Transient protein-protein interactions: structural, functional, and network properties

Protein-Protein Interaction Prediction via Structure-Based Deep Learning

Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with various sequence lengths and suffer from low generalization and prediction accuracy. In this study, we proposed a novel end-to-end deep learning framework, RSPPI, combining residual neural network (ResNet) and spatial pyramid pooling (SPP), to predict PPIs based on the protein sequence physicochemistry properties and spatial structural information. In the RSPPI model, ResNet was employed to extract the structural and physicochemical information from the protein three-dimensional structure and primary sequence; the SPP layer was used to transform feature maps to a single vector and avoid the fixed-length requirement. The RSPPI model possessed excellent cross-species performance and outperformed several state-of-the-art methods based either on protein sequence or gene ontology in most evaluation metrics. The RSPPI model provides a novel strategy to develop an AI PPI prediction algorithm.

Microscale measurements of protein complexes from single cells

Proteins execute numerous cell functions in concert with one another in protein-protein interactions (PPI). While essential in each cell, such interactions are not identical from cell to cell. Instead, PPI heterogeneity contributes to cellular phenotypic heterogeneity in health and diseases such as cancer. Understanding cellular phenotypic heterogeneity thus requires measurements of properties of PPIs such as abundance, stoichiometry, and kinetics at the single-cell level. Here, we review recent, exciting progress in single-cell PPI measurements. Novel technology in this area is enabled by microscale and microfluidic approaches that control analyte concentration in timescales needed to outpace PPI disassembly kinetics. We describe microscale innovations, needed technical capabilities, and methods poised to be adapted for single-cell analysis in the near future.

A native mass spectrometry approach to qualitatively elucidate interfacial epitopes of transient protein-protein interactions

Native mass spectrometric analysis of TPR2A and GrpE with unpurified peptides derived from limited proteolysis of their respective PPI partners (HSP90 C-terminus and DnaK) facilitated efficient, qualitative identification of interfacial epitopes involved in transient PPI formation. Application of this approach can assist in elucidating interfaces of currently uncharacterised transient PPIs.

Association mechanism between Arabidopsis immune coreceptor BAK1 and Pseudomonas syringae effector HopF2

Brassinosteroid activated kinase 1 (BAK1) is a cell-surface coreceptor which plays multiple roles in innate immunity of plants. HopF2 is an effector secreted by the bacterial pathogen Pseudomonas syringae pv. tomato DC3000 into Arabidopsis and suppresses host immune system through interaction with BAK1 as well as its downstream kinase MKK5. The association mechanism of HopF2 to BAK1 remains unclear, which prohibits our understanding and subsequent interfering of their interaction for pathogen management. Herein, we found the kinase domain of BAK1 (BAK1-KD) is sufficient for HopF2 association. With a combination of hydrogen/deuterium exchange mass spectrometry and mutational assays, we found a region of BAK1-KD N-lobe and a region of HopF2 head subdomain are critical for intermolecular interaction, which is also supported by unbiased protein-protein docking with ClusPro and kinase activity assay. Collectively, this research presents the interaction mechanism between Arabidopsis BAK1 and P. syringae HopF2, which could pave the way for bactericide development that blocking the functioning of HopF2 toward BAK1.

Database-Driven Identification of Structurally Similar Protein-Protein Interfaces

Analyzing the similarity of protein interfaces in protein-protein interactions gives new insights into protein function and assists in discovering new drugs. Usually, tools that assess the similarity focus on the interactions between two protein interfaces, while sometimes we only have one predicted interface. Herein, we present PiMine, a database-driven protein interface similarity search. It compares interface residues of one or two interacting chains by calculating and searching tetrahedral geometric patterns of α-carbon atoms and calculating physicochemical and shape-based similarity. On a dedicated, tailor-made dataset, we show that PiMine outperforms commonly used comparison tools in terms of early enrichment when considering interfaces of sequentially and structurally unrelated proteins. In an application example, we demonstrate its usability for protein interaction partner prediction by comparing predicted interfaces to known protein-protein interfaces.

Generation and Characterization of Engineered Ubiquitin Variants to Modulate the Ubiquitin Signaling Cascade

The ubiquitin signaling cascade plays a crucial role in human cells. Consistent with this, malfunction of ubiquitination and deubiquitination is implicated in the initiation and progression of numerous human diseases, including cancer. Therefore, the development of potent and specific modulators of ubiquitin signal transduction has been at the forefront of drug development. In the past decade, a structure-based combinatorial protein-engineering approach has been used to generate ubiquitin variants (UbVs) as protein-based modulators of multiple components in the ubiquitin-proteasome system. Here, we review the design and generation of phage-displayed UbV libraries, including the processes of binder selection and library improvement. We also provide a comprehensive overview of the general in vitro and cellular methodologies involved in characterizing UbV binders. Finally, we describe two recent applications of UbVs for developing molecules with therapeutic potential.

The knowns and unknowns of callose biosynthesis in terrestrial plants

Callose, a linear (1,3)-β-glucan, is an indispensable carbohydrate polymer required for plant growth and development. Advances in biochemical, genetic, and genomic tools, along with specific antibodies, have significantly enhanced our understanding of callose biosynthesis. As additional components of the callose synthase machinery emerge, the elucidation of molecular biosynthetic mechanisms is expected to follow. Short-term objectives involve defining the stoichiometry and turnover rates of callose synthase subunits. Long-term goals include generating recombinant callose synthases to elucidate their biochemical properties and molecular mechanisms, potentially culminating in the determination of callose synthase three-dimensional structure. This review delves into the structures and intricate molecular processes underlying callose biosynthesis, emphasizing regulatory elements and assembly mechanisms.

Tripartite Split-GFP for High Throughput Screening of Small Molecules: A Powerful Strategy for Targeting Transient/Labile Interactors like E2-E3 Ubiquitination Enzymes

The search for inhibitors of the Ubiquitin Proteasome System (UPS) is an expanding area, due to the crucial role of UPS enzymes in several diseases. The complexity of the UPS and the multiple protein-protein interactions (PPIs) involved, either between UPS proteins themselves or between UPS components and theirs targets, offer an incredibly wide field for the development of chemical compounds for specifically modulating or inhibiting metabolic pathways. However, numerous UPS PPIs are transient/labile, due the processivity of the system (Ubiquitin [Ub] chain elongation, Ub transfer, etc.). Among the different strategies that can be used either for deciphering UPS PPI or for identifying/characterizing small compounds inhibitors, the split-GFP approach offers several advantages notably for high throughput screening of drugs. Split-GFP is based on the principle of protein-fragment complementation assay (PCA). PCA allows addressing PPIs by coupling each protein of interest (POI) to fragments of a reporter protein whose reconstitution is linked to the interaction of the POI. Here, we review the evolution of the split-GFP approach from bipartite to tripartite Split-GFP and its recent applicability for screening chemical compounds targeting the UPS.

Spray-type modifications: an emerging paradigm in post-translational modifications

A post-translational modification (PTM) occurs when a nucleophilic residue (e.g., lysine of a target protein) attacks electrophilic substrate molecules (e.g., acyl-AMP), involving writer enzymes or even occurring spontaneously. Traditionally, this phenomenon was thought to be sequence specific; however, recent research suggests that PTMs can also occur in a non-sequence-specific manner confined to a specific location in a cell. In this Opinion, we compile the accumulated evidence of spray-type PTMs and propose a mechanism for this phenomenon based on the exposure level of reactive electrophilic substrate molecules at the active site of the PTM writers. Overall, a spray-type PTM conceptual framework is useful for comprehending the promiscuous PTM writer events that cannot be adequately explained by the traditional concept of sequence-dependent PTM events.

Programming interchangeable and reversible heterooligomeric protein self-assembly using a bifunctional ligand

Protein design for self-assembly allows us to explore the emergence of protein-protein interfaces through various chemical interactions. Heterooligomers, unlike homooligomers, inherently offer a comprehensive range of structural and functional variations. Besides, the macromolecular repertoire and their applications would significantly expand if protein components could be easily interchangeable. This study demonstrates that a rationally designed bifunctional linker containing an enzyme inhibitor and maleimide can guide the formation of diverse protein heterooligomers in an easily applicable and exchangeable manner without extensive sequence optimizations. As proof of concept, we selected four structurally and functionally unrelated proteins, carbonic anhydrase, aldolase, acetyltransferase, and encapsulin, as building block proteins. The combinations of two proteins with the bifunctional linker yielded four two-component heterooligomers with discrete sizes, shapes, and enzyme activities. Besides, the overall size and formation kinetics of the heterooligomers alter upon adding metal chelators, acidic buffer components, and reducing agents, showing the reversibility and tunability in the protein self-assembly. Given that the functional groups of both the linker and protein components are readily interchangeable, our work broadens the scope of protein-assembled architectures and their potential applications as functional biomaterials.

Searching for EGF Fragments Recreating the Outer Sphere of the Growth Factor Involved in Receptor Interactions

The aims of this study were to determine whether it is possible to use peptide microarrays obtained using the SPOT technique (immobilized on cellulose) and specific polyclonal antibodies to select fragments that reconstruct the outer sphere of proteins and to ascertain whether the selected peptide fragments can be useful in the study of their protein-protein and/or peptide-protein interactions. Using this approach, epidermal growth factor (EGF) fragments responsible for the interaction with the EGF receptor were searched. A library of EGF fragments immobilized on cellulose was obtained using triazine condensing reagents. Experiments on the interactions with EGFR confirmed the high affinity of the selected peptide fragments. Biological tests on cells showed the lack of cytotoxicity of the EGF fragments. Selected EGF fragments can be used in various areas of medicine.

Predictive Models and Impact of Interfacial Contacts and Amino Acids on Protein-Protein Binding Affinity

Protein-protein interactions (PPIs) play a central role in nearly all cellular processes. The strength of the binding in a PPI is characterized by the binding affinity (BA) and is a key factor in controlling protein-protein complex formation and defining the structure-function relationship. Despite advancements in understanding protein-protein binding, much remains unknown about the interfacial region and its association with BA. New models are needed to predict BA with improved accuracy for therapeutic design. Here, we use machine learning approaches to examine how well different types of interfacial contacts can be used to predict experimentally determined BA and to reveal the impact of the specific amino acids at the binding interface on BA. We create a series of multivariate linear regression models incorporating different contact features at both residue and atomic levels and examine how different methods of identifying and characterizing these properties impact the performance of these models. Particularly, we introduce a new and simple approach to predict BA based on the quantities of specific amino acids at the protein-protein interface. We found that the numbers of specific amino acids at the protein-protein interface were correlated with BA. We show that the interfacial numbers of amino acids can be used to produce models with consistently good performance across different data sets, indicating the importance of the identities of interfacial amino acids in underlying BA. When trained on a diverse set of complexes from two benchmark data sets, the best performing BA model was generated with an explicit linear equation involving six amino acids. Tyrosine, in particular, was identified as the key amino acid in controlling BA, as it had the strongest correlation with BA and was consistently identified as the most important amino acid in feature importance studies. Glycine and serine were identified as the next two most important amino acids in predicting BA. The results from this study further our understanding of PPIs and can be used to make improved predictions of BA, giving them implications for drug design and screening in the pharmaceutical industry.

Cell state dependent effects of Bmal1 on melanoma immunity and tumorigenicity

The circadian clock regulator Bmal1 modulates tumorigenesis, but its reported effects are inconsistent. Here, we show that Bmal1 has a context-dependent role in mouse melanoma tumor growth. Loss of Bmal1 in YUMM2.1 or B16-F10 melanoma cells eliminates clock function and diminishes hypoxic gene expression and tumorigenesis, which could be rescued by ectopic expression of HIF1α in YUMM2.1 cells. By contrast, over-expressed wild-type or a transcriptionally inactive mutant Bmal1 non-canonically sequester myosin heavy chain 9 (Myh9) to increase MRTF-SRF activity and AP-1 transcriptional signature, and shift YUMM2.1 cells from a Sox10high to a Sox9high immune resistant, mesenchymal cell state that is found in human melanomas. Our work describes a link between Bmal1, Myh9, mouse melanoma cell plasticity, and tumor immunity. This connection may underlie cancer therapeutic resistance and underpin the link between the circadian clock, MRTF-SRF and the cytoskeleton.

APP-C31: An Intracellular Promoter of Both Metal-Free and Metal-Bound Amyloid-β40 Aggregation and Toxicity in Alzheimer's Disease

Intracellular C-terminal cleavage of the amyloid precursor protein (APP) is elevated in the brains of Alzheimer's disease (AD) patients and produces a peptide labeled APP-C31 that is suspected to be involved in the pathology of AD. But details about the role of APP-C31 in the development of the disease are not known. Here, this work reports that APP-C31 directly interacts with the N-terminal and self-recognition regions of amyloid-β40 (Aβ40 ) to form transient adducts, which facilitates the aggregation of both metal-free and metal-bound Aβ40 peptides and aggravates their toxicity. Specifically, APP-C31 increases the perinuclear and intranuclear generation of large Aβ40 deposits and, consequently, damages the nucleus leading to apoptosis. The Aβ40 -induced degeneration of neurites and inflammation are also intensified by APP-C31 in human neurons and murine brains. This study demonstrates a new function of APP-C31 as an intracellular promoter of Aβ40 amyloidogenesis in both metal-free and metal-present environments, and may offer an interesting alternative target for developing treatments for AD that have not been considered thus far.

Using PrISMa to reveal the interactome of the human claudins family

Here, we provide a protocol for the systematic screening of protein-protein interactions mediated by short linear motifs using the Protein Interaction Screen on a peptide Matrix (PrISMa) technique. We describe how to pull down interacting proteins in a parallelized manner and identify them by mass spectrometry. Finally, we describe a bioinformatic workflow necessary to identify highly probable interaction partners in the large-scale dataset. We describe the application of this method for the transient interactome of the claudin protein family. For complete details on the use and execution of this protocol, please refer to Suarez-Artiles et al.1.

The Proinflammatory Role of ANGPTL8 R59W Variant in Modulating Inflammation through NF-κB Signaling Pathway under TNFα Stimulation

BACKGROUND

Angiopoietin-like protein 8 (ANGPTL8) is known to regulate lipid metabolism and inflammation. It interacts with ANGPTL3 and ANGPTL4 to regulate lipoprotein lipase (LPL) activity and with IKK to modulate NF-κB activity. Further, a single nucleotide polymorphism (SNP) leading to the ANGPTL8 R59W variant associates with reduced low-density lipoprotein/high-density lipoprotein (LDL/HDL) and increased fasting blood glucose (FBG) in Hispanic and Arab individuals, respectively. In this study, we investigate the impact of the R59W variant on the inflammatory activity of ANGPTL8.

METHODS

The ANGPTL8 R59W variant was genotyped in a discovery cohort of 867 Arab individuals from Kuwait. Plasma levels of ANGPTL8 and inflammatory markers were measured and tested for associations with the genotype; the associations were tested for replication in an independent cohort of 278 Arab individuals. Impact of the ANGPTL8 R59W variant on NF-κB activity was examined using approaches including overexpression, luciferase assay, and structural modeling of binding dynamics.

RESULTS

The ANGPTL8 R59W variant was associated with increased circulatory levels of tumor necrosis factor alpha (TNFα) and interleukin 7 (IL7). Our in vitro studies using HepG2 cells revealed an increased phosphorylation of key inflammatory proteins of the NF-κB pathway in individuals with the R59W variant as compared to those with the wild type, and TNFα stimulation further elevated it. This finding was substantiated by increased luciferase activity of NF-κB p65 with the R59W variant. Modeled structural and binding variation due to R59W change in ANGPTL8 agreed with the observed increase in NF-κB activity.

CONCLUSION

ANGPTL8 R59W is associated with increased circulatory TNFα, IL7, and NF-κB p65 activity. Weak transient binding of the ANGPTL8 R59W variant explains its regulatory role on the NF-κB pathway and inflammation.

Elucidating the dynamic remodelling of Escherichia coli interactome in different growth conditions using multiplex co-fractionation MS (mCF-MS)

Most proteins function by forming complexes within a dynamic interconnected network that underlies various biological mechanisms. To systematically investigate such interactomes, high-throughput techniques, including CF-MS, have been developed to capture, identify, and quantify protein-protein interactions (PPIs) on a large scale. Compared to other techniques, CF-MS allows the global identification and quantification of native protein complexes in one setting, without genetic manipulation. Furthermore, quantitative CF-MS can potentially elucidate the distribution of a protein in multiple co-elution features, informing the stoichiometries and dynamics of a target protein complex. In this issue, Youssef et al. (Proteomics 2023, 00, e2200404) combined multiplex CF-MS and a new algorithm to study the dynamics of the PPI network for Escherichia coli grown under ten different conditions. Although the results demonstrated that most proteins remained stable, the authors were able to detect disrupted interactions that were growth condition specific. Further bioinformatics analyses also revealed the biophysical properties and structural patterns that govern such a response.

Comparative analysis of permanent and transient domain-domain interactions in multi-domain proteins

Protein domains are structural, functional, and evolutionary units. These domains bring out the diversity of functionality by means of interactions with other co-existing domains and provide stability. Hence, it is important to study intra-protein inter-domain interactions from the perspective of types of interactions. Domains within a chain could interact over short timeframes or permanently, rather like protein-protein interactions (PPIs). However, no systematic study has been carried out between two classes, namely permanent and transient domain-domain interactions. In this work, we studied 263 two-domain proteins, belonging to either of these classes and their interfaces on the basis of several factors, such as interface area and details of interactions (number, strength, and types of interactions). We also characterized them based on residue conservation at the interface, correlation of residue motions across domains, its involvement in repeat formation, and their involvement in particular molecular processes. Finally, we could analyze the interactions arising from domains in two-domain monomeric proteins, and we observed significant differences between these two classes of domain interactions and a few similarities. This study will help to obtain a better understanding of structure-function and folding principles of multi-domain proteins.

Computational analysis of regulatory regions in human protein kinases

Eukaryotic proteins often feature modular domain structures comprising globular domains that are connected by linker regions and intrinsically disordered regions that may contain important functional motifs. The intramolecular interactions of globular domains and nonglobular regions can play critical roles in different aspects of protein function. However, studying these interactions and their regulatory roles can be challenging due to the flexibility of nonglobular regions, the long insertions separating interacting modules, and the transient nature of some interactions. Obtaining the experimental structures of multiple domains and functional regions is more difficult than determining the structures of individual globular domains. High-quality structural models generated by AlphaFold offer a unique opportunity to study intramolecular interactions in eukaryotic proteins. In this study, we systematically explored intramolecular interactions between human protein kinase domains (KDs) and potential regulatory regions, including globular domains, N- and C-terminal tails, long insertions, and distal nonglobular regions. Our analysis identified intramolecular interactions between human KDs and 35 different types of globular domains, exhibiting a variety of interaction modes that could contribute to orthosteric or allosteric regulation of kinase activity. We also identified prevalent interactions between human KDs and their flanking regions (N- and C-terminal tails). These interactions exhibit group-specific characteristics and can vary within each specific kinase group. Although long-range interactions between KDs and nonglobular regions are relatively rare, structural details of these interactions offer new insights into the regulation mechanisms of several kinases, such as HASPIN, MAPK7, MAPK15, and SIK1B.

Single-molecule tracking to determine the abundances and stoichiometries of freely-diffusing protein complexes in living cells: Past applications and future prospects

Most biological processes in living cells rely on interactions between proteins. Live-cell compatible approaches that can quantify to what extent a given protein participates in homo- and hetero-oligomeric complexes of different size and subunit composition are therefore critical to advance our understanding of how cellular physiology is governed by these molecular interactions. Biomolecular complex formation changes the diffusion coefficient of constituent proteins, and these changes can be measured using fluorescence microscopy-based approaches, such as single-molecule tracking, fluorescence correlation spectroscopy, and fluorescence recovery after photobleaching. In this review, we focus on the use of single-molecule tracking to identify, resolve, and quantify the presence of freely-diffusing proteins and protein complexes in living cells. We compare and contrast different data analysis methods that are currently employed in the field and discuss experimental designs that can aid the interpretation of the obtained results. Comparisons of diffusion rates for different proteins and protein complexes in intracellular aqueous environments reported in the recent literature reveal a clear and systematic deviation from the Stokes-Einstein diffusion theory. While a complete and quantitative theoretical explanation of why such deviations manifest is missing, the available data suggest the possibility of weighing freely-diffusing proteins and protein complexes in living cells by measuring their diffusion coefficients. Mapping individual diffusive states to protein complexes of defined molecular weight, subunit stoichiometry, and structure promises to provide key new insights into how protein-protein interactions regulate protein conformational, translational, and rotational dynamics, and ultimately protein function.

N-terminal proteoforms may engage in different protein complexes

Alternative translation initiation and alternative splicing may give rise to N-terminal proteoforms, proteins that differ at their N-terminus compared with their canonical counterparts. Such proteoforms can have altered localizations, stabilities, and functions. Although proteoforms generated from splice variants can be engaged in different protein complexes, it remained to be studied to what extent this applies to N-terminal proteoforms. To address this, we mapped the interactomes of several pairs of N-terminal proteoforms and their canonical counterparts. First, we generated a catalogue of N-terminal proteoforms found in the HEK293T cellular cytosol from which 22 pairs were selected for interactome profiling. In addition, we provide evidence for the expression of several N-terminal proteoforms, identified in our catalogue, across different human tissues, as well as tissue-specific expression, highlighting their biological relevance. Protein-protein interaction profiling revealed that the overlap of the interactomes for both proteoforms is generally high, showing their functional relation. We also showed that N-terminal proteoforms can be engaged in new interactions and/or lose several interactions compared with their canonical counterparts, thus further expanding the functional diversity of proteomes.

"Common-Precursor" Protein Mimetic Approach to Rescue Aβ Aggregation-Mediated Alzheimer's Phenotypes

Abberent protein-protein interactions (aPPIs) are associated with an array of pathological conditions, which make them important therapeutic targets. The aPPIs are mediated via specific chemical interactions that spread over a large and hydrophobic surface. Therefore, ligands that can complement the surface topography and chemical fingerprints could manipulate aPPIs. Oligopyridylamides (OPs) are synthetic protein mimetics that have been shown to manipulate aPPIs. However, the previous OP library used to disrupt these aPPIs was moderate in number (∼30 OPs) with very limited chemical diversity. The onus is on the laborious and time-consuming synthetic pathways with multiple chromatography steps. We have developed a novel chromatography-free technique to synthesize a highly diverse chemical library of OPs using a "common-precursor" approach. We significantly expanded the chemical diversity of OPs using a chromatography-free high-yielding method. To validate our novel approach, we have synthesized an OP with identical chemical diversity to a pre-existing OP-based potent inhibitor of Aβ aggregation, a process central to Alzheimer's disease (AD). The newly synthesized OP ligand (RD242) was very potent in inhibiting Aβ aggregation and rescuing AD phenotypes in an in vivo model. Moreover, RD242 was very effective in rescuing AD phenotypes in a post-disease onset AD model. We envision that our "common-precursor" synthetic approach will have tremendous potential as it is expandable for other oligoamide scaffolds to enhance affinity for disease-relevant targets.

The formation and function of plant metabolons

Metabolons are temporary structural-functional complexes of sequential enzymes of a metabolic pathway that are distinct from stable multi-enzyme complexes. Here we provide a brief history of the study of enzyme-enzyme assemblies with a particular focus on those that mediate substrate channeling in plants. Large numbers of protein complexes have been proposed for both primary and secondary metabolic pathways in plants. However, to date only four substrate channels have been demonstrated. We provide an overview of current knowledge concerning these four metabolons and explain the methodologies that are currently being applied to unravel their functions. Although the assembly of metabolons has been documented to arise through diverse mechanisms, the physical interaction within the characterized plant metabolons all appear to be driven by interaction with structural elements of the cell. We therefore pose the question as to what methodologies could be brought to bear to enhance our knowledge of plant metabolons that assemble via different mechanisms? In addressing this question, we review recent findings in non-plant systems concerning liquid droplet phase separation and enzyme chemotaxis and propose strategies via which such metabolons could be identified in plants. We additionally discuss the possibilities that could be opened up by novel approaches based on: (i) subcellular-level mass spectral imaging, (ii) proteomics, and (iii) emergent methods in structural and computational biology.

Investigating the dynamics of protein-protein interactions in plants

Both stable and transient protein interactions play an important role in the complex assemblies required for the proper functioning of living cells. Several methods have been developed to monitor protein-protein interactions in plants. However, the detection of dynamic protein complexes is very challenging, with few technologies available for this purpose. Here, we developed a new platform using the plant UBIQUITIN promoter to drive transgene expression and thereby to detect protein interactions in planta. Typically, to decide which side of the protein to link the tags, the subcellular localization of the protein fused either N-terminal or C-terminal mCitrine was firstly confirmed by using eight different specific mCherry markers. Following stable or transient protein expression in plants, the protein interaction network was detected by affinity purification mass spectrometry. These interactions were subsequently confirmed by bimolecular fluorescence complementation (BiFC), bioluminescence resonance energy transfer and co-immunoprecipitation assays. The dynamics of these interactions were monitored by Förster resonance energy transfer (FRET) and split-nano luciferase, whilst the ternary protein complex association was monitored by BiFC-FRET. Using the canonical glycolytic metabolon as an example, the interaction between these enzymes was characterized under conditions that mimic physiologically relevant energy statuses.

Exploring substrate interaction in respiratory alternative complex III from Rhodothermus marinus

Rhodothermus marinus is a thermohalophilic organism that has optimized its microaerobic metabolism at 65 °C. We have been exploring its respiratory chain and observed the existence of a quinone:cytochrome c oxidoreductase complex, named Alternative Complex III, structurally different from the bc₁ complex. In the present work, we took profit from nanodiscs and liposomes technology to investigate ACIII activity in membrane-mimicking systems. In addition, we studied the interaction of ACIII with menaquinone, its potential electron acceptors (HiPIP and cytochrome c) and the caa₃ oxygen reductase.

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

Drug repurposing screens identify compounds that inhibit α-synuclein oligomers' membrane disruption and block antibody interactions

Small soluble oligomers of the protein α-synuclein (αSO) have been linked to disruptions in neuronal homeostasis, contributing to the development of Parkinson's Disease (PD). While this makes αSO an obvious drug target, the development of effective therapeutics against αSO is challenged by its low abundance and structural and morphological complexity. Here, we employ two different approaches to neutralize toxic interactions made by αSOs with different cellular components. First, we use available data to identify four neuronal proteins as likely candidates for αSO interactions, namely Cfl1, Uchl1, Sirt2 and SerRS. However, despite promising results when immobilized, all 4 proteins only bind weakly to αSO in solution in microfluidic assays, making them inappropriate for screening. In contrast, the formation of stable contacts formed between αSO and vesicles consisting of anionic lipids not only mimics a likely biological role of αSO but also provided a platform to screen two small molecule libraries for disruptors of these contacts. Of the 7 best leads obtained in this way, 2 significantly impaired αSO contacts with other proteins in a sandwich ELISA assay using αSO-binding monoclonal antibodies and nanobodies. In addition, 5 of these leads suppressed α-synuclein amyloid formation. Thus, a repurposing screening that directly targets a key culprit in PD pathogenesis shows therapeutic potential.

Protein-protein interaction and interference of carcinogenesis by supramolecular modifications

Protein-protein interactions (PPIs) are essential in normal biological processes, but they can become disrupted or imbalanced in cancer. Various technological advancements have led to an increase in the number of PPI inhibitors, which target hubs in cancer cell's protein networks. However, it remains difficult to develop PPI inhibitors with desired potency and specificity. Supramolecular chemistry has only lately become recognized as a promising method to modify protein activities. In this review, we highlight recent advances in the use of supramolecular modification approaches in cancer therapy. We make special note of efforts to apply supramolecular modifications, such as molecular tweezers, to targeting the nuclear export signal (NES), which can be used to attenuate signaling processes in carcinogenesis. Finally, we discuss the strengths and weaknesses of using supramolecular approaches to targeting PPIs.

Evaluation of affinity-purification coupled to mass spectrometry approaches for capture of short linear motif-based interactions

Low affinity and transient protein-protein interactions, such as short linear motif (SLiM)-based interactions, require dedicated experimental tools for discovery and validation. Here, we evaluated and compared biotinylated peptide pulldown and protein interaction screen on peptide matrix (PRISMA) coupled to mass-spectrometry (MS) using a set of peptides containing interaction motifs. Eight different peptide sequences that engage in interactions with three distinct protein domains (KEAP1 Kelch, MDM2 SWIB, and TSG101 UEV) with a wide range of affinities were tested. We found that peptide pulldown can be an effective approach for SLiM validation, however, parameters such as protein abundance and competitive interactions can prevent the capture of known interactors. The use of tandem peptide repeats improved the capture and preservation of some interactions. When testing PRISMA, it failed to provide comparable results for model peptides that successfully pulled down known interactors using biotinylated peptide pulldown. Overall, in our hands, we find that albeit more laborious, biotin-peptide pulldown was more successful in terms of validation of known interactions. Our results highlight that the tested affinity-capture MS-based methods for validation of SLiM-based interactions from cell lysates are suboptimal, and we identified parameters for consideration for method development.

Perspective on the potential of tandem-ion mobility /mass spectrometry methods for structural proteomics applications

Cellular processes are usually carried out collectively by the entirety of all proteins present in a biological cell, i.e. the proteome. Mass spectrometry-based methods have proven particularly successful in identifying and quantifying the constituent proteins of proteomes, including different molecular forms of a protein. Nevertheless, protein sequences alone do not reveal the function or dysfunction of the identified proteins. A straightforward way to assign function or dysfunction to proteins is characterization of their structures and dynamics. However, a method capable to characterize detailed structures of proteins and protein complexes in a large-scale, systematic manner within the context of cellular processes does not yet exist. Here, we discuss the potential of tandem-ion mobility / mass spectrometry (tandem-IM/MS) methods to provide such ability. We highlight the capability of these methods using two case studies on the protein systems ubiquitin and avidin using the tandem-TIMS/MS technology developed in our laboratory and discuss these results in the context of other developments in the broader field of tandem-IM/MS.

Structure of the Sec14 domain of Kalirin reveals a distinct class of lipid-binding module in RhoGEFs

Gated entry of lipophilic ligands into the enclosed hydrophobic pocket in stand-alone Sec14 domain proteins often links lipid metabolism to membrane trafficking. Similar domains occur in multidomain mammalian proteins that activate small GTPases and regulate actin dynamics. The neuronal RhoGEF Kalirin, a central regulator of cytoskeletal dynamics, contains a Sec14 domain (Kal^bSec14) followed by multiple spectrin-like repeats and catalytic domains. Previous studies demonstrated that Kalirin lacking its Sec14 domain fails to maintain cell morphology or dendritic spine length, yet whether and how Kal^bSec14 interacts with lipids remain unknown. Here, we report the structural and biochemical characterization of Kal^bSec14. Kal^bSec14 adopts a closed conformation, sealing off the canonical ligand entry site, and instead employs a surface groove to bind a limited set of lysophospholipids. The low-affinity interactions of Kal^bSec14 with lysolipids are expected to serve as a general model for the regulation of Rho signaling by other Sec14-containing Rho activators.

Protein-protein interactions in plant antioxidant defense

The regulation of reactive oxygen species (ROS) levels in plants is ensured by mechanisms preventing their over accumulation, and by diverse antioxidants, including enzymes and nonenzymatic compounds. These are affected by redox conditions, posttranslational modifications, transcriptional and posttranscriptional modifications, Ca²⁺, nitric oxide (NO) and mitogen-activated protein kinase signaling pathways. Recent knowledge about protein-protein interactions (PPIs) of antioxidant enzymes advanced during last decade. The best-known examples are interactions mediated by redox buffering proteins such as thioredoxins and glutaredoxins. This review summarizes interactions of major antioxidant enzymes with regulatory and signaling proteins and their diverse functions. Such interactions are important for stability, degradation and activation of interacting partners. Moreover, PPIs of antioxidant enzymes may connect diverse metabolic processes with ROS scavenging. Proteins like receptor for activated C kinase 1 may ensure coordination of antioxidant enzymes to ensure efficient ROS regulation. Nevertheless, PPIs in antioxidant defense are understudied, and intensive research is required to define their role in complex regulation of ROS scavenging.

Short Linear Motifs in Colorectal Cancer Interactome and Tumorigenesis

Colorectal tumorigenesis is driven by alterations in genes and proteins responsible for cancer initiation, progression, and invasion. This multistage process is based on a dense network of protein-protein interactions (PPIs) that become dysregulated as a result of changes in various cell signaling effectors. PPIs in signaling and regulatory networks are known to be mediated by short linear motifs (SLiMs), which are conserved contiguous regions of 3-10 amino acids within interacting protein domains. SLiMs are the minimum sequences required for modulating cellular PPI networks. Thus, several in silico approaches have been developed to predict and analyze SLiM-mediated PPIs. In this review, we focus on emerging evidence supporting a crucial role for SLiMs in driver pathways that are disrupted in colorectal cancer (CRC) tumorigenesis and related PPI network alterations. As a result, SLiMs, along with short peptides, are attracting the interest of researchers to devise small molecules amenable to be used as novel anti-CRC targeted therapies. Overall, the characterization of SLiMs mediating crucial PPIs in CRC may foster the development of more specific combined pharmacological approaches.

Characterizing Transient Protein-Protein Interactions by Trp-Cys Quenching and Computer Simulations

Transient protein-protein interactions occur frequently under the crowded conditions encountered in biological environments. Tryptophan-cysteine quenching is introduced as an experimental approach with minimal labeling for characterizing such interactions between proteins due to its sensitivity to nano- to microsecond dynamics on subnanometer length scales. The experiments are paired with computational modeling at different resolutions including fully atomistic molecular dynamics simulations for interpretation of the experimental observables and to gain molecular-level insights. This approach is applied to model systems, villin variants and the drkN SH3 domain, in the presence of protein G crowders. It is demonstrated that Trp-Cys quenching experiments can differentiate between overall attractive and repulsive interactions between different proteins, and they can discern variations in interaction preferences at different protein surface locations. The close integration between experiment and simulations also provides an opportunity to evaluate different molecular force fields for the simulation of concentrated protein solutions.

A dynamical view of protein-protein complexes: Studies by molecular dynamics simulations

Protein-protein interactions are at the basis of many protein functions, and the knowledge of 3D structures of protein-protein complexes provides structural, mechanical and dynamical pieces of information essential to understand these functions. Protein-protein interfaces can be seen as stable, organized regions where residues from different partners form non-covalent interactions that are responsible for interaction specificity and strength. They are commonly described as a peripheral region, whose role is to protect the core region that concentrates the most contributing interactions, from the solvent. To get insights into the dynamics of protein-protein complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on eight different protein-protein complexes of different functional class and interface size by taking into account the bound and unbound forms. On the one hand, we characterized structural changes upon binding of the proteins, and on the other hand we extensively analyzed the interfaces and the structural waters involved in the binding. Based on our analysis, in 6 cases out of 8, the interfaces rearranged during the simulation time, in stable and long-lived substates with alternative residue-residue contacts. These rearrangements are not restricted to side-chain fluctuations in the periphery but also affect the core interface. Finally, the analysis of the waters at the interface and involved in the binding pointed out the importance to take into account their role in the estimation of the interaction strength.

Structural basis for the interaction between the first SURP domain of the SF3A1 subunit in U2 snRNP and the human splicing factor SF1

SURP domains are exclusively found in splicing-related proteins in all eukaryotes. SF3A1, a component of the U2 snRNP, has two tandem SURP domains, SURP1, and SURP2. SURP2 is permanently associated with a specific short region of SF3A3 within the SF3A protein complex whereas, SURP1 binds to the splicing factor SF1 for recruitment of U2 snRNP to the early spliceosomal complex, from which SF1 is dissociated during complex conversion. Here, we determined the solution structure of the complex of SURP1 and the human SF1 fragment using nuclear magnetic resonance (NMR) methods. SURP1 adopts the canonical topology of α1-α2-3₁₀ -α3, in which α1 and α2 are connected by a single glycine residue in a particular backbone conformation, allowing the two α-helices to be fixed at an acute angle. A hydrophobic patch, which is part of the characteristic surface formed by α1 and α2, specifically contacts a hydrophobic cluster on a 16-residue α-helix of the SF1 fragment. Furthermore, whereas only hydrophobic interactions occurred between SURP2 and the SF3A3 fragment, several salt bridges and hydrogen bonds were found between the residues of SURP1 and the SF1 fragment. This finding was confirmed through mutational studies using bio-layer interferometry. The study also revealed that the dissociation constant between SURP1 and the SF1 fragment peptide was approximately 20 μM, indicating a weak or transient interaction. Collectively, these results indicate that the interplay between U2 snRNP and SF1 involves a transient interaction of SURP1, and this transient interaction appears to be common to most SURP domains, except for SURP2.

A microRNA-microRNA crosstalk network inferred from genome-wide single nucleotide polymorphism variants in natural populations of Arabidopsis thaliana

To adapt to variable natural conditions, plants have evolved several strategies to respond to different environmental stresses. MicroRNA (miRNA)-mediated gene regulation is one of such strategies. Variants, e.g., single nucleotide polymorphisms (SNPs) within the mature miRNAs or their target sites may cause the alteration of regulatory networks and serious phenotype changes. In this study, we proposed a novel approach to construct a miRNA-miRNA crosstalk network in Arabidopsis thaliana based on the notion that two cooperative miRNAs toward common targets are under a strong pressure to be inherited together across ecotypes. By performing a genome-wide scan of the SNPs within the mature miRNAs and their target sites, we defined a "regulation fate profile" to describe a miRNA-target regulation being static (kept) or dynamic (gained or lost) across 1,135 ecotypes compared with the reference genome of Col-0. The cooperative miRNA pairs were identified by estimating the similarity of their regulation fate profiles toward the common targets. The reliability of the cooperative miRNA pairs was supported by solid expressional correlation, high PPImiRFS scores, and similar stress responses. Different combinations of static and dynamic miRNA-target regulations account for the cooperative miRNA pairs acting on various biological characteristics of miRNA conservation, expression, homology, and stress response. Interestingly, the targets that are co-regulated dynamically by both cooperative miRNAs are more likely to be responsive to stress. Hence, stress-related genes probably bear selective pressures in a certain group of ecotypes, in which miRNA regulations on the stress genes reprogram. Finally, three case studies showed that reprogramming miRNA-miRNA crosstalk toward the targets in specific ecotypes was associated with these ecotypes' climatic variables and geographical locations. Our study highlights the potential of miRNA-miRNA crosstalk as a genetic basis underlying environmental adaptation in natural populations.

Structural Determinants of Yeast Protein-Protein Interaction Interface Evolution at the Residue Level

Interfaces of contact between proteins play important roles in determining the proper structure and function of protein-protein interactions (PPIs). Therefore, to fully understand PPIs, we need to better understand the evolutionary design principles of PPI interfaces. Previous studies have uncovered that interfacial sites are more evolutionarily conserved than other surface protein sites. Yet, little is known about the nature and relative importance of evolutionary constraints in PPI interfaces. Here, we explore constraints imposed by the structure of the microenvironment surrounding interfacial residues on residue evolutionary rate using a large dataset of over 700 structural models of baker's yeast PPIs. We find that interfacial residues are, on average, systematically more conserved than all other residues with a similar degree of total burial as measured by relative solvent accessibility (RSA). Besides, we find that RSA of the residue when the PPI is formed is a better predictor of interfacial residue evolutionary rate than RSA in the monomer state. Furthermore, we investigate four structure-based measures of residue interfacial involvement, including change in RSA upon binding (ΔRSA), number of residue-residue contacts across the interface, and distance from the center or the periphery of the interface. Integrated modeling for evolutionary rate prediction in interfaces shows that ΔRSA plays a dominant role among the four measures of interfacial involvement, with minor, but independent contributions from other measures. These results yield insight into the evolutionary design of interfaces, improving our understanding of the role that structure plays in the molecular evolution of PPIs at the residue level.

Spatial organization of hydrophobic and charged residues affects protein thermal stability and binding affinity

What are the molecular determinants of protein–protein binding affinity and whether they are similar to those regulating fold stability are two major questions of molecular biology, whose answers bring important implications both from a theoretical and applicative point of view. Here, we analyze chemical and physical features on a large dataset of protein–protein complexes with reliable experimental binding affinity data and compare them with a set of monomeric proteins for which melting temperature data was available. In particular, we probed the spatial organization of protein (1) intramolecular and intermolecular interaction energies among residues, (2) amino acidic composition, and (3) their hydropathy features. Analyzing the interaction energies, we found that strong Coulombic interactions are preferentially associated with a high protein thermal stability, while strong intermolecular van der Waals energies correlate with stronger protein–protein binding affinity. Statistical analysis of amino acids abundances, exposed to the molecular surface and/or in interaction with the molecular partner, confirmed that hydrophobic residues present on the protein surfaces are preferentially located in the binding regions, while charged residues behave oppositely. Leveraging on the important role of van der Waals interface interactions in binding affinity, we focused on the molecular surfaces in the binding regions and evaluated their shape complementarity, decomposing the molecular patches in the 2D Zernike basis. For the first time, we quantified the correlation between local shape complementarity and binding affinity via the Zernike formalism. In addition, considering the solvent interactions via the residue hydropathy, we found that the hydrophobicity of the binding regions dictates their shape complementary as much as the correlation between van der Waals energy and binding affinity. In turn, these relationships pave the way to the fast and accurate prediction and design of optimal binding regions as the 2D Zernike formalism allows a rapid and superposition-free comparison between possible binding surfaces.

Amplifying Intermolecular Events by Streptavidin-Induced Proximity

Weak interactions between biomolecules play important roles in many cellular functions. Structural and kinetic analyses of these interactions, however, have been hindered by the transient nature of such events. Here, we pointed out a general approach to overcome this obstacle─anchoring the molecular partners to streptavidin hosts─and achieved constrained proximity and stoichiometry for the sought-after molecular coupling. We elaborated this idea through a series of DNA hybridization reactions and quantitatively characterized them using single-molecule experiments. Compared to a nominally 1 μM solution, for example, the streptavidin-induced proximity (SIP) amounted to an effective molarity of ∼10-30 μM for the binding partners. There was also a significantly increased proportion of molecular association, manifested in both ensemble population and single-molecule residence time. As an application example, we showed how SIP enabled the observation and quantitative characterization of an unstable complex between Cas9-RNA and noncognate DNA substrates, interactions that had been challenging to characterize previously. Conceptually simple and implementationally robust, SIP was shown to considerably enhance the efficacy in capturing weak interactions and, as demonstrated here, could empower scientists to see the otherwise unseeable.

Cooperative stability renders protein complex formation more robust and controllable

Protein complexes are the fundamental units of many biological functions. Despite their many advantages, one major adverse impact of protein complexes is accumulations of unassembled subunits that may disrupt other processes or exert cytotoxic effects. Synthesis of excess subunits can be inhibited via negative feedback control or they can be degraded more efficiently than assembled subunits, with this latter being termed cooperative stability. Whereas controlled synthesis of complex subunits has been investigated extensively, how cooperative stability acts in complex formation remains largely unexplored. To fill this knowledge gap, we have built quantitative models of heteromeric complexes with or without cooperative stability and compared their behaviours in the presence of synthesis rate variations. A system displaying cooperative stability is robust against synthesis rate variations as it retains high dimer/monomer ratios across a broad range of parameter configurations. Moreover, cooperative stability can alleviate the constraint of limited supply of a given subunit and makes complex abundance more responsive to unilateral upregulation of another subunit. We also conducted an in silico experiment to comprehensively characterize and compare four types of circuits that incorporate combinations of negative feedback control and cooperative stability in terms of eight systems characteristics pertaining to optimality, robustness and controllability. Intriguingly, though individual circuits prevailed for distinct characteristics, the system with cooperative stability alone achieved the most balanced performance across all characteristics. Our study provides theoretical justification for the contribution of cooperative stability to natural biological systems and represents a guideline for designing synthetic complex formation systems with desirable characteristics.

Novel protein contact points among TP53 and minichromosome maintenance complex proteins 2, 3, and 5

OBJECTIVE

Identify protein contact points between TP53 and minichromosome maintenance (MCM) complex proteins 2, 3, and 5 with high resolution allowing for potential novel Cancer drug design.

METHODS

A next-generation sequencing-based protein-protein interaction method developed in our laboratory called AVA-Seq was applied to a gold-standard human protein interaction set. Proteins including TP53, MCM2, MCM3, MCM5, HSP90AA1, PCNA, NOD1, and others were sheared and ligated into the AVA-Seq system. Protein-protein interactions were then identified in both mild and stringent selective conditions.

RESULTS

Known interactions among MCM2, MCM3, and MCM5 were identified with the AVA-Seq system. The interacting regions detected between these three proteins overlap with the structural data of the MCM complex, and novel domains were identified with high resolution determined by multiple overlapping fragments. Fragments of wild type TP53 were shown to interact with MCM2, MCM3, and MCM5, and details on the location of the interactions were provided. Finally, a mini-network of known and novel cancer protein interactions was provided, which could have implications for fundamental changes in multiple cancers.

CONCLUSION

We provide a high-resolution mini-interactome that could direct novel drug targets and implicate possible effects of specific cancer mutations.

Implications of critical node-dependent unidirectional cross-talk of Plasmodium SUMO pathway proteins

The endoparasitic pathogen, Plasmodium falciparum (Pf), modulates protein-protein interactions to employ post-translational modifications like SUMOylation to establish successful infections. The interaction between E1 and E2 (Ubc9) enzymes governs species specificity in the Plasmodium SUMOylation pathway. Here, we demonstrate that a unidirectional cross-species interaction exists between Pf-SUMO and human E2, whereas Hs-SUMO1 failed to interact with Pf-E2. Biochemical and biophysical analyses revealed that surface-accessible aspartates of Pf-SUMO determine the efficacy and specificity of SUMO-Ubc9 interactions. Furthermore, we demonstrate that critical residues of the Pf-Ubc9 N terminus are responsible for diminished Hs-SUMO1 and Pf-Ubc9 interaction. Mutating these residues to corresponding Hs-Ubc9 residues restores electrostatic, π-π, and hydrophobic interactions and allows efficient cross-species interactions. We suggest that, in comparison with human counterparts, Plasmodium SUMO and Ubc9 proteins have acquired critical changes on their surfaces as nodes, which Plasmodium can use to exploit the host SUMOylation machinery.

A novel computational strategy for defining the minimal protein molecular surface representation

Most proteins perform their biological function by interacting with one or more molecular partners. In this respect, characterizing local features of the molecular surface, that can potentially be involved in the interaction with other molecules, represents a step forward in the investigation of the mechanisms of recognition and binding between molecules. Predictive methods often rely on extensive samplings of molecular patches with the aim to identify hot spots on the surface. In this framework, analysis of large proteins and/or many molecular dynamics frames is often unfeasible due to the high computational cost. Thus, finding optimal ways to reduce the number of points to be sampled maintaining the biological information (including the surface shape) carried by the molecular surface is pivotal. In this perspective, we here present a new theoretical and computational algorithm with the aim of defining a set of molecular surfaces composed of points not uniformly distributed in space, in such a way as to maximize the information of the overall shape of the molecule by minimizing the number of total points. We test our procedure’s ability in recognizing hot-spots by describing the local shape properties of portions of molecular surfaces through a recently developed method based on the formalism of 2D Zernike polynomials. The results of this work show the ability of the proposed algorithm to preserve the key information of the molecular surface using a reduced number of points compared to the complete surface, where all points of the surface are used for the description. In fact, the methodology shows a significant gain of the information stored in the sampling procedure compared to uniform random sampling.

Characterizing the stabilization effects of stabilizers in protein-protein systems with end-point binding free energy calculations

Drug design targeting protein-protein interactions (PPIs) associated with the development of diseases has been one of the most important therapeutic strategies. Besides interrupting the PPIs with PPI inhibitors/blockers, increasing evidence shows that stabilizing the interaction between two interacting proteins may also benefit the therapy, such as the development of various types of molecular glues/stabilizers that mostly work by stabilizing the two interacting proteins to regulate the downstream biological effects. However, characterizing the stabilization effect of a stabilizer is usually hard or too complicated for traditional experiments since it involves ternary interactions [protein-protein-stabilizer (PPS) interaction]. Thus, developing reliable computational strategies will facilitate the discovery/design of molecular glues or PPI stabilizers. Here, by fully analyzing the energetic features of the binary interactions in the PPS ternary complex, we systematically investigated the performance of molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) methods on characterizing the stabilization effects of stabilizers in 14-3-3 systems. The results show that both MM/PBSA and MM/GBSA are powerful tools in distinguishing the stabilizers from the decoys (with area under the curves of 0.90-0.93 for all tested cases) and are reasonable for ranking protein-peptide interactions in the presence or absence of stabilizers as well (with the average Pearson correlation coefficient of ~0.6 at a relatively high dielectric constant for both methods). Moreover, to give a detailed picture of the stabilization effects, the stabilization mechanism is also analyzed from the structural and energetic points of view for individual systems containing strong or weak stabilizers. This study demonstrates a potential strategy to accelerate the discovery of PPI stabilizers.

In silico analysis of the predicted protein-protein interaction of syntaxin-18, a putative receptor of Peregrinus maidis Ashmead (Hemiptera: Delphacidae) with Maize mosaic virus glycoprotein

The corn planthopper, Peregrinus maidis Ashmead (Hemiptera:Delphacidae), is a widely distributed insect pest which serves as a vector of two phytopathogenic viruses, Maize mosaic virus (MMV) and Maize stripe virus (MStV). It transmits the viruses in a persistent and propagative manner. MMV is an alphanucleorhabdovirus with a negative-sense, single-stranded RNA unsegmented genome. One identified insect vector protein that may serve as receptor to MMV is Syntaxin-18 (PmStx18) which belongs to the SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) proteins. SNAREs play major roles in the final stage of docking and subsequent fusion of diverse vesicle-mediated transport events. In this work, in silico analysis of the interaction of MMV glycoprotein (MMV G) and PmStx18 was performed. Various freely available protein-protein docking web servers were used to predict the 3 D complex of MMV G and PmStx18. Analysis and protein-protein interaction (PPI) count showed that the complex predicted by the ZDOCK server has the highest number of interaction and highest affinity, as suggested by the calculated solvation free energy gain upon formation of the interface (ΔⁱG = -31 kcal/mol). Molecular dynamics simulation of the complex revealed important interactions at the interface over the course of 25 ns. This is the first in silico analysis performed for the interaction on a putative receptor of P. maidis and MMV G. The results of the PPI prediction provide novel information for studying the role of Stx18 in the transport, docking and fusion events involved in virus particle transport in the insect vector cells and its release.Communicated by Ramaswamy H. Sarma.

Are transient protein-protein interactions more dispensable?

Protein-protein interactions (PPIs) are key drivers of cell function and evolution. While it is widely assumed that most permanent PPIs are important for cellular function, it remains unclear whether transient PPIs are equally important. Here, we estimate and compare dispensable content among transient PPIs and permanent PPIs in human. Starting with a human reference interactome mapped by experiments, we construct a human structural interactome by building three-dimensional structural models for PPIs, and then distinguish transient PPIs from permanent PPIs using several structural and biophysical properties. We map common mutations from healthy individuals and disease-causing mutations onto the structural interactome, and perform structure-based calculations of the probabilities for common mutations (assumed to be neutral) and disease mutations (assumed to be mildly deleterious) to disrupt transient PPIs and permanent PPIs. Using Bayes' theorem we estimate that a similarly small fraction (<~20%) of both transient and permanent PPIs are completely dispensable, i.e., effectively neutral upon disruption. Hence, transient and permanent interactions are subject to similarly strong selective constraints in the human interactome.