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A comparison of traditional de novo drug discovery and development versus drug repurposing. The translation gap (“valley of death”) describes the problem of translation of basic scientific findings in a laboratory setting into human applications and potential treatments (Butler, 2008; Gamo et al., 2017). Drug repurposing reduces this gap and thus the time, risk, and investment associated with the development of new therapies.
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Rationally designed multi-target drugs (also termed multimodal drugs, network therapeutics, or designed multiple ligands) have emerged as an attractive drug discovery paradigm in the last 10–20 years, as potential therapeutic solutions for diseases of complex etiology and diseases with significant drug-resistance problems. Such agents that modulate...
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... Targeted approaches involve imaging specific drug molecules or targets, while untargeted approaches analyze a wide range of molecules to discover drug metabolites, effects on endogenous molecules, and disease-related changes. These imaging techniques also unveil anatomical, structural, metabolomic, lipidomic, and proteomic alterations in response to drug treatments at tissue and organ levels, advancing drug design and delivery [94][95][96]. ...
This article delves into the intersection of generative AI and digital twins within drug discovery, exploring their synergistic potential to revolutionize pharmaceutical research and development. Through various instances and examples, we illuminate how generative AI algorithms, capable of simulating vast chemical spaces and predicting molecular properties, are increasingly integrated with digital twins of biological systems to expedite drug discovery. By harnessing the power of computational models and machine learning, researchers can design novel compounds tailored to specific targets, optimize drug candidates, and simulate their behavior within virtual biological environments. This paradigm shift offers unprecedented opportunities for accelerating drug development, reducing costs, and, ultimately, improving patient outcomes. As we navigate this rapidly evolving landscape, collaboration between interdisciplinary teams and continued innovation will be paramount in realizing the promise of generative AI and digital twins in advancing drug discovery.
... Initially, drug development focused on single targets to identify and address key molecules or pathways. While successful in some cases, the limitations of this approach became clear, especially for complex diseases [20][21][22][23]. Advances in genomics and high-throughput technologies have led to a better understanding of diseases at the genetic and molecular levels. ...
Alzheimer’s disease (AD) remains a significant challenge in the field of neurodegenerative disorders, even nearly a century after its discovery, due to the elusive nature of its causes. The development of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system’s role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, opening new possibilities for treatment. Despite these advancements, conventional therapies for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, underscoring the need for innovative solutions. This necessity has led to the incorporation advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.
... In addition, the so-called multi-target drugs, also known as multimodal, network, or multiple ligand therapy, deserve attention, the reason being that they are indicated as solutions for diseases that have complex etiologies and that are resistant to conventional treatments, as is the case of epilepsy. Such agents can modulate several targets simultaneously, resulting in improved efficacy and increased safety when compared to drugs and associations that target only a single target [9]. ...
Epilepsy is a neurological disease with no defined cause, characterized by recurrent epilep- tic seizures. These occur due to the dysregulation of excitatory and inhibitory neurotransmitters in the central nervous system (CNS). Psychopharmaceuticals have undesirable side effects; many patients require more than one pharmacotherapy to control crises. With this in mind, this work emphasizes the discovery of new substances from natural products that can combat epileptic seizures. Using in silico techniques, this review aims to evaluate the antiepileptic and multi-target activity of phenylpropanoid derivatives. Initially, ligand-based virtual screening models (LBVS) were performed with 468 phe- nylpropanoid compounds to predict biological activities. The LBVS were developed for the targets al- pha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), voltage-gated calcium channel T- type (CaV), gamma-aminobutyric acid A (GABAA), gamma-aminobutyric acid transporter type 1 (GAT-1), voltage-gated potassium channel of the Q family (KCNQ), voltage-gated sodium channel (NaV), and N-methyl D-aspartate (NMDA). The compounds that had good results in the LBVS were analyzed for the absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and later, the best molecules were evaluated in the molecular docking consensus. The TR430 com- pound showed the best results in pharmacokinetic parameters; its oral absorption was 99.03%, it did not violate any Lipinski rule, it showed good bioavailability, and no cytotoxicity was observed either from the molecule or from the metabolites in the evaluated parameters. TR430 was able to bind with GABAA (activation) and AMPA (inhibition) targets and demonstrated good binding energy and sig- nificant interactions with both targets. The studied compound showed to be a promising molecule with a possible multi-target activity in both fundamental pharmacological targets for the treatment of epi- lepsy.
... It acts as voltage-stimulated sodium channels, stable the presynaptic neuronal membranes and blocking the release of pre-synaptic aspartate and glutamate. 8 LTG was found to show the tolerance of extended release as compared to tolerance of immediate release from the pain. The most known side effects are diplopia, dizziness, ataxia and nausea and somnolence and rash. ...
Background: Anti-depressant are used to treat various disorders like neuropathic pain, migraine etc. Anticonvulsant drugs may have a role in the modulation of changes include inhibition of voltage gated ion channels at sites of spinal, supraspinal and peripheral. Objectives: An experimental observational study was carried out to find the role of anti-nociceptive outcomes of anticonvulsant/antidepressant medicines in the management of formalin induced pain in group of mice. Methods: A total of 20 albino mice weighed 20-30 gm. were taken from animal dwelling of The University of Lahore. Formalin induced pain was judged by observing the lifting of paw and behavior. Animals were divided in 4 groups (five mice in each group) group no 1: Control, group no 2: Paracetamol, group no 3: Fluvoxamine, group no 4: Lamotrigine. After given the doses of drugs, 5.0 % formalin solution was injected. Number of counts of licking paw and paw-lifting of mice during first phase and second phase was noted. Percentage effectiveness was calculated by the formula. The palliative action of the medicine was evaluated by calculating the latency moment in reaction to stimulus of heat. The animals were positioned on hot plate at time interval zero min, 30 min, 60 min and 90 min subsequent the administration of medicine. The Latency time until animal began either jumping or licking was noted. Percentage of maximum possible effects (MPE) is calculated by formula. Conclusion: Our study shows the anti-nociceptive outcomes of fluvoxamine & lamotrigine in the management of formalin induced pain in group of mice
... Targeted approaches involve imaging specific drug molecules or targets, while untargeted approaches analyze a wide range of molecules to discover drug metabolites, effects on endogenous molecules, and disease-related changes. These imaging techniques also unveil anatomical, structural, metabolomic, lipidomic, and proteomic alterations in response to drug treatments at tissue and organ levels, advancing drug design and delivery [94][95][96]. ...
This article delves into the intersection of generative AI and digital twins within drug discovery, exploring their synergistic potential to revolutionize pharmaceutical research and development. Through various instances and examples, we illuminate how generative AI algorithms, capable of simulating vast chemical spaces and predicting molecular properties, are increasingly integrated with digital twins of biological systems to expedite drug discovery. By harnessing the power of computational models and machine learning, researchers can design novel compounds tailored to specific targets, optimize drug candidates, and simulate their behavior within virtual biological environments. This paradigm shift offers unprecedented opportunities for accelerating drug development, reducing costs, and, ultimately, improving patient outcomes. As we navigate this rapidly evolving landscape, collaboration between interdisciplinary teams and continued innovation will be paramount in realizing the promise of generative AI and digital twins in advancing drug discovery.
... Of note, recent review conducted by Löscher highlighted that in addition to its modulation of the GABAergic system, ivermectin possesses multiple other modes of action [18]. However, the use of combinatorial and multitarget pharmacological therapy, together with the investigation of synergistic combinations of repurposed pharmaceuticals, may prove to be a more successful strategy in avoiding epilepsy [19]. Nevertheless, it is still uncertain whether ivermectin can confer protective effects against SE, and the specific pharmacological mechanisms underlying any potential protective effects remain unclear. ...
Status epilepticus (SE) is a critical medical emergency marked by persistent or rapidly repeating seizures, posing a threat to life. Using the lithium-pilocarpine-induced SE model, we decide to evaluate the anti-seizure effects of ivermectin as a positive allosteric modulator of GABAA receptor and the underlying mechanisms involved. Lithium chloride was injected intraperitoneally at a dose of 127 mg/kg, followed by the administration of pilocarpine at a dose of 60 mg/kg after a 20-h interval in order to induce SE. Subsequently, the rats received varying amounts of ivermectin (0.3, 1, 3, 5, and 10 mg/kg, i.p.) 30 min before the onset of SE. To study the underlying molecular mechanisms, we had pharmacological interventions of diazepam (1 mg/kg), glibenclamide and nicorandil as ATP-sensitive potassium channel blocker and opener (both 1 mg/kg, i.p.), naltrexone and morphine, as opioid receptor antagonist and agonist (1 mg/kg and 0.5 mg/kg, i.p., respectively). In addition, three nitric oxide inhibitors, namely, L-NAME (10 mg/kg, i.p.), 7-NI (30 mg/kg, i.p.), and aminoguanidine (100 mg/kg, i.p.), were administered to the rats in the experiment. Finally, we use ELISA and western blotting, respectively, to examine the amounts of pro-inflammatory cytokines (TNF-α and IL-1β), nitrite, and GABAA receptors in the rat hippocampal tissue. The study found that ivermectin, at doses of 3, 5, and 10 mg/kg, exerts anti-seizure effects and decrease Racine’s scale SE score. Interestingly glibenclamide and naltrexone reduced the anti-seizure effects of ivermectin, and from other hand diazepam, nicorandil, morphine, L-NAME, 7-NI, and aminoguanidine, enhance the effects when co-administrated with subeffective dose of ivermectin. Additionally, the study found that ivermectin decreased the elevated levels of TNF-α and IL-1β following SE, while increased the reduced expression of GABAA receptors. Overall, these findings suggest that ivermectin has anti-seizure effects in a SE seizure which may be mediated by the modulation of GABAergic, opioidergic, and nitrergic pathways and KATP channels.
... Initially, drug development focused on single targets to identify and address key molecules or pathways. While successful in some cases, the limitations of this approach became clear, especially for complex diseases [20][21][22][23]. Advances in genomics and high-throughput technologies have led to a better understanding of diseases at the genetic and molecular levels. ...
Alzheimer's disease (AD) remains a significant challenge in the field of neurodegenerative disor-ders, even nearly a century after its discovery, due to the elusive nature of its causes. The develop-ment of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system's role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, open-ing new possibilities for treatment. Despite these advancements, conventional treatments for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, under-scoring the need for innovative solutions. This necessity has led to the incorporating of advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.
... Networks not only improve the therapeutic efficacy of drugs while predicting unwanted side effects but also provide a broader choice of disease targets, which revolutionizes the definition and treatment of diseases. With an increased understanding of the underlying therapeutic mechanisms of approved drugs on the market, it is demonstrated that many drugs with definite efficacy do not act on only one target, but frequently on multiple targets, such as anti-epileptic drugs Felbamate and Topiramate [7]. In addition, taking advantage of independent action targets and complementary mechanisms of action with more therapeutic benefit and less toxicity and resistance, the combination treatment is superior to monotherapy [8][9][10][11], as shown in the fixed combination of Vildagliptin/Metformin in type 2 diabetic patients [12]. ...
Network pharmacology can ascertain the therapeutic mechanism of drugs for treating diseases at the level of biological targets and pathways. The effective mechanism study of traditional Chinese medicine (TCM) characterized by multi-component, multi-targeted, and integrative efficacy, perfectly corresponds to the application of network pharmacology. Currently, network pharmacology has been widely utilized to clarify the mechanism of the physiological activity of TCM. In this review, we comprehensively summarize the application of network pharmacology in TCM to reveal its potential of verifying the phenotype and underlying causes of diseases, realizing the personalized and accurate application of TCM. We searched the literature using “TCM network pharmacology” and “network pharmacology” as keywords from Web of Science, PubMed, Google Scholar, as well as Chinese National Knowledge Infrastructure in the last decade. The origins, development, and application of network pharmacology are closely correlated with the study of TCM which has been applied in China for thousands of years. Network pharmacology and TCM have the same core idea and promote each other. A well-defined research strategy for network pharmacology has been utilized in several aspects of TCM research, including the elucidation of the biological basis of diseases and syndromes, the prediction of TCM targets, the screening of TCM active compounds, and the decipherment of mechanisms of TCM in treating diseases. However, several factors limit its application, such as the selection of databases and algorithms, the unstable quality of the research results, and the lack of standardization. This review aims to provide references and ideas for the research of TCM and to encourage the personalized and precise use of Chinese medicine.
... Therefore, the development of anti-leishmaniasis drugs with multiple targets holds promise as they are less susceptible to targeting mechanisms. In recent decades, the dominant paradigm in drug discovery has been the "one target, one drug" approach, assuming that modulating a single disease-related biological target can effectively control disease symptoms or progression [7][8][9][10] . However, approximately twenty years ago, a group of pioneering researchers proposed the efficient utilization of small organic molecules with multitarget profiles. ...
Antioxidant defense mechanisms are important for a parasite to overcome oxidative stress and survive within host macrophage cells. Mitochondrial iron superoxide dismutase A (FeSODA) and trypanothione reductase (TR) are critical enzymes in the antioxidant defense mechanism of Leishmania donovani . FeSODA is responsible for neutralizing reactive oxygen species in mitochondria, while TR is responsible for reducing trypanothione, the molecules that help the parasite fight oxidative stress in Leishmania. In this study, we used multitarget ligands to inhibit both the FeSODA and TR enzymes. We combined structure-based drug design using virtual screening approach to find inhibitors against both the targets. The ZINC15 database of biogenic compounds was utilized to extract drugs-like molecules against leishmaniasis. The compounds were screened by standard precision (SP) and extra precision (XP) docking methods. Two compounds, ZINC000008876351 and ZINC000253403245, were selected based on molecular docking based on the binding affinity for both the targets. The screened molecules ZINC000008876351 and ZINC000253403245 showed strong hydrogen bonding with the target proteins according to the Molecular mechanics with generalised Born and surface area solvation (MM-GBSA) techniques. These two compounds were also experimentally investigated on promastigotes stage of L. donovani . Under in vitro condition, the compounds show inhibitory effects on L. donovani promastigotes with IC 50 values of 24.82 ± 0.61 µM for ZINC000008876351 and 7.52 ± 0.17 µM for ZINC000253403245. Thus, the screened compounds seem to have good potential as therapeutic candidates for leishmaniasis.
... Exploring drug resistant epilepsy requires the utilization of advanced in-vivo animal models that can mimic the complex nature of this condition (Löscher W et al., 2011). These models not only provide valuable insights into the mechanisms underlying drug resistance, but also serve as indispensable tools in the development and evaluation of potential antiepileptic drugs (Ngoupaye GT et al., 2022). ...
The development of effective antiepileptic drugs (AEDs) is crucial in the management of epilepsy, a chronic neurological disorder characterized by recurrent seizures. In order to identify potential AEDs, researchers employ a range of screening models that encompass both in-vitro and in-vivo approaches. These models provide valuable insights into the pharmacological properties and mechanisms of action of candidate compounds, aiding in the selection and optimization of drug candidates for further development. In-vitro screening models involve conducting experiments on isolated cells or tissues in controlled laboratory conditions. They allow researchers to examine the effects of AEDs on specific molecular targets involved in epileptogenesis, such as ion channels or neurotransmitter receptors. In-vitro models offer advantages such as cost-effectiveness, high throughput capacity, and the ability to study drug interactions with isolated components of the nervous system. Furthermore, they facilitate mechanistic investigations that elucidate the underlying pathways through which AEDs exert their antiepileptic effects. Hence, this review was focused for the various methods indicating the In-vitro and In-vivo pharmacological screening models for antiepileptic drugs.
