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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.

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.

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.

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.

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.

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.

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.

Transmembrane proteins (TMPs) play important roles in cells, ranging from transport processes and cell adhesion to communication. Many of these functions are mediated by intrinsically disordered regions (IDRs), flexible protein segments without a well-defined structure. Although a variety of prediction methods are available for predicting IDRs, their accuracy is very limited on TMPs due to their special physico-chemical properties. We prepared a dataset containing membrane proteins exclusively, using X-ray crystallography data. MemDis is a novel prediction method, utilizing convolutional neural network and long short-term memory networks for predicting disordered regions in TMPs. In addition to attributes commonly used in IDR predictors, we defined several TMP specific features to enhance the accuracy of our method further. MemDis achieved the highest prediction accuracy on TMP-specific dataset among other popular IDR prediction methods.

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

Cells adapt to different stress conditions, such as the antibiotics presence. This adaptation sometimes is achieved by changing relevant protein positions, of which the mutability is limited by structural constrains. Understanding the basis of these constrains represent an important challenge for both basic science and potential biotechnological applications. To study these constraints, we performed a systematic saturation mutagenesis of the transmembrane region of HokC, a toxin used by Escherichia coli to control its own population, and observed that 92% of single-point mutations are tolerated and that all the non-tolerated mutations have compensatory mutations that reverse their effect. We provide experimental evidence that HokC accumulates multiple compensatory mutations that are found as correlated mutations in the HokC family multiple sequence alignment. In agreement with these observations, transmembrane proteins show higher probability to present correlated mutations and are less densely packed locally than globular proteins; previous mutagenesis results on transmembrane proteins further support our observations on the high tolerability to mutations of transmembrane regions of proteins. Thus, our experimental results reveal the HokC transmembrane region high tolerance to loss-of-function mutations that is associated with low sequence conservation and high rate of correlated mutations in the HokC family sequences alignment, which are features shared with other transmembrane proteins.

Nascent HIV-1 particles incorporate the viral envelope glycoprotein and multiple host transmembrane proteins during assembly at the plasma membrane. At least some of these host transmembrane proteins on the surface of virions are reported as pro-viral factors that enhance virus attachment to target cells or facilitate trans-infection of CD4+ T cells via interactions with non-T cells. In addition to the pro-viral factors, anti-viral transmembrane proteins are incorporated into progeny virions. These virion-incorporated transmembrane proteins inhibit HIV-1 entry at the point of attachment and fusion. In infected polarized CD4+ T cells, HIV-1 Gag localizes to a rear-end protrusion known as the uropod. Regardless of cell polarization, Gag colocalizes with and promotes the virion incorporation of a subset of uropod-directed host transmembrane proteins, including CD162, CD43, and CD44. Until recently, the functions of these virion-incorporated proteins had not been clear. Here, we review the recent findings about the roles played by virion-incorporated CD162, CD43, and CD44 in HIV-1 spread to CD4+ T cells.

β-barrel membrane proteins have several important biological functions, including transporting water and solutes across the membrane. They are active in the highly hydrophobic environment of the lipid membrane, as opposed to soluble proteins, which function in a more polar, aqueous environment. Globular soluble proteins typically have a hydrophobic core and a polar surface that interacts favorably with water. In the fuzzy oil drop (FOD) model, this distribution is represented by the 3D Gauss function (3DG). In contrast, membrane proteins expose hydrophobic residues on the surface, and, in the case of ion channels, the polar residues face inwards towards a central pore. The distribution of hydrophobic residues in membrane proteins can be characterized by means of 1–3DG, a complementary 3D Gauss function. Such an analysis was carried out on the transmembrane proteins of bacteria, which, despite the considerable similarities of their super-secondary structure (β-barrel), have highly differentiated properties in terms of stabilization based on hydrophobic interactions. The biological activity and substrate specificity of these proteins are determined by the distribution of the polar and nonpolar amino acids. The present analysis allowed us to compare the ways in which the different proteins interact with antibiotics and helped us understand their relative importance in the development of the resistance mechanism. We showed that beta barrel membrane proteins with a hydrophobic core interact less strongly with the molecules they transport.

Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.

Space travel has always been the man’s ultimate destination. With the ability of spaceflight though, came the realization that exposure to microgravity has lasting effects on the human body. To counteract these, many studies were and are undertaken, on multiple levels. Changes in cell growth, gene, and protein expression have been described in different models on Earth and in space. Extracellular vesicles, and in particular exosomes, are important cell-cell communicators, being secreted from almost all the cells and therefore, are a perfect target to further investigate the underlying reasons of the organism’s adaptations to microgravity. Here, we studied supernatants harvested from the CellBox-1 experiment, which featured human thyroid cancer cells flown to the International Space Station during the SpaceX CRS-3 cargo mission. The initial results show differences in the number of secreted exosomes, as well as in the distribution of subpopulations in regards to their surface protein expression. Notably, alteration of their population regarding the tetraspanin surface expression was observed. This is a promising step into a new area of microgravity research and will potentially lead to the discovery of new biomarkers and pathways of cellular cross-talk.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a novel epidemic strain of Betacoronavirus that is responsible for the current viral pandemic, coronavirus disease 2019 (COVID-19), a global health crisis. Other epidemic Betacoronaviruses include the 2003 SARS-CoV-1 and the 2009 Middle East Respiratory Syndrome Coronavirus (MERS-CoV), the genomes of which, particularly that of SARS-CoV-1, are similar to that of the 2019 SARS-CoV-2. In this extensive review, we document the most recent information on Coronavirus proteins, with emphasis on the membrane proteins in the Coronaviridae family. We include information on their structures, functions, and participation in pathogenesis. While the shared proteins among the different coronaviruses may vary in structure and function, they all seem to be multifunctional, a common theme interconnecting these viruses. Many transmembrane proteins encoded within the SARS-CoV-2 genome play important roles in the infection cycle while others have functions yet to be understood. We compare the various structural and nonstructural proteins within the Coronaviridae family to elucidate potential overlaps and parallels in function, focusing primarily on the transmembrane proteins and their influences on host membrane arrangements, secretory pathways, cellular growth inhibition, cell death and immune responses during the viral replication cycle. We also offer bioinformatic analyses of potential viroporin activities of the membrane proteins and their sequence similarities to the Envelope (E) protein. In the last major part of the review, we discuss complement, stimulation of inflammation, and immune evasion/suppression that leads to CoV-derived severe disease and mortality. The overall pathogenesis and disease progression of CoVs is put into perspective by indicating several stages in the resulting infection process in which both host and antiviral therapies could be targeted to block the viral cycle. Lastly, we discuss the development of adaptive immunity against various structural proteins, indicating specific vulnerable regions in the proteins. We discuss current CoV vaccine development approaches with purified proteins, attenuated viruses and DNA vaccines.

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.

In biological cells, membrane proteins are the most crucial component for the maintenance of cell physiology and processes, including ion transportation, cell signaling, cell adhesion, and recognition of signal molecules. Therefore, researchers have proposed a number of membrane platforms to mimic the biological cell environment for transmembrane protein incorporation. The performance and selectivity of these transmembrane proteins based biomimetic platforms are far superior to those of traditional material platforms, but their lack of stability and scalability rule out their commercial presence. This review highlights the development of transmembrane protein-based biomimetic platforms for four major applications, which are biosensors, molecular interaction studies, energy harvesting, and water purification. We summarize the fundamental principles and recent progress in transmembrane protein biomimetic platforms for each application, discuss their limitations, and present future outlooks for industrial implementation.

Lipid membranes regulate the flow of nutrients and communication signaling between cells and protect the sub-cellular structures. Recent attempts to fabricate artificial systems using nanostructures that mimic the physiological properties of natural lipid bilayer membranes (LBM) fused with transmembrane proteins have helped demonstrate the importance of temperature, pH, ionic strength, adsorption behavior, conformational reorientation and surface density in cellular membranes which all affect the incorporation of proteins on solid surfaces. Much of this work is performed on artificial templates made of polymer sponges or porous materials based on alumina, mica, and porous silicon (PSi) surfaces. For example, porous silicon materials have high biocompatibility, biodegradability, and photoluminescence, which allow them to be used both as a support structure for lipid bilayers or a template to measure the electrochemical functionality of living cells grown over the surface as in vivo. The variety of these media, coupled with the complex physiological conditions present in living systems, warrant a summary and prospectus detailing which artificial systems provide the most promise for different biological conditions. This study summarizes the use of electrochemical impedance spectroscopy (EIS) data on artificial biological membranes that are closely matched with previously published biological systems using both black lipid membrane and patch clamp techniques.

For many viruses, one or two proteins enable cell binding, membrane fusion and entry. The large number of proteins employed by poxviruses is unprecedented and may be related to their ability to infect a wide range of cells. There are two main infectious forms of vaccinia virus, the prototype poxvirus: the mature virion (MV), which has a single membrane, and the extracellular enveloped virion (EV), which has an additional outer membrane that is disrupted prior to fusion. Four viral proteins associated with the MV membrane facilitate attachment by binding to glycosaminoglycans or laminin on the cell surface, whereas EV attachment proteins have not yet been identified. Entry can occur at the plasma membrane or in acidified endosomes following macropinocytosis and involves actin dynamics and cell signaling. Regardless of the pathway or whether the MV or EV mediates infection, fusion is dependent on 11 to 12 non-glycosylated, transmembrane proteins ranging in size from 4- to 43-kDa that are associated in a complex. These proteins are conserved in poxviruses making it likely that a common entry mechanism exists. Biochemical studies support a two-step process in which lipid mixing of viral and cellular membranes is followed by pore expansion and core penetration.

The Eisenberg plot or hydrophobic moment plot methodology is one of the most frequently used methods of bioinformatics. Bioinformatics is more and more recognized as a helpful tool in Life Sciences in general, and recent developments in approaches recognizing lipid binding regions in proteins are promising in this respect. In this study a bioinformatics approach specialized in identifying lipid binding helical regions in proteins was used to obtain an Eisenberg plot. The validity of the Heliquest generated hydrophobic moment plot was checked and exemplified. This study indicates that the Eisenberg plot methodology can be transferred to another hydrophobicity scale and renders a user-friendly approach which can be utilized in routine checks in protein–lipid interaction and in protein and peptide lipid binding characterization studies. A combined approach seems to be advantageous and results in a powerful tool in the search of helical lipid-binding regions in proteins and peptides. The strength and limitations of the Eisenberg plot approach itself are discussed as well. The presented approach not only leads to a better understanding of the nature of the protein–lipid interactions but also provides a user-friendly tool for the search of lipid-binding regions in proteins and peptides.

Many biological cellular processes occur at the micro- or millisecond time scale. With traditional all-atom molecular modeling techniques it is difficult to investigate the dynamics of long time scales or large systems, such as protein aggregation or activation. Coarse graining (CG) can be used to reduce the number of degrees of freedom in such a system, and reduce the computational complexity. In this paper the first version of a coarse grained model for transmembrane proteins is presented. This model differs from other coarse grained protein models due to the introduction of a novel angle potential as well as a hydrogen bonding potential. These new potentials are used to stabilize the backbone. The model has been validated by investigating the adaptation of the hydrophobic mismatch induced by the insertion of WALP-peptides into a lipid membrane, showing that the first step in the adaptation is an increase in the membrane thickness, followed by a tilting of the peptide.

Poxviruses replicate in the cytoplasm, where they acquire multiple lipoprotein membranes. Although a proposal that the initial membrane arises de novo has not been substantiated, there is no accepted explanation for its formation from cellular membranes. A subsequent membrane-wrapping step involving modified trans-Golgi or endosomal cisternae results in a particle with three membranes. These wrapped virions traverse the cytoplasm on microtubules; the outermost membrane is lost during exocytosis, the middle one is lost just prior to cell entry, and the remaining membrane fuses with the cell to allow the virus core to enter the cytoplasm and initiate a new infection.