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Molecular Docking Simulation

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Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer.

Molecules (Basel, Switzerland)
NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in the genetic makeup of NEK7 leads to the development of cancer malignancies and fatal inflammatory dis...

Predicting Protein-Ligand Docking Structure with Graph Neural Network.

Journal of chemical information and modeling
Modern day drug discovery is extremely expensive and time consuming. Although computational approaches help accelerate and decrease the cost of drug discovery, existing computational software packages for docking-based drug discovery suffer from both...

Carvacrol protects against carbonyl osmolyte-induced structural modifications and aggregation to serum albumin: Insights from physicochemical and molecular interaction studies.

International journal of biological macromolecules
The robust use of osmolytes (i.e., polyols and sugars) in the key therapeutic regimens/formulations has questioned their impact beyond the stability of therapeutic proteins as these osmolytes trigger structural alterations into proteins including mis...

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches.

PeerJ
An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was reported to be caused by a novel coronavirus which has infected approximately 220 million people worldwide with a death toll of 4.5 million as of September...

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions.

Journal of chemical information and modeling
Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding...

Machine learning approaches and their applications in drug discovery and design.

Chemical biology & drug design
This review is focused on several machine learning approaches used in chemoinformatics. Machine learning approaches provide tools and algorithms to improve drug discovery. Many physicochemical properties of drugs like toxicity, absorption, drug-drug ...

Pose Classification Using Three-Dimensional Atomic Structure-Based Neural Networks Applied to Ion Channel-Ligand Docking.

Journal of chemical information and modeling
The identification of promising lead compounds showing pharmacological activities toward a biological target is essential in early stage drug discovery. With the recent increase in available small-molecule databases, virtual high-throughput screening...

Affinity prediction using deep learning based on SMILES input for D3R grand challenge 4.

Journal of computer-aided molecular design
Modern molecular docking comprises the prediction of pose and affinity. Prediction of docking poses is required for affinity prediction when three-dimensional coordinates of the ligand have not been provided. However, a large number of feature engine...

PharmRF: A machine-learning scoring function to identify the best protein-ligand complexes for structure-based pharmacophore screening with high enrichments.

Journal of computational chemistry
Structure-based pharmacophore models are often developed by selecting a single protein-ligand complex with good resolution and better binding affinity data which prevents the analysis of other structures having a similar potential to act as better te...

Design of SARS-CoV-2 Mpro, PLpro dual-target inhibitors based on deep reinforcement learning and virtual screening.

Future medicinal chemistry
Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the ...