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Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis
Tuberculosis (TB), caused by Mycobacterium tuberculosis , ranks among the top causes of global human mortality, as reported by the World Health...
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Potential drug targets for tumors identified through Mendelian randomization analysis
According to the latest cancer research data, there are a significant number of new cancer cases and a substantial mortality rate each year. Although...
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Unveiling potential drug targets for hyperparathyroidism through genetic insights via Mendelian randomization and colocalization analyses
Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions...
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Exploration of potential novel drug targets for diabetic retinopathy by plasma proteome screening
The aim of this study is to identify novel potential drug targets for diabetic retinopathy (DR). A bidirectional two-sample Mendelian randomization...
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A machine learning method for the identification and characterization of novel COVID-19 drug targets
In addition to vaccines, the World Health Organization sees novel medications as an urgent matter to fight the ongoing COVID-19 pandemic. One...
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A publication-wide association study (PWAS), historical language models to prioritise novel therapeutic drug targets
Most biomedical knowledge is published as text, making it challenging to analyse using traditional statistical methods. In contrast,...
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A reanalysis and integration of transcriptomics and proteomics datasets unveil novel drug targets for Mekong schistosomiasis
Schistosomiasis, caused by Schistosoma trematodes, is a significant global health concern, particularly affecting millions in Africa and Southeast...
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SARS-CoV-2 potential drugs, drug targets, and biomarkers: a viral-host interaction network-based analysis
COVID-19 is a global pandemic impacting the daily living of millions. As variants of the virus evolve, a complete comprehension of the disease and...
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Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches
Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and...
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Pharmacophore modelling based virtual screening and molecular dynamics identified the novel inhibitors and drug targets against Waddlia chondrophila
Waddlia chondrophila is a possible cause of fetal death in humans. This Chlamydia-related bacterium is an emergent pathogen that causes human...
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Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure
We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more...
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Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus
Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining)....
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Finding genetically-supported drug targets for Parkinson’s disease using Mendelian randomization of the druggable genome
Parkinson’s disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in...
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Shared molecular signatures between coronavirus infection and neurodegenerative diseases provide targets for broad-spectrum drug development
Growing evidences have suggested the association between coronavirus infection and neurodegenerative diseases. However, the molecular mechanism...
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Multimodal CNN-DDI: using multimodal CNN for drug to drug interaction associated events
Drug-to-drug interaction (DDIs) occurs when a patient consumes multiple drugs. Therefore, it is possible that any medication can influence other...
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Using Mendelian randomization provides genetic insights into potential targets for sepsis treatment
Sepsis is recognized as a major contributor to the global disease burden, but there is a lack of specific and effective therapeutic agents. Utilizing...
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Systems biology and machine learning approaches identify drug targets in diabetic nephropathy
Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the...
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RSDB: A rare skin disease database to link drugs with potential drug targets for rare skin diseases
Rare skin diseases include more than 800 diseases affecting more than 6.8 million patients worldwide. However, only 100 drugs have been developed for...
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Sequence-based drug design as a concept in computational drug design
Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design...
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Computer-aided pattern scoring – A multitarget dataset-driven workflow to predict ligands of orphan targets
The identification of lead molecules and the exploration of novel pharmacological drug targets are major challenges of medical life sciences today....
