Publications by authors named "Xinting Li"

Library screening and selection methods can determine the binding activities of individual members of large protein libraries given a physical link between protein and nucleotide sequence, which enables identification of functional molecules by DNA sequencing. However, the solution properties of individual protein molecules cannot be probed using such approaches because they are completely altered by DNA attachment. Mass spectrometry enables parallel evaluation of protein properties amenable to physical fractionation such as solubility and oligomeric state, but current approaches are limited to libraries of 1,000 or fewer proteins.

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Ferroptosis is a type of iron-dependent programmed cell death characterized by a depletion of glutathione. Although generally less harmful to normal cells, in tumor cells, the high demand for iron ions provides conditions conducive to ferroptosis. In this review, we provide an overview of recent progress in research on the regulation of ferroptosis in tumor cells, summarizing and assessing the current state, trends, and applications of nanomaterials in the regulation of ferroptosis in tumor cells.

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Submerged macrophytes in constructed wetlands (CWs) can effectively improve wastewater quality. However, the effectiveness of different submerged macrophytes in removing antibiotic-resistant genes (ARGs) from wastewater remains unexplored. Additionally, wastewater loading in wetlands can fluctuate due to climate change, potentially affecting ARG removal efficiency.

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The proto-oncogene Ras which governs diverse intracellular pathways has four major isoforms (KRAS4A, KRAS4B, HRAS, and NRAS) with substantial sequence homology and similar biochemistry. There is considerable interest in investigating the roles of these independently as their association with different cancers vary, but there are few Ras isoform-specific binding reagents as the only significant sequence differences are in their disordered and highly charged C-termini which have been difficult to elicit antibodies against. To overcome this limitation, we use deep learning-based methods to design Ras isoform-specific binders (RIBs) for all major Ras isoforms that specifically target the Ras C-terminus.

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The development of therapies and vaccines targeting integral membrane proteins has been complicated by their extensive hydrophobic surfaces, which can make production and structural characterization difficult. Here we describe a general deep learning-based design approach for solubilizing native membrane proteins while preserving their sequence, fold, and function using genetically encoded protein WRAPs (Water-soluble RFdiffused Amphipathic Proteins) that surround the lipid-interacting hydrophobic surfaces, rendering them stable and water-soluble without the need for detergents. We design WRAPs for both beta-barrel outer membrane and helical multi-pass transmembrane proteins, and show that the solubilized proteins retain the binding and enzymatic functions of the native targets with enhanced stability.

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Structural colors find wide applications for color printing, intelligent display, filtering imaging, etc., owing to their benefits, including high resolution, stable properties, and dynamic tunability. This review first illustrates the mechanisms of structural color generation, such as surface plasmon resonances, localized surface plasmon resonances, Fabry-Perot resonances, Mie resonances, etc.

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Osteoarthritis (OA), a prevalent joint disorder, can lead to disability, with no effective treatment available. Interleukin-1 (IL-1) plays a crucial role in the progression of OA, and its receptor antagonist (IL-1Ra), a natural IL-1 inhibitor, represents a promising therapeutic target by obstructing the IL-1 signaling pathway. This study delivered IL-1Ra via adeno-associated virus (AAV), a gene therapy vector enabling long-term protein expression, to treat knee osteoarthritis (KOA) in animal models.

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Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging unsolved problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign tasks, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers.

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Sophisticated multispectral detectors have made single-band camouflage materials ineffective, consequently leading to significant advancements in metasurfaces that possess both infrared (IR), radar, and visible stealth capabilities. However, the mutual constraints of stealth principles across different bands and the demand for environment-adaptive camouflage raise challenges to existing multispectral compatible stealth solutions. Here a multifunctional-hierarchical flexible metasurface (MHFM) including an infrared suppression layer (IRSL), three microwave absorbing layers (MAL), an environmental adaptation layer (EAL), and a total reflective sheet (TRS), was designed to simultaneously achieve IR, radar, and dynamic visible stealth.

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Indigenous rangers play a critical role in achieving global biodiversity goals by facilitating effective conservation and community development. However, there is limited knowledge about rangers' livelihoods and responses to conservation policies. This study examined indigenous rangers' perceptions of livelihood impacts and attitudes toward national park management in Three-River-Source National Park (TRSNP).

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Protein denoising diffusion probabilistic models are used for the de novo generation of protein backbones but are limited in their ability to guide generation of proteins with sequence-specific attributes and functional properties. To overcome this limitation, we developed ProteinGenerator (PG), a sequence space diffusion model based on RoseTTAFold that simultaneously generates protein sequences and structures. Beginning from a noised sequence representation, PG generates sequence and structure pairs by iterative denoising, guided by desired sequence and structural protein attributes.

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Background: Respiratory cancer is the leading cause of cancer-related deaths worldwide, but its statistics vary between the East and West. This study aimed to estimate the burdens of tracheal, bronchus, and lung (TBL) cancer and larynx cancer and their attributable risks from 1990 to 2019 in Asia, and at regional and national levels.

Methods: This research evaluated the incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) for respiratory tract cancers using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 database.

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Major Histocompatibility Complex Class II Deficiency is a rare primary immunodeficiency disease with autosomal recessive inheritance. It is characterized by the absence of Major Histocompatibility Complex Class II molecules on the surface of immune cells. In this article, we will present a four-month-old baby girl who presented with recurrent fever and progressive exacerbation of respiratory symptoms since a month ago.

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Francis Crick's global parameterization of coiled coil geometry has been widely useful for guiding design of new protein structures and functions. However, design guided by similar global parameterization of beta barrel structures has been less successful, likely due to the deviations from ideal barrel geometry required to maintain inter-strand hydrogen bonding without introducing backbone strain. Instead, beta barrels have been designed using 2D structural blueprints; while this approach has successfully generated new fluorescent proteins, transmembrane nanopores, and other structures, it requires expert knowledge and provides only indirect control over the global shape.

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Intrinsically disordered proteins and peptides play key roles in biology, but the lack of defined structures and the high variability in sequence and conformational preferences has made targeting such systems challenging. We describe a general approach for designing proteins that bind intrinsically disordered protein regions in diverse extended conformations with side chains fitting into complementary binding pockets. We used the approach to design binders for 39 highly diverse unstructured targets and obtain designs with pM to 100 nM affinities in 34 cases, testing ∼22 designs per target (including polar targets).

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Article Synopsis
  • - We developed a method to create small proteins that can bind strongly to specific molecules, using advanced deep learning techniques to design their shapes based on repeating structural units.
  • - We test these designs by docking various small molecules into the optimal binding sites and then experimentally validate which designs have the highest binding affinity.
  • - Our successful designs include binders for diverse molecules like methotrexate and thyroxine, and we also used our designs to create systems for chemical dimerization and sensitive nanopore sensors that reassemble when a molecule is added.
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Article Synopsis
  • Integrin α5β1 plays a key role in how cells attach and move, making it important for development and healing, with its binding proteins being useful in regenerative medicine.* -
  • Researchers developed custom proteins called NeoNectins that specifically target and stabilize the active form of α5β1, leading to improved cell attachment and spread in lab tests.* -
  • When used on titanium surfaces and in 3D hydrogels, NeoNectins showed better results compared to traditional options in boosting tissue integration and bone growth in animal studies, highlighting their potential in biomedicine.*
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Chemoresistance is one of the major hindrances to many cancer therapies, including esophageal squamous cell carcinoma (ESCC). Ferroptosis, a new programmed cell death, plays an essential role in chemoresistance. IQ-domain GTPase activating protein 1 (IQGAP1) is a scaffold protein and functions as an oncogene in various human malignancies.

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In natural proteins, structured loops have central roles in molecular recognition, signal transduction and enzyme catalysis. However, because of the intrinsic flexibility and irregularity of loop regions, organizing multiple structured loops at protein functional sites has been very difficult to achieve by de novo protein design. Here we describe a solution to this problem that designs tandem repeat proteins with structured loops (9-14 residues) buttressed by extensive hydrogen bonding interactions.

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Limited knowledge exists regarding gasoline and diesel exhaust effects on lipid metabolism. This study collected gasoline and diesel exhaust under actual driving conditions and conducted inhalation exposure on male young and middle-aged C57BL/6J mice for 4 h/day for 5 days to simulate commuting exposure intensity. Additionally, PM from actual roadways, representing gasoline and diesel vehicles, was generated for exposure to human umbilical vein endothelial cells (HUVECs) and normal liver cells (LO2) for 24, 48, and 72 h to further investigate exhaust particle toxicity.

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Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations.

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Segments of proteins with high β-strand propensity can self-associate to form amyloid fibrils implicated in many diseases. We describe a general approach to bind such segments in β-strand and β-hairpin conformations using de novo designed scaffolds that contain deep peptide-binding clefts. The designs bind their cognate peptides in vitro with nanomolar affinities.

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Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids and DNA bases with an atomic representation of all other groups to model assemblies that contain proteins, nucleic acids, small molecules, metals, and covalent modifications, given their sequences and chemical structures. By fine-tuning on denoising tasks, we developed RFdiffusion All-Atom (RFdiffusionAA), which builds protein structures around small molecules.

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