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With dengue virus (DENV) becoming endemic in tropical and subtropical regions worldwide, there is a pressing global demand for effective strategies to control the mosquitoes that spread this disease. Recent advances in genetic engineering technologies have made it possible to create mosquitoes with reduced vector competence, limiting their ability to acquire and transmit pathogens. Here we describe the development of Aedes aegypti mosquitoes synthetically engineered to impede vector competence to DENV. These mosquitoes express a gene encoding an engineered single-chain variable fragment derived from a broadly neutralizing DENV human monoclonal antibody and have significantly reduced viral infection, dissemination, and transmission rates for all four major antigenically distinct DENV serotypes. Importantly, this is the first engineered approach that targets all DENV serotypes, which is crucial for effective disease suppression. These results provide a compelling route for developing effective genetic-based DENV control strategies, which could be extended to curtail other arboviruses.
Cytochrome P450 enzymes (P450s) are broadly distributed among living organisms and play crucial roles in natural product biosynthesis, degradation of xenobiotics, steroid biosynthesis, and drug metabolism. P450s are considered as the most versatile biocatalysts in nature because of the vast variety of substrate structures and the types of reactions they catalyze. In particular, P450s can catalyze regio- and stereoselective oxidations of nonactivated C-H bonds in complex organic molecules under mild conditions, making P450s useful biocatalysts in the production of commodity pharmaceuticals, fine or bulk chemicals, bioremediation agents, flavors, and fragrances. Major efforts have been made in engineering improved P450 systems that overcome the inherent limitations of the native enzymes. In this review, we focus on recent progress of different strategies, including protein engineering, redox-partner engineering, substrate engineering, electron source engineering, and P450-mediated metabolic engineering, in efforts to more efficiently produce pharmaceuticals and other chemicals. We also discuss future opportunities for engineering and applications of the P450 systems.
© 2020 Li et al.
Membrane proteins are prone to misfolding and degradation within the cell, yet the nature of the conformational defects involved in this process remain poorly understood. The earliest stages of membrane protein folding are mediated by the Sec61 translocon, a molecular machine that facilitates the lateral partitioning of the polypeptide into the membrane. Proper membrane integration is an essential prerequisite for folding of the nascent chain. However, the marginal energetic drivers of this reaction suggest the translocon may operate with modest fidelity. In this work, we employed biophysical modeling in conjunction with quantitative biochemical measurements in order to evaluate the extent to which cotranslational folding defects influence membrane protein homeostasis. Protein engineering was employed to selectively perturb the topological energetics of human rhodopsin, and the expression and cellular trafficking of engineered variants were quantitatively compared. Our results reveal clear relationships between topological energetics and the efficiency of rhodopsin biogenesis, which appears to be limited by the propensity of a polar transmembrane domain to achieve its correct topological orientation. Though the polarity of this segment is functionally constrained, we find that its topology can be stabilized in a manner that enhances biogenesis without compromising the functional properties of rhodopsin. Furthermore, sequence alignments reveal this topological instability has been conserved throughout the course of evolution. These results suggest that topological defects significantly contribute to the inefficiency of membrane protein folding in the cell. Additionally, our findings suggest that the marginal stability of rhodopsin may represent an evolved trait.
Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies.
Artificial transcription factors (ATFs) are precision-tailored molecules designed to bind DNA and regulate transcription in a preprogrammed manner. Libraries of ATFs enable the high-throughput screening of gene networks that trigger cell fate decisions or phenotypic changes. We developed a genome-scale library of ATFs that display an engineered interaction domain (ID) to enable cooperative assembly and synergistic gene expression at targeted sites. We used this ATF library to screen for key regulators of the pluripotency network and discovered three combinations of ATFs capable of inducing pluripotency without exogenous expression of Oct4 (POU domain, class 5, TF 1). Cognate site identification, global transcriptional profiling, and identification of ATF binding sites reveal that the ATFs do not directly target Oct4; instead, they target distinct nodes that converge to stimulate the endogenous pluripotency network. This forward genetic approach enables cell type conversions without a priori knowledge of potential key regulators and reveals unanticipated gene network dynamics that drive cell fate choices.
Structure-based design of vaccines, particularly the iterative optimization used so successfully in the structure-based design of drugs, has been a long-sought goal. We previously developed a first-generation vaccine antigen called DS-Cav1, comprising a prefusion-stabilized form of the fusion (F) glycoprotein, which elicits high-titer protective responses against respiratory syncytial virus (RSV) in mice and macaques. Here we report the improvement of DS-Cav1 through iterative cycles of structure-based design that significantly increased the titer of RSV-protective responses. The resultant second-generation 'DS2'-stabilized immunogens have their F subunits genetically linked, their fusion peptides deleted and their interprotomer movements stabilized by an additional disulfide bond. These DS2 immunogens are promising vaccine candidates with superior attributes, such as their lack of a requirement for furin cleavage and their increased antigenic stability against heat inactivation. The iterative structure-based improvement described here may have utility in the optimization of other vaccine antigens.
Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD) paradigm. Multi-specificity design (MSD), on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON). The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain) an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.
Cytotoxic therapeutic monoclonal antibodies (mAbs) often mediate target cell-killing by eliciting immune effector functions via Fc region interactions with cellular and humoral components of the immune system. Key functions include antibody-dependent cell-mediated cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and complement-dependent cytotoxicity (CDC). However, there has been increased appreciation that along with cell-killing functions, the induction of antibody-dependent cytokine release (ADCR) can also influence disease microenvironments and therapeutic outcomes. Historically, most Fc engineering approaches have been aimed toward modulating ADCC, ADCP, or CDC. In the present study, we describe an Fc engineering approach that, while not resulting in impaired ADCC or ADCP, profoundly affects ADCR. As such, when peripheral blood mononuclear cells are used as effector cells against mAb-opsonized tumor cells, the described mAb variants elicit a similar profile and quantity of cytokines as IgG1. In contrast, although the variants elicit similar levels of tumor cell-killing as IgG1 with macrophage effector cells, the variants do not elicit macrophage-mediated ADCR against mAb-opsonized tumor cells. This study demonstrates that Fc engineering approaches can be employed to uncouple macrophage-mediated phagocytic and subsequent cell-killing functions from cytokine release.
Traditional pharmacology is defined as the science that deals with drugs and their actions. While small molecule drugs have clear advantages, there are many cases where they have proved to be ineffective, prone to unacceptable side effects, or where due to a particular disease aetiology they cannot possibly be effective. A dominant feature of the small molecule drugs is their single mindedness: they provide either continuous inhibition or continuous activation of the target. Because of that, these drugs tend to engage compensatory mechanisms leading to drug tolerance, drug resistance or, in some cases, sensitization and consequent loss of therapeutic efficacy over time and/or unwanted side effects. Here we discuss new and emerging therapeutic tools and approaches that have potential for treating the majority of disorders for which small molecules are either failing or cannot be developed. These new tools include biologics, such as recombinant hormones and antibodies, as well as approaches involving gene transfer (gene therapy and genome editing) and the introduction of specially designed self-replicating cells. It is clear that no single method is going to be a 'silver bullet', but collectively, these novel approaches hold promise for curing practically every disorder.
© 2015 The British Pharmacological Society.
The 24th Antibody Engineering & Therapeutics meeting brought together a broad range of participants who were updated on the latest advances in antibody research and development. Organized by IBC Life Sciences, the gathering is the annual meeting of The Antibody Society, which serves as the scientific sponsor. Preconference workshops on 3D modeling and delineation of clonal lineages were featured, and the conference included sessions on a wide variety of topics relevant to researchers, including systems biology; antibody deep sequencing and repertoires; the effects of antibody gene variation and usage on antibody response; directed evolution; knowledge-based design; antibodies in a complex environment; polyreactive antibodies and polyspecificity; the interface between antibody therapy and cellular immunity in cancer; antibodies in cardiometabolic medicine; antibody pharmacokinetics, distribution and off-target toxicity; optimizing antibody formats for immunotherapy; polyclonals, oligoclonals and bispecifics; antibody discovery platforms; and antibody-drug conjugates.