The Design and Cell-Free Protein Synthesis of a Pembrolizumab Single-Chain Variable Fragment

Eichholz K., Fukazawa Y., Peterson C.W., Haeseleer F., Medina M., Hoffmeister S., Duell D.M., Varco-Merth B.D., Dross S., Park H., Labriola C.S., Axthelm M.K., Murnane R.D., Smedley J.V., Jin L., et. al.

Kim M.S., Prasad V.

The current approval indications for pembrolizumab are complex, reflecting the inclusion criteria of numerous clinical trials that led to approvals. Here we argue that allowing the use of pembrolizumab to any advanced solid tumor in any tumor type in any line of therapy for a fixed duration may be preferable to the current assortment of indications. The aggregate response rate in landmark clinical trials for approved indications of pembrolizumab is low and even lower in real-world populations. Due to heterogeneity of response to checkpoint inhibitors and limited predictive biomarkers, there are subsets of patients without approved indications for pembrolizumab that may have response to checkpoint inhibitors. The current regulatory framework of numerous overlapping clinical trials leading to complex approval indications is redundant and inefficient. We conclude that giving pembrolizumab in any metastatic solid tumor in any setting may lead to better outcomes with minimal increase in cost. Randomized clinical trials should focus more on optimal duration of treatment based on tumor type and initial response to checkpoint inhibitors.

Hart J.R., Liu X., Pan C., Liang A., Ueno L., Xu Y., Quezada A., Zou X., Yang S., Zhou Q., Schoonooghe S., Hassanzadeh-Ghassabeh G., Xia T., Shui W., Yang D., et. al.

Nanobodies and chemical cross-linking were used to gain information on the identity and positions of flexible domains of PI3Kα. The application of chemical cross-linking mass spectrometry (CXMS) facilitated the identification of the p85 domains BH, cSH2, and SH3 as well as their docking positions on the PI3Kα catalytic core. Binding of individual nanobodies to PI3Kα induced activation or inhibition of enzyme activity and caused conformational changes that could be correlated with enzyme function. Binding of nanobody Nb3-126 to the BH domain of p85α substantially improved resolution for parts of the PI3Kα complex, and binding of nanobody Nb3-159 induced a conformation of PI3Kα that is distinct from known PI3Kα structures. The analysis of CXMS data also provided mechanistic insights into the molecular underpinning of the flexibility of PI3Kα.

Moreno C., Haynie C., Johnson A., Weber K.S.

For nearly three decades, chimeric antigen receptors (CARs) have captivated the interest of researchers seeking to find novel immunotherapies to treat cancer. CARs were first designed to work with T cells, and the first CAR T cell therapy was approved to treat B cell lymphoma in 2017. Recent advancements in CAR technology have led to the development of modified CARs, including multi-specific CARs and logic gated CARs. Other immune cell types, including natural killer (NK) cells and macrophages, have also been engineered to express CARs to treat cancer. Additionally, CAR technology has been adapted in novel approaches to treating autoimmune disease and other conditions and diseases. In this article, we review these recent advancements in alternative CAR therapies and design, as well as their mechanisms of action, challenges in application, and potential future directions.

Guo H., Perminov A., Bekele S., Kedziora G., Farajollahi S., Varaljay V., Hinkle K., Molinero V., Meister K., Hung C., Dennis P., Kelley-Loughnane N., Berry R.

AlphaFold 2 (AF2) has placed Molecular Biology in a new era where we can visualize, analyze and interpret the structures and functions of all proteins solely from their primary sequences. We performed AF2 structure predictions for various protein systems, including globular proteins, a multi-domain protein, an intrinsically disordered protein (IDP), a randomized protein, two larger proteins (> 1000 AA), a heterodimer and a homodimer protein complex. Our results show that along with the three dimensional (3D) structures, AF2 also decodes protein sequences into residue flexibilities via both the predicted local distance difference test (pLDDT) scores of the models, and the predicted aligned error (PAE) maps. We show that PAE maps from AF2 are correlated with the distance variation (DV) matrices from molecular dynamics (MD) simulations, which reveals that the PAE maps can predict the dynamical nature of protein residues. Here, we introduce the AF2-scores, which are simply derived from pLDDT scores and are in the range of [0, 1]. We found that for most protein models, including large proteins and protein complexes, the AF2-scores are highly correlated with the root mean square fluctuations (RMSF) calculated from MD simulations. However, for an IDP and a randomized protein, the AF2-scores do not correlate with the RMSF from MD, especially for the IDP. Our results indicate that the protein structures predicted by AF2 also convey information of the residue flexibility, i.e., protein dynamics.

Harrasser M., Gohil S.H., Lau H., Della Peruta M., Muczynski V., Patel D., Miranda E., Grigoriadis K., Grigoriadis A., Granger D., Evans R., Nathwani A.C.

Chimeric antigen receptor (CAR)-T cells can induce powerful immune responses in patients with hematological malignancies but have had limited success against solid tumors. This is in part due to the immunosuppressive tumor microenvironment (TME) which limits the activity of tumor-infiltrating lymphocytes (TILs) including CAR-T cells. We have developed a next-generation armored CAR (F i-CAR) targeting receptor tyrosine kinase-like orphan receptor 1 (ROR1), which is expressed at high levels in a range of aggressive tumors including poorly prognostic triple-negative breast cancer (TNBC). The F i-CAR-T is designed to release an anti-PD-1 checkpoint inhibitor upon CAR-T cell activation within the TME, facilitating activation of CAR-T cells and TILs while limiting toxicity. To bolster potency, we developed a F i-CAR construct capable of IL-2-mediated, NFAT-induced secretion of anti-PD-1 single-chain variable fragments (scFv) within the tumor microenvironment, following ROR1-mediated activation. Cytotoxic responses against TNBC cell lines as well as levels and binding functionality of released payload were analyzed in vitro by ELISA and flow cytometry. In vivo assessment of potency of F i-CAR-T cells was performed in a TNBC NSG mouse model. F i-CAR-T cells released measurable levels of anti-PD-1 payload with 5 h of binding to ROR1 on tumor and enhanced the cytotoxic effects at challenging 1:10 E:T ratios. Treatment of established PDL1 + TNBC xenograft model with F i-CAR-T cells resulted in significant abrogation in tumor growth and improved survival of mice (71 days), compared to non-armored CAR cells targeting ROR1 (F CAR-T) alone (49 days) or in combination with systemically administered anti-PD-1 antibody (57 days). Crucially, a threefold increase in tumor-infiltrating T cells was observed with F i-CAR-T cells and was associated with increased expression of genes related to cytotoxicity, migration and proliferation. Our next-generation of ROR1-targeting inducible armored CAR platform enables the release of an immune stimulating payload only in the presence of target tumor cells, enhancing the therapeutic activity of the CAR-T cells. This technology provided a significant survival advantage in TNBC xenograft models. This coupled with its potential safety attributes merits further clinical evaluation of this approach in TNBC patients.

Mirdita M., Schütze K., Moriwaki Y., Heo L., Ovchinnikov S., Steinegger M.

AbstractColabFold offers accelerated prediction of protein structures and complexes by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold’s 40−60-fold faster search and optimized model utilization enables prediction of close to 1,000 structures per day on a server with one graphics processing unit. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding. ColabFold is open-source software available at https://github.com/sokrypton/ColabFold and its novel environmental databases are available at https://colabfold.mmseqs.com.

Wheeler R.J.

AbstractAlphaFold2 and RoseTTAfold represent a transformative advance for predicting protein structure. They are able to make very high-quality predictions given a high-quality alignment of the protein sequence with related proteins. These predictions are now readily available via the AlphaFold database of predicted structures and AlphaFold/RoseTTAfold Colaboratory notebooks for custom predictions. However, predictions for some species tend to be lower confidence than model organisms. This includes Trypanosoma cruzi and Leishmania infantum: important unicellular eukaryotic human parasites in an early-branching eukaryotic lineage. The cause appears to be due to poor sampling of this branch of life in the protein sequences databases used for the AlphaFold database and ColabFold. Here, by comprehensively gathering openly available protein sequence data for species from this lineage, significant improvements to AlphaFold2 protein structure prediction over the AlphaFold database and ColabFold are demonstrated. This is made available as an easy-to-use tool for the parasitology community in the form of Colaboratory notebooks for generating multiple sequence alignments and AlphaFold2 predictions of protein structure for Trypanosoma, Leishmania and related species.

Soltani M., Hunt J.P., Bundy B.C.

Human body fluids contain biomarkers which are used extensively for prognostication, diagnosis, monitoring, and evaluation of different treatments for a variety of diseases and disorders. The application of biosensors based on cell-free protein synthesis (CFPS) offers numerous advantages including on-demand and at-home use for fast, accurate detection of a variety of biomarkers in human fluids at an affordable price. However, current CFPS-based biosensors use commercial RNase inhibitors to inhibit different RNases present in human fluids and this reagent is approximately 90% of the expense of these biosensors. Here the flexible nature of Escherichia coli-lysate-based CFPS was used for the first time to produce murine RNase Inhibitor (m-RI) and to optimize its soluble and active production by tuning reaction temperature, reaction time, reduced potential, and addition of GroEL/ES folding chaperons. Furthermore, RNase inhibition activity of m-RI with the highest activity and stability was determined against increasing amounts of three human fluids of serum, saliva, and urine (0%-100% v/v) in lyophilized CFPS reactions. To further demonstrate the utility of the CFPS-produced m-RI, a lyophilized saliva-based glutamine biosensor was demonstrated to effectively work with saliva samples. Overall, the use of CFPS-produced m-RI reduces the total reagent costs of CFPS-based biosensors used in human body fluids approximately 90%.

Jumper J., Evans R., Pritzel A., Green T., Figurnov M., Ronneberger O., Tunyasuvunakool K., Bates R., Žídek A., Potapenko A., Bridgland A., Meyer C., Kohl S.A., Ballard A.J., Cowie A., et. al.

AbstractProteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1–4, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences6,7. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’8—has been an important open research problem for more than 50 years9. Despite recent progress10–14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

Stukalov A., Girault V., Grass V., Karayel O., Bergant V., Urban C., Haas D.A., Huang Y., Oubraham L., Wang A., Hamad M.S., Piras A., Hansen F.M., Tanzer M.C., Paron I., et. al.

The emergence and global spread of SARS-CoV-2 has resulted in the urgent need for an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology1–10. Integration of such datasets to obtain a holistic view of virus–host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. Here we report a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactomes of both viruses, as well as their influence on the transcriptome, proteome, ubiquitinome and phosphoproteome of a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon infection with SARS-CoV-2 and SARS-CoV at different levels and enabled identification of distinct and common molecular mechanisms of these closely related coronaviruses. The TGF-β pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy was specifically dysregulated by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org ) highlights many hotspots that could be targeted by existing drugs and may be used to guide rational design of virus- and host-directed therapies, which we exemplify by identifying inhibitors of kinases and matrix metalloproteases with potent antiviral effects against SARS-CoV-2. Multi-omics profiling of effects of SARS-CoV-2 and SARS-CoV on A549, a lung-derived human cell line, produces a dataset enabling identification of common and virus-specific mechanisms of infection.

Urquhart L.

Smith A.K., Soltani M., Wilkerson J.W., Timmerman B.D., Zhao E.L., Bundy B.C., Knotts T.A.

PEGylated and surface-tethered proteins are used in a variety of biotechnological applications, but traditional methods offer little control over the placement of the functionalization sites on the protein. Fortunately, recent experimental methods functionalize the protein at any location on the amino acid sequence, so the question becomes one of selecting the site that will result in the best protein function. This work shows how molecular simulation can be used to screen potential attachment sites for surface tethering or PEGylation. Previous simulation work has shown promise in this regard for a model protein, but these studies are limited to screening only a few of the surface-accessible sites or only considered surface tethering or PEGylation separately rather than their combined effects. This work is done to overcome these limitations by screening all surface-accessible functionalization sites on a protein of industrial and therapeutic importance (TEM-1) and to evaluate the effects of tethering and PEGylation simultaneously in an effort to create a more accurate screen. The results show that functionalization site effectiveness appears to be a function of super-secondary and tertiary structures rather than the primary structure, as is often currently assumed. Moreover, sites in the middle of secondary structure elements, and not only those in loops regions, are shown to be good options for functionalization—a fact not appreciated in current practice. Taken as a whole, the results show how rigorous molecular simulation can be done to identify candidate amino acids for functionalization on a protein to facilitate the rational design of protein devices.

Davis Z., Felices M., Lenvik T., Badal S., Walker J.T., Hinderlie P., Riley J.L., Vallera D.A., Blazar B.R., Miller J.S.

Abstract Expression of programmed cell death protein 1 (PD-1) on natural killer (NK) cells has been difficult to analyze on human NK cells. By testing commercial clones and novel anti-PD-1 reagents, we found expression of functional PD-1 on resting human NK cells in healthy individuals and reconstituting NK cells early after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Peripheral blood samples from healthy individuals and transplant recipients were stained for PD-1 expression using the commercial anti-PD-1 clone PD1.3.1.3, fluorescein isothiocyanate (FITC)–labeled pembrolizumab, or an FITC-labeled single-chain variable fragment (scFv) reagent made from pembrolizumab. These reagents identified low yet consistent basal PD-1 expression on resting NK cells, a finding verified by finding lower PD-1 transcripts in sorted NK cells compared with those in resting or activated T cells. An increase in PD-1 expression was identified on paired resting NK cells after allo-HSCT. Blockade of PD-1 on resting NK cells from healthy donors with pembrolizumab did not enhance NK function against programmed death-ligand 1 (PD-L1)–expressing tumor lines, but blocking with its scFv derivative resulted in a twofold increase in NK cell degranulation and up to a fourfold increase in cytokine production. In support of this mechanism, PD-L1 overexpression of K562 targets suppressed NK cell function. Interleukin-15 (IL-15) activity was potent and could not be further enhanced by PD-1 blockade. A similar increase in function was observed with scFv PD-1 blockade on resting blood NK cells after allo-HSCT. We identify the functional importance of the PD-1/PD-L1 axis on human NK cells in which blockade or activation to overcome inhibition will enhance NK cell–mediated antitumor control.

Deering R.W., Whalen K.E., Alvarez I., Daffinee K., Beganovic M., LaPlante K.L., Kishore S., Zhao S., Cezairliyan B., Yu S., Rosario M., Mincer T.J., Rowley D.C.

The emergence of multi-drug resistant pathogenic bacteria represents a serious and growing threat to national healthcare systems. Most pressing is an immediate need for the development of novel antibacterial agents to treat Gram-negative multi-drug resistant infections, including the opportunistic, hospital-derived pathogen, Acinetobacter baumannii. Herein we report a naturally occurring 1,2-benzisoxazole with minimum inhibitory concentrations as low as 6.25 μg ml−1 against clinical strains of multi-drug resistant A. baumannii and investigate its possible mechanisms of action. This molecule represents a new chemotype for antibacterial agents against A. baumannii and is easily accessed in two steps via de novo synthesis. In vitro testing of structural analogs suggest that the natural compound may already be optimized for activity against this pathogen. Our results demonstrate that supplementation of 4-hydroxybenzoate in minimal media was able to reverse 1,2-benzisoxazole’s antibacterial effects in A. baumannii. A search of metabolic pathways involving 4-hydroxybenzoate coupled with molecular modeling studies implicates two enzymes, chorismate pyruvate-lyase and 4-hydroxybenzoate octaprenyltransferase, as promising leads for the target of 3,6-dihydroxy-1,2-benzisoxazole.

Caschera F.