AIMC Topic: Molecular Docking Simulation

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Identification of gene signatures associated with lactation for predicting prognosis and treatment response in breast cancer patients through machine learning.

Scientific reports
As a newly discovered histone modification, abnormal lactation has been found to be present in and contribute to the development of various cancers. The aim of this study was to investigate the potential role between lactylation and the prognosis of ...

In-silico investigation integrated with machine learning to identify potential inhibitors targeting AKT2: Key driver of cancer cell progression and metastasis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In search of a key driver for the invasive growth of cancer metastasis, AKT2 is found to be exceptionally expressed in colorectal cancer and its metastasis. Again, exceeding genomic arrangements of AKT2 can be held responsib...

Comprehensive insights into carbonic anhydrase inhibition: A triad of In vitro, In silico, and In vivo perspectives.

Enzyme and microbial technology
Carbonic anhydrases (CAs) are zinc-dependent metalloenzymes essential for sustaining physiological balance by facilitating the reversible conversion of carbon dioxide to its hydrated form. Their biological significance, coupled with their involvement...

Identification of key therapeutic targets in nicotine-induced intracranial aneurysm through integrated bioinformatics and machine learning approaches.

BMC pharmacology & toxicology
BACKGROUND: Intracranial aneurysm (IA) is a critical cerebrovascular condition, and nicotine exposure is a known risk factor. This study delves into the toxicological mechanisms of nicotine in IA, aiming to identify key biomarkers and therapeutic tar...

Bioactive structures for inhibitors of polymerase enzyme by artificial intelligence.

Future medicinal chemistry
AIMS: Present new bioactive compounds, created by De novo Drug Design and artificial intelligence (AI), as possible inhibitors of polymerase.

In silico design of ankyrin repeat proteins that bind to the insulin-like growth factor type 1 receptor.

Journal of molecular graphics & modelling
Ankyrins are proteins widely distributed in nature that mediate protein‒protein interactions. Owing to their outstanding stability and ability to recognize targets, ankyrins have been used as therapeutic and diagnostic tools in several diseases, incl...

Integration of machine learning and experimental validation reveals new lipid-lowering drug candidates.

Acta pharmacologica Sinica
Hyperlipidemia, a major risk factor for cardiovascular diseases, is associated with limitations in clinical lipid-lowering medications. Drug repurposing strategies expedite the research process and mitigate development costs, offering an innovative a...

Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer.

Scientific reports
Prostate cancer (PC) is one of the most common types of malignancies in men, with a noteworthy increase in newly diagnosed cases in recent years. PARP1 is a ubiquitous nuclear enzyme involved in DNA repair, nuclear transport, ribosome synthesis, and ...

Revealing the Oxidative Stress-Related Molecular Characteristics and Potential Therapeutic Targets of Schizophrenia through Integrated Gene Expression Data Analysis.

Molecular neurobiology
Schizophrenia is a severe mental disorder characterized by oxidative stress imbalances. The underlying mechanisms of oxidative stress-related gene expression in schizophrenia require further investigation. Additionally, the diagnosis of schizophrenia...