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1.
Int Rev Immunol ; : 1-20, 2024 Jul 10.
Artículo en Inglés | MEDLINE | ID: mdl-38982912

RESUMEN

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development.


The application of vaccines is one of the most promising treatments for numerous infectious diseases. However, the design and development of effective vaccines involve huge investments and resources, and only a handful of candidates successfully reach the market. Only relying on traditional methods is both time-consuming and expensive. Various computational tools and software have been developed to accelerate the vaccine design and development. Further, AI-enabled computational tools have revolutionized the field of vaccine design and development by creating predictive models and data-driven decision-making processes. Therefore, information and awareness of these AI-enabled computational resources will immensely facilitate the development of vaccines against emerging pathogens. In this review, we have meticulously summarized the available computational tools for each step of in-silico vaccine design and development, delving into the transformative applications of AI and ML in this domain, which would help to choose appropriate tools for each step during vaccine development, and also highlighting the limitations of these tools to facilitate the selection of appropriate tools for each step of vaccine design.

2.
Front Cell Dev Biol ; 10: 984311, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36158215

RESUMEN

Cancer is still one of the world's deadliest health concerns. As per latest statistics, lung, breast, liver, prostate, and cervical cancers are reported topmost worldwide. Although chemotherapy is most widely used methodology to treat cancer, poor pharmacokinetic parameters of anticancer drugs render them less effective. Novel nano-drug delivery systems have the caliber to improve the solubility and biocompatibility of various such chemical compounds. In this regard, cyclodextrins (CD), a group of natural nano-oligosaccharide possessing unique physicochemical characteristics has been highly exploited for drug delivery and other pharmaceutical purposes. Their cup-like structure and amphiphilic nature allows better accumulation of drugs, improved solubility, and stability, whereas CDs supramolecular chemical compatibility renders it to be highly receptive to various kinds of functionalization. Therefore combining physical, chemical, and bio-engineering approaches at nanoscale to specifically target the tumor cells can help in maximizing the tumor damage without harming non-malignant cells. Numerous combinations of CD nanocomposites were developed over the years, which employed photodynamic, photothermal therapy, chemotherapy, and hyperthermia methods, particularly targeting cancer cells. In this review, we discuss the vivid roles of cyclodextrin nanocomposites developed for the treatment and theranostics of most important cancers to highlight its clinical significance and potential as a medical tool.

3.
Molecules ; 27(3)2022 Jan 26.
Artículo en Inglés | MEDLINE | ID: mdl-35164069

RESUMEN

The human population is still facing appalling conditions due to several outbreaks of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. The absence of specific drugs, appropriate vaccines for mutants, and knowledge of potential therapeutic agents makes this situation more difficult. Several 1, 2, 4-triazolo [1, 5-a] pyrimidine (TP)-derivative compounds were comprehensively studied for antiviral activities against RNA polymerase of HIV, HCV, and influenza viruses, and showed immense pharmacological interest. Therefore, TP-derivative compounds can be repurposed against the RNA-dependent RNA polymerase (RdRp) protein of SARS-CoV-2. In this study, a meta-analysis was performed to ensure the genomic variability and stability of the SARS-CoV-2 RdRp protein. The molecular docking of natural and synthetic TP compounds to RdRp and molecular dynamic (MD) simulations were performed to analyse the dynamic behaviour of TP compounds at the active site of the RdRp protein. TP compounds were also docked against other non-structural proteins (NSP1, NSP2, NSP3, NSP5, NSP8, NSP13, and NSP15) of SARS-CoV-2. Furthermore, the inhibition potential of TP compounds was compared with Remdesivir and Favipiravir drugs as a positive control. Additionally, TP compounds were analysed for inhibitory activity against SARS-CoV RdRp protein. This study demonstrates that TP analogues (monomethylated triazolopyrimidine and essramycin) represent potential lead molecules for designing an effective inhibitor to control viral replication. Furthermore, in vitro and in vivo studies will strengthen the use of these inhibitors as suitable drug candidates against SARS-CoV-2.


Asunto(s)
ARN Polimerasa Dependiente de ARN de Coronavirus/efectos de los fármacos , ARN Polimerasa Dependiente de ARN de Coronavirus/metabolismo , Pirimidinas/farmacología , Triazoles/farmacología , Adenosina Monofosfato/análogos & derivados , Adenosina Monofosfato/farmacología , Alanina/análogos & derivados , Alanina/farmacología , Amidas/farmacología , COVID-19/metabolismo , Dominio Catalítico/efectos de los fármacos , Biología Computacional/métodos , Humanos , Simulación del Acoplamiento Molecular , Simulación de Dinámica Molecular , Pirazinas/farmacología , Pirimidinas/química , ARN Viral/efectos de los fármacos , ARN Polimerasa Dependiente del ARN/efectos de los fármacos , ARN Polimerasa Dependiente del ARN/metabolismo , SARS-CoV-2/efectos de los fármacos , SARS-CoV-2/metabolismo , Triazoles/química , Replicación Viral/efectos de los fármacos , Tratamiento Farmacológico de COVID-19
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