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      An anti-ANGPTL3/8 antibody decreases circulating triglycerides by binding to a LPL-inhibitory leucine zipper-like motif

      research-article
      , , , , , , , , , , , , , , , ,
      Journal of Lipid Research
      American Society for Biochemistry and Molecular Biology
      lipoprotein lipase (LPL), triglycerides (TG), angiopoietin-like protein (ANGPTL), apolipoprotein (Apo), hydrogen-deuterium exchange mass spectrometry (HDXMS), leucine zipper, nano-imaging, molecular modeling, epitopes, transmission electron microscopy (TEM), ApoA5, apolipoprotein A5, CCD, coiled coil domain, EL, endothelial lipase, FLD, fibrinogen-like domain, HDXMS, hydrogen-deuterium exchange mass spectrometry, PL, phospholipid, TEM, transmission electron microscopy

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          Abstract

          Triglycerides (TG) are required for fatty acid transport and storage and are essential for human health. Angiopoietin-like-protein 8 (ANGPTL8) has previously been shown to form a complex with ANGPTL3 that increases circulating TG by potently inhibiting LPL. We also recently showed that the TG-lowering apolipoprotein A5 (ApoA5) decreases TG levels by suppressing ANGPTL3/8-mediated LPL inhibition. To understand how LPL binds ANGPTL3/8 and ApoA5 blocks this interaction, we used hydrogen-deuterium exchange mass-spectrometry and molecular modeling to map binding sites of LPL and ApoA5 on ANGPTL3/8. Remarkably, we found that LPL and ApoA5 both bound a unique ANGPTL3/8 epitope consisting of N-terminal regions of ANGPTL3 and ANGPTL8 that are unmasked upon formation of the ANGPTL3/8 complex. We further used ANGPTL3/8 as an immunogen to develop an antibody targeting this same epitope. After refocusing on antibodies that bound ANGPTL3/8, as opposed to ANGPTL3 or ANGPTL8 alone, we utilized bio-layer interferometry to select an antibody exhibiting high-affinity binding to the desired epitope. We revealed an ANGPTL3/8 leucine zipper-like motif within the anti-ANGPTL3/8 epitope, the LPL-inhibitory region, and the ApoA5-interacting region, suggesting the mechanism by which ApoA5 lowers TG is via competition with LPL for the same ANGPTL3/8-binding site. Supporting this hypothesis, we demonstrate that the anti-ANGPTL3/8 antibody potently blocked ANGPTL3/8-mediated LPL inhibition in vitro and dramatically lowered TG levels in vivo. Together, these data show that an anti-ANGPTL3/8 antibody targeting the same leucine zipper-containing epitope recognized by LPL and ApoA5 markedly decreases TG by suppressing ANGPTL3/8-mediated LPL inhibition.

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          Highly accurate protein structure prediction with AlphaFold

          Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 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 years 9 . Despite recent progress 10 – 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. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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            Accurate prediction of protein structures and interactions using a 3-track neural network

            DeepMind presented remarkably accurate predictions at the recent CASP14 protein structure prediction assessment conference. We explored network architectures incorporating related ideas and obtained the best performance with a 3-track network in which information at the 1D sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The 3-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short circuiting traditional approaches which require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.
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              Adaptive linear step-up procedures that control the false discovery rate

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                Author and article information

                Contributors
                Journal
                J Lipid Res
                J Lipid Res
                Journal of Lipid Research
                American Society for Biochemistry and Molecular Biology
                0022-2275
                1539-7262
                17 March 2022
                May 2022
                17 March 2022
                : 63
                : 5
                : 100198
                Affiliations
                [1]Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
                Author notes
                []For correspondence: Robert J. Konrad konrad_robert@ 123456lilly.com
                [‡]

                These authors contributed equally to this work.

                Article
                S0022-2275(22)00031-1 100198
                10.1016/j.jlr.2022.100198
                9036128
                35307397
                74067da3-bb05-4d5d-a344-175fc8a315fc
                © 2022 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 3 September 2021
                : 24 February 2022
                Categories
                Research Article

                Biochemistry
                lipoprotein lipase (lpl),triglycerides (tg),angiopoietin-like protein (angptl),apolipoprotein (apo),hydrogen-deuterium exchange mass spectrometry (hdxms),leucine zipper,nano-imaging,molecular modeling,epitopes,transmission electron microscopy (tem),apoa5, apolipoprotein a5,ccd, coiled coil domain,el, endothelial lipase,fld, fibrinogen-like domain,hdxms, hydrogen-deuterium exchange mass spectrometry,pl, phospholipid,tem, transmission electron microscopy

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