Understanding Membrane Protein Drug Targets in Computational Perspective

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

BACKGROUND

Most of the important biological mechanisms and functions of transmembrane proteins (TMPs) are realized through their interactions with non-transmembrane proteins(nonTMPs). The interactions between TMPs and nonTMPs in cells play vital roles in intracellular signaling, energy metabolism, investigating membrane-crossing mechanisms, correlations between disease and drugs.

RESULTS

Despite the importance of TMP-nonTMP interactions, the study of them remains in the wet experimental stage, lacking specific and comprehensive studies in the field of bioinformatics. To fill this gap, we performed a comprehensive statistical analysis of known TMP-nonTMP interactions and constructed a deep learning-based predictor to identify potential interactions. The statistical analysis describes known TMP-nonTMP interactions from various perspectives, such as distributions of species and protein families, enrichment of GO and KEGG pathways, as well as hub proteins and subnetwork modules in the PPI network. The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541.

CONCLUSIONS

To our knowledge, we were the first to focus on TMP-nonTMP interactions. We comprehensively analyzed them using bioinformatics methods and predicted them via deep learning-based solely on their sequence. This research completes a key link in the protein network, benefits the understanding of protein functions, and helps in pathogenesis studies of diseases and associated drug development.

Glycoproteome-Wide Discovery of Cortical Glycoproteins That May Provide Cognitive Resilience in Older Adults

BACKGROUND AND OBJECTIVES

Molecular omics studies have identified proteins related to cognitive resilience but unrelated to Alzheimer disease and Alzheimer disease-related dementia (AD/ADRD) pathologies. Posttranslational modifications of proteins with glycans can modify protein function. In this study, we identified glycopeptiforms associated with cognitive resilience.

METHODS

We studied brains from adults with annual cognitive testing with postmortem indices of 10 AD/ADRD pathologies and proteome-wide data from dorsal lateral prefrontal cortex (DLPFC). We quantified 11, 012 glycopeptiforms from DLPFC using liquid chromatography with tandem mass spectrometry. We used linear mixed-effects models to identify glycopeptiforms associated with cognitive decline correcting for multiple comparisons (p < 5 × 10-6). Then, we regressed out the effect of AD/ADRD pathologies to identify glycopeptiforms that may provide cognitive resilience.

RESULTS

We studied 366 brains, average age at death 89 years, and 70% female with no cognitive impairment = 152, mild cognitive impairment = 93, and AD = 121 cognitive status at death. In models adjusting for age, sex and education, 11 glycopeptiforms were associated with cognitive decline. In further modeling, 8 of these glycopeptiforms remained associated with cognitive decline after adjusting for AD/ADRD pathologies: NPTX2a (Est., 0.030, SE, 0.005, p = 1 × 10-4); NPTX2b (Est.,0.019, SE, 0.005, p = 2 × 10-4) NECTIN1(Est., 0.029, SE, 0.009, p = 9 × 10-4), NPTX2c (Est., 0.015, SE, 0.004, p = 9 × 10-4), HSPB1 (Est., -0.021, SE, 0.006, p = 2 × 10-4), PLTP (Est., -0.027, SE, 0.009, p = 4.2 × 10-3), NAGK (Est., -0.027, SE, 0.008, p = 1.4 × 10-3), and VAT1 (Est., -0.020, SE, 0.006, p = 1.1 × 10-3). Higher levels of 4 resilience glycopeptiforms derived through glycosylation were associated with slower decline and higher levels of 4 derived through glycation were related to faster decline. Together, these 8 glycopeptiforms accounted for an additional 6% of cognitive decline over the 33% accounted for the 10 brain pathologies and demographics. All 8 resilience glycopeptiforms remained associated with cognitive decline after adjustments for the expression level of their corresponding protein. Exploratory gene ontology suggested that molecular mechanisms of glycopeptiforms associated with cognitive decline may involve metabolic pathways including pyruvate and NADH pathways and highlighted the importance of molecular mechanisms involved in glucose metabolism.

DISCUSSION

Glycopeptiforms in aging brains may provide cognitive resilience. Targeting these glycopeptiforms may lead to therapies that maintain cognition through resilience.

Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Clean-up Techniques

The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identification. Single-pot, solid-phase-enhanced sample preparation (SP3) is a clean-up technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. However, recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Thus, solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer clean-up technique that employs protein-aggregation to capture proteins without modified particles. SP4 has previously enriched low-solubility proteins, though differences in protein capture could affect which proteins are detected and identified. We hypothesize that the mechanisms of capture for SP3 and SP4 are distinct. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. From these results, we recommend clean-up techniques based on protein-sample hydrophobicity to yield high proteome coverage in biological samples.

Exosomes: Membrane-associated proteins, challenges and perspectives

Membrane proteins determine the precise function of each membrane and, therefore, the function of each cell type. These proteins essential roles in cell physiology, participating in the maintenance of the cell metabolism, its homeostasis or promoting proper cell growth. Membrane proteins, as has long been described, are located both in the plasma membrane and in complex subcellular structures. However, they can also be released into the extracellular environment associated with extracellular vesicles (EVs). To date, most of the research have been focused on understanding the role of exosomal RNA in several processes. Recently, there has been increasing interest in studying the function of exosome membrane proteins for exosome-based therapy, but not much research has been done yet on the function of exosome membrane proteins. One of the major limitations of studying exosome membrane proteins and their application to translational research of exosome-based therapeutics is the low yield of exosome isolation. Here, we have introduced a new perspective on exosome membrane protein research by reviewing studies showing the important role of exosome membrane proteins in exosome-based therapies. Furthermore, we have proposed a new strategy to boost the yield of exosome isolation: hybridization of liposomes with exosome-derived membrane. Liposomes have already been reported to affect the cell excitation to increase exosome production in tumor cells. Therefore, increasing cellular uptake of these liposomes would enhance exosome release by increasing cellular excitation. This new perspective could be a breakthrough in exosome-based therapeutic research.

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

Protein-lipid charge interactions control the folding of outer membrane proteins into asymmetric membranes

Biological membranes consist of two leaflets of phospholipid molecules that form a bilayer, each leaflet comprising a distinct lipid composition. This asymmetry is created and maintained in vivo by dedicated biochemical pathways, but difficulties in creating stable asymmetric membranes in vitro have restricted our understanding of how bilayer asymmetry modulates the folding, stability and function of membrane proteins. In this study, we used cyclodextrin-mediated lipid exchange to generate liposomes with asymmetric bilayers and characterize the stability and folding kinetics of two bacterial outer membrane proteins (OMPs), OmpA and BamA. We found that excess negative charge in the outer leaflet of a liposome impedes their insertion and folding, while excess negative charge in the inner leaflet accelerates their folding relative to symmetric liposomes with the same membrane composition. Using molecular dynamics, mutational analysis and bioinformatics, we identified a positively charged patch critical for folding and stability. These results rationalize the well-known 'positive-outside' rule of OMPs and suggest insights into the mechanisms that drive OMP folding and assembly in vitro and in vivo.

Insight into the effect of ibuprofen on the permeability of the membrane: a molecular dynamic simulation study

Studying interactions between drugs and cell membranes is of great interest to designing novel drugs, optimizing drug delivery, and discerning drug mechanism action. In this study, we investigated the physical properties of the bilayer membrane model of POPC upon interaction with ibuprofen (IBU) using molecular dynamics simulations. The area per lipid (APL) was calculated to describe the effect of ibuprofen on the packing properties of the lipid bilayer. The APL was 0.58 nm2 and 0.63 nm2 for the membrane in low and high IBU respectively, and 0.57 nm2 for the membrane without IBU. Our finding showed that the mean square deviation (MSD) increased with increased ibuprofen content. In addition, the order parameter for the hydrocarbon chain of lipids increased with increased ibuprofen content. There was an increment in the transfer free energy after the head group region while it was maximum in the hydrophobic core for hydrogen peroxide (H2O2) (∼6.2 kcal.mol-1) and H2O (∼3.4 kcal.mol-1) which then decreased to respective values of (∼4.6 kcal.mol-1), and (∼2.3 kcal.mol-1) at the center of the bilayer in the presence of IBU. It seems that in the presence of ibuprofen, the free energy profile of the permeability of water and H2O2 significantly decreased. These findings show that ibuprofen significantly influences the physical properties of the bilayer by decreasing the packing and intermolecular interaction in the hydrocarbon chain region and increasing the water permeability of the bilayer. These results may provide insights into the local cytotoxic side effects of ibuprofen and its underlying molecular mechanisms.Communicated by Ramaswamy H. Sarma.

A Simple and Low-cost Preliminary Quantification of Target Membrane Protein in Single Cells

To study the heterogeneity of target membrane proteins in single cells with cellular integrity, we proposed a simple and low-cost method to obtain the copy number of the membrane proteins. HeLa cells were labeled by FITC affinity bodies specifically targeting HER2 membrane proteins. The immunolabeled HeLa cells were quantified by a laboratory-built laser induced fluorescence detector. A series of fluorescent microspheres with known number of FITC molecules on the surface were used to establish the calibration curve, instead of the standard fluorescent solutions, because the morphology of the microspheres was similar to the cells, and the distribution of FITC on the spheres were similar to the distribution of HER2 on the HeLa. The fluorescence intensity of the cells was converted to the molecule number of HER2 by the calibration curve. A capillary electrophoresis system was used to drive the microspheres and cells through the detection window. The copy number of HER2 in HeLa cells ranged from 4,036 to 1,224,920 ± 100 (2.5-97.5%), and the median of copy numbers were 104,438 ± 100 per cell. This method for measuring low-abundance membrane proteins can be utilized for the initial exploration of proteomics in ordinary laboratories.

Metal organic layers enabled cell surface engineering coupling biomembrane fusion for dynamic membrane proteome profiling

Systematically dissecting the highly dynamic and tightly communicating membrane proteome of living cells is essential for the system-level understanding of fundamental cellular processes and intricate relationship between membrane-bound organelles constructed through membrane traffic. While extensive efforts have been made to enrich membrane proteins, their comprehensive analysis with high selectivity and deep coverage remains a challenge, especially at the living cell state. To address this problem, we developed the cell surface engineering coupling biomembrane fusion method to map the whole membrane proteome from the plasma membrane to various organelle membranes taking advantage of the exquisite interaction between two-dimensional metal-organic layers and phospholipid bilayers on the membrane. This approach, which bypassed conventional biochemical fractionation and ultracentrifugation, facilitated the enrichment of membrane proteins in their native phospholipid bilayer environment, helping to map the membrane proteome with a specificity of 77% and realizing the deep coverage of the HeLa membrane proteome (5087 membrane proteins). Furthermore, membrane N-phosphoproteome was profiled by integrating the N-phosphoproteome analysis strategy, and the dynamic membrane proteome during apoptosis was deciphered in combination with quantitative proteomics. The features of membrane protein N-phosphorylation modifications and many differential proteins during apoptosis associated with mitochondrial dynamics and ER homeostasis were found. The method provided a simple and robust strategy for efficient analysis of membrane proteome, offered a reliable platform for research on membrane-related cell dynamic events and expanded the application of metal-organic layers.

Applications of genetic code expansion and photosensitive UAAs in studying membrane proteins

Membrane proteins are the targets for most drugs and play essential roles in many life activities in organisms. In recent years, unnatural amino acids (UAAs) encoded by genetic code expansion (GCE) technology have been widely used, which endow proteins with different biochemical properties. A class of photosensitive UAAs has been widely used to study protein structure and function. Combined with photochemical control with high temporal and spatial resolution, these UAAs have shown broad applicability to solve the problems of natural ion channels and receptor biology. This review will focus on several application examples of light-controlled methods to integrate GCE technology to study membrane protein function in recent years. We will summarize the typical research methods utilizing some photosensitive UAAs to provide common strategies and further new ideas for studying protein function and advancing biological processes.

Overview of Membrane Protein Sample Preparation for Single-Particle Cryo-Electron Microscopy Analysis

Single-particle cryo-electron microscopy (cryo-EM SPA) has recently emerged as an exceptionally well-suited technique for determining the structure of membrane proteins (MPs). Indeed, in recent years, huge increase in the number of MPs solved via cryo-EM SPA at a resolution better than 3.0 Å in the Protein Data Bank (PDB) has been observed. However, sample preparation remains a significant challenge in the field. Here, we evaluated the MPs solved using cryo-EM SPA deposited in the PDB in the last two years at a resolution below 3.0 Å. The most critical parameters for sample preparation are as follows: (i) the surfactant used for protein extraction from the membrane, (ii) the surfactant, amphiphiles, nanodiscs or other molecules present in the vitrification step, (iii) the vitrification method employed, and (iv) the type of grids used. The aim is not to provide a definitive answer on the optimal sample conditions for cryo-EM SPA of MPs but rather assess the current trends in the MP structural biology community towards obtaining high-resolution cryo-EM structures.

CrMP-Sol database: classification, bioinformatic analyses and comparison of cancer-related membrane proteins and their water-soluble variant designs

Membrane proteins are critical mediators for tumor progression and present enormous therapeutic potentials. Although gene profiling can identify their cancer-specific signatures, systematic correlations between protein functions and tumor-related mechanisms are still unclear. We present here the CrMP-Sol database ( https://bio-gateway.aigene.org.cn/g/CrMP ), which aims to breach the gap between the two. Machine learning was used to extract key functional descriptions for protein visualization in the 3D-space, where spatial distributions provide function-based predictive connections between proteins and cancer types. CrMP-Sol also presents QTY-enabled water-soluble designs to facilitate native membrane protein studies despite natural hydrophobicity. Five examples with varying transmembrane helices in different categories were used to demonstrate the feasibility. Native and redesigned proteins exhibited highly similar characteristics, predicted structures and binding pockets, and slightly different docking poses against known ligands, although task-specific designs are still required for proteins more susceptible to internal hydrogen bond formations. The database can accelerate therapeutic developments and biotechnological applications of cancer-related membrane proteins.

Tris(hydroxymethyl)aminomethane Linker-Bearing Triazine-Based Triglucosides for Solubilization and Stabilization of Membrane Proteins

High-resolution membrane protein structures are essential for a fundamental understanding of the molecular basis of diverse cellular processes and for drug discovery. Detergents are widely used to extract membrane-spanning proteins from membranes and maintain them in a functional state for downstream characterization. Due to limited long-term stability of membrane proteins encapsulated in conventional detergents, development of novel agents is required to facilitate membrane protein structural study. In the current study, we designed and synthesized tris(hydroxymethyl)aminomethane linker-bearing triazine-based triglucosides (TTGs) for solubilization and stabilization of membrane proteins. When these glucoside detergents were evaluated for four membrane proteins including two G protein-coupled receptors, a few TTGs including TTG-C10 and TTG-C11 displayed markedly enhanced behaviors toward membrane protein stability relative to two maltoside detergents [DDM (n-dodecyl-β-d-maltoside) and LMNG (lauryl maltose neopentyl glycol)]. This is a notable feature of the TTGs as glucoside detergents tend to be inferior to maltoside detergents at stabilizing membrane proteins. The favorable behavior of the TTGs for membrane protein stability is likely due to the high hydrophobicity of the lipophilic groups, an optimal range of hydrophilic-lipophilic balance, and the absence of cis-trans isomerism.

The Drp1-Mediated Mitochondrial Fission Protein Interactome as an Emerging Core Player in Mitochondrial Dynamics and Cardiovascular Disease Therapy

Mitochondria, the membrane-bound cell organelles that supply most of the energy needed for cell function, are highly regulated, dynamic organelles bearing the ability to alter both form and functionality rapidly to maintain normal physiological events and challenge stress to the cell. This amazingly vibrant movement and distribution of mitochondria within cells is controlled by the highly coordinated interplay between mitochondrial dynamic processes and fission and fusion events, as well as mitochondrial quality-control processes, mainly mitochondrial autophagy (also known as mitophagy). Fusion connects and unites neighboring depolarized mitochondria to derive a healthy and distinct mitochondrion. In contrast, fission segregates damaged mitochondria from intact and healthy counterparts and is followed by selective clearance of the damaged mitochondria via mitochondrial specific autophagy, i.e., mitophagy. Hence, the mitochondrial processes encompass all coordinated events of fusion, fission, mitophagy, and biogenesis for sustaining mitochondrial homeostasis. Accumulated evidence strongly suggests that mitochondrial impairment has already emerged as a core player in the pathogenesis, progression, and development of various human diseases, including cardiovascular ailments, the leading causes of death globally, which take an estimated 17.9 million lives each year. The crucial factor governing the fission process is the recruitment of dynamin-related protein 1 (Drp1), a GTPase that regulates mitochondrial fission, from the cytosol to the outer mitochondrial membrane in a guanosine triphosphate (GTP)-dependent manner, where it is oligomerized and self-assembles into spiral structures. In this review, we first aim to describe the structural elements, functionality, and regulatory mechanisms of the key mitochondrial fission protein, Drp1, and other mitochondrial fission adaptor proteins, including mitochondrial fission 1 (Fis1), mitochondrial fission factor (Mff), mitochondrial dynamics 49 (Mid49), and mitochondrial dynamics 51 (Mid51). The core area of the review focuses on the recent advances in understanding the role of the Drp1-mediated mitochondrial fission adaptor protein interactome to unravel the missing links of mitochondrial fission events. Lastly, we discuss the promising mitochondria-targeted therapeutic approaches that involve fission, as well as current evidence on Drp1-mediated fission protein interactions and their critical roles in the pathogeneses of cardiovascular diseases (CVDs).

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Characterization as well as prediction of the secondary and tertiary structure of hypothetical proteins from their amino acid sequences uploaded in databases by in silico approach are the critical issues in computational biology. Severe acute respiratory syndrome-associated coronavirus (SARS-CoV), which is responsible for pneumonia alike diseases, possesses a wide range of proteins of which many are still uncharacterized. The current study was conducted to reveal the physicochemical characteristics and structures of an uncharacterized protein Q6S8D9_SARS of SARS-CoV. Following the common flowchart of characterizing a hypothetical protein, several sophisticated computerized tools e.g., ExPASy Protparam, CD Search, SOPMA, PSIPRED, HHpred, etc. were employed to discover the functions and structures of Q6S8D9_SARS. After delineating the secondary and tertiary structures of the protein, some quality evaluating tools e.g., PROCHECK, ProSA-web etc. were performed to assess the structures and later the active site was identified also by CASTp v.3.0. The protein contains more negatively charged residues than positively charged residues and a high aliphatic index value which make the protein more stable. The 2D and 3D structures modeled by several bioinformatics tools ensured that the proteins had domain in it which indicated it was functional protein having the ability to trouble host antiviral inflammatory cytokine and interferon production pathways. Moreover, active site was found in the protein where ligand could bind. The study was aimed to unveil the features and structures of an uncharacterized protein of SARS-CoV which can be a therapeutic target for development of vaccines against the virus. Further research are needed to accomplish the task.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Protein Fusion Strategies for Membrane Protein Stabilization and Crystal Structure Determination

Crystal structures of membrane proteins are highly desired for their use in the mechanistic understanding of their functions and the designing of new drugs. However, obtaining the membrane protein structures is difficult. One way to overcome this challenge is with protein fusion methods, which have been successfully used to determine the structures of many membrane proteins, including receptors, enzymes and adhesion molecules. Existing fusion strategies can be categorized into the N or C terminal fusion, the insertion fusion and the termini restraining. The fusions facilitate protein expression, purification, crystallization and phase determination. Successful applications often require further optimization of protein fusion linkers and interactions, whose design can be facilitated by a shared helix strategy and by AlphaFold prediction in the future.

Application of polymersomes in membrane protein study and drug discovery: Progress, strategies, and perspectives

Membrane proteins (MPs) play key roles in cellular signaling pathways and are responsible for intercellular and intracellular interactions. Dysfunctional MPs are directly related to the pathogenesis of various diseases, and they have been exploited as one of the most sought-after targets in the pharmaceutical industry. However, working with MPs is difficult given that their amphiphilic nature requires protection from biological membrane or membrane mimetics. Polymersomes are bilayered nano-vesicles made of self-assembled block copolymers that have been widely used as cell membrane mimetics for MP reconstitution and in engineering of artificial cells. This review highlights the prevailing trend in the application of polymersomes in MP study and drug discovery. We begin with a review on the techniques for synthesis and characterization of polymersomes as well as methods of MP insertion to form proteopolymersomes. Next, we review the structural and functional analysis of the different types of MPs reconstituted in polymersomes, including membrane transport proteins, MP complexes, and membrane receptors. We then summarize the factors affecting reconstitution efficiency and the quality of reconstituted MPs for structural and functional studies. Additionally, we discuss the potential in using proteopolymersomes as platforms for high-throughput screening (HTS) in drug discovery to identify modulators of MPs. We conclude by providing future perspectives and recommendations on advancing the study of MPs and drug development using proteopolymersomes.

Novel In Silico Insights into Rv1417 and Rv2617c as Potential Protein Targets: The Importance of the Medium on the Structural Interactions with Exported Repetitive Protein (Erp) of Mycobacterium tuberculosis

Nowadays, tuberculosis is the second leading cause of death from a monopathogenic transmitted disease, only ahead of COVID-19. The role of exported repetitive protein (Erp) in the virulence of Mycobacterium tuberculosis has been extensively demonstrated. In vitro and in vivo assays have identified that Erp interacts with Rv1417 and Rv2617c proteins, forming putative transient molecular complexes prior to localization to the cell envelope. Although new insights into the interactions and functions of Erp have emerged over the years, knowledge about its structure and protein–protein interactions at the atomistic level has not been sufficiently explored. In this work, we have combined several in silico methodologies to gain new insights into the structural relationship between these proteins. Two system conditions were evaluated by MD simulations: Rv1417 and Rv2617c embedded in a lipid membrane and another with a semi-polar solvent to mimic the electrostatic conditions on the membrane surface. The Erp protein was simulated as an unanchored structure. Stabilized structures were docked, and complexes were evaluated to recognize the main residues involved in protein–protein interactions. Our results show the influence of the medium on the structural conformation of proteins. Globular conformations were favored under high polarity conditions and showed a higher energetic affinity in complex formation. Meanwhile, disordered conformations were favored under semi-polar conditions and an increase in the number of contacts between residues was observed. In addition, the electrostatic potential analysis showed remarkable changes in protein interactions due to the polarity of the medium, demonstrating the relevance of Erp protein in heterodimer formation. On the other hand, contact analysis showed that several C-terminal residues of Erp were involved in the protein interactions, which seems to contradict experimental observations; however, these complexes could be transient forms. The findings presented in this work are intended to open new perspectives in the studies of Erp protein molecular interactions and to improve the knowledge about its function and role in the virulence of Mycobacterium tuberculosis.

Foldable detergents for membrane protein stability

Detergents are widely used for membrane protein structural study. Many recently developed detergents contain multiple tail and head groups, which are typically connected via a small and branched linker. Due to their inherent compact structures, with small inter-alkyl chain distances, these detergents form micelles with high alkyl chain density in the interiors, a feature favorably associated with membrane protein stability. A recent study on tandem triazine maltosides (TZM) revealed a distinct trend; despite possession of an apparently large inter-alkyl chain distance, the TZM-Es were highly effective at stabilizing membrane proteins. Thanks to the incorporation of a flexible spacer between the two triazine rings in the linker region, these detergents are prone to folding into a compact architecture in micellar environments instead of adopting an extended conformation. Detergent foldability represents a new concept of novel detergent design with significant potential for future detergent development.

Development of 1,3-acetonedicarboxylate-derived glucoside amphiphiles (ACAs) for membrane protein study

Detergents are extensively used for membrane protein manipulation. Membrane proteins solubilized in conventional detergents are prone to denaturation and aggregation, rendering downstream characterization of these bio-macromolecules difficult. Although many amphiphiles have been developed to overcome the limited efficacy of conventional detergents for protein stabilization, only a handful of novel detergents have so far proved useful for membrane protein structural studies. Here, we introduce 1,3-acetonedicarboxylate-derived amphiphiles (ACAs) containing three glucose units and two alkyl chains as head and tail groups, respectively. The ACAs incorporate two different patterns of alkyl chain attachment to the core detergent unit, generating two sets of amphiphiles: ACA-As (asymmetrically alkylated) and ACA-Ss (symmetrically alkylated). The difference in the attachment pattern of the detergent alkyl chains resulted in minor variation in detergent properties such as micelle size, critical micelle concentration, and detergent behaviors toward membrane protein extraction and stabilization. In contrast, the impact of the detergent alkyl chain length on protein stability was marked. The two C11 variants (ACA-AC11 and ACA-SC11) were most effective at stabilizing the tested membrane proteins. The current study not only introduces new glucosides as tools for membrane protein study, but also provides detergent structure–property relationships important for future design of novel amphiphiles.

Newly developed amphiphiles, designated ACAs, are not only efficient at extracting G protein-coupled receptors from the membranes, but also conferred enhanced stability to the receptors compared to the gold standards (DDM and LMNG).

Mass Spectrometry Methods for Measuring Protein Stability

Mass spectrometry is a central technology in the life sciences, providing our most comprehensive account of the molecular inventory of the cell. In parallel with developments in mass spectrometry technologies targeting such assessments of cellular composition, mass spectrometry tools have emerged as versatile probes of biomolecular stability. In this review, we cover recent advancements in this branch of mass spectrometry that target proteins, a centrally important class of macromolecules that accounts for most biochemical functions and drug targets. Our efforts cover tools such as hydrogen-deuterium exchange, chemical cross-linking, ion mobility, collision induced unfolding, and other techniques capable of stability assessments on a proteomic scale. In addition, we focus on a range of application areas where mass spectrometry-driven protein stability measurements have made notable impacts, including studies of membrane proteins, heat shock proteins, amyloidogenic proteins, and biotherapeutics. We conclude by briefly discussing the future of this vibrant and fast-moving area of research.

MiRNA-disease association prediction based on meta-paths

Since miRNAs can participate in the posttranscriptional regulation of gene expression, they may provide ideas for the development of new drugs or become new biomarkers for drug targets or disease diagnosis. In this work, we propose an miRNA-disease association prediction method based on meta-paths (MDPBMP). First, an miRNA-disease-gene heterogeneous information network was constructed, and seven symmetrical meta-paths were defined according to different semantics. After constructing the initial feature vector for the node, the vector information carried by all nodes on the meta-path instance is extracted and aggregated to update the feature vector of the starting node. Then, the vector information obtained by the nodes on different meta-paths is aggregated. Finally, miRNA and disease embedding feature vectors are used to calculate their associated scores. Compared with the other methods, MDPBMP obtained the highest AUC value of 0.9214. Among the top 50 predicted miRNAs for lung neoplasms, esophageal neoplasms, colon neoplasms and breast neoplasms, 49, 48, 49 and 50 have been verified. Furthermore, for breast neoplasms, we deleted all the known associations between breast neoplasms and miRNAs from the training set. These results also show that for new diseases without known related miRNA information, our model can predict their potential miRNAs. Code and data are available at https://github.com/LiangYu-Xidian/MDPBMP.

Binding site identification of G protein-coupled receptors through a 3D Zernike polynomials-based method: application to C. elegans olfactory receptors

Studying the binding processes of G protein-coupled receptors (GPCRs) proteins is of particular interest both to better understand the molecular mechanisms that regulate the signaling between the extracellular and intracellular environment and for drug design purposes. In this study, we propose a new computational approach for the identification of the binding site for a specific ligand on a GPCR. The method is based on the Zernike polynomials and performs the ligand-GPCR association through a shape complementarity analysis of the local molecular surfaces. The method is parameter-free and it can distinguish, working on hundreds of experimentally GPCR-ligand complexes, binding pockets from randomly sampled regions on the receptor surface, obtaining an Area Under ROC curve of 0.77. Given its importance both as a model organism and in terms of applications, we thus investigated the olfactory receptors of the C. elegans, building a list of associations between 21 GPCRs belonging to its olfactory neurons and a set of possible ligands. Thus, we can not only carry out rapid and efficient screenings of drugs proposed for GPCRs, key targets in many pathologies, but also we laid the groundwork for computational mutagenesis processes, aimed at increasing or decreasing the binding affinity between ligands and receptors.

Advances in sample preparation for membrane proteome quantification

Membrane proteins mediate various biological processes. Most drugs commercially available target proteins on the cell surface. Therefore, proteomics of plasma membrane proteins provides useful information for drug discovery. However, membrane proteins are one of the most difficult biological groups to quantify by proteomics because of their hydrophobicity and low protein content. To obtain unbiased quantitative membrane proteomics data, specific strategies should be followed during sample preparation. This review explores the most recent advances in sample preparation for the quantitative analysis of the membrane proteome, including enrichment by subcellular fractionation and trypsin digestion.

Recombinant production of membrane proteins in yeast

Biochemical pathways are compartmentalized in living cells. This permits each cell to maintain chemical compositions that differ between the cytosol, intracellular organelles and the external environment. Achieving this requires each compartment to be very selective in what is allowed to enter and leave. Nature has solved this by surrounding each cell and each organelle with a virtually solute impermeable lipid membrane, embedded with integral membrane proteins that mediate strictly controlled trans-membrane movement of matter and information. Access to pure and active integral membrane proteins is therefore required to comprehend membrane biology, ultimately through high-resolution structures of the membrane proteome and, therefore, also for our understanding of physiology. Unfortunately, apart from a few exceptions, membrane proteins cannot be purified from native tissue but need to be produced recombinantly, which is eminently challenging. This chapter shows how we have engineered yeast to provide high levels of prime quality membrane proteins of prokaryotic, archaeal or eukaryotic origin for structural biology.

Structural and Functional Elucidation of IF-3 Protein of Chloroflexus aurantiacus Involved in Protein Biosynthesis: An In Silico Approach

Chloroflexus aurantiacus is a thermophilic bacterium that produces a multitude of proteins within its genome. Bioinformatics strategies can facilitate comprehending this organism through functional and structural interpretation assessments. This study is aimed at allocating the structure and function through an in silico approach required for bacterial protein biosynthesis. This in silico viewpoint provides copious properties, including the physicochemical properties, subcellular location, three-dimensional structure, protein-protein interactions, and functional elucidation of the protein (WP_012256288.1). The STRING program is utilized for the explication of protein-protein interactions. The in silico investigation documented the protein's hydrophilic nature with predominantly alpha (α) helices in its secondary structure. The tertiary-structure model of the protein has been shown to exhibit reasonably high consistency based on various quality assessment methods. The functional interpretation suggested that the protein can act as a translation initiation factor, a protein required for translation and protein biosynthesis. Protein-protein interactions also demonstrated high credence that the protein interconnected with 30S ribosomal subunit involved in protein synthesis. This study bioinformatically examined that the protein (WP_012256288.1) is affiliated in protein biosynthesis as a translation initiation factor IF-3 of C. aurantiacus.

Saccharomyces cerevisiae as a superior host for overproduction of prokaryotic integral membrane proteins

Integral membrane proteins (IMPs) constitute ~30% of all proteins encoded by the genome of any organism and Escherichia coli remains the first-choice host for recombinant production of prokaryotic IMPs. However, the expression levels of prokaryotic IMPs delivered by this bacterium are often low and overproduced targets often accumulate in inclusion bodies. The targets are therefore often discarded to avoid an additional and inconvenient refolding step in the purification protocol. Here we compared expression of five prokaryotic (bacterial and archaeal) IMP families in E. coli and Saccharomyces cerevisiae. We demonstrate that our S. cerevisiae-based production platform is superior in expression of four investigated IMPs, overall being able to deliver high quantities of active target proteins. Surprisingly, in case of the family of zinc transporters (Zrt/Irt-like proteins, ZIPs), S. cerevisiae rescued protein expression that was undetectable in E. coli. We also demonstrate the effect of localization of the fusion tag on expression yield and sample quality in detergent micelles. Lastly, we present a road map to achieve the most efficient expression of prokaryotic IMPs in our yeast platform. Our findings demonstrate the great potential of S. cerevisiae as host for high-throughput recombinant overproduction of bacterial and archaeal IMPs for downstream biophysical characterization.

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S. cerevisiae is superior to E. coli in expressing correctly folded and active IMPs.

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S. cerevisiae completely rescues the expression of the family of zinc transporters.

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Localization of the fusion tag affects expression yields and protein quality.

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We provide a roadmap to efficient expression of prokaryotic IMPs in S. cerevisiae.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Serial Crystallography for Structure-Based Drug Discovery

Rational drug discovery has greatly accelerated the development of safer and more efficacious therapeutics, assisted significantly by insights from experimentally determined 3D structures of ligands in complex with their targets. Serial crystallography (SX) with X-ray free-electron lasers has enabled structural determination using micrometer- or nanometer-size crystals. This technology, applied in the past decade to solve structures of notoriously difficult-to-study drug targets at room temperature, has now been adapted for use in synchrotron radiation facilities. Ultrashort time scales allow time-resolved characterization of dynamic structural changes and pave the road to study the molecular mechanisms by 'molecular movie.' This article summarizes the latest progress in SX technology and deliberates its demanding applications in future structure-based drug discovery.

Membrane Chemistry Tunes the Structure of a Peptide Transporter

Membrane proteins require lipid bilayers for function. While lipid compositions reach enormous complexities, high-resolution structures are usually obtained in artificial detergents. To understand whether and how lipids guide membrane protein function, we use single-molecule FRET to probe the dynamics of DtpA, a member of the proton-coupled oligopeptide transporter (POT) family, in various lipid environments. We show that detergents trap DtpA in a dynamic ensemble with cytoplasmic opening. Only reconstitutions in more native environments restore cooperativity, allowing an opening to the extracellular side and a sampling of all relevant states. Bilayer compositions tune the abundance of these states. A novel state with an extreme cytoplasmic opening is accessible in bilayers with anionic head groups. Hence, chemical diversity of membranes translates into structural diversity, with the current POT structures only sampling a portion of the full structural space.

Hydrolysis of Peptide Bonds in Protein Micelles Promoted by a Zirconium(IV)-Substituted Polyoxometalate as an Artificial Protease

The development of artificial proteases is challenging, but important for many applications in modern proteomics and biotechnology. The hydrolysis of hydrophobic or unstructured proteins is particularly difficult due to their poor solubility, which often requires the presence of surfactants. Herein, it is shown that a zirconium(IV)-substituted Keggin polyoxometalate (POM), (Et₂ NH₂ )₁₀ [Zr(α-PW₁₁ O₃₉ )₂ ] (1), is able to selectively hydrolyze β-casein, which is an intrinsically unstructured protein at pH 7.4 and 60 °C. Four surfactants (sodium dodecyl sulfate (SDS), N-dodecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (ZW3-12), 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS), and polyethylene glycol tert-octylphenyl ether (TX-100)), which differ in the nature of their polar groups, were investigated for their role in influencing the selectivity and efficiency of protein hydrolysis. Under experimental conditions, β-casein forms micellar structures in which the hydrophilic part of the protein is water accessible and able to interact with 1. Identical fragmentation patterns of β-casein in the presence of 1 were observed through SDS poly(acrylamide) gel electrophoresis both in the presence and absence of surfactants, but the rate of hydrolysis varied, depending on the nature of surfactant. Whereas TX-100 surfactant, which has a neutral polar head, caused only a slight decrease in the hydrolysis rate, stronger inhibition was observed in the presence surfactants with charges in their polar heads (CHAPS, ZW3-12, SDS). These results were consistent with those of tryptophan fluorescencequenching studies, which showed that the binding between β-casein and 1 decreased with increasing repulsion between the POM and the polar heads of the surfactants. In all cases, the micellar structure of β-casein was not significantly affected by the presence of POM or surfactants, as indicated by circular dichroism spectroscopy.

Promoting crystallization of intrinsic membrane proteins with conjugated micelles

A new technique for promoting nucleation and growth of membrane protein (MP) crystals from micellar environments is reported. It relies on the conjugation of micelles that sequester MPs in protein detergent complexes (PDCs). Conjugation via amphiphilic [metal:chelator] complexes presumably takes place at the micelle/water interface, thereby bringing the PDCs into proximity, promoting crystal nucleation and growth. We have successfully applied this approach to two light-driven proton pumps: bacteriorhodopsin (bR) and the recently discovered King Sejong 1-2 (KS1-2), using the amphiphilic 4,4'-dinonyl-2,2'-dipyridyl (Dinonyl) (0.7 mM) chelator in combination with Zn2+, Fe2+, or Ni2+ (0.1 mM). Crystal growth in the presence of the [metal-chelator] complexes leads to purple, hexagonal crystals (50-75 µm in size) of bR or pink, rectangular/square crystals (5-15 µm) of KS1-2. The effects of divalent cation identity and concentration, chelator structure and concentration, ionic strength and pH on crystal size, morphology and process kinetics, are described.