a computational method that by combining gradient boosted trees and conditional random field models predicts binding sites of IDRs with performance approaching state-of-the-art globular interface predictions, making it suitable for proteome-wide applications. Although designed and trained with a focus on molecular recognition features, which are long interaction-mediating-elements in IDRs, IDRBind also predicts the binding sites of short peptides more accurately than existing specialized predictors. Consistent with IDRBind's specificity, a comparison of protein interface categories uncovered uniform trends in multiple physicochemical properties, positioning molecular recognition feature interfaces between peptide and globular interfaces.

Anti-virus reagents targeting the capsid protein assembly

The capsid protein is a promising target for the development of therapeutic anti-virus agents.