Canonical: https://instain.ru/en/ai/alphafold/ Language: en Google DeepMind and Isomorphic Labs Model of Biomolecule Structure # AlphaFold. Structure prediction and region-by-region confidence review 4.50 / 5 [Directory score](https://instain.ru/en/ai/alphafold/#editorial-rating) [Official website ](https://deepmind.google/science/alphafold/) AlphaFold 3 models the structure of proteins and other supported molecules in a complex. When analyzing the result, it is important to look at confidence and compare with known data. ![Google DeepMind Repository with AlphaFold 3 Launch Order](https://instain.ru/assets/images/alphafold-screen-93558b6a5b7a-1200.webp) Google DeepMind repository with AlphaFold 3 launch order. [Open the source ](https://github.com/google-deepmind/alphafold3) ## Start with the famous complex For the exercise, select a small complex with a public experimental structure. Record chain identifiers and verify that the sequences match. AlphaFold 3 predicts the arrangement of supported molecules in a complex, and the result depends on the input. If the prediction shows a different shape in one region, check that you are comparing the same chains and conditions. An input preparation error can show up even in a simple visualization. ## Confidence is not the same throughout the complex Compare regions individually. Part of a chain can look plausible while its position relative to a neighboring chain remains uncertain. Record where prediction and experiment differ. Attach the inputs and run settings so someone else can repeat the comparison. Agreement in a computational result cannot establish interaction strength or compound efficacy. ## How to choose a way of access To view the finished structure, start from the base, and for a new calculation, check the capabilities of the server or local implementation. They have different sets of allowable inputs, requirements and conditions of use. For a local start, separately study the receipt of model parameters and equipment requirements. A learning example is useful to complete with a small table of discrepancies, rather than one picture. Indicate what conclusions follow from the open experiment and what assumptions remain. Separately check whether the data is available, which can then be checked the most controversial area. In the report next to the picture, leave an indication of the experimental source. ## Suitable tasks - See areas of confidence in the educational complex - Compare forecast with published structure Features ## Strengths - Supports several types of biomolecules - There is a server, structure database and published code Things to consider ## Limitations - High model confidence does not measure binding affinity - Access terms differ by option ## Selection and conditions Free access Yes Trial period Not confirmed No sign-up required Not confirmed Russian interface Not confirmed Local installation Yes API Not confirmed “Not confirmed” means there is not enough information. The feature may still be available; check the developer’s terms. Input formats Data Result Data ### Terms Google describes a free server for noncommercial research. Local use requires computing resources and is subject to separate terms for access to model parameters. High model confidence does not measure binding affinity. From task to first result ## Practical example Task See areas of confidence in the educational complex What to prepare Educational complex with open experimental structure and known sequences. ### Task brief or prompt Compare the predicted configuration with an open structure. Write down the version of the model and select areas that require separate verification. ### Expected result A table of observations about confidence and discrepancies with the experiment. ### How to check the result - Check the chains and numbering of residues. - Separate computational prediction from experimental observation. An editorial teaching example of a task brief, not the result of hands-on testing of the service. Check that the required mode is available, that you have rights to the source material and that the intended use of the result is permitted. Check details ## Official sources - [Review of the AlphaFold family ](https://deepmind.google/science/alphafold/) - [The official AlphaFold 3 repository ](https://github.com/google-deepmind/alphafold3) - [Access to AlphaFold Server ](https://alphafoldserver.com/) This description is based on the developer’s material. Features, prices and availability may change; check the primary source before use. About the tool Developer Google DeepMind and Isomorphic Labs Category [Code](https://instain.ru/en/category/code/) Access You can access published structures, a server for noncommercial research, and a separate local implementation of AlphaFold 3. The supported inputs and access terms differ. Payment Google describes a free server for noncommercial research. Local use requires computing resources and is subject to separate terms for access to model parameters. API No separate API specified [Developer terms ](https://alphafoldserver.com/) Directory score 4.50 / 5 Features 4.70 / 5 Workflows 4.20 / 5 Ecosystem 4.60 / 5 Documentation 4.50 / 5 Scores are an editorial guide to the directory. They are not user reviews or the results of personal testing. [See the methodology ](https://instain.ru/en/methodology/)