AIMC Topic: Molecular Docking Simulation

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Deep learning-based dipeptidyl peptidase IV inhibitor screening, experimental validation, and GaMD/LiGaMD analysis.

BMC biology
BACKGROUND: Dipeptidyl peptidase-4 (DPP4) is considered a crucial enzyme in type 2 diabetes (T2D) treatment, targeted by inhibitors due to its role in cleaving glucagon-like peptide-1 (GLP-1). In this study, a novel DPP4 inhibitor screening strategy ...

Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy.

Scientific reports
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are a growing global health concern, especially among the elderly, posing significant challenges to well-being and survival. GSK3β, a serine/threonine...

SE(3)-equivariant ternary complex prediction towards target protein degradation.

Nature communications
Targeted protein degradation (TPD) has rapidly emerged as a powerful modality for drugging previously "undruggable" proteins. TPD employs small molecules like PROTACs and molecular glue degraders (MGD) to induce target protein degradation via the for...

Unveiling the mechanisms and promising molecular targets of curcumin in pancreatic cancer through multi-dimensional data.

Scientific reports
Pancreatic cancer (PC) is a highly aggressive and fatal malignancy, primarily affecting older males. Curcumin, a potential anti-cancer agent, has been shown to regulate key molecules in cancer progression, but its specific mechanisms in PC remain unc...

Multi-level evidence reveals PANK2 as a potential target of PFOA/PFOS-induced bone metabolism disruption: From network toxicology to in vitro validation.

Ecotoxicology and environmental safety
Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are two representative per- and polyfluoroalkyl substances (PFAS) that have attracted increasing attention due to their environmental persistence and potential health risks, while ...

Discovery of SARS-CoV-2 papain-like protease inhibitors through machine learning and molecular simulation approaches.

Drug discoveries & therapeutics
The papain-like protease (PLpro), a cysteine protease found in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), plays a crucial role in viral replication by cleaving the viral polyproteins and interfering with the host's innate immune re...

AffiGrapher: Contrastive Heterogeneous Graph Learning with Aromatic Virtual Nodes for RNA-Small Molecule Binding Affinity Prediction.

Journal of chemical information and modeling
RNA molecules exhibit diverse structures and functions, making them promising drug targets. However, predicting RNA-small molecule binding affinity remains challenging due to limited experimental data and the structural variability introduced by mult...

In-silico study of approved drugs as potential inhibitors against 3CLpro and other viral proteins of CoVID-19.

PloS one
The global pandemic, due to the emergence of COVID-19, has created a public health crisis. It has a huge morbidity rate that was never comprehended in the recent decades. Despite numerous efforts, potent antiviral drugs are lacking. Repurposing of dr...

Novel insights from comprehensive analysis: The role of cuproptosis and peripheral immune infiltration in Alzheimer's disease.

PloS one
BACKGROUND: Cuproptosis is increasingly recognized as an essential factor in the pathological process of Alzheimer's disease (AD). However, the specific role of cuproptosis-related genes in AD remains poorly understood.

generation of peptide binders with desired properties by deep generative models reinforced through enrichment of focused sets for iterative fine-tuning.

Chemical communications (Cambridge, England)
Recurrent neural networks underwent reinforcement procedures for generation of peptide binders with desired properties. Docking and scoring of peptides from these models allowed enrichment of focused sets with validated sequences for iterative fine-...