Publications by authors named "Uche A K Chude-Okonkwo"

This dataset demonstrates the use of computational fragmentation-based and machine learning-aided drug discovery to generate new lead molecules for the treatment of hypertension. Specifically, the focus is on agents targeting the renin-angiotensin-aldosterone system (RAAS), commonly classified as Angiotensin-Converting Enzyme Inhibitors (ACEIs) and Angiotensin II Receptor Blockers (ARBs). The preliminary dataset was a target-specific, user-generated fragment library of 63 molecular fragments of the 26 approved ACEI and ARB molecules obtained from the ChEMBL and DrugBank molecular databases.

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In this paper, we present a model of the bio-cyber interface for the Internet of Bio-Nano Things application. The proposed model is inspired by the gains of integrating the Clustered Regularly Interspace Short Palindromic Repeats (CRISPR) technology with the Graphene-Field effect transistor (GFET). The capabilities of the integrated system are harnessed to detect nucleic acids transcribed by another component of the bio-cyber interface, a bioreporter, on being exposed to the signalling molecule of interest.

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Targeted drug delivery (TDD) modality promises a smart localization of appropriate dose of therapeutic drugs to the targeted part of the body at reduced system toxicity. To achieve the desired goals of TDD, accurate analysis of the system is important. Recent advances in molecular communication (MC) present prospects to analyzing the TDD process using engineering concepts and tools.

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Targeted drug delivery (TDD) for disease therapy using liposomes as nanocarriers has received extensive attention in the literature. The liposome's ability to incorporate capabilities such as long circulation, stimuli responsiveness, and targeting characteristics, makes it a versatile nanocarrier. Timely drug release at the targeted site requires that trigger stimuli such as pH, light, and enzymes be uniquely overexpressed at the targeted site.

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Synopsis of recent research by authors named "Uche A K Chude-Okonkwo"

  • - Uche A K Chude-Okonkwo's research primarily focuses on the intersection of computational drug design, molecular communication, and bio-cyber interfaces, particularly in the context of hypertension treatment and targeted drug delivery methodologies.
  • - His recent work includes developing a dataset aimed at generating novel small molecules targeting the renin-angiotensin-aldosterone system, enhancing the efficiency of drug discovery through machine learning and computational fragment-based approaches.
  • - Additionally, he explores innovative applications of CRISPR technology integrated with graphene transistors for real-time monitoring in therapeutic processes, alongside an information-theoretic framework to analyze molecular signaling in targeted drug delivery systems.