Binding Of Fragments Research Articles

Drug Discovery in the Age of Artificial Intelligence: Transformative Target-Based Approaches.

The complexities inherent in drug development are multi-faceted and often hamper accuracy, speed and efficiency, thereby limiting success. This review explores how recent developments in machine learning (ML) are significantly impacting target-based drug discovery, particularly in small-molecule approaches. The Simplified Molecular Input Line Entry System (SMILES), which translates a chemical compound's three-dimensional structure into a string of symbols, is now widely used in drug design, mining, and repurposing. Utilizing ML and natural language processing techniques, SMILES has revolutionized lead identification, high-throughput screening and virtual screening. ML models enhance the accuracy of predicting binding affinity and selectivity, reducing the need for extensive experimental screening. Additionally, deep learning, with its strengths in analyzing spatial and sequential data through convolutional neural networks (CNNs) and recurrent neural networks (RNNs), shows promise for virtual screening, target identification, and de novo drug design. Fragment-based approaches also benefit from ML algorithms and techniques like generative adversarial networks (GANs), which predict fragment properties and binding affinities, aiding in hit selection and design optimization. Structure-based drug design, which relies on high-resolution protein structures, leverages ML models for accurate predictions of binding interactions. While challenges such as interpretability and data quality remain, ML's transformative impact accelerates target-based drug discovery, increasing efficiency and innovation. Its potential to deliver new and improved treatments for various diseases is significant.

Mapping Protein Conformational Landscapes from Crystallographic Drug Fragment Screens.

Proteins are dynamic macromolecules. Knowledge of a protein's thermally accessible conformations is critical to determining important transitions and designing therapeutics. Accessible conformations are highly constrained by a protein's structure such that concerted structural changes due to external perturbations likely track intrinsic conformational transitions. These transitions can be thought of as paths through a conformational landscape. Crystallographic drug fragment screens are high-throughput perturbation experiments, in which thousands of crystals of a drug target are soaked with small-molecule drug precursors (fragments) and examined for fragment binding, mapping potential drug binding sites on the target protein. Here, we describe an open-source Python package, COnformational LAndscape Visualization (COLAV), to infer conformational landscapes from such large-scale crystallographic perturbation studies. We apply COLAV to drug fragment screens of two medically important systems: protein tyrosine phosphatase 1B (PTP1B), which regulates insulin signaling, and the SARS CoV-2 Main Protease (MPro). With enough fragment-bound structures, we find that such drug screens enable detailed mapping of proteins' conformational landscapes.

In Vitro Genome-Wide Identification of Transcription Factor Binding Sites.

DNA affinity purification followed by sequencing (DAP-seq) profiles transcription factor (TF) binding sites in vitro, in which recombinant TF captures the genomic fragments with TF binding sites. Here, I describe the preparation of pre-PCR DNA-seq libraries for 96 TFs, including the expression and purification of recombinant TF, the affinity purification of TF binding fragments, and the sequencing-ready library preparation. Using this method, up to 96 DAP-seq libraries can be prepared in 2days.

Aligning fermentation conditions with non-canonical amino acid addition strategy is essential for Nε-((2-azidoethoxy)carbonyl)-L-lysine uptake and incorporation into the target protein

Protein engineering with non-canonical amino acids (ncAAs) holds great promises for diverse applications, however, there are still limitations in the implementation of this technology at manufacturing scale. The know-how to efficiently produce ncAA-incorporated proteins in a scalable manner is still very limited. In the present study, we incorporated the ncAA N6-[(2-azidoethoxy)carbonyl]-L-lysine (Azk) into an antigen binding fragment (Fab) in Escherichia coli. We used the orthogonal pyrrolysyl-tRNA synthetase/suppressor tRNACUAPyl pair from Methanosarcina mazei to incorporate Azk site-specifically. We characterized Azk uptake and Fab production at bench-scale under different fermentation conditions, varying timing and mode of Azk addition, Azk-to-cell ratio and induction time. Our results indicate that Azk uptake is comparatively efficient in the batch phase. We discovered that the time between Azk uptake and inducing its incorporation into the Fab must be kept short, which suggests that intracellular Azk is consumed and/or degraded. The results obtained in this study are an important step towards the development of efficient production methods for Azk-incorporated proteins in E. coli. The developed process is scalable and provides excellent yields of 2.95 mg functionalized Fab per g CDM, which corresponds to 80% of yield obtained with the wild type Fab. We also identified the cellular uptake of Azk being dependent on the physiological state of the cell as a potential bottleneck in production.

Cryo-EM Structure of Phospholipase Cε Defines N-terminal Domains and their Roles in Activity.

Phospholipase Cε (PLCε) increases intracellular Ca 2+ and protein kinase C (PKC) activity in the cardiovascular system in response to stimulation of G protein coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs). The ability of PLCε to respond to these diverse inputs is due, in part, to multiple, conformationally dynamic regulatory domains. However, this heterogeneity has also limited structural studies of the lipase to either individual domains or its catalytic core. Here, we report the 3.9 Å reconstruction of the largest fragment of PLCε to date in complex with an antigen binding fragment (Fab). The structure reveals that PLCε contains a pleckstrin homology (PH) domain and four tandem EF hands, including subfamily-specific insertions and intramolecular interactions with the catalytic core. The structure, together with a model of the holoenzyme, suggest that part of the N-terminus and PH domain form a continuous surface that could engage cytoplasmic leaflets of the plasma and perinuclear membranes, contributing to activity. Functional characterization of this surface confirm it is critical for maximum basal and G protein-stimulated activities. This study provides new insights into the autoinhibited, basal conformation of PLCε and the first mechanistic insights into how it engages cellular membranes for activity.

PDCD4 interacting with PIK3CB and CTSZ promotes the apoptosis of multiple myeloma cells.

The role of programmed cell death 4 (PDCD4) in multiple myeloma (MM) development remains unknown. Here, we investigated its role and action mechanism in MM. Bioinformatic analysis indicated that patients with MM and high PDCD4 expression had higher overall survival than those with low PDCD4 expression. PDCD4 expression promoted MM cell apoptosis and inhibited their viability invitro and tumor growth invivo. RNA-binding protein immunoprecipitation sequencing analysis showed that PDCD4 is bound to the 5' UTR of the apoptosis-related genes PIK3CB, Cathepsin Z (CTSZ), and X-chromosome-linked apoptosis inhibitor (XIAP). PDCD4 knockdown reduced the cell apoptosis rate, which was rescued by adding PIK3CB, CTSZ, or XIAP inhibitors. Dual luciferase reporter assays confirmed the internal ribosome entry site (IRES) activity of the 5' UTRs of PIK3CB and CTSZ. An RNA pull-down assay confirmed binding of the 5' UTR of PIK3CB and CTSZ to PDCD4, identifying the specific binding fragments. PDCD4 is expected to promote MM cell apoptosis by binding to the IRES domain in the 5' UTR of PIK3CB and CTSZ and inhibiting their translation. Our findings suggest that PDCD4 plays an important role in MM development by regulating the expression of PIK3CB, CTSZ, and XIAP, and highlight new potential molecular targets for MM treatment.

Identification of small molecule antagonists of sonic hedgehog/heparin binding with activity in hedgehog functional assays

Sonic hedgehog (Shh) is a morphogen with important roles in embryonic development and in the development of a number of cancers. Its activity is modulated by interactions with binding partners and co-receptors including heparin and heparin sulfate proteoglycans (HSPG). To identify antagonists of Shh/heparin binding, a diverse collection of 34,560 chemicals was screened in single point 384-well format. We identified and confirmed twenty six novel small molecule antagonists with diverse structures including four scaffolds that gave rise to multiple hits. Nineteen of the confirmed hits blocked binding of the N-terminal fragment of Shh (ShhN) to heparin with IC50 values < 50 μM. In the Shh-responsive C3H10T1/2 cell model, four of the compounds demonstrated the ability to block ShhN-induced alkaline phosphatase activity. To demonstrate a direct and selective effect on ShhN ligand mediated activity, two of the compounds were able to block induction of Gli1 mRNA, a primary downstream marker for Shh signaling activity, in Shh-mediated but not Smoothened agonist (SAG)-mediated C3H10T1/2 cells. Direct binding of the two compounds to ShhN was confirmed by thermal shift assay and molecular docking simulations, with both compounds docking with the N-terminal heparin binding domain of Shh. Overall, our findings indicate that small molecule compounds that block ShhN binding to heparin and act to inhibit Shh mediated activity in vitro can be identified. We propose that the interaction between Shh and HSPGs provides a novel target for identifying small molecules that bind Shh, potentially leading to novel tool compounds to probe Shh ligand function.

Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis.

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 μs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

Mapping protein conformational landscapes from crystallographic drug fragment screens.

Proteins are dynamic macromolecules. Knowledge of a protein's thermally accessible conformations is critical to determining important transitions and designing therapeutics. Accessible conformations are highly constrained by a protein's structure such that concerted structural changes due to external perturbations likely track intrinsic conformational transitions. These transitions can be thought of as paths through a conformational landscape. Crystallographic drug fragment screens are high-throughput perturbation experiments, in which thousands of crystals of a drug target are soaked with small-molecule drug precursors (fragments) and examined for fragment binding, mapping potential drug binding sites on the target protein. Here, we describe an open-source Python package, COLAV (COnformational LAndscape Visualization), to infer conformational landscapes from such large-scale crystallographic perturbation studies. We apply COLAV to drug fragment screens of two medically important systems: protein tyrosine phosphatase 1B (PTP-1B), which regulates insulin signaling, and the SARS CoV-2 Main Protease (MPro). With enough fragment-bound structures, we find that such drug screens also enable detailed mapping of proteins' conformational landscapes.

Sensitive Detection of Structural Differences using a Statistical Framework for Comparative Crystallography.

Chemical and conformational changes underlie the functional cycles of proteins. Comparative crystallography can reveal these changes over time, over ligands, and over chemical and physical perturbations in atomic detail. A key difficulty, however, is that the resulting observations must be placed on the same scale by correcting for experimental factors. We recently introduced a Bayesian framework for correcting (scaling) X-ray diffraction data by combining deep learning with statistical priors informed by crystallographic theory. To scale comparative crystallography data, we here combine this framework with a multivariate statistical theory of comparative crystallography. By doing so, we find strong improvements in the detection of protein dynamics, element-specific anomalous signal, and the binding of drug fragments.

Protein-Protein Stabilization in VIVO/8-Hydroxyquinoline-Lysozyme adduct: A Spectroscopic, Crystallographic, and Computational Study.

The binding of the potential drug[VIVO(8-HQ)2], where 8-HQ is 8-hydroxyquinolinato, with hen egg white lysozyme (HEWL) was evaluated through spectroscopic (electron paramagnetic resonance, EPR, and UV-visible), spectrometric (electrospray ionization-mass spectrometry, ESI-MS), crystallographic (X-ray diffraction, XRD), and computational (DFT and docking) studies. ESI-MS indicates the interaction of [VIVO(8-HQ)(H2O)]+ and [VIVO(8-HQ)2(H2O)] species with HEWL. Room temperature EPR spectra suggest both covalent and non-covalent binding of the two different V-containing fragments. XRD analyses confirm these findings, showing that [VIVO(8-HQ)(H2O)]+ interacts covalently with the solvent exposed Asp119, while cis-[VIVO(8-HQ)2(H2O)] non-covalently with Arg128 and Lys96 from a symmetry mate. The covalent binding of [VIVO(8-HQ)(H2O)]+ to Asp119 is favored by a π-π contact with Trp62 and a H-bond with Asn103 of a symmetry-related molecule. Additionally, the covalent binding of VVO2+ to Asp48 and non-covalent binding of other V-containing fragments to Arg5, Cys6, and Glu7 is revealed. Molecular docking indicates that, in the absence of the interactions occurring at the protein-protein interface close to Asp119, the binding to Glu35 or Asp52 should be preferred. Such a protein-protein stabilization could be more common than what believed up today, at least in the solid state, and should be considered in the characterization of metal-protein adducts.

Anthrax Vaccination, Gulf War Illness, and Human Leukocyte Antigen (HLA).

We report on a highly significant, positive association between anthrax vaccination and occurrence of Gulf War Illness (GWI) in 111 Gulf War veterans (42 with GWI and 69 controls). GWI was diagnosed in 47.1% of vaccinated veterans but only in 17.2% of non-vaccinated veterans (Pearson χ2 = 7.08, p = 0.008; odds ratio = 3.947; relative risk = 2.617), with 1.6x higher GWI symptom severity in vaccinated veterans (p = 0.007, F-test in analysis of covariance). Next, we tested the hypothesis that the susceptibility to GWI following anthrax vaccination could be due to inability to make antibodies against the anthrax protective antigen (PA), the key protein contained in the vaccine. Since the first step in initiating antibody production would be the binding of PA peptide fragments (typically 15-amino acid long [15-mer]) to peptide-binding motifs of human leukocyte antigen (HLA) Class II molecules, we assessed the binding-motif affinities of such HLA specific molecules to all linear 15-mer peptide fragments of the anthrax PA. We identified a total of 58 HLA Class II alleles carried by the veterans in our sample and found that, of those, 18 (31%) were present in the vaccinated group that did not develop GWI but were absent from the vaccinated group who developed GWI. Remarkably, in silico analyses revealed very high binding affinities of peptide-binding motifs of those 18 HLA alleles with fragments of anthrax vaccine PA, leading to the successful production of anti-PA antibodies. Conversely, the absence of these protective HLA alleles points to a reduced ability to develop antibodies against PA, thus resulting in harmful PA persistence and development of GWI.

Structural basis for inhibition of coagulation factor VIII reveals a shared antigenic hotspot on the C1 domain

BackgroundHemophilia A arises from dysfunctional or deficient coagulation factor (F)VIII and leads to inefficient fibrin clot formation and uncontrolled bleeding events. The development of antibody inhibitors is a clinical complication in hemophilia A patients receiving FVIII replacement therapy. LE2E9 is an anti-C1 domain inhibitor previously isolated from a mild/moderate hemophilia A patient and disrupts FVIII interactions with von Willebrand factor and FIXa, though the intermolecular contacts that underpin LE2E9-mediated FVIII neutralization are undefined. ObjectivesTo determine the structure of the complex between FVIII and LE2E9 and characterize its mechanism of inhibition. MethodsFVIII was bound to the antigen binding fragment (Fab) of NB2E9, a recombinant construct of LE2E9, and its structure was determined by cryogenic electron microscopy. ResultsThis report communicates the 3.46 Å structure of FVIII bound to NB2E9, with its epitope comprising FVIII residues S2040 to Y2043, K2065 to W2070, and R2150 to H2155. Structural analysis reveals that the LE2E9 epitope overlaps with portions of the epitope for 2A9, a murine-derived inhibitor, suggesting that these residues represent a shared antigenic region on the C1 domain between FVIII−/− mice and hemophilia A patients. Furthermore, the FVIII:NB2E9 structure elucidates the orientation of the LE2E9 glycan, illustrating how the glycan sterically blocks interactions between the FVIII C1 domain and the von Willebrand factor D′ domain. A putative model of the FVIIIa:FIXa complex suggests potential clashing between the NB2E9 glycan and FIXa light chain. ConclusionThese results describe an antigenic “hotspot” on the FVIII C1 domain and provide a structural basis for engineering FVIII replacement therapeutics with reduced antigenicity.

High-confidence placement of low-occupancy fragments into electron density using the anomalous signal of sulfur and halogen atoms.

Fragment-based drug design using X-ray crystallography is a powerful technique to enable the development of new lead compounds, or probe molecules, against biological targets. This study addresses the need to determine fragment binding orientations for low-occupancy fragments with incomplete electron density, an essential step before further development of the molecule. Halogen atoms play multiple roles in drug discovery due to their unique combination of electronegativity, steric effects and hydrophobic properties. Fragments incorporating halogen atoms serve as promising starting points in hit-to-lead development as they often establish halogen bonds with target proteins, potentially enhancing binding affinity and selectivity, as well as counteracting drug resistance. Here, the aim was to unambiguously identify the binding orientations of fragment hits for SARS-CoV-2 nonstructural protein 1 (nsp1) which contain a combination of sulfur and/or chlorine, bromine and iodine substituents. The binding orientations of carefully selected nsp1 analogue hits were focused on by employing their anomalous scattering combined with Pan-Dataset Density Analysis (PanDDA). Anomalous difference Fourier maps derived from the diffraction data collected at both standard and long-wavelength X-rays were compared. The discrepancies observed in the maps of iodine-containing fragments collected at different energies were attributed to site-specific radiation-damage stemming from the strong X-ray absorption of I atoms, which is likely to cause cleavage of the C-I bond. A reliable and effective data-collection strategy to unambiguously determine the binding orientations of low-occupancy fragments containing sulfur and/or halogen atoms while mitigating radiation damage is presented.

In silico analysis of the wild-type and mutant-type of BRCA2 gene

BackgroundThe aim of this study was to conduct an in silico analysis of a novel compound heterozygous variant in breast cancer susceptibility gene 2 (BRCA2) to clarify its structure–function relationship and elucidate the molecular mechanisms underlying triple-negative breast cancer (TNBC).MethodsA tumor biopsy sample was obtained from a 42-year-old Chinese woman during surgery, and a maxBRCA™ test was conducted using the patient’s whole blood. We obtained an experimentally determined 3D structure (1mje.pdb) of the BRCA2 protein from the Protein Data Bank (PDB) as a relatively reliable reference. Subsequently, the wild-type and mutant structures were predicted using SWISS-MODEL and AlphaFold, and the accuracy of these predictions was assessed through the SAVES online server. Furthermore, we utilized a high ambiguity-driven protein–protein docking (HADDOCK) algorithm and protein–ligand interaction profiler (PLIP) to predict the pathogenicity of the mutations and elucidate pathogenic mechanisms that potentially underlies TNBC.ResultsHistological examination revealed that the tumor biopsy sample exhibited classical pathological characteristics of TNBC. Furthermore, the maxBRCA™ test revealed two compound heterozygous BRCA2 gene mutations (c.7670 C > T.pA2557V and c.8356G > A.pA2786T). Through performing in silico structural analyses and constructing of 3D models of the mutants, we established that the mutant amino acids valine and threonine were located in the helical domain and oligonucleotide binding 1 (OB1), regions that interact with DSS1.ConclusionOur analysis revealed that substituting valine and threonine in the helical domain region alters the structure and function of BRCA2 proteins. This mutation potentially affects the binding of proteins and DNA fragments and disrupts interactions between the helical domain region and OB1 with DSS1, potentially leading to the development of TNBC. Our findings suggest that the identified compound heterozygous mutation contributes to the clinical presentation of TNBC, providing new insights into the pathogenesis of TNBC and the influence of compound heterozygous mutations in BRCA2.

Application of an NMR/Crystallography Fragment Screening Platform for the Assessment and Rapid Discovery of New HIV-CA Binding Fragments.

Identification and assessment of novel targets is essential to combat drug resistance in the treatment of HIV/AIDS. HIV Capsid (HIV-CA), the protein playing a major role in both the early and late stages of the viral life cycle, has emerged as an important target. We have applied an NMR fragment screening platform and identified molecules that bind to the N-terminal domain (NTD) of HIV-CA at a site close to the interface with the C-terminal domain (CTD). Using X-ray crystallography, we have been able to obtain crystal structures to identify the binding mode of these compounds. This allowed for rapid progression of the initial, weak binding, fragment starting points to compounds 37 and 38, which have 19F-pKi values of 5.3 and 5.4 respectively.

Enhancing Cellular Uptake of Native Proteins through Bio-Orthogonal Conjugation with Chemically Synthesized Cell-Penetrating Peptides.

The potential for native proteins to serve as a platform for biocompatible, targeted, and personalized therapeutics in the context of genetic and metabolic disorders is vast. Nevertheless, their clinical application encounters challenges, particularly in overcoming biological barriers and addressing the complexities involved in engineering transmembrane permeability. This study is dedicated to the development of a multifunctional nanoentity in which a model therapeutic protein is covalently linked to a cell-penetrating peptide, NickFect 55, with the objective of enhancing its intracellular delivery. Successful binding of the nanoentity fragments was achieved through the utilization of an intein-mediated protein-trans splicing reaction. Our research demonstrates that the fully assembled nanoentity-containing protein was effectively internalized by the cells, underscoring the potential of this approach in overcoming barriers associated with protein-based therapeutics for the treatment of genetic disorders.

Extracting binding energies and binding modes from biomolecular simulations of fragment binding to endothiapepsin.

Fragment-based drug discovery (FBDD) aims to discover a set of small binding fragments that may be subsequently linked together. Therefore, in-depth knowledge of the individual fragments' structural and energetic binding properties is essential. In addition to experimental techniques, the direct simulation of fragment binding by molecular dynamics (MD) simulations became popular to characterize fragment binding. However, former studies showed that long simulation times and high computational demands per fragment are needed, which limits applicability in FBDD. Here, we performed short, unbiased MD simulations of direct fragment binding to endothiapepsin, a well-characterized model system of pepsin-like aspartic proteases. To evaluate the strengths and limitations of short MD simulations for the structural and energetic characterization of fragment binding, we predicted the fragments' absolute free energies and binding poses based on the direct simulations of fragment binding and compared the predictions to experimental data. The predicted absolute free energies are in fair agreement with the experiment. Combining the MD data with binding mode predictions from molecular docking approaches helped to correctly identify the most promising fragments for further chemical optimization. Importantly, all computations and predictions were done within 5 days, suggesting that MD simulations may become a viable tool in FBDD projects.

Combining Cellular Immunization and Phage Display Screening Results in Novel, FcγRI-Specific Antibodies.

Antibodies that specifically bind to individual human fragment crystallizable γ receptors (FcγRs) are of interest as research tools in studying immune cell functions, as well as components in bispecific antibodies for immune cell engagement in cancer therapy. Monoclonal antibodies for human low-affinity FcγRs have been successfully generated by hybridoma technology and are widely used in pre-clinical research. However, the generation of monoclonal antibodies by hybridoma technology that specifically bind to the high-affinity receptor FcγRI is challenging. Monomeric mouse IgG2a, IgG2b, and IgG3 bind human FcγRI with high affinity via the Fc part, leading to an Fc-mediated rather than a fragment for antigen binding (Fab)-mediated selection of monoclonal antibodies. Blocking the Fc-binding site of FcγRI with an excess of human IgG or Fc during screening decreases the risk of Fc-mediated interactions but can also block the potential epitopes of new antibody candidates. Therefore, we replaced hybridoma technology with phage display of a single-chain fragment variable (scFv) antibody library that was generated from mice immunized with FcγRI-positive cells and screened it with a cellular panning approach assisted by next-generation sequencing (NGS). Seven new FcγRI-specific antibody sequences were selected with this methodology, which were produced as Fc-silent antibodies showing FcγRI-restricted specificity.

Chimeric Antigen Receptor (CAR)-T Cell Therapy for Non-Hodgkin's Lymphoma.

This review focuses on the use of chimeric antigen receptor (CAR)-T cell therapy to treat non-Hodgkin's lymphoma (NHL), a classification of heterogeneous malignant neoplasms of the lymphoid tissue. Despite various conventional and multidrug chemotherapies, the poor prognosis for NHL patients remains and has prompted the utilization of groundbreaking personalized therapies such as CAR-T cells. CAR-T cells are T cells engineered to express a CAR that enables T cells to specifically lyse tumor cells with extracellular expression of a tumor antigen of choice. A CAR is composed of an extracellular antibody fragment or target protein binding domain that is conjugated to activating intracellular signaling motifs common to T cells. In general, CAR-T cell therapies for NHL are designed to recognize cellular markers ubiquitously expressed on B cells such as CD19+, CD20+, and CD22+. Clinical trials using CAR-T cells such as ZUMA-7 and TRANSFORM demonstrated promising results compared to standard of care and ultimately led to FDA approval for the treatment of relapsed/refractory NHL. Despite the success of CAR-T therapy for NHL, challenges include adverse side effects as well as extrinsic and intrinsic mechanisms of tumor resistance that lead to suboptimal outcomes. Overall, CAR-T cell therapies have improved clinical outcomes in NHL patients and generated optimism around their future applications.