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Molecular Docking Simulation

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AIDDISON: Empowering Drug Discovery with AI/ML and CADD Tools in a Secure, Web-Based SaaS Platform.

Journal of chemical information and modeling
The widespread proliferation of artificial intelligence (AI) and machine learning (ML) methods has a profound effect on the drug discovery process. However, many scientists are reluctant to utilize these powerful tools due to the steep learning curve...

1,3,4-oxadiazole derivatives: synthesis, characterization, antifungal activity, DNA binding investigations, TD-DFT calculations, and molecular modelling.

Journal of biomolecular structure & dynamics
1,3,4-Oxadiazole-based heterocyclic analogs (3a-3m) were synthesized cyclization of Schiff bases with substituted aldehydes in the presence of bromine and acetic acid. The structural clarification of synthesized molecules was carried out with variou...

Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations.

Journal of biomolecular structure & dynamics
The enzyme dipeptidyl peptidase 4 (DPP4) is a potential therapeutic target for type 2 diabetes (T2DM). Many synthetic anti-DPP4 medications are available to treat T2DM. The need for secure and efficient medicines has been unmet due to the adverse sid...

Integrating machine learning and high throughput screening for the discovery of allosteric AKT1 inhibitors.

Journal of biomolecular structure & dynamics
Evidence from clinical and experimental investigations reveals the role of AKT in oral cancer, which has led to the development of therapeutic and pharmacological medications for inhibiting AKT protein. Despite prodigious effort, researchers are sear...

A Multimodal Deep Learning Framework for Predicting PPI-Modulator Interactions.

Journal of chemical information and modeling
Protein-protein interactions (PPIs) are essential for various biological processes and diseases. However, most existing computational methods for identifying PPI modulators require either target structure or reference modulators, which restricts thei...

Identification of new potential candidates to inhibit EGF via machine learning algorithm.

European journal of pharmacology
One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The advantage of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerat...

Discovery of potential RIPK1 inhibitors by machine learning and molecular dynamics simulations.

Physical chemistry chemical physics : PCCP
Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) plays a crucial role in inflammation and cell death, so it is a promising candidate for the treatment of autoimmune, inflammatory, neurodegenerative, and ischemic diseases. So far, there ...

Predicting molecular docking of per- and polyfluoroalkyl substances to blood protein using generative artificial intelligence algorithm DiffDock.

BioTechniques
This study computationally evaluates the molecular docking affinity of various perfluoroalkyl and polyfluoroalkyl substances (PFAs) towards blood proteins using a generative machine-learning algorithm, DiffDock, specialized in protein-ligand blind-do...

Exploring the potential of machine learning to design antidiabetic molecules: a comprehensive study with experimental validation.

Journal of biomolecular structure & dynamics
Recent advances in hardware and software algorithms have led to the rise of data-driven approaches for designing therapeutic modalities. One of the major causes of human mortality is diabetes. Thus, there is a tremendous opportunity for research into...

Equivariant Flexible Modeling of the Protein-Ligand Binding Pose with Geometric Deep Learning.

Journal of chemical theory and computation
Flexible modeling of the protein-ligand complex structure is a fundamental challenge for in silico drug development. Recent studies have improved commonly used docking tools by incorporating extra-deep learning-based steps. However, such strategies l...