ArticleACS chemical neuroscience2021
Systematic Structure-Based Virtual Screening Approach to Antibody Selection and Design of a Humanized Antibody against Multiple Addictive Opioids without Affecting Treatment Agents Naloxone and Naltrexone.
Article in ACS chemical neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 4 citations in OpenAlex.
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5 authors at 1 institution in 1 country.
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Abstract
Opioid drug use, especially heroin, is known as a growing national crisis in America. Heroin itself is a prodrug and is converted to the most active metabolite 6-monoacetylmorphine (6-MAM) responsible for the acute toxicity of heroin and then to a relatively less-active metabolite morphine responsible for the long-term toxicity of heroin. Monoclonal antibodies (mAbs) are recognized as a potentially promising therapeutic approach in the treatment of opioid use disorders (OUDs). Due to the intrinsic challenges of discovering an mAb against multiple ligands, here we describe a general, systematic structure-based virtual screening and design approach which has been used to identify a known anti-morphine antibody 9B1 and a humanized antibody h9B1 capable of binding to multiple addictive opioids (including 6-MAM, morphine, heroin, and hydrocodone) without significant binding with currently available OUD treatment agents naloxone, naltrexone, and buprenorphine. The humanized antibody may serve as a promising candidate for the treatment of OUDs. The experimental binding affinities reasonably correlate with the computationally predicted binding free energies. The experimental activity data strongly support the computational predictions, suggesting that the systematic structure-based virtual screening and humanization design protocol is reliable. The general, systematic structure-based virtual screening and design approach will be useful for many other antibody selection and design efforts in the future.
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