Structures of drug-specific monoclonal antibodies bound to opioids and nicotine reveal a common mode of binding

Rodarte, Justas; Baehr, Carly; Hicks, Dustin; Liban, Tyler L.; Weidle, C.; Rupert, Peter B.; Jahan, Rajwana; Wall, Abigail; McGuire, Andrew T.; Strong, Roland K.; Runyon, Scott P.; Pravetoni, Marco; Pancera, Marie

doi:10.1016/j.str.2022.11.008

Cited by 10 publications

(2 citation statements)

References 42 publications

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“…Notably, additional crystal structures of fentanyl-bound mAbs were published during this article’s revision process. 61 The crystals reveal important differences related to the residues involved in ligand binding, the overall topology of the antibody-ligand interaction (we observe an approximately 180° inversion in docking mode relative to the published models), and the conformational changes involved in ligand binding (identified through the combination of the crystallography and ITC-based thermodynamics). We hypothesize that this conformational change that “traps” the fentanyl is key to high affinity and subsequent protection.…”

Section: Discussionmentioning

confidence: 77%

A trypanosome-derived immunotherapeutics platform elicits potent high-affinity antibodies, negating the effects of the synthetic opioid fentanyl

Triller¹,

Vlachou²,

Hashemi³

et al. 2023

Cell Reports

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Section: Discussionmentioning

confidence: 77%

A trypanosome-derived immunotherapeutics platform elicits potent high-affinity antibodies, negating the effects of the synthetic opioid fentanyl

Triller¹,

Vlachou²,

Hashemi³

et al. 2023

Cell Reports

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“…Additionally, some high-affinity drugs have functional groups branching from the center N that may clash with CDR H2 in the bound C10-S66K structure, but the binding observed in Table 1 suggests that CDR H2 should be able to adopt different conformations to accommodate them (Figure 4). In contrast, other published antibodies like HY6-F9, 24 FenAb609, 12 and FenAb208 12 have binding pockets that interact with unique functional groups of fentanyl, making them unlikely to bind to fentanyl analogs. Therefore, C10-S66K represents a promising candidate for antibody therapeutics that recognize fentanyl, carfentanil, and related drugs that share the core phenylethyl and piperidinyl group.…”

mentioning

confidence: 99%

An Engineered Human-Antibody Fragment with Fentanyl Pan-Specificity That Reverses Carfentanil-Induced Respiratory Depression

Eubanks

Pholcharee

Oyen

et al. 2023

ACS Chem. Neurosci.

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The opioid overdose crisis primarily driven by potent synthetic opioids resulted in more than 500,000 deaths in the US over the last 20 years. Though naloxone, a short-acting medication, remains the primary treatment option for temporarily reversing opioid overdose effects, alternative countermeasures are needed. Monoclonal antibodies present a versatile therapeutic opportunity that can be tailored to synthetic opioids and help prevent post-treatment renarcotization. The ultrapotent analog carfentanil is especially concerning due to its unique pharmacological properties. With this in mind, we generated a fully human antibody through a drug-specific B cell sorting strategy with a combination of carfentanil and fentanyl probes. The resulting panspecific antibody was further optimized through scFv phage display, producing C10-S66K. This monoclonal antibody displays high affinity to carfentanil, fentanyl, and other analogs and reversed carfentanil-induced respiratory depression. Additionally, X-ray crystal structures with carfentanil and fentanyl bound provided structural insight into key drug:antibody interactions.

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Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle‐Decorated Carbon Nanotube‐Based Field‐Effect Transistor Sensors

Shao,

Sorescu,

Liu

et al. 2024

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The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid‐related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug‐testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)‐decorated single‐walled carbon nanotube (SWCNT)‐based field‐effect transistors (FETs) are utilized for machine learning‐assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave‐one‐out cross‐validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au‐SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au‐SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL−1.

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Structures of drug-specific monoclonal antibodies bound to opioids and nicotine reveal a common mode of binding

Cited by 10 publications

References 42 publications

A trypanosome-derived immunotherapeutics platform elicits potent high-affinity antibodies, negating the effects of the synthetic opioid fentanyl

A trypanosome-derived immunotherapeutics platform elicits potent high-affinity antibodies, negating the effects of the synthetic opioid fentanyl

An Engineered Human-Antibody Fragment with Fentanyl Pan-Specificity That Reverses Carfentanil-Induced Respiratory Depression

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle‐Decorated Carbon Nanotube‐Based Field‐Effect Transistor Sensors

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