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How can you ensure the accuracy of molecular docking simulations?

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Molecular docking is a computational technique that simulates the interaction between a small molecule (ligand) and a protein (receptor) in order to predict their binding affinity and mode. Molecular docking can help design new drugs, identify potential targets, and understand biological processes. However, molecular docking is not a perfect method and its accuracy depends on several factors, such as the quality of the input structures, the choice of the docking algorithm, the scoring function, and the validation criteria. In this article, you will learn how to ensure the accuracy of molecular docking simulations by following some best practices and tips.

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1 Input structures

The first step to ensure the accuracy of molecular docking simulations is to use high-quality input structures for both the ligand and the receptor. Ideally, you should use experimental structures obtained from crystallography or NMR, as they represent the most reliable source of information about the 3D shape and conformation of the molecules. However, if experimental structures are not available, you can use homology modeling or de novo methods to generate theoretical structures, but you should be aware of the limitations and uncertainties of these methods. You should also check the resolution, completeness, and consistency of the input structures, and remove any water molecules, ions, or cofactors that are not relevant for the docking.

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Vivek Srivastava

Protein Chemist | Molecular Biologist
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Begin with selecting structures from PDB with high resolutions (<1.5 ?), the confidence in orderness will be high. Use docking programs and rank the scores to determine the binding affinities between enzyme and ligands. The higher the negative value the better the docking. Basis the rank of hits use an assessment tool to minimize the false positives and improve accuracy.

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2 Docking algorithm

The second step to ensure the accuracy of molecular docking simulations is to choose an appropriate docking algorithm that suits your research question and computational resources. There are two main types of docking algorithms: rigid and flexible. Rigid docking assumes that the ligand and the receptor do not change their shape during the docking process, while flexible docking allows some degree of conformational change. Rigid docking is faster and simpler, but it may miss some important interactions or induce steric clashes. Flexible docking is more realistic and accurate, but it is also more complex and time-consuming. You should consider the trade-off between speed and accuracy, and the level of flexibility that is relevant for your system.

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James Demmitt, MBA

CEO, Purveyor of customer value, innovation, and employee growth. Always a student. | USMC Veteran
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If exploring how a small molecule binds to a well-defined active site, rigid docking might suffice. However, for larger, more complex ligands or when the binding site is flexible, a flexible docking algorithm becomes necessary. Some advanced algorithms combine features of both rigid and flexible docking. They might treat parts of the ligand or receptor as rigid while allowing flexibility in other parts. This hybrid approach can balance accuracy and computational efficiency. Integrating molecular dynamics simulations with docking can enhance the flexibility and realism of the docking process.

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3 Scoring function

The third step to ensure the accuracy of molecular docking simulations is to use a reliable scoring function that can rank the docking poses according to their binding affinity and select the best ones. A scoring function is a mathematical formula that calculates a score based on the intermolecular interactions, such as electrostatics, van der Waals, hydrogen bonds, and hydrophobic effects. There are many types of scoring functions, such as empirical, knowledge-based, force field, or machine learning, and each one has its own advantages and disadvantages. You should compare different scoring functions and evaluate their performance on your system, as well as on benchmark datasets or experimental data.

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4 Validation criteria

The fourth step to ensure the accuracy of molecular docking simulations is to apply rigorous validation criteria that can assess the quality and reliability of the docking results. Validation criteria can be based on different aspects, such as the agreement with experimental data, the reproducibility of the docking runs, the diversity of the docking poses, the stability of the ligand-receptor complex, and the rationality of the binding mode. You should use multiple validation criteria and combine them to obtain a comprehensive picture of the docking accuracy. You should also be aware of the limitations and uncertainties of the validation methods, and avoid overfitting or underfitting the data.

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5 Best practices and tips

To ensure the accuracy of molecular docking simulations, it is important to follow some best practices and tips. Preprocessing the input structures by adding hydrogen atoms, assigning charges, removing clashes, and optimizing the geometry is key. Additionally, using multiple conformers of the ligand to account for its flexibility and diversity is a must. You should also define a reasonable docking box that covers the binding site of the receptor and avoids unnecessary regions. A docking protocol that includes a global search and a local refinement of the docking poses should be used. Visual inspection, statistical analysis, and molecular dynamics simulations should be used to analyze the docking results. Furthermore, it is important to compare the docking results with other methods, such as pharmacophore modeling, QSAR, or network analysis. Finally, document and report the docking parameters, results, and validation methods for accurate insights into biotechnology research. Following these steps will ensure the accuracy of molecular docking simulations.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you ensure the accuracy of molecular docking simulations?

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1 Input structures

2 Docking algorithm

3 Scoring function

4 Validation criteria

5 Best practices and tips

6 Here’s what else to consider

Biotechnology

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