AIMC Topic: Methyltransferases

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AttentionScore: A Target-Specific, Bias-Aware Scoring Function for Structure-Based Virtual Screening: A Case Study on METTL3.

Journal of chemical information and modeling
Target-specific scoring functions offer a promising route to improve structure-based virtual screening beyond generic, bias-prone scoring schemes. Here, we introduce AttentionScore, a deep learning-based scoring function for METTL3 that integrates li...

Multi-omics and experimental validation identify methylation-related genes and METTL16 as key regulators in diabetic foot ulcer pathogenesis.

Scientific reports
Diabetic foot ulcers (DFUs) are a severe complication of diabetes, characterized by impaired wound healing, chronic inflammation, and tissue degradation. N-methyladenosine (mA), has emerged as a critical regulator in gene expression and cellular func...

Toxicity assessment of doxycycline-aided artificial intelligence-assisted drug design targeting candidate 16S rRNA methyltransferase gene.

BMC pharmacology & toxicology
BACKGROUND: The misfunction of the protein 16SrRNA methyltransferase can result in Urinary tract infections (UTI), Gastrointestinal (GI) infections, sepsis, pneumonia, and wound infections; various tactics are used to lessen the fatal consequences. I...

Integrated Nanopore and short-read RNA sequencing identifies dysregulation of METTL3- m6A modifications in endocrine therapy- sensitive and resistant breast cancer cells.

Functional & integrative genomics
The role of epitranscriptomic changes in the development of acquired endocrine therapy (ET)- resistance in estrogen receptor α (ER) expressing breast cancer (BC) is unknown. We tested the hypothesis that inhibition of METTL3, the methyltransferase re...

A generalized platform for artificial intelligence-powered autonomous enzyme engineering.

Nature communications
Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we r...

PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.

Molecular diversity
Protein methyltransferases (PMTs) are a group of enzymes that help catalyze the transfer of a methyl group to its substrates. These enzymes play an important role in epigenetic regulation and can methylate various substrates with DNA, RNA, protein, a...

Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance.

mSystems
UNLABELLED: The erythromycin resistance RNA methyltransferase () confers cross-resistance to all therapeutically important macrolides, lincosamides, and streptogramins (MLS phenotype). The expression of is often induced by the macrolide-mediated rib...

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation.

Computers in biology and medicine
BACKGROUND: The O6-methylguanine-DNA methyltransferase (MGMT) is a deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential clinical brain tumor biomarker for Glioblastoma Multiforme (GBM). Knowing the status of MGMT met...

Retrospective Data Analysis of the Influence of Age and Sex on TPMT Activity and Its Phenotype-Genotype Correlation.

The journal of applied laboratory medicine
BACKGROUND: Therapeutic efficacy and toxicity of thiopurine drugs (used as anticancer and immunosuppressant agents) are affected by thiopurine S-methyltransferase (TPMT) enzyme activity. genotype and/or phenotype is used to predict the risk for adve...