Introduction to molecular visualization: Difference between revisions

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Proteopedia Page Contributors and Editors (what is this?)Proteopedia Page Contributors and Editors (what is this?)

Eric Martz, Karsten Theis

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 ==Obtaining Molecular Models==
-Methods for searching the [[Protein Data Bank]] for published empirical 3D models are [[Practical_Guide_to_Homology_Modeling#Do_you_need_a_homology_model.3F|explained here]]. ''Empirical models'' are those determined by experimentation, notably [[X-ray diffraction]], [[solution nuclear magnetic resonance]], or cryo-electron microscopy. Empirical models are far more reliable than [[theoretical models]], but one must pay attention to the [[Quality assessment for molecular models|quality of an empirical model]] since some are more reliable than others.
+You can browse for molecular models at the [http://atlas.molviz.org Atlas of Macromolecules], the [http://pdb101.rcsb.org/ Molecule of the Month], or [https://web.expasy.org/spotlight/ Protein Spotlight].
-Empirical models are available for only a small fraction of all proteins, probably <10%. If an empirical model is not available, the next best thing would be a [[homology model]]. About one third of all proteins can be reliably homology modeled, but homology models have [[Practical_Guide_to_Homology_Modeling#Limitations_of_Homology_Modeling|more uncertainties]] than do empirical models.
+[[How To Find A Structure]] explains an easy way to find a structure for a protein of interest, and how to choose the best one available when there is more than one. [[Empirical models]] are those determined by experimentation, notably [[X-ray diffraction]], [[solution nuclear magnetic resonance]], or [[electron cryomicroscopy]]. Empirical models are the most reliable, but one must pay attention to the [[Quality assessment for molecular models|quality of an empirical model]] since some are more reliable than others.
+Empirical models are available for only a small fraction of all proteins, probably <10%. When an empirical model is not available, [[AlphaFold]] has a proven track record of predicting protein structures correctly from their sequences, using artificial intelligence (AI). [[AlphaFold]] also reliably predicts the confidence of each part of a predicted structure.
 ==See Also==
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 *[[History of Macromolecular Visualization]]
 *[[Molecular Sculpture]]
+[[Category: Alternate Renderings]]