From emartz at microbio.umass.edu Thu Mar 18 20:30:40 2021
From: emartz at microbio.umass.edu (Eric Martz)
Date: Thu, 18 Mar 2021 20:30:40 -0400
Subject: [Proteopedia] AlphaFold2 Breakthrough in Protein Structure
Prediction
Message-ID: <2fcc8ee9-7b9a-ec16-f0dd-8bbf9433f63e@microbio.umass.edu>
Last month, thanks to some of my colleagues*, I was introduced to the
breakthrough by AlphaFold2 announced November, 2020.
AlphaFold2 predicted protein structures with truly astonishing accuracy,
certified by the bi-annual double-blind competition, CASP 14, founded by
John Moult in the early 1990s. Its predictions were based on the amino
acid sequences of the target proteins, using massive artificial
intelligence machine learning from sequence and structure databases.
Predictions were made "blind", without access to empirical structures of
the targets, and were judged later in 2020 when empirical structures
became public. The judges did not know who made which prediction.
AlphaFold2 was one of over 100 groups that submitted predictions for
over 100 target single-chain domains. In most cases, AlphaFold2 made the
best prediction, while the second best prediction was far less accurate.
This was particularly impressive for "free modeling" targets, those for
which no suitable homology modeling templates were available.
I have briefly summarized the breakthrough here:
https://proteopedia.org/w/Theoretical_modeling#Ab_Initio_Models
I have analyzed two free modeling cases in detail, with interactive 3D
comparisons. One (92 amino acids) is the ORF8 virulence factor from
SARS-CoV-2. Among the free modeling targets, it had the largest
discrepancy between the best and 2nd best predictions. The second is a
phage RNA polymerase, the longest free-modeling target domain (404 amino
acids). See:
https://proteopedia.org/w/AlphaFold2_examples_from_CASP_14
I welcome comments, corrections, additions, or feedback!
*Special thanks to my colleagues Roman Sloutsky, Nathaniel Kuzio, Erik
Nordquist, Can Ozden, Thomas Sawyer, Katie Wahlbeck, Jeanne Hardy, and
Scott Garman all at UMass Amherst, and Woody Sherman of Silicon
Therapeutics.
-Eric
Eric Martz, Professor Emeritus, Dept Microbiology (he/him/his)
U Mass, Amherst -- Martz.MolviZ.Org
Guided Exploration of Macromolecules with Powerpoint-Ready Animations:
FirstGlance.Jmol.Org
Protein 3D Structure Wiki: Proteopedia.Org
Education: Biochem in 3D at MolviZ.Org
Find Functional Patches in Proteins: ConSurf.tau.ac.il
Atlas of Macromolecules: Atlas.MolviZ.Org
See multiple protein sequence alignments clearly: MSAReveal.Org
Pockets And Cavities Using Pseudoatoms in Proteins: PACUPP
Interactive Molecules in Architectural Spaces: MolecularPlayground.Org
Syllabi: Workshops.MolviZ.Org
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From emartz at microbio.umass.edu Tue Mar 23 19:01:30 2021
From: emartz at microbio.umass.edu (Eric Martz)
Date: Tue, 23 Mar 2021 19:01:30 -0400
Subject: [Proteopedia] FirstGlance in Jmol at YouTube
Message-ID: <398b23f9-7c33-887b-f5ac-04fb947d61c9@microbio.umass.edu>
I've just put on YouTube an introduction to FirstGlance in Jmol
(demonstration), along with my design goals, recorded in a Zoom meeting
last November hosted by BioMolViz.Org.
https://www.youtube.com/watch?v=80og2ASrvnQ
(or in the YouTube search slot, look for "firstglance biomolviz")
If you'd like to get the flavor of FirstGlance, and a bit of how its
forerunners (such as RasMol, PyMOL) inspired me, its in this video. My
goals are to make understanding the structure of a macromolecule as easy
as possible (NO command language, using non-technical language with
explanations of the technical terms, etc.).
Its also super easy to generate a Powerpoint-ready video of any
molecular view you obtain in FirstGlance.
In Proteopedia, every page titled with a 4-character PDB entry has a
link to explore that model in FirstGlance. Thanks to Jaim Prilusky and
Joel Sussman for providing the server host for FirstGlance!
-Eric
Eric Martz, Professor Emeritus, Dept Microbiology (he/him/his)
Univ. Massachusetts, Amherst -- Martz.MolviZ.Org
Guided Exploration of Macromolecules with Powerpoint-Ready Animations:
FirstGlance.Jmol.Org
Protein 3D Structure Wiki: Proteopedia.Org
Education: Biochem in 3D at MolviZ.Org
Find Functional Patches in Proteins: ConSurf.tau.ac.il
Atlas of Macromolecules: Atlas.MolviZ.Org
See multiple protein sequence alignments clearly: MSAReveal.Org
Pockets And Cavities Using Pseudoatoms in Proteins: PACUPP
Interactive Molecules in Architectural Spaces: MolecularPlayground.Org
Syllabi: Workshops.MolviZ.Org
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