Browsing by Author "Alexiou, Athanasios"

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Abetting Host Immune Response by Inhibiting Rhipicephalus sanguineus Evasin-1
(Daffodil International University, 22-09-13) Castrosanto, Melvin A.; Mukerjee, Nobendu; Ramos, Ana Rose; Maitra, Swastika; Manuben, John Julius P.; Das, Padmashree; Malik, Sumira; Hasan, Mohammad Mehedi; Alexiou, Athanasios; Dey, Abhijit; Kamal, Mohammad Amjad; Aljarba, Nada H.; Alkahtani, Saad; Ghosh, Arabinda
The brown dog tick (Rhipicephalus sanguineus) is the most prevalent tick in the world and a well-recognized vector of many pathogens affecting dogs and occasionally humans. Pathogens exploit tick salivary molecules for their survival and multiplication in the vector and transmission to and establishment in the hosts. Tick saliva contains various non-proteinaceous substances and secreted proteins that are differentially produced during feeding and comprise of inhibitors of blood congealing and platelet aggregation, vasodilatory and immunomodulatory substances, and compounds preventing itch and pain. One of these proteins is Evasin-1, which has a high binding affinity to certain types of chemokines. The binding of Evasin-1 to chemokines prevents the detection and immune response of the host to R. sanguineus, which may result in the successful transmission of pathogens. In this study, we screened potential Evasin-1 inhibitor based on the pharmacophore model derived from the binding site residues. Hit ligands were further screened via molecular docking and virtual ADMET prediction, which resulted in ZINC8856727 as the top ligand (binding affinity: -9.1 kcal/mol). Molecular dynamics simulation studies, coupled with MM-GBSA calculations and principal component analysis revealed that ZINC8856727 plays a vital role in the stability of Evasin-1. We recommend continuing the study by developing a formulation that serves as a potential medicine aid immune response during R. sanguineus infestation.
COVID-19 Diagnostic Methods in Developing Countries
(Daffodil International University, 2022-05-27) Maniruzzaman, Md.; Islam, Md. Missile; Ali, Md. Hazrat; Mukerjee, Nobendu; Maitra, Swastika; Kamal, Mohammad Amjad; Ghosh, Arabinda; Castrosanto, Melvin A.; Alexiou, Athanasios; Ashraf, Ghulam Md.; Tagde, Priti; Rahman, Md. Habibur
COVID-19 has become one of the few leading causes of death and has evolved into a pandemic that disrupts everyone’s routine, and balanced way of life worldwide, and will continue to do so. To bring an end to this pandemic, scientists had put their all effort into discovering the vaccine for SARS-CoV-2 infection. For their dedication, now, we have a handful of COVID-19 vaccines. Worldwide, millions of people are at risk due to the current pandemic of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). Despite the lack of clinically authorized antiviral medications and vaccines for COVID-19, clinical trials of many recognized antiviral agents, their combination, and vaccine development in patients with confirmed COVID-19 are still ongoing. This discovery gave us a chance to get immune to this disease worldwide and end the pandemic. However, the unexpected capacity of mutation of the SARS-CoV-2 virus makes it difficult, like the recent SAS-CoV-2 Omicron variant. Therefore, there is a great necessity to spread the vaccination programs and prevent the spread of this dreadful epidemic by identifying and isolating afflicted patients. Furthermore, several COVID-19 tests are thought to be expensive, time-consuming, and require the use of adequately qualified persons to be carried out efficiently. In addition, we also conversed about how the various COVID-19 testing methods can be implemented for the first time in a developing country and their cost-effectiveness, accuracy, human resources requirements, and laboratory facilities.
Current Trends of Computational Tools in Geriatric Medicine and Frailty Management
(Daffodil International University, 2022-07-19) Louka, Anna Maria; Tsagkaris, Christos; Christoforou, Panagiotis; Khan, Andleeb; Alexiou, Filia; Simou, Panagiota; Haranas, Loannis; Gkigkitzis, Loannis; Zouganelis, Georgios; Jha, Niraj Kumar; Uddin, Md Sahab; Shen, Bairong; Kamal, Mohammad A.; Ashraf, Ghulam Md; Alexiou, Athanasios
While frailty corresponds to a multisystem failure, geriatric assessment can recognize multiple pathophysiological lesions and age changes. Up to now, a few frailty indexes have been introduced, presenting definitions of psychological problems, dysregulations in nutritional intake, behavioral abnormalities, and daily functions, genetic, environmental, and cardiovascular comorbidities. The geriatric evaluation includes a vast range of health professionals; therefore, we describe a broad range of applications and frailty scales-biomarkers to investigate and formulate the relationship between frailty lesions, diagnosis, monitoring, and treatment. Additionally, artificial intelligence applications and computational tools are presented, targeting a more efficacy individualized geriatric management of healthy aging.
DeePred-BBB
(Daffodil International University, 2022-05-03) Kumar, Rajnish; Sharma, Anju; Alexiou, Athanasios; Bilgrami, Anwar L.; Kamal, Mohammad Amjad; Ashraf, Ghulam Md
The blood-brain barrier (BBB) is a selective and semipermeable boundary that maintains homeostasis inside the central nervous system (CNS). The BBB permeability of compounds is an important consideration during CNS-acting drug development and is difficult to formulate in a succinct manner. Clinical experiments are the most accurate method of measuring BBB permeability. However, they are time taking and labor-intensive. Therefore, numerous efforts have been made to predict the BBB permeability of compounds using computational methods. However, the accuracy of BBB permeability prediction models has always been an issue. To improve the accuracy of the BBB permeability prediction, we applied deep learning and machine learning algorithms to a dataset of 3,605 diverse compounds. Each compound was encoded with 1,917 features containing 1,444 physicochemical (1D and 2D) properties, 166 molecular access system fingerprints (MACCS), and 307 substructure fingerprints. The prediction performance metrics of the developed models were compared and analyzed. The prediction accuracy of the deep neural network (DNN), one-dimensional convolutional neural network, and convolutional neural network by transfer learning was found to be 98.07, 97.44, and 97.61%, respectively. The best performing DNN-based model was selected for the development of the “DeePred-BBB” model, which can predict the BBB permeability of compounds using their simplified molecular input line entry system (SMILES) notations. It could be useful in the screening of compounds based on their BBB permeability at the preliminary stages of drug development. The DeePred-BBB is made available at https://github.com/12rajnish/DeePred-BBB.
Dietary Alterations in Impaired Mitochondrial Dynamics Due to Neurodegeneration
(Daffodil International University, 2022-07-11) Ashraf, Ghulam Md; Chatzichronis, Stylianos; Alexiou, Athanasios; Firdousi, Gazala; Kamal, Mohammad Amjad; Ganash, Magdah
Alzheimer’s disease is still an incurable disease with significant social and economic impact globally. Nevertheless, newly FDA-approved drugs and non-pharmacological techniques may offer efficient disease treatments. Furthermore, it is widely accepted that early diagnosis or even prognosis of Alzheimer’s disease using advanced computational tools could offer a compelling alternative way of management. In addition, several studies have presented an insight into the role of mitochondrial dynamics in Alzheimer’s development. In combination with diverse dietary and obesity-related diseases, mitochondrial bioenergetics may be linked to neurodegeneration. Considering the probabilistic expectations of Alzheimer’s disease development or progression due to specific risk factors or biomarkers, we designed a Bayesian model to formulate the impact of diet-induced obesity with an impaired mitochondrial function and altered behavior. The applied probabilities are based on clinical trials globally and are continuously subject to updating and redefinition. The proposed multiparametric model combines various data types based on uniform probabilities. The program simulates all the variables with a uniform distribution in a sample of 1000 patients. First, the program initializes the variable age (30–95) and the four different diet types (“HFO_diet,” “Starvation,” “HL_diet,” “CR”) along with the factors that are related to prodromal or mixed AD (ATP, MFN1, MFN2, DRP1, FIS1, Diabetes, Oxidative_Stress, Hypertension, Obesity, Depression, and Physical_activity). Besides the known proteins related to mitochondrial dynamics, our model includes risk factors like Age, Hypertension, Oxidative Stress, Obesity, Depression, and Physical Activity, which are associated with Prodromal Alzheimer’s. The outcome is the disease progression probability corresponding to a random individual ID related to diet choices and mitochondrial dynamics parameters. The proposed model and the programming code are adjustable to different parameters and values. The program is coded and executed in Python and is fully and freely available for research purposes and testing the correlation between diet type and Alzheimer’s disease progression regarding various risk factors and biomarkers.
Editorial: The Alzheimer’s Disease Challenge, Volume II
(Frontier Scientific Publishing, 2023-01-10) Kamal, Mohammad Amjad; Alexiou, Athanasios; Perveen, Asma
Data analysis obtained from the 2019 Global Burden of Disease (GBD) database, the numbers and age-standardized rates (ASRs) of incidence, prevalence, death, and disability-adjusted life-years (DALYs) of AD and other dementias from 1990 to 2019 by Li X. et al. support the emerging necessity of supporting health strategies for more effective prevention and treatment measures in a rapidly increasing aging population. Li X. et al. identified a constantly increasing incidence and prevalence of AD and other dementias over these 30 years. Furthermore, the risk of developing dementia is proportional to age, with females and the elderly having a higher risk. Additionally, the researchers identified smoking as a significant risk factor for the disease burden, and the age-standardized rates (ASRs) of incidence, prevalence, and disability-adjusted life-years (DALYs) were positively correlated with the sociodemographic index (SDI) (Li X. et al.).
Emerging Promise of Therapeutic Approaches Targeting Mitochondria in Neurodegenerative Disorders
(Emerald Publishing Limited, 2023-04-12) Rahman, Md Mominur; Tumpa, Mst Afroza Alam; Rahaman, Md Saidur; Islam, Fahadul; Islam, Fahadul; Sutradhar, Popy Rani; Ahmed, Muniruddin; Alghamdi, Badrah S.; Hafeez, Abdul; Alexiou, Athanasios; Perveen, Asma; Ashraf, Ghulam Md
Mitochondria are critical for homeostasis and metabolism in all cellular eukaryotes. Brain mitochondria are the primary source of fuel that supports many brain functions, including intracellular energy supply, cellular calcium regulation, regulation of limited cellular oxidative capacity, and control of cell death. Much evidence suggests that mitochondria play a central role in neurodegenerative disorders (NDDs) such as Parkinson's disease, Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis. Ongoing studies of NDDs have revealed that mitochondrial pathology is mainly found in inherited or irregular NDDs and is thought to be associated with the pathophysiological cycle of these disorders. Typical mitochondrial disturbances in NDDs include increased free radical production, decreased ATP synthesis, alterations in mitochondrial permeability, and mitochondrial DNA damage. The main objective of this review is to highlight the basic mitochondrial problems that occur in NDDs and discuss the use mitochondrial drugs, especially mitochondrial antioxidants, mitochondrial permeability transition blockade, and mitochondrial gene therapy, for the treatment and control of NDDs.
Natural Products in the Management of Neurodegenerative Diseases
(Springer Nature, 2024-05-16) Goyal, Rajat; Mittal, Pooja; Gautam, Rupesh K.; Kamal, Mohammad Amjad; Perveen, Asma; Garg, Vandana; Alexiou, Athanasios; Saboor, Muhammad; Haque, Shafiul; Farhana, Aisha; Papadakis, Marios; Ashraf, Ghulam Md
"Neurodegenerative diseases represent one of the utmost imperative well-being health issues and apprehensions due to their escalating incidence of mortality. Natural derivatives are more efficacious in various preclinical models of neurodegenerative illnesses. These natural compounds include phytoconstituents in herbs, vegetables, fruits, nuts, and marine and freshwater flora, with remarkable efficacy in mitigating neurodegeneration and enhancing cognitive abilities in preclinical models. According to the latest research, the therapeutic activity of natural substances can be increased by adding phytoconstituents in nanocarriers such as nanoparticles, nanogels, and nanostructured lipid carriers. They can enhance the stability and specificity of the bioactive compounds to a more considerable extent. Nanotechnology can also provide targeting, enhancing their specificity to the respective site of action. In light of these findings, this article discusses the biological and therapeutic potential of natural products and their bioactive derivatives to exert neuroprotective effects and some clinical studies assessing their translational potential to treat neurodegenerative disorders. Graphical Abstract Common mechanisms, therapeutic targets, and molecular pathogenesis of neurodegeneration. It is focused on the biological and therapeutic potential of natural products and their bioactive derivatives to exert a neuroprotective effect on the pathologies of neurodegenerative diseases."
Natural products in the management of neurodegenerative diseases
(2024-05-16) Rajat, Goyal; Mittal, Pooja; Gautam, Rupesh K.; Kamal, Mohammad Amjad; Perveen, Asma; Garg, Vandana; Alexiou, Athanasios; Saboor, Muhammad; Haque, Shafiul; Farhana, Aisha; Papadakis, Marios; Ashraf, Ghulam Md
Neurodegenerative diseases represent one of the utmost imperative well-being health issues and apprehensions due to their escalating incidence of mortality. Natural derivatives are more efficacious in various preclinical models of neurodegenerative illnesses. These natural compounds include phytoconstituents in herbs, vegetables, fruits, nuts, and marine and freshwater flora, with remarkable efficacy in mitigating neurodegeneration and enhancing cognitive abilities in preclinical models. According to the latest research, the therapeutic activity of natural substances can be increased by adding phytoconstituents in nanocarriers such as nanoparticles, nanogels, and nanostructured lipid carriers. They can enhance the stability and specificity of the bioactive compounds to a more considerable extent. Nanotechnology can also provide targeting, enhancing their specificity to the respective site of action. In light of these findings, this article discusses the biological and therapeutic potential of natural products and their bioactive derivatives to exert neuroprotective effects and some clinical studies assessing their translational potential to treat neurodegenerative disorders.
Repurposing Food Molecules as a Potential BACE1 Inhibitor for Alzheimer's Disease
(Daffodil International University, 2022-08-22) Mukerjee, Nobendu; Das, Anubhab; Jawarkar, Rahul D.; Maitra, Swastika; Das, Padmashree; Castrosanto, Melvin A.; Paul, Soumyadip; Samad, Abdul; Zaki, Magdi E. A.; Al-Hussain, Sami A.; Masand, Vijay H.; Hasan, Mohammad Mehedi; Bukhari, Syed Nasir Abbas; Perveen, Asma; Alghamdi, Badrah S.; Alexiou, Athanasios; Kamal, Mohammad Amjad; Dey, Abhijit; Malik, Sumira; Bakal, Ravindra L.; Abuzenadah, Adel Mohammad; Ghosh, Arabinda; Ashraf, Ghulam Md
Alzheimer’s disease (AD) is a severe neurodegenerative disorder of the brain that manifests as dementia, disorientation, difficulty in speech, and progressive cognitive and behavioral impairment. The emerging therapeutic approach to AD management is the inhibition of β-site APP cleaving enzyme-1 (BACE1), known to be one of the two aspartyl proteases that cleave β-amyloid precursor protein (APP). Studies confirmed the association of high BACE1 activity with the proficiency in the formation of β-amyloid-containing neurotic plaques, the characteristics of AD. Only a few FDA-approved BACE1 inhibitors are available in the market, but their adverse off-target effects limit their usage. In this paper, we have used both ligand-based and target-based approaches for drug design. The QSAR study entails creating a multivariate GA-MLR (Genetic Algorithm-Multilinear Regression) model using 552 molecules with acceptable statistical performance (R2 = 0.82, Q2loo = 0.81). According to the QSAR study, the activity has a strong link with various atoms such as aromatic carbons and ring Sulfur, acceptor atoms, sp2-hybridized oxygen, etc. Following that, a database of 26,467 food compounds was primarily used for QSAR-based virtual screening accompanied by the application of the Lipinski rule of five; the elimination of duplicates, salts, and metal derivatives resulted in a truncated dataset of 8,453 molecules. The molecular descriptor was calculated and a well-validated 6-parametric version of the QSAR model was used to predict the bioactivity of the 8,453 food compounds. Following this, the food compounds whose predicted activity (pKi) was observed above 7.0 M were further docked into the BACE1 receptor which gave rise to the Identification of 4-(3,4-Dihydroxyphenyl)-2-hydroxy-1H-phenalen-1-one (PubChem I.D: 4468; Food I.D: FDB017657) as a hit molecule (Binding Affinity = −8.9 kcal/mol, pKi = 7.97 nM, Ki = 10.715 M). Furthermore, molecular dynamics simulation for 150 ns and molecular mechanics generalized born and surface area (MMGBSA) study aided in identifying structural motifs involved in interactions with the BACE1 enzyme. Molecular docking and QSAR yielded complementary and congruent results. The validated analyses can be used to improve a drug/lead candidate’s inhibitory efficacy against the BACE1. Thus, our approach is expected to widen the field of study of repurposing nutraceuticals into neuroprotective as well as anti-cancer and anti-viral therapeutic interventions.
The Association between the Risk of Breast Cancer and Epigallocat-Echin-3-Gallate Intake: a Literature Review of a Potential Chemopre-Ventive Agent
(Scopus, 22-08-27) Athanasiou, Efstratios; Verras, Georgios-Ioannis; Papageorgiou, Savvas; Kelesis, Ioannis; Gatsis, Athanasios; Karaoulani, Christina; Stouras, Ioannis; Kanatas, Panagiotis; Saitani, Elmina-Marina; Oikonomou, Maria-Eleni; Vlassi, Danae-Anastasia; Vasileiou, Maria; Tsagkaris, Christos; Alexiou, Athanasios; Kamal, Mohammad Amjad
According to the latest epidemiological data, breast cancer has recently been the most frequently diagnosed malignancy. To date, a body of evidence has established the involvement of multiple - and frequently interrelated - genetic and environmental factors in the pathogenesis of the disease. Emerging research on cancer prevention has highlighted the deterrence potential of interventions targeting environmental risk factors, particularly diet. In this aspect, the current review reveals the latest scientific results regarding epigallocatechin-3-gallate (EGCG) - a catechin most commonly found in green tea, as a potential chemopreventive dietary agent against breast cancer. in vitro studies on EGCG have demonstrated its effect on cell cycle progression and its potential to suppress several intracellular signaling pathways involved in breast cancer pathogenesis. In addition, EGCG possesses specific apoptosis-inducing characteristics that seem to enhance its role as a regulator of cell survival. Preclinical data seem to support using EGCG as an effective adjunct to EGFR-targeting treatments. The authors' appraisal of the literature suggests that although preclinical evidence has documented the anticarcinogenic features of EGCG, limited large-scale epidemiological studies are investigating the consumption of EGCG - containing nutrients in the prevention and management of breast cancer risk. This literature review aims to liaise between preclinical and epidemiological research, surveying the existing evidence and unraveling relevant knowledge gaps.