Computational Drug Repositioning for Ischemic Stroke: Neuroprotective Drug Discovery

Li, Yunong; Yang, Jingbo; Zhang, Yan; Meng, Qingkang; Bender, Andreas; Chen, Xiujie

doi:10.4155/fmc-2021-0022

Cited by 4 publications

(1 citation statement)

References 29 publications

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“…CCR5 inhibitors were also considered to be potentially repurposed for stroke recovery [8] . Li et al has utilized the computational drug repositioning approach for IS and identified 252 drugs with potential neuroprotective effects [9] . Moreover, as a peroxisome proliferator-activated receptor gamma and cannabinoid receptor type 2 dual agonist, VCE-004.8 has shown the possibility of repurposing its use as a delayed treatment option for IS [10] .…”

Section: Introductionmentioning

confidence: 99%

Network-based drug repurposing for potential stroke therapy

Wu¹,

Chen²,

Liu³

et al. 2023

Computational and Structural Biotechnology Journal

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Section: Introductionmentioning

confidence: 99%

Network-based drug repurposing for potential stroke therapy

Wu¹,

Chen²,

Liu³

et al. 2023

Computational and Structural Biotechnology Journal

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Synergy between machine learning and natural products cheminformatics: Application to the lead discovery of anthraquinone derivatives

et al. 2022

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Cheminformatics utilizing machine learning (ML) techniques have opened up a new horizon in drug discovery. This is owing to vast chemical space expansion with rocketing numbers of expected hits and lead compounds that match druggable macromolecular targets, in particular from natural compounds. Due to the natural products' (NP) structural complexity, uniqueness, and diversity, they could occupy a bigger space in pharmaceuticals, allowing the industry to pursue more selective leads in the nanomolar range of binding affinity. ML is an essential part of each step of the drug design pipeline, such as target prediction, compound library preparation, and lead optimization. Notably, molecular mechanic and dynamic simulations, induced docking, and free energy perturbations are essential in predicting best binding poses, binding free energy values, and molecular mechanics force fields. Those applications have leveraged from artificial intelligence (AI), which decreases the computational costs required for such costly simulations. This review aimed to describe chemical space and compound libraries related to NPs. High-throughput screening utilized for fractionating NPs and high-throughput virtual screening and their strategies, and significance, are reviewed. Particular emphasis was given to AI approaches, ML tools, algorithms, and techniques, especially in drug discovery of macrocyclic compounds and approaches in computer-aided and ML-based drug discovery. Anthraquinone derivatives were discussed as a source of new lead compounds that can be developed using ML tools for diverse medicinal uses such as cancer, infectious diseases, and metabolic disorders. Furthermore, the power of principal component analysis in understanding relevant protein conformations, and molecular modeling of protein-ligand interaction were also presented. Apart from being a concise reference for cheminformatics, this review is a useful text to understand the application of ML-based algorithms to molecular dynamics simulation and in silico absorption, distribution, metabolism, excretion, and toxicity prediction.

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The Efficacy of Needle-Warming Moxibustion Combined with Hyperbaric Oxygen Therapy for Ischemic Stroke and Its Effect on Neurological Function

Zhu

Chen

et al. 2022

Computational and Mathematical Methods in Medicine

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Objective. To elucidate the therapeutic efficacy of needle-warming moxibustion (NWM) combined with hyperbaric oxygen therapy (HBOT) in the treatment of patients with ischemic stroke and its effect on neurological function. Methods. One hundred patients with ischemic stroke admitted to the Xuzhou Medical University Affiliated Hospital of Lianyungang from January 2019 to July 2021 were enrolled. Among them, 45 patients treated with NWM were set as the control group, and the rest 55 patients treated by NWM combined with HBOT were included in the research group. The curative effect, neurological deficit score, activity of daily living (ADL), balance ability, and the levels of serum proinflammatory factors in both groups were observed and recorded. Of them, the neurological deficit of patients was evaluated by the National Institutes of Health Stroke Scale (NHISS), the ADL ability was determined by the Barthel index score, and the balance ability was assessed by the Berg balance scale. Results. The total effective rate of the research group was higher than that of the control group. Better ADL and balance ability and milder neurologic impairment were determined in the research group compared with the control group. After treatment, the secretion levels of proinflammatory factors such as C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and interleukin-8 (IL-8) in the serum of patients in the research group were statistically lower than those before treatment and the control group. Conclusions. NWM combined with HBOT is effective in the treatment of patients with ischemic stroke, which can not only improve patients’ neurological function, ADL, and balance ability but also inhibit serum inflammatory reactions.

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Computational Drug Repositioning for Ischemic Stroke: Neuroprotective Drug Discovery

Cited by 4 publications

References 29 publications

Network-based drug repurposing for potential stroke therapy

Network-based drug repurposing for potential stroke therapy

Synergy between machine learning and natural products cheminformatics: Application to the lead discovery of anthraquinone derivatives

The Efficacy of Needle-Warming Moxibustion Combined with Hyperbaric Oxygen Therapy for Ischemic Stroke and Its Effect on Neurological Function

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