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Molecular Docking Simulation

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Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Molecules (Basel, Switzerland)
Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calcula...

Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening.

Accounts of chemical research
Molecular docking, also termed ligand docking (LD), is a pivotal element of structure-based virtual screening (SBVS) used to predict the binding conformations and affinities of protein-ligand complexes. Traditional LD methodologies rely on a search a...

SurfPro-NN: A 3D point cloud neural network for the scoring of protein-protein docking models based on surfaces features and protein language models.

Computational biology and chemistry
Protein-protein interactions (PPI) play a crucial role in numerous key biological processes, and the structure of protein complexes provides valuable clues for in-depth exploration of molecular-level biological processes. Protein-protein docking tech...

Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network.

Journal of chemical information and modeling
Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale b...

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens.

Vaccine
Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain vir...

A suite of designed protein cages using machine learning and protein fragment-based protocols.

Structure (London, England : 1993)
Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, but their creation remains challenging. Here, we apply computational approaches to design a suite of tetrahedrally symmetric, se...

Deep Learning-Based construction of a Drug-Like compound database and its application in virtual screening of HsDHODH inhibitors.

Methods (San Diego, Calif.)
The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper uti...

Drug Repositioning via Graph Neural Networks: Identifying Novel JAK2 Inhibitors from FDA-Approved Drugs through Molecular Docking and Biological Validation.

Molecules (Basel, Switzerland)
The increasing utilization of artificial intelligence algorithms in drug development has proven to be highly efficient and effective. One area where deep learning-based approaches have made significant contributions is in drug repositioning, enabling...

In-depth discovery and taste presentation mechanism studies on umami peptides derived from fermented sea bass based on peptidomics and machine learning.

Food chemistry
Umami peptides originating from fermented sea bass impart a distinctive flavor to food. Nevertheless, large-scale and rapid screening for umami peptides using conventional techniques is challenging because of problems such as prolonged duration and c...

Computational discovery of novel FYN kinase inhibitors: a cheminformatics and machine learning-driven approach to targeted cancer and neurodegenerative therapy.

Molecular diversity
In this study, we explored the potential of novel inhibitors for FYN kinase, a critical target in cancer and neurodegenerative disorders, by integrating advanced cheminformatics, machine learning, and molecular simulation techniques. Our approach inv...