AIMC Topic: Molecular Docking Simulation

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The role of mitochondrial dysfunction in the pathogenesis of atherosclerosis: A new exploration from bioinformatics analysis.

Medicine
Atherosclerosis (AS) is a complex cardiovascular disease associated with mitochondrial dysfunction (MD), which contributes to plaque formation and instability. This study explores the relationship and shared risk factors between the pathogenesis of A...

AI-Assisted Protein-Peptide Complex Prediction in a Practical Setting.

Journal of computational chemistry
Accurate prediction of protein-peptide complex structures plays a critical role in structure-based drug design, including antibody design. Most peptide-docking benchmark studies were conducted using crystal structures of protein-peptide complexes; as...

Drug repurposing targeting COVID-19 3CL protease using molecular docking and machine learning regression approaches.

Scientific reports
The COVID-19 pandemic has initiated a global health emergency, with an exigent need for an effective cure. Progressively, drug repurposing is emerging as a promising solution for saving time, cost, and labor. However, the number of drug candidates th...

Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.

Scientific reports
Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration, exhibits limited sensitivity to conventional radiochemotherapy. Although immunotherapy has shown efficacy in some patients, its applicability is not ...

AbSet: A Standardized Data Set of Antibody Structures for Machine Learning Applications.

Journal of chemical information and modeling
Machine learning algorithms have played a fundamental role in the development of therapeutic antibodies by being trained on data sets of sequences and/or structures. However, structural data sets remain limited, especially those that include antibody...

Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening.

Journal of chemical information and modeling
Physics-based docking methods have long been the cornerstone of structure-based virtual screening (VS). However, the emergence of machine learning (ML)-based docking approaches has opened new possibilities for enhancing VS technologies. In this study...

AI-Driven Design and Development of Nontoxic DYRK1A Inhibitors.

Journal of medicinal chemistry
Dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) is implicated in several human diseases, including DYRK1A syndrome, cancer, and neurodegenerative disorders such as Alzheimer's disease, making it a relevant therapeutic target. I...

Identifying Lactylation-related biomarkers and therapeutic drugs in ulcerative colitis: insights from machine learning and molecular docking.

BMC pharmacology & toxicology
BACKGROUND: Ulcerative colitis (UC), a chronic relapsing-remitting inflammatory bowel disease. Recent studies have shown that lactylation modifications may be involved in metabolic-immune interactions in intestinal inflammation through epigenetic reg...

Small Molecules Targeting the Structural Dynamics of AR-V7 Partially Disordered Proteins Using Deep Ensemble Docking.

Journal of chemical theory and computation
The extensive conformational dynamics of partially disordered proteins hinders the efficiency of traditional in-silico structure-based drug discovery approaches due to the challenge of screening large chemical spaces of compounds, albeit with an exce...