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Molecular Dynamics Simulation

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Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: a natural products database.

Molecular diversity
Alzheimer's disease is the most common form of dementia, representing 60-70% of dementia cases. The enzyme acetylcholinesterase (AChE) cleaves the ester bonds in acetylcholine and plays an important role in the termination of acetylcholine activity a...

A Deep-Learning Sequence-Based Method to Predict Protein Stability Changes Upon Genetic Variations.

Genes
Several studies have linked disruptions of protein stability and its normal functions to disease. Therefore, during the last few decades, many tools have been developed to predict the free energy changes upon protein residue variations. Most of these...

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2.

The journal of physical chemistry letters
SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine lear...

Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning.

Scientific reports
We developed a method to improve protein thermostability, "loop-walking method". Three consecutive positions in 12 loops of Burkholderia cepacia lipase were subjected to random mutagenesis to make 12 libraries. Screening allowed us to identify L7 as ...

Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets.

Nature communications
Understanding the structural determinants of a protein's biochemical properties, such as activity and stability, is a major challenge in biology and medicine. Comparing computer simulations of protein variants with different biochemical properties is...

Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol.

Molecules (Basel, Switzerland)
Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins,...

Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides.

Scientific reports
Cell-penetrating peptides have important therapeutic applications in drug delivery, but the variety of known cell-penetrating peptides is still limited. With a promise to accelerate peptide development, artificial intelligence (AI) techniques includi...

Treasuring the computational approach in medicinal plant research.

Progress in biophysics and molecular biology
Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was...

Integrated support vector machine and pharmacophore based virtual screening driven identification of thiophene carboxamide scaffold containing compound as potential PARP1 inhibitor.

Journal of biomolecular structure & dynamics
Poly (ADP-ribose) polymerase-1 (PARP1) inhibition strategy for cancer treatment is gaining advantage particularly in patients having a mutation in BRCA1/BRCA2 gene. To date, four drugs have obtained FDA approval and some inhibitors are in clinical tr...

Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

Journal of biomolecular structure & dynamics
causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them. Drug-resistant poses very serious public health issues. To overcome this, the development of effec...