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Tetraspanins regulate signal transduction by interacting with partner proteins belonging to remarkably different protein families, including extracellular enzymes, integrins, members of the immunoglobulin superfamily, and intracellular signaling proteins. Structures of full-length tetraspanins have revealed a common overall architecture, with a cone-shaped transmembrane (TM) domain containing an intramembrane binding pocket. This pocket can bind lipids, which appear to modulate tetraspanin function. Many tetraspanins are conformationally dynamic, existing in at least two states with distinct TM conformations and ectodomain orientations. The molecular association of a tetraspanin with its partner can be mediated through the large extracellular loop (EC2 domain) and/or the TM domain. The dependency for each region differs based on the bound partner. Tetraspanins are a large, highly conserved family of four-pass transmembrane (TM) proteins that play critical roles in a variety of essential cellular functions, including cell migration, protein trafficking, maintenance of membrane integrity, and regulation of signal transduction. Tetraspanins carry out these biological functions primarily by interacting with partner proteins. Here, we summarize significant advances that have revealed fundamental principles underpinning structure–function relationships in tetraspanins. We first review the structural features of tetraspanin ectodomains and full-length apoproteins, and then discuss how recent structural studies of tetraspanin complexes have revealed plasticity in partner-protein recognition that enables tetraspanins to bind to remarkably different protein families, viral proteins, and antibody fragments. Finally, we discuss major questions and challenges that remain in studying tetraspanin complexes. [ABSTRACT FROM AUTHOR]

The low-molecular-weight PsbM and PsbT proteins of Photosystem II (PS II) are both located at the monomer-monomer interface of the mature PS II dimer. Since the extrinsic proteins are associated with the final step of assembly of an active PS II monomer and, in the case of PsbO, are known to impact the stability of the PS II dimer, we have investigated the potential cooperativity between the PsbM and PsbT subunits and the PsbO, PsbU and PsbV extrinsic proteins. Blue-native polyacrylamide electrophoresis and western blotting detected stable PS II monomers in the ∆PsbM:∆PsbO and ∆PsbT:∆PsbO mutants that retained sufficient oxygen-evolving activity to support reduced photoautotrophic growth. In contrast, the ∆PsbM:∆PsbU and ∆PsbT:∆PsbU mutants assembled dimeric PS II at levels comparable to wild type and supported photoautotrophic growth at rates similar to those obtained with the corresponding ∆PsbM and ∆PsbT cells. Removal of PsbV was more detrimental than removal of PsbO. Only limited levels of dimeric PS II were observed in the ∆PsbM:∆PsbV mutant and the overall reduced level of assembled PS II in this mutant resulted in diminished rates of photoautotrophic growth and PS II activity below those obtained in the ∆PsbM:∆PsbO and ∆PsbT:∆PsbO strains. In addition, the ∆PsbT:∆PsbV mutant did not assemble active PS II centers although inactive monomers could be detected. The inability of the ∆PsbT:∆PsbV mutant to grow photoautotrophically, or to evolve oxygen, suggested a stable oxygen-evolving complex could not assemble in this mutant. [ABSTRACT FROM AUTHOR]

Residue contact maps provide a condensed two-dimensional representation of three-dimensional protein structures, serving as a foundational framework in structural modeling but also as an effective tool in their own right in identifying inter-helical binding sites and drawing insights about protein function. Treating contact maps primarily as an intermediate step for 3D structure prediction, contact prediction methods have limited themselves exclusively to sequential features. Now that AlphaFold2 predicts 3D structures with good accuracy in general, we examine (1) how well predicted 3D structures can be directly used for deciding residue contacts, and (2) whether features from 3D structures can be leveraged to further improve residue contact prediction. With a well-known benchmark dataset, we tested predicting inter-helical residue contact based on AlphaFold2's predicted structures, which gave an 83% average precision, already outperforming a sequential features-based state-of-the-art model. We then developed a procedure to extract features from atomic structure in the neighborhood of a residue pair, hypothesizing that these features will be useful in determining if the residue pair is in contact, provided the structure is decently accurate, such as predicted by AlphaFold2. Training on features generated from experimentally determined structures, we leveraged knowledge from known structures to significantly improve residue contact prediction, when testing using the same set of features but derived using AlphaFold2 structures. Our results demonstrate a remarkable improvement over AlphaFold2, achieving over 91.9% average precision for a held-out subset and over 89.5% average precision in cross-validation experiments. [ABSTRACT FROM AUTHOR]

Transmembrane proteins are active in amphipathic environments. To stabilize the protein in such surrounding the exposure of hydrophobic residues on the protein surface is required. Transmembrane proteins are responsible for the transport of various molecules. Therefore, they often represent structures in the form of channels. This analysis focused on the stability and local flexibility of transmembrane proteins, particularly those related to their biological activity. Different forms of anchorage were identified using the fuzzy oil‐drop model (FOD) and its modified form, FOD‐M. The mainly helical as well as β‐barrel structural forms are compared with respect to the mechanism of stabilization in the cell membrane. The different anchoring system was found to stabilize protein molecules with possible local fluctuation. [ABSTRACT FROM AUTHOR]

A series of monoclonal antibodies with therapeutic potential against cancer have been generated and developed. Ninety-one are currently used in the clinics, either alone or in combination with chemotherapeutic agents or other antibodies, including immune checkpoint antibodies. These advances helped to coin the term personalized medicine or precision medicine. However, it seems evident that in addition to the current work on the analysis of mechanisms to overcome drug resistance, the use of different classes of antibodies (IgA, IgE, or IgM) instead of IgG, the engineering of the Ig molecules to increase their half-life, the acquisition of additional effector functions, or the advantages associated with the use of agonistic antibodies, to allow a broad prospective usage of precision medicine successfully, a strategy change is required. Here, we discuss our view on how these strategic changes should be implemented and consider their pros and cons using therapeutic antibodies against cancer as a model. The same strategy can be applied to therapeutic antibodies against other diseases, such as infectious or autoimmune diseases. [ABSTRACT FROM AUTHOR]

Numerous potential drug targets, including G-protein-coupled receptors and ion channel proteins, reside on the cell surface as multi-pass membrane proteins. Unfortunately, despite advances in engineering technologies, engineering biologics against multi-pass membrane proteins remains a formidable task. In this review, we focus on the different methods used to prepare/present multi-pass transmembrane proteins for engineering target-specific biologics such as antibodies, nanobodies and synthetic scaffold proteins. The engineered biologics exhibit high specificity and affinity, and have broad applications as therapeutics, probes for cell staining and chaperones for promoting protein crystallization. We primarily cover publications on this topic from the past 10 years, with a focus on the different formats of multi-pass transmembrane proteins. Finally, the remaining challenges facing this field and new technologies developed to overcome a number of obstacles are discussed. [ABSTRACT FROM AUTHOR]

The structural investigation of biological macromolecules is indispensable in understanding the molecular mechanisms underlying diseases. Several structural biology techniques have been introduced to unravel the structural facets of biomolecules. Among these, the electron cryomicroscopy (cryo-EM) method microcrystal electron diffraction (MicroED) has produced atomic resolution structures of important biological and small molecules. Since its inception in 2013, MicroED established a demonstrated ability for solving structures of difficult samples using vanishingly small crystals. However, membrane proteins remain the next big frontier for MicroED. The intrinsic properties of membrane proteins necessitate improved sample handling and imaging techniques to be developed and optimized for MicroED. Here, we summarize the milestones of electron crystallography of two-dimensional crystals leading to MicroED of three-dimensional crystals. Then, we focus on four different membrane protein families and discuss representatives from each family solved by MicroED.

Oncologic disease is a significant global health issue that causes thousands of deaths annually, and it has a significant impact on the quality of life of patients. Prostate cancer (PCa) is the second most diagnosed cancer and the fourth leading cause of cancer-related death in men in the Western world. Delineation of pathogenetic pathways and key driver molecular alterations involved in PCa development has provided a roadmap for the evaluation of biomarkers in predicting disease outcome and to identify potential therapeutic targets. Chemotherapeutic agents introduced from the 1990s include the taxanes (paclitaxel, docetaxel, and cabazitaxel), which are the anticancer drugs used most frequently for PCa treatment. This review presents the current knowledge about the onset and development of PCa, the state of the art of the use of taxane-based therapy, and their combination with targeting different transmembrane oncoproteins in PCa. The silencing of some transmembrane proteins can improve taxane sensitivity, and therefore may be a mechanism to improve the effectiveness of these drugs in PCa treatment. This combined therapy needs to be explored as a potential therapeutic agent for reducing cell proliferation, migration, and invasiveness in PCa.

The dense alignment surface (DAS) transmembrane (TM) prediction method was first published more than 25 years ago. DAS was the one of the earliest tools to discriminate TM proteins from globular ones and to predict the sequence positions of TM helices in proteins with high accuracy from their amino acid sequence alone. The algorithmic improvements that followed in 2002 (DAS-TMfilter) made it one of the best performing tools among those relying on local sequence information for TM prediction. Since then, many more experimental data about membrane proteins (including thousands of 3D structures of membrane proteins) have accumulated but there has been no significant improvement concerning performance in the area of TM helix prediction tools. Here, we report a new implementation of the DAS-TMfilter prediction web server. We reevaluated the performance of the method using a five-times-larger, updated test dataset. We found that the method performs at essentially the same accuracy as the original even without any change to the parametrization of the program despite the much larger dataset. Thus, the approach captures the physico-chemistry of TM helices well, essentially solving this scientific problem. [ABSTRACT FROM AUTHOR]

Transmembrane proteins are receptors, enzymes, transporters and ion channels that are instrumental in regulating a variety of cellular activities, such as signal transduction and cell communication. Despite tremendous progress in computational capacities to support protein research, there is still a significant gap in the availability of specialized computational analysis toolkits for transmembrane protein research. Here, we introduce TMKit, an open-source Python programming interface that is modular, scalable and specifically designed for processing transmembrane protein data. TMKit is a one-stop computational analysis tool for transmembrane proteins, enabling users to perform database wrangling, engineer features at the mutational, domain and topological levels, and visualize protein–protein interaction interfaces. In addition, TMKit includes seqNetRR, a high-performance computing library that allows customized construction of a large number of residue connections. This library is particularly well suited for assigning correlation matrix-based features at a fast speed. TMKit should serve as a useful tool for researchers in assisting the study of transmembrane protein sequences and structures. TMKit is publicly available through https://github.com/2003100127/tmkit and https://tmkit-guide.herokuapp.com/doc/overview. [ABSTRACT FROM AUTHOR]

Oncologic disease is a significant global health issue that causes thousands of deaths annually, and it has a significant impact on the quality of life of patients. Prostate cancer (PCa) is the second most diagnosed cancer and the fourth leading cause of cancer-related death in men in the Western world. Delineation of pathogenetic pathways and key driver molecular alterations involved in PCa development has provided a roadmap for the evaluation of biomarkers in predicting disease outcome and to identify potential therapeutic targets. Chemotherapeutic agents introduced from the 1990s include the taxanes (paclitaxel, docetaxel, and cabazitaxel), which are the anticancer drugs used most frequently for PCa treatment. This review presents the current knowledge about the onset and development of PCa, the state of the art of the use of taxane-based therapy, and their combination with targeting different transmembrane oncoproteins in PCa. The silencing of some transmembrane proteins can improve taxane sensitivity, and therefore may be a mechanism to improve the effectiveness of these drugs in PCa treatment. This combined therapy needs to be explored as a potential therapeutic agent for reducing cell proliferation, migration, and invasiveness in PCa. [ABSTRACT FROM AUTHOR]

BACKGROUND The high rates of unintended pregnancy and the ever-growing world population impose health, economic, social, and environmental threats to countries. Expanding contraceptive options, including male methods, are urgently needed to tackle these global challenges. Male contraception is limited to condoms and vasectomy, which are unsuitable for many couples. Thus, novel male contraceptive methods may reduce unintended pregnancies, meet the contraceptive needs of couples, and foster gender equality in carrying the contraceptive burden. In this regard, the spermatozoon emerges as a source of druggable targets for on-demand, non-hormonal male contraception based on disrupting sperm motility or fertilization. OBJECTIVE AND RATIONALE A better understanding of the molecules governing sperm motility can lead to innovative approaches toward safe and effective male contraceptives. This review discusses cutting-edge knowledge on sperm-specific targets for male contraception, focusing on those with crucial roles in sperm motility. We also highlight challenges and opportunities in male contraceptive drug development targeting spermatozoa. SEARCH METHODS We conducted a literature search in the PubMed database using the following keywords: 'spermatozoa', 'sperm motility', 'male contraception', and 'drug targets' in combination with other related terms to the field. Publications until January 2023 written in English were considered. OUTCOMES Efforts for developing non-hormonal strategies for male contraception resulted in the identification of candidates specifically expressed or enriched in spermatozoa, including enzymes (PP1γ2, GAPDHS, and sAC), ion channels (CatSper and KSper), transmembrane transporters (sNHE, SLC26A8, and ATP1A4), and surface proteins (EPPIN). These targets are usually located in the sperm flagellum. Their indispensable roles in sperm motility and male fertility were confirmed by genetic or immunological approaches using animal models and gene mutations associated with male infertility due to sperm defects in humans. Their druggability was demonstrated by the identification of drug-like small organic ligands displaying spermiostatic activity in preclinical trials. WIDER IMPLICATIONS A wide range of sperm-associated proteins has arisen as key regulators of sperm motility, providing compelling druggable candidates for male contraception. Nevertheless, no pharmacological agent has reached clinical developmental stages. One reason is the slow progress in translating the preclinical and drug discovery findings into a drug-like candidate adequate for clinical development. Thus, intense collaboration among academia, private sectors, governments, and regulatory agencies will be crucial to combine expertise for the development of male contraceptives targeting sperm function by (i) improving target structural characterization and the design of highly selective ligands, (ii) conducting long-term preclinical safety, efficacy, and reversibility evaluation, and (iii) establishing rigorous guidelines and endpoints for clinical trials and regulatory evaluation, thus allowing their testing in humans. [ABSTRACT FROM AUTHOR]

Residue contact maps provide a condensed two-dimensional representation of three-dimensional protein structures, serving as a foundational framework in structural modeling but also as an effective tool in their own right in identifying inter-helical binding sites and drawing insights about protein function. Treating contact maps primarily as an intermediate step for 3D structure prediction, contact prediction methods have limited themselves exclusively to sequential features. Now that AlphaFold2 predicts 3D structures with good accuracy in general, we examine (1) how well predicted 3D structures can be directly used for deciding residue contacts, and (2) whether features from 3D structures can be leveraged to further improve residue contact prediction. With a well-known benchmark dataset, we tested predicting inter-helical residue contact based on AlphaFold2’s predicted structures, which gave an 83% average precision, already outperforming a sequential features-based state-of-the-art model. We then developed a procedure to extract features from atomic structure in the neighborhood of a residue pair, hypothesizing that these features will be useful in determining if the residue pair is in contact, provided the structure is decently accurate, such as predicted by AlphaFold2. Training on features generated from experimentally determined structures, we leveraged knowledge from known structures to significantly improve residue contact prediction, when testing using the same set of features but derived using AlphaFold2 structures. Our results demonstrate a remarkable improvement over AlphaFold2, achieving over 91.9% average precision for a held-out subset and over 89.5% average precision in cross-validation experiments.

The nuclear pore complex (NPC) serves as a pivotal subcellular structure, acting as a gateway that orchestrates nucleocytoplasmic transport through a selectively permeable barrier. Nucleoporins (Nups), particularly those containing phenylalanine–glycine (FG) motifs, play indispensable roles within this barrier. Recent advancements in technology have significantly deepened our understanding of the NPC's architecture and operational intricacies, owing to comprehensive investigations. Nevertheless, the conspicuous presence of intrinsically disordered regions within FG-Nups continues to present a formidable challenge to conventional static characterization techniques. Historically, a multitude of strategies have been employed to unravel the intricate organization and behavior of FG-Nups within the NPC. These endeavors have given rise to multiple models that strive to elucidate the structural layout and functional significance of FG-Nups. Within this exhaustive review, we present a comprehensive overview of these prominent models, underscoring their proposed dynamic and structural attributes, supported by pertinent research. Through a comparative analysis, we endeavor to shed light on the distinct characteristics and contributions inherent in each model. Simultaneously, it remains crucial to acknowledge the scarcity of unequivocal validation for any of these models, as substantiated by empirical evidence.

Low temperature stress significantly threatens crop productivity and economic sustainability. Plants counter this by deploying advanced molecular mechanisms to perceive and respond to cold stress. Transmembrane proteins initiate these responses, triggering a series of events involving secondary messengers such as calcium ions (Ca2+), reactive oxygen species (ROS), and inositol phosphates. Of these, calcium signaling is paramount, activating downstream phosphorylation cascades and the transcription of cold-responsive genes, including coldregulated (COR) genes. This review focuses on how plants manage freezeinduced damage through dual strategies: cold tolerance and cold avoidance. Tolerance mechanisms involve acclimatization to decreasing temperatures, fostering gradual accumulation of cold resistance. In contrast, avoidance mechanisms rely on cryoprotectant molecules like potassium ions (K+), proline, glycerol, and antifreeze proteins (AFPs). Cryoprotectants modulate intracellular solute concentration, lower the freezing point, inhibit ice formation, and preserve plasma membrane fluidity. Additionally, these molecules demonstrate antioxidant activity, scavenging ROS, preventing protein denaturation, and subsequently mitigating cellular damage. By forming extensive hydrogen bonds with water molecules, cryoprotectants also limit intercellular water movement, minimizing extracellular ice crystal formation, and cell dehydration. The deployment of cryoprotectants is a key adaptive strategy that bolsters plant resilience to cold stress and promotes survival in freezing environments. However, the specific physiological and molecular mechanisms underlying these protective effects remain insufficiently understood. Therefore, this review underscores the need for further research to elucidate these mechanisms and assess their potential impact on crop productivity and sustainability, contributing to the progressive discourse in plant biology and environmental science. [ABSTRACT FROM AUTHOR]

The analysis of transmembrane proteins in Frankia genomes provided insight into the host-microbe interaction strategy of this nitrogen-fixing Actinobacteria. The transmembrane proteins (TM) with their extracellular part exposed on the surface of the cell and the peripheral membrane proteins play a crucial role in the interaction of Frankia with the infected host plant and are termed as 'surfactome' for this study. Our analysis identified two categories of transmembrane proteins: signaling-TM (STM) and non-signaling TM (NSTM) proteins. The STM category was further subdivided into Lipo, Sec, and TAT. The codon and amino acid usage analysis revealed the importance of compositional constraints, translational efficiency, tRNA adaptation index, and RSCU over Frankia. The COG analysis proved the role of surfactome in signal transduction. It was evident that STMs were evolving faster than NSTMs. Moreover, the signal part of the STM proteins was found to be more evolved than the mature part. This rapid evolution enables the signaling proteins to interact with diverse external stimuli more effectively, which may be essential for the host-microbe association between Frankia and Actinorhizal plants. In conclusion, the comprehensive analysis of surfactome among Frankia genomes provided valuable perceptions into the host-microbe interaction strategy of this nitrogen-fixing actinobacteria. The results suggest that the composition and evolution of these proteins are essential for successful host-microbe associations. Considering the uniqueness of these proteins we coined the term "surfactome" for them and called for further research on the mechanisms of plant–microbe interactions. [ABSTRACT FROM AUTHOR]

The FtsQBL is an essential molecular complex sitting midway through bacterial divisome assembly. To visualize and understand its structure, and the consequences of its membrane anchorage, we produced a model of the E. coli complex using the deep-learning prediction utility, AlphaFold 2. The heterotrimeric model was inserted into a 3-lipid model membrane and subjected to a 500-ns atomistic molecular dynamics simulation. The model is superb in quality and captures most experimentally derived structural features, at both the secondary structure and the side-chain levels. The model consists of a uniquely interlocking module contributed by the C-terminal regions of all three proteins. The functionally important constriction control domain residues of FtsB and FtsL are located at a fixed vertical position of ∼43–49 Å from the membrane surface. While the periplasmic domains of all three proteins are well-defined and rigid, the single transmembrane helices of each are flexible and their collective twisting and bending contribute to most structural variations, according to principal component analysis. Considering FtsQ only, the protein is more flexible in its free state relative to its complexed state—with the biggest structural changes located at the elbow between the transmembrane helix and the α-domain. The disordered N-terminal domains of FtsQ and FtsL associate with the cytoplasmic surface of the inner membrane instead of freely venturing into the solvent. Contact network analysis highlighted the formation of the interlocking trimeric module in FtsQBL as playing a central role in mediating the overall structure of the complex.

Transmembrane protein 72 (TMEM72) is involved in normal kidney development and tumorigenesis in renal cell carcinoma. However, the function of TMEM72 has not been experimentally examined; therefore, the role of TMEM72 is incompletely understood. In this study, we initially demonstrated that TMEM72 has four transmembrane domains (TMDs) and a long C‐terminal tail. Immunofluorescence analysis showed that TMEM72 is localized on the plasma membrane but not on the outer mitochondrial membrane. Experiments performed with a series of TMEM72 deletion mutants and an evaluation of the unfolded protein response indicated that these TMDs are needed for proper protein folding or assembly. In contrast, domain‐specific replacement analysis indicated the essential role of the C‐terminal region of TMEM72 in protein transport. Spatial colocalization and immunoprecipitation assays showed that the proximal C‐terminal region is responsible for anterograde protein transport. An amino acid sequence analysis and an immunocytochemical evaluation revealed that KRKKRKAAPEVLA, which corresponds to amino acid positions 132–144 in TMEM72, participates in efficient cellular transport. The motifs 132KRKKRK137 and 139APEVLA144 are associated with COPII and are considered to cooperate with membrane trafficking. Because efficient membrane trafficking is crucial for cells to maintain normal function, our data may contribute to elucidating the pathogenesis of membrane trafficking‐associated diseases, particularly renal carcinoma and chronic kidney disease. [ABSTRACT FROM AUTHOR]

Low temperature stress significantly threatens crop productivity and economic sustainability. Plants counter this by deploying advanced molecular mechanisms to perceive and respond to cold stress. Transmembrane proteins initiate these responses, triggering a series of events involving secondary messengers such as calcium ions (Ca2+), reactive oxygen species (ROS), and inositol phosphates. Of these, calcium signaling is paramount, activating downstream phosphorylation cascades and the transcription of cold-responsive genes, including cold-regulated (COR) genes. This review focuses on how plants manage freeze-induced damage through dual strategies: cold tolerance and cold avoidance. Tolerance mechanisms involve acclimatization to decreasing temperatures, fostering gradual accumulation of cold resistance. In contrast, avoidance mechanisms rely on cryoprotectant molecules like potassium ions (K+), proline, glycerol, and antifreeze proteins (AFPs). Cryoprotectants modulate intracellular solute concentration, lower the freezing point, inhibit ice formation, and preserve plasma membrane fluidity. Additionally, these molecules demonstrate antioxidant activity, scavenging ROS, preventing protein denaturation, and subsequently mitigating cellular damage. By forming extensive hydrogen bonds with water molecules, cryoprotectants also limit intercellular water movement, minimizing extracellular ice crystal formation, and cell dehydration. The deployment of cryoprotectants is a key adaptive strategy that bolsters plant resilience to cold stress and promotes survival in freezing environments. However, the specific physiological and molecular mechanisms underlying these protective effects remain insufficiently understood. Therefore, this review underscores the need for further research to elucidate these mechanisms and assess their potential impact on crop productivity and sustainability, contributing to the progressive discourse in plant biology and environmental science.

DNA replication, transcription, and translation in eukaryotic cells occur with decreasing but still high fidelity. In contrast, for the estimated 33% of the human proteome that is inserted as transmembrane (TM) proteins, insertion with a non-functional inverted topology is frequent. Correct topology is essential for function and trafficking to appropriate cellular compartments and is controlled principally by responses to charged residues within 15 residues of the inserted TM domain (TMD); the flank with the higher positive charge remains in the cytosol (inside), following the positive inside rule (PIR). Yeast (Saccharomyces cerevisiae) mutants that increase insertion contrary to the PIR were selected. Mutants with strong phenotypes were found only in SPF1 and STE24 (human cell orthologs are ATP13A1 and ZMPSte24) with, at the time, no known relevant functions. Spf1/Atp13A1 is now known to dislocate to the cytosol TM proteins inserted contrary to the PIR, allowing energy-conserving reinsertion. We hypothesize that Spf1 and Ste24 both recognize the short, positively charged ER luminal peptides of TM proteins inserted contrary to the PIR, accepting these peptides into their large membrane-spanning, water-filled cavities through interaction with their many interior surface negative charges. While entry was demonstrated for Spf1, no published evidence directly demonstrates substrate entry to the Ste24 cavity, internal access to its zinc metalloprotease (ZMP) site, or active withdrawal of fragments, which may be essential for function. Spf1 and Ste24 comprise a PIR quality control system that is conserved in all eukaryotes and presumably evolved in prokaryotic progenitors as they gained differentiated membrane functions. About 75% of the PIR is imposed by this quality control system, which joins the UPR, ERAD, and autophagy (ER-phagy) in coordinated, overlapping quality control of ER protein function.

A series of monoclonal antibodies with therapeutic potential against cancer have been generated and developed. Ninety-one are currently used in the clinics, either alone or in combination with chemotherapeutic agents or other antibodies, including immune checkpoint antibodies. These advances helped to coin the term personalized medicine or precision medicine. However, it seems evident that in addition to the current work on the analysis of mechanisms to overcome drug resistance, the use of different classes of antibodies (IgA, IgE, or IgM) instead of IgG, the engineering of the Ig molecules to increase their half-life, the acquisition of additional effector functions, or the advantages associated with the use of agonistic antibodies, to allow a broad prospective usage of precision medicine successfully, a strategy change is required. Here, we discuss our view on how these strategic changes should be implemented and consider their pros and cons using therapeutic antibodies against cancer as a model. The same strategy can be applied to therapeutic antibodies against other diseases, such as infectious or autoimmune diseases.

Polyphosphoinositides (PPIs) are essential phospholipids located in the cytoplasmic leaflet of eukaryotic cell membranes. Despite contributing only a small fraction to the bulk of cellular phospholipids, they make remarkable contributions to practically all aspects of a cell's life and death. They do so by recruiting cytoplasmic proteins/effectors or by interacting with cytoplasmic domains of membrane proteins at the membrane-cytoplasm interface to organize and mold organelle identity. The present study summarizes aspects of our current understanding concerning the metabolism, manipulation, measurement, and intimate roles these lipids play in regulating membrane homeostasis and vital cell signaling reactions in health and disease.

Simple Summary: The sorting nexin (SNX) family of proteins mediate the sorting and trafficking of endocytosed transmembrane proteins between the endosomal compartments, lysosome, trans-Golgi network, and plasma membrane. SNXs are characterized by the presence of a Phox domain; however, SNX27 is a unique member of this family as it contains an additional PDZ domain. Evidence suggests that SNX27, in association with the retromer complex, binds cargo via its PDZ domain and recycles them from the early endosomes to the plasma membrane, thereby escaping their lysosomal degradation. The roles of SNX27 in cancer is largely unexplored, however many of its identified cargoes have been indicated in tumorigenesis. In this review we provide a summary of the current knowledge, as supported by scientific literature and evidence, regarding the fundamental structure, biological function, and implication of SNX27 in human cancers. SNX27 belongs to the sorting nexin (SNX) family of proteins that play a critical role in protein sorting and trafficking in the endocytosis pathway. This protein family is characterized by the presence of a Phox (PX) domain; however, SNX27 is unique in containing an additional PDZ domain. Recently, SNX27 has gained popularity as an important sorting protein that is associated with the retromer complex and mediates the recycling of internalized proteins from endosomes to the plasma membrane in a PDZ domain-dependent manner. Over 100 cell surface proteins have been identified as binding partners of the SNX27–retromer complex. However, the roles and underlying mechanisms governed by SNX27 in tumorigenesis remains to be poorly understood. Many of its known binding partners include several G-protein coupled receptors, such as β2-andrenergic receptor and parathyroid hormone receptor, are associated with multiple pathways implicated in oncogenic signaling and tumorigenesis. Additionally, SNX27 mediates the recycling of GLUT1 and the activation of mTORC1, both of which can regulate intracellular energy balance and promote cell survival and proliferation under conditions of nutrient deprivation. In this review, we summarize the structure and fundamental roles of SNX proteins, with a focus on SNX27, and provide the current evidence indicating towards the role of SNX27 in human cancers. We also discuss the gap in the field and future direction of SNX27 research. Insights into the emerging roles and mechanism of SNX27 in cancers will provide better development strategies to prevent and treat tumorigenesis. [ABSTRACT FROM AUTHOR]

During coronavirus infection, three non-structural proteins, nsp3, nsp4, and nsp6, are of great importance as they induce the formation of double-membrane vesicles where the replication and transcription of viral gRNA takes place, and the interaction of nsp3 and nsp4 lumenal regions triggers membrane pairing. However, their structural states are not well-understood. We investigated the interactions between nsp3 and nsp4 by predicting the structures of their lumenal regions individually and in complex using AlphaFold2 as implemented in ColabFold. The ColabFold prediction accuracy of the nsp3–nsp4 complex was increased compared to nsp3 alone and nsp4 alone. All cysteine residues in both lumenal regions were modelled to be involved in intramolecular disulphide bonds. A linker region in the nsp4 lumenal region emerged as crucial for the interaction, transitioning to a structured state when predicted in complex. The key interactions modelled between nsp3 and nsp4 appeared stable when the transmembrane regions of nsp3 and nsp4 were added to the modelling either alone or together. While molecular dynamics simulations (MD) demonstrated that the proposed model of the nsp3 lumenal region on its own is not stable, key interactions between nsp and nsp4 in the proposed complex model appeared stable after MD. Together, these observations suggest that the interaction is robust to different modelling conditions. Understanding the functional importance of the nsp4 linker region may have implications for the targeting of double membrane vesicle formation in controlling coronavirus infection. [ABSTRACT FROM AUTHOR]

Numerous potential drug targets, including G-protein-coupled receptors and ion channel proteins, reside on the cell surface as multi-pass membrane proteins. Unfortunately, despite advances in engineering technologies, engineering biologics against multi-pass membrane proteins remains a formidable task. In this review, we focus on the different methods used to prepare/present multi-pass transmembrane proteins for engineering target-specific biologics such as antibodies, nanobodies and synthetic scaffold proteins. The engineered biologics exhibit high specificity and affinity, and have broad applications as therapeutics, probes for cell staining and chaperones for promoting protein crystallization. We primarily cover publications on this topic from the past 10 years, with a focus on the different formats of multi-pass transmembrane proteins. Finally, the remaining challenges facing this field and new technologies developed to overcome a number of obstacles are discussed.

The dense alignment surface (DAS) transmembrane (TM) prediction method was first published more than 25 years ago. DAS was the one of the earliest tools to discriminate TM proteins from globular ones and to predict the sequence positions of TM helices in proteins with high accuracy from their amino acid sequence alone. The algorithmic improvements that followed in 2002 (DAS-TMfilter) made it one of the best performing tools among those relying on local sequence information for TM prediction. Since then, many more experimental data about membrane proteins (including thousands of 3D structures of membrane proteins) have accumulated but there has been no significant improvement concerning performance in the area of TM helix prediction tools. Here, we report a new implementation of the DAS-TMfilter prediction web server. We reevaluated the performance of the method using a five-times-larger, updated test dataset. We found that the method performs at essentially the same accuracy as the original even without any change to the parametrization of the program despite the much larger dataset. Thus, the approach captures the physico-chemistry of TM helices well, essentially solving this scientific problem.

Human African trypanosomiasis (HAT) is a neglected tropical disease that is caused by flagellated parasites of the genus Trypanosoma. HAT imposes a significant socio-economic burden on many countries in sub-Saharan Africa and its control is hampered by several drawbacks ranging from the ineffectiveness of drugs, complex dosing regimens, drug resistance, and lack of a vaccine. Despite more than a century of research and investigations, the development of a vaccine to tackle HAT is still challenging due to the complex biology of the pathogens. Advancements in computational modeling coupled with the availability of an unprecedented amount of omics data from different organisms have allowed the design of new generation vaccines that offer better antigenicity and safety profile. One of such new generation approaches is a multi-epitope vaccine (MEV) designed from a collection of antigenic peptides. A MEV can stimulate both cellular and humoral immune responses as well as avoiding possible allergenic reactions. Herein, we take advantage of this approach to design a MEV from conserved hypothetical plasma membrane proteins of Trypanosoma brucei gambiense, the trypanosome subspecies that is responsible for the west and central African forms of HAT. The designed MEV is 402 amino acids long (41.5 kDa). It is predicted to be antigenic, non-toxic, to assume a stable 3D conformation, and to interact with a key immune receptor. In addition, immune simulation foresaw adequate immune stimulation by the putative antigen and a lasting memory. Therefore, the designed chimeric vaccine represents a potential candidate that could be used to target HAT.

Computationally designed transmembrane α-helical peptides (CHAMP) have been used to compete for helix-helix interactions within the membrane, enabling the ability to probe the activation of the integrins αIIbβ3 and αvβ3. Here, this method is extended towards the design of CHAMP peptides that inhibit the association of the α5β1 transmembrane (TM) domains, targeting the Ala-X3-Gly motif within α5. Our previous design algorithm was performed alongside a new workflow implemented within the widely used Rosetta molecular modeling suite. Peptides from each computational approach activated integrin α5β1 but not αVβ3 in human endothelial cells. Two CHAMP peptides were shown to directly associate with an α5 TM domain peptide in detergent micelles to a similar degree as a β1 TM peptide does. By solution-state nuclear magnetic resonance, one of these CHAMP peptides was shown to bind primarily the integrin β1 TM domain, which itself has a Gly-X3-Gly motif. The second peptide associated modestly with both α5 and β1 constructs, with slight preference for α5. Although the design goal was not fully realized, this work characterizes novel CHAMP peptides activating α5β1 that can serve as useful reagents for probing integrin biology.

Transmembrane proteins participate in various physiological activities in plants, including signal transduction, substance transport, and energy conversion. Although more than 20% of gene products are predicted to be transmembrane proteins in the genome era, due to the complexity of transmembrane domains they are difficult to reliably identify in the predicted protein, and they may have different overall three-dimensional structures. Therefore, it is challenging to study their biological function. In this review, we describe the typical structures of transmembrane proteins and their roles in plant growth, development, and stress responses. We propose a model illustrating the roles of transmembrane proteins during plant growth and response to various stresses, which will provide important references for crop breeding. [ABSTRACT FROM AUTHOR]

Integral membrane proteins (MPs) are dominated by transmembrane α-helical (TMH) proteins playing critical roles in cellular signaling processes. These proteins display a wide range of sizes from one TMH domain to at least 26 TMH domains and diverse structural folds. A common feature of most of these folds is the TM orientation of the helical domains and the approximately parallel packing of these domains into helical bundles of varying stability, however, it has been challenging to study the folding of these proteins experimentally. The contribution of helix stabilization in membrane and interface to the folding energy landscape are investigated here for the full range of TMH protein sizes containing 1 TM domain (1-TMH protein) to 24 TM domains (24-TMH protein) for all TMH proteins with available structures using structural bioinformatics based hydropathy analysis. The TM helix insertion stabilization energies from Water to membrane-water Interface (WAT→INT energies) are on average half of those insertion energies from water to transmembrane orientation (WAT→TM energies) for the whole polytopic helical membrane proteome (1-TMH to 24-TMH proteins). This suggests a potentially dominant role of the membrane-water interface as a viable holding vestibule for the TM helices during their release from the translocon. This provides proteome-level evidence for the broadly applicable four-step thermodynamic framework by White and co-workers as well as a natural extension of Popot and Engelman's original two-stage model of helical MP folding to a three-stage model, where, in the new intermediate stage, the membrane-water interface acts as a holding vestibule for the translated TM helices, reconciling the interface's critical role in MP folding seen in many previous studies. Support for this model is provided by showing the stability of hydrophobic TM helices at the membrane-water interface through several microsecond long molecular dynamics simulations of five hydrophobic helical domains and a helical hairpin pre-folded from the ribosomal exit vestibule. • Structure based hydropathy analysis was carried out for all TM domains of the helical membrane proteome (with structures) spanning 1 TM through 24 TM domains. • The membrane-water interface emerges as an important vestibule stage in the proposed three-stage helical membrane protein folding process. • Six different hydrophobic helical domains are stable at the membrane-water interface during long atomistic MD simulations supporting the vestibule role of the membrane-water interface. [ABSTRACT FROM AUTHOR]

The spread of coronavirus infectious disease (COVID-19) is associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has risked public health more than any other infectious disease. Researchers around the globe use multiple approaches to identify an effective approved drug (drug repurposing) that treats viral infections. Most of the drug repurposing approaches target spike protein or main protease. Here we use transmembrane serine protease 2 (TMPRSS2) as a target that can prevent the virus entry into the cell by interacting with the surface receptors. By hypothesizing that the TMPRSS2 binders may help prevent the virus entry into the cell, we performed a systematic drug screening over the current approved drug database. Furthermore, we screened the Enamine REAL fragments dataset against the TMPRSS2 and presented nine potential drug-like compounds that give us clues about which kinds of groups the pocket prefers to bind, aiding future structure-based drug design for COVID-19. Also, we employ molecular dynamics simulations, binding free energy calculations, and well-tempered metadynamics to validate the obtained candidate drug and fragment list. Our results suggested three potential FDA-approved drugs against human TMPRSS2 as a target. These findings may pave the way for more drugs to be exposed to TMPRSS2, and testing the efficacy of these drugs with biochemical experiments will help improve COVID-19 treatment. [ABSTRACT FROM AUTHOR]

• Staphylococcus lugdunensis , emerged as a consequential human pathogen, contributing to a spectrum of infections including skin and soft tissue infections, endocarditis, and bacteremia. • Abscess formation is a prevalent manifestation of S. lugdunensis infections, showcasing its potential transition from a harmless skin commensal to a potentially fatal pathogen skin to infective endocarditis. • This study focuses on addressing this challenge through the development of a potent Staphylococcus lugdunensis vaccine. • This study underscores the transformative potential of computational approaches in revolutionizing Staphylococcus lugdunensis vaccine development. Staphylococcus lugdunensis has emerged as a significant human pathogen, responsible for a range of infections from skin and soft tissue infections to endocarditis and bacteremia. Notably, abscess formation is a common manifestation, reflecting its potential shift from a benign skin commensal to a serious pathogen, akin to infective endocarditis. With the rising prevalence of antibiotic resistance, there is a pressing need for novel therapeutic strategies. This study addresses this need by exploring the development of an effective S. lugdunensis vaccine. Multiepitope vaccines, which incorporate various antigenic fragments from S. lugdunensis proteins, offer a promising approach to elicit a robust immune response. Computational tools are instrumental in selecting epitopes based on their predicted immunogenicity and non-toxicity. Molecular docking and molecular dynamics (MD) simulations further elucidate the interactions between vaccine constructs and immune system molecules, such as B-cell and T-cell receptors, providing detailed insights into binding affinity, specificity, and stability. This study highlights the potential of integrating multiepitope vaccine design with advanced computational methods to expedite and enhance vaccine development, addressing a critical gap amid escalating antibiotic resistance. [ABSTRACT FROM AUTHOR]

Transmembrane proteins (TMEMs) are integrated membrane proteins that span the entire lipid bilayer and are permanently anchored to it. TMEMs participate in various cellular processes. Some TMEMs usually exist and perform their physiological functions as dimers rather than monomers. TMEM dimerization is associated with various physiological functions, such as the regulation of enzyme activity, signal transduction, and cancer immunotherapy. In this review, we focus on the dimerization of transmembrane proteins in cancer immunotherapy. This review is divided into three parts. First, the structures and functions of several TMEMs related to tumor immunity are introduced. Second, the characteristics and functions of several typical TMEM dimerization processes are analyzed. Finally, the application of the regulation of TMEM dimerization in cancer immunotherapy is introduced.

Mast cells (MCs), hematopoietic cells of the myeloid lineage, are well-known for their pro-inflammatory nature contributing to the development of various allergic and autoimmune diseases. One of the characteristic receptors on MCs, the high-affinity receptor for IgE (FcεRI), is activated in its IgE-bound state via binding and crosslinking by polyvalent antigen. This results in its phosphorylation by the SRC family kinase LYN, initiating differential signaling pathways, eventually triggering immunological effector functions, such as degranulation and cytokine production. Few publications have reported on FcεRI-dependent but antigen-independent MC activation by antibody-mediated crosslinking of membrane molecules (e.g., transmembrane proteins and glycosphingolipids) that are both localized in membrane rafts and in close vicinity to the FcεRI. In this Viewpoint we will briefly introduce FcεRI-mediated MC stimulation, cite examples of FcεRI-proximal molecules, the crosslinking of which can cause FcεRI-dependent MC activation, and discuss the potential of certain viruses as well as auto-antibodies to act as indirect FcεRI-crosslinking agents. In latter cases, antigen-independent FcεRI-mediated pro-inflammatory MC activation could contribute to the development of detrimental cytokine storms. [ABSTRACT FROM AUTHOR]

Establishment of correct synaptic connections is a crucial step during neural circuitry formation. The Teneurin family of neuronal transmembrane proteins promotes cell–cell adhesion via homophilic and heterophilic interactions, and is required for synaptic partner matching in the visual and hippocampal systems in vertebrates. It remains unclear how individual Teneurins form macromolecular cis‐ and trans‐synaptic protein complexes. Here, we present a 2.7 Å cryo‐EM structure of the dimeric ectodomain of human Teneurin4. The structure reveals a compact conformation of the dimer, stabilized by interactions mediated by the C‐rich, YD‐shell, and ABD domains. A 1.5 Å crystal structure of the C‐rich domain shows three conserved calcium binding sites, and thermal unfolding assays and SAXS‐based rigid‐body modeling demonstrate that the compactness and stability of Teneurin4 dimers are calcium‐dependent. Teneurin4 dimers form a more extended conformation in conditions that lack calcium. Cellular assays reveal that the compact cis‐dimer is compatible with homomeric trans‐interactions. Together, these findings support a role for teneurins as a scaffold for macromolecular complex assembly and the establishment of cis‐ and trans‐synaptic interactions to construct functional neuronal circuits. Synopsis: Teneurin‐family transmembrane proteins promoting homo‐ and heterophilic neuronal interactions are important for synaptic partner matching. Here, structural studies of the dimeric human Teneurin4 ectodomain reveal a compact conformation compatible with homomeric trans interactions. 2.7 Å cryo‐EM structure reveals a compact calcium‐stabilized conformation of the Teneurin4 dimer ectodomain.Crystal structure of the C‐rich domain shows three calcium ions coordinated by conserved residues.Teneurin4 can change its conformation in cis from an extended form to a more compact one.The compact Teneurin4 dimer supports homomeric cell‐cell interactions. [ABSTRACT FROM AUTHOR]

Historically, the genetic analysis of mammalian cells entailed the isolation of randomly arising mutant cell lines with altered properties, followed by laborious genetic mapping experiments to identify the mutant gene responsible for the phenotype. In recent years, somatic cell genetics has been revolutionized by functional genomics screens, in which expression of every protein‐coding gene is systematically perturbed, and the phenotype of the perturbed cells is determined. We outline here a novel functional genomics screening strategy that differs fundamentally from commonly used approaches. In this strategy, we express libraries of artificial transmembrane proteins named traptamers and select rare cells with the desired phenotype because, by chance, a traptamer specifically perturbs the expression or activity of a target protein. Active traptamers are then recovered from the selected cells and can be used as tools to dissect the biological process under study. We also briefly describe how we have used this new strategy to provide insights into the complex process by which human papillomaviruses enter cells. [ABSTRACT FROM AUTHOR]

Highly expressed proteins tend to evolve slowly, a trend known as the expression level–rate of evolution (E–R) anticorrelation. Whereas the reasons for this anticorrelation remain unclear, the most influential hypotheses attribute it to highly expressed proteins being subjected to strong selective pressures to avoid misfolding and/or misinteraction. In accordance with these hypotheses, work in our laboratory has recently shown that extracellular (secreted) proteins lack an E–R anticorrelation (or exhibit a weaker than usual E–R anticorrelation). Extracellular proteins are folded inside the endoplasmic reticulum, where enhanced quality control of folding mechanisms exist, and function in the extracellular space, where misinteraction is unlikely to occur or to produce deleterious effects. Transmembrane proteins contain both intracellular domains (which are folded and function in the cytosol) and extracellular domains (which complete their folding in the endoplasmic reticulum and function in the extracellular space). We thus hypothesized that the extracellular domains of transmembrane proteins should exhibit a weaker E–R anticorrelation than their intracellular domains. Our analyses of human, Saccharomyces and Arabidopsis transmembrane proteins allowed us to confirm our hypothesis. Our results are in agreement with models attributing the E–R anticorrelation to the deleterious effects of misfolding and/or misinteraction. [ABSTRACT FROM AUTHOR]

ATP-binding cassette (ABC) transporters perform multiple functions in reproductive tissues. During ovarian tissue vitrification, the plasma membrane has important functions in the influx or efflux of water, and substances such as cryoprotectants and channel proteins that are required in this process. Thus, the present study aimed to verify the relative abundance of mRNA transcript of ABC transporters ABCB1, ABCG2 , and MRP2 after vitrification and in vitro culture (IVC) of ovine ovarian tissue. For this study, the ovarian cortex fragments were proportioned into four groups as fresh control, vitrified control, fresh culture, and vitrified culture groups. After vitrification and in vitro culture, the ovarian tissue was evaluated using morphological procedures. Further, relative abundance of ABCB1, ABCG2 , and MRP2 transporter mRNA transcripts in the ovarian cortex subjected to aforementioned treatment conditions were evaluated using qPCR. Our results showed a negative association between degenerated follicles and mRNA transcript abundances of ABCB1 and ABCG2. In addition, the percentage of growing follicles in the ovine ovarian cortex after vitrification was similar to that of the fresh control tissue without in vitro culture. The in vitro culture of fresh and vitrified tissue however, showed a significant decrease in the percentage of growing follicles. To the best of our knowledge, we believe that our data for the first time has studied the relative abundances of ABCB1 and ABCG2 mRNA transcripts in the ovine ovarian cortex. In addition, alterations of these protein channels may be indicative of a deleterious effect of osmotic stress on follicular survival during vitrification. Furthermore, these effects were detectable only after the IVC of the ovarian tissues. Nonetheless, further studies are required to investigate the functions of ABC transporters in ovine folliculogenesis, especially after in vitro culture of ovarian tissue. • There was a negative association of degenerated follicles with ABCB1 and ABCG2 relative abundances. • A relationship of degenerated follicles with mRNA expression levels. • The addition percentage of growing follicles after vitrification was similar to fresh control. • After in vitro culture of fresh and vitrified tissue, a significant increase in percentage of growing follicles. [ABSTRACT FROM AUTHOR]

Transmembrane (TM) proteins are major drug targets, but their structure determination, a prerequisite for rational drug design, remains challenging. Recently, the DeepMind’s AlphaFold2 machine learning method greatly expanded the structural coverage of sequences with high accuracy. Since the employed algorithm did not take specific properties of TM proteins into account, the reliability of the generated TM structures should be assessed. Therefore, we quantitatively investigated the quality of structures at genome scales, at the level of ABC protein superfamily folds and for specific membrane proteins (e.g. dimer modeling and stability in molecular dynamics simulations). We tested template-free structure prediction with a challenging TM CASP14 target and several TM protein structures published after AlphaFold2 training. Our results suggest that AlphaFold2 performs well in the case of TM proteins and its neural network is not overfitted. We conclude that cautious applications of AlphaFold2 structural models will advance TM protein-associated studies at an unexpected level. [ABSTRACT FROM AUTHOR]

Coarse-grained (CG) modelling with the Martini force field has come of age. By combining a variety of bead types and sizes with a new mapping approach, the newest version of the model is able to accurately simulate large biomolecular complexes at millisecond timescales. In this perspective, we discuss possible applications of the Martini 3 model in drug discovery and development pipelines and highlight areas for future development. Owing to its high simulation efficiency and extended chemical space, Martini 3 has great potential in the area of drug design and delivery. However, several aspects of the model should be improved before Martini 3 CG simulations can be routinely employed in academic and industrial settings. These include the development of automatic parameterisation protocols for a variety of molecule types, the improvement of backmapping procedures, the description of protein flexibility and the development of methodologies enabling efficient sampling. We illustrate our view with examples on key areas where Martini could give important contributions such as drugs targeting membrane proteins, cryptic pockets and protein-protein interactions and the development of soft drug delivery systems. [ABSTRACT FROM AUTHOR]

Alpha-helical proteins ($\alpha$ α TMPs) are essential in various biological processes. Despite their tertiary structures are crucial for revealing complex functions, experimental structure determination remains challenging and costly. In the past decades, various sequence-based topology prediction methods have been developed to bridge the gap between the sequences and structures by characterizing the structural features, but significant improvements are still required. Deep learning brings a great opportunity for its powerful representation learning capability from limited original data. In this work, we improved our $\alpha$ α TMP topology prediction method DMCTOP using deep learning, which composed of two deep convolutional blocks to simultaneously extract local and global contextual features. Consequently, the inputs were simplified to reflect the original features of the sequence, including a protein sequence feature and an evolutionary conservation feature. DMCTOP can efficiently and accurately identify all topological types and the N-terminal orientation for an $\alpha$ α TMP sequence. To validate the effectiveness of our method, we benchmarked DMCTOP against 13 peer methods according to the whole sequence, the transmembrane segment and the traditional criterion in testing experiments. All the results reveal that our method achieved the highest prediction accuracy and outperformed all the previous methods. The method is available at https://icdtools.nenu.edu.cn/dmctop. [ABSTRACT FROM AUTHOR]

Abstract Background This study is motivated by the following three considerations: a) the physico-chemical properties of transmembrane (TM) proteins are distinctly different from those of globular proteins, necessitating the development of specialized structure prediction techniques, b) for many structural features no specialized predictors for TM proteins are available at all, and c) deep learning algorithms allow to automate the feature engineering process and thus facilitate the development of multi-target methods for predicting several protein properties at once. Results We present AllesTM, an integrated tool to predict almost all structural features of transmembrane proteins that can be extracted from atomic coordinate data. It blends several machine learning algorithms: random forests and gradient boosting machines, convolutional neural networks in their original form as well as those enhanced by dilated convolutions and residual connections, and, finally, long short-term memory architectures. AllesTM outperforms other available methods in predicting residue depth in the membrane, flexibility, topology, relative solvent accessibility in its bound state, while in torsion angles, secondary structure and monomer relative solvent accessibility prediction it lags only slightly behind the currently leading technique SPOT-1D. High accuracy on a multitude of prediction targets and easy installation make AllesTM a one-stop shop for many typical problems in the structural bioinformatics of transmembrane proteins. Conclusions In addition to presenting a highly accurate prediction method and eliminating the need to install and maintain many different software tools, we also provide a comprehensive overview of the impact of different machine learning algorithms and parameter choices on the prediction performance. AllesTM is freely available at https://github.com/phngs/allestm .

Epidermal barrier is one is one of the most important structures of the skin, it performs protective function, ensure internal environment constancy by selective ions and molecules transport and by transepidermal water loss regulation. The biochemical basis of the epidermal barrier consists of complex, integrated and balanced molecular processes leading to keratinocytes death due to terminal differentiation and plasma membrane replacement with horny insoluble macromolecular stratum corneum. Filaggrin and tight junctions (TJs) proteins are important structural components of the epidermal barrier. Filaggrin, after hydrolysis, maintains pH level, preserves water, protects the skin from microbial agents. Whereas TJs proteins with active expression regulate epidermis permeability and create the barrier for exterior antigens.

Coarse-grained (CG) modelling with the Martini force field has come of age. By combining a variety of bead types and sizes with a new mapping approach, the newest version of the model is able to accurately simulate large biomolecular complexes at millisecond timescales. In this perspective, we discuss possible applications of the Martini 3 model in drug discovery and development pipelines and highlight areas for future development. Owing to its high simulation efficiency and extended chemical space, Martini 3 has great potential in the area of drug design and delivery. However, several aspects of the model should be improved before Martini 3 CG simulations can be routinely employed in academic and industrial settings. These include the development of automatic parameterisation protocols for a variety of molecule types, the improvement of backmapping procedures, the description of protein flexibility and the development of methodologies enabling efficient sampling. We illustrate our view with examples on key areas where Martini could give important contributions such as drugs targeting membrane proteins, cryptic pockets and protein–protein interactions and the development of soft drug delivery systems.

The major energy-producing reactions of biochemistry occur at biological membranes. Computational protein design now provides the opportunity to elucidate the underlying principles of these processes and to construct bioenergetic pathways on our own terms. Here, we review recent achievements in this endeavour of 'synthetic bioenergetics', with a particular focus on new enabling tools that facilitate the computational design of biocompatible de novo integral membrane proteins. We use recent examples to showcase some of the key computational approaches in current use and highlight that the overall philosophy of 'surface-swapping' - the replacement of solvent-facing residues with amino acids bearing lipid-soluble hydrophobic sidechains - is a promising avenue in membrane protein design. We conclude by highlighting outstanding design challenges and the emerging role of AI in sequence design and structure ideation., (© 2024 The Author(s).)

During coronavirus infection, three non-structural proteins, nsp3, nsp4, and nsp6, are of great importance as they induce the formation of double-membrane vesicles where the replication and transcription of viral gRNA takes place, and the interaction of nsp3 and nsp4 lumenal regions triggers membrane pairing. However, their structural states are not well-understood. We investigated the interactions between nsp3 and nsp4 by predicting the structures of their lumenal regions individually and in complex using AlphaFold2 as implemented in ColabFold. The ColabFold prediction accuracy of the nsp3–nsp4 complex was increased compared to nsp3 alone and nsp4 alone. All cysteine residues in both lumenal regions were modelled to be involved in intramolecular disulphide bonds. A linker region in the nsp4 lumenal region emerged as crucial for the interaction, transitioning to a structured state when predicted in complex. The key interactions modelled between nsp3 and nsp4 appeared stable when the transmembrane regions of nsp3 and nsp4 were added to the modelling either alone or together. While molecular dynamics simulations (MD) demonstrated that the proposed model of the nsp3 lumenal region on its own is not stable, key interactions between nsp and nsp4 in the proposed complex model appeared stable after MD. Together, these observations suggest that the interaction is robust to different modelling conditions. Understanding the functional importance of the nsp4 linker region may have implications for the targeting of double membrane vesicle formation in controlling coronavirus infection.

Measuring the expression levels of membrane proteins (MPs) is crucial for understanding cell differentiation and tissue specificity, defining disease characteristics, identifying biomarkers, and developing therapeutics. While bottom-up proteomics addresses the need for accurately surveying the membrane proteome, the lower abundance and hydrophobic nature of MPs pose challenges in sample preparation. As MPs normally reside in the lipid bilayer, conventional extraction methods rely on detergents, introducing here a paradox - detergents prevent aggregation and facilitate protein processing, but themselves become contaminants that interfere with downstream analytical applications. Various detergent removal methods exist to mitigate this issue, including filter-aided sample preparation, SP3, suspension trapping, and membrane mimetics. This review delves into the fundamentals of each strategy, applications, merits, and limitations, providing insights into their effectiveness in MP research., (© 2024 The Author(s).)

Transmembrane (TM) proteins constitute over 30% of the mammalian proteome and play essential roles in mediating cell-cell communication, synaptic transmission, and plasticity in the central nervous system. Many of these proteins, especially the G protein-coupled receptors (GPCRs), are validated or candidate drug targets for therapeutic development for mental diseases, yet their expression profiles are underrepresented in most global proteomic studies. Herein, we establish a brain TM protein-enriched spectral library based on 136 data-dependent acquisition runs acquired from various brain regions of both naïve mice and mental disease models. This spectral library comprises 3043 TM proteins including 171 GPCRs, 231 ion channels, and 598 transporters. Leveraging this library, we analyzed the data-independent acquisition data from different brain regions of two mouse models exhibiting depression- or anxiety-like behaviors. By integrating multiple informatics workflows and library sources, our study significantly expanded the mental stress-perturbed TM proteome landscape, from which a new GPCR regulator of depression was verified by in vivo pharmacological testing. In summary, we provide a high-quality mouse brain TM protein spectral library to largely increase the TM proteome coverage in specific brain regions, which would catalyze the discovery of new potential drug targets for the treatment of mental disorders., Competing Interests: Conflict of interest The authors declare that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Proteins transporting ions or other molecules across the membrane, whose proper concentration is required to maintain homeostasis, perform very sophisticated biological functions. The symport and antiport active transport can be performed only by the structures specially prepared for this purpose. In the present work, such structures in both In and Out conformations have been analyzed with respect to the hydrophobicity distribution using the FOD-M model. This allowed for identifying the role of individual protein chain fragments in the stabilization of the specific cell membrane environment as well as the contribution of hydrophobic interactions to the conformational changes between In/Out conformations.

Transmembrane proteins participate in various physiological activities in plants, including signal transduction, substance transport, and energy conversion. Although more than 20% of gene products are predicted to be transmembrane proteins in the genome era, due to the complexity of transmembrane domains they are difficult to reliably identify in the predicted protein, and they may have different overall three-dimensional structures. Therefore, it is challenging to study their biological function. In this review, we describe the typical structures of transmembrane proteins and their roles in plant growth, development, and stress responses. We propose a model illustrating the roles of transmembrane proteins during plant growth and response to various stresses, which will provide important references for crop breeding.