From a900c5f30a3281e9a89e323ff8e444f9f689c410 Mon Sep 17 00:00:00 2001 From: Arthur Zalevsky Date: Thu, 28 Mar 2024 12:22:19 -0700 Subject: [PATCH] fix MolProbity spelling --- templates/full_validation_pdf.html | 12 ++++++------ templates/main.html | 4 ++-- templates/references.csv | 2 +- templates/validation_help.html | 6 +++--- 4 files changed, 12 insertions(+), 12 deletions(-) diff --git a/templates/full_validation_pdf.html b/templates/full_validation_pdf.html index 056355c5..eb0408e8 100644 --- a/templates/full_validation_pdf.html +++ b/templates/full_validation_pdf.html @@ -143,7 +143,7 @@

{{ date }}

  • Python-IHM Version {{ python_ihm_version }}
    • {% if molprobity_version is not none %} -
  • Molprobity Version {{ molprobity_version }}
    • +
  • MolProbity Version {{ molprobity_version }}
    • {% endif %} {% if sas|length > 0 and sasdb_sascif|length > 0 %} @@ -222,12 +222,12 @@

    This validation report contains model quality assessments for all structures, data quality assessment for SAS datasets and fit to model assessments for SAS datasets. Data quality and fit to model assessments for other datasets and model uncertainty are under development. Number of plots is limited to {{MAXPLOTS}}.

    - +
    {% if disclaimer == 0 %} {% if assess_excluded_volume == 'Not applicable' %}
    - Model Quality: Molprobity Analysis + Model Quality: MolProbity Analysis
    {% else %}
    @@ -242,7 +242,7 @@
    {% endfor %} {% elif disclaimer == 1 %}

    - Molprobity assessments and/or excluded volume assessments can not be evaluated for this current model. + MolProbity assessments and/or excluded volume assessments can not be evaluated for this current model.

    {% endif %}
    @@ -594,7 +594,7 @@

    Excluded volume satisfaction Python-IHM Version {{ python_ihm_version }} {% if molprobity_version is not none %} -
  • Molprobity Version {{ molprobity_version }}
    • +
  • MolProbity Version {{ molprobity_version }}
    • {% endif %} {% if sas|length > 0 and sasdb_sascif|length > 0 %} diff --git a/templates/references.csv b/templates/references.csv index 9d81d19d..a19bd614 100644 --- a/templates/references.csv +++ b/templates/references.csv @@ -55,7 +55,7 @@ scikit-learn | https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html | Pedrego trRosetta | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983395/ | Yang J, Anishchenko I, Park H, Peng Z, Ovchinnikov S, Baker D. Improved protein structure prediction using predicted interresidue orientations. Proc Natl Acad Sci U S A. 2020;117(3):1496-1503. trRossetta | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983395/ | Yang J, Anishchenko I, Park H, Peng Z, Ovchinnikov S, Baker D. Improved protein structure prediction using predicted interresidue orientations. Proc Natl Acad Sci U S A. 2020;117(3):1496-1503. PROSESS | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896095/ | Berjanskii M, Liang Y, Zhou J, et al. PROSESS: a protein structure evaluation suite and server. Nucleic Acids Res. 2010;38(Web Server issue):W633-W640. -Molprobity | https://pubmed.ncbi.nlm.nih.gov/29067766/ | Williams CJ, Headd JJ, Moriarty NW, Prisant MG, Videau LL, Deis LN, Verma V, Keedy DA, Hintze BJ, Chen VB, Jain S, Lewis SM, Arendall WB 3rd, Snoeyink J, Adams PD, Lovell SC, Richardson JS, Richardson DC. MolProbity: More and better reference data for improved all-atom structure validation. Protein Sci. 2018 Jan;27(1):293-315. +MolProbity | https://pubmed.ncbi.nlm.nih.gov/29067766/ | Williams CJ, Headd JJ, Moriarty NW, Prisant MG, Videau LL, Deis LN, Verma V, Keedy DA, Hintze BJ, Chen VB, Jain S, Lewis SM, Arendall WB 3rd, Snoeyink J, Adams PD, Lovell SC, Richardson JS, Richardson DC. MolProbity: More and better reference data for improved all-atom structure validation. Protein Sci. 2018 Jan;27(1):293-315. multicoil2 | https://pubmed.ncbi.nlm.nih.gov/21901122/ | Trigg J, Gutwin K, Keating AE, Berger B. Multicoil2: predicting coiled coils and their oligomerization states from sequence in the twilight zone. PLoS One. 2011;6(8). mCSM | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3904523/ | Pires DE, Ascher DB, Blundell TL. mCSM: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics. 2014;30(3):335-342. QRNAS | http://genesilico.pl/software/stand-alone/qrnas | Stasiewicz J, Mukherjee S, Nithin C, Bujnicki JM. QRNAS: software tool for refinement of nucleic acid structures. BMC Struct Biol. 2019;19(1):5. diff --git a/templates/validation_help.html b/templates/validation_help.html index 2b6298dc..d10d0b3b 100644 --- a/templates/validation_help.html +++ b/templates/validation_help.html @@ -42,7 +42,7 @@
  • 5. Model Quality Assessment
    • @@ -83,7 +83,7 @@

    1.2. Data quality assessment : Data quality assessments are only available for Small Angle Scattering datasets (SAS). This section was developed in collaboration with the SASBDB community. For details on the metrics, guidelines, and recommendations used, refer the 2017 community article (Trewhella et al. 2017). All experimental datasets used to build the model are listed, however, validation criteria for other experimental datasets are currently under development.

    -

    1.3. Model quality assessment : Model quality for models at atomic resolution is assessed using Molprobity (Williams et al. 2018), consistent with PDB. Model quality for coarse-grained or multi-resolution structures are assessed by computing excluded volume satisfaction based on reported distances and sizes of beads in the structures.

    +

    1.3. Model quality assessment : Model quality for models at atomic resolution is assessed using MolProbity (Williams et al. 2018), consistent with PDB. Model quality for coarse-grained or multi-resolution structures are assessed by computing excluded volume satisfaction based on reported distances and sizes of beads in the structures.

    1.4. Fit to data used to build the model : Fit to data used to build the model is only available for SAS datasets. This section was developed in collaboration with the SASBDB (Valentini et al. 2015). For details on the metrics, guidelines, and recommendations used, refer the 2017 community article (Trewhella et al. 2017). All experimental datasets used to build the model are listed, however, validation criteria for other experimental datasets are currently under development.

    @@ -166,7 +166,7 @@

    5. Model Quality Assessment

    Excluded volume assessments are performed for coarse-grained structures and MolProbity analysis is performed for atomic structures.

    5.1a. Excluded Volume Analysis : Excluded volume violation is defined as percentage of overlaps between coarse-grained beads in a structure. This percentage is obtained by dividing the number of overlaps/violations by the total number of pair distances in a structure. An overlap or violation between two beads occurs if the distance between the two beads is less than the sum of their radii (S. J. Kim et al. 2018).

    -

    5.1b. Molprobity Analysis : Molprobity analysis for atomic structures reported is consistent with PDB standards for X-ray structures (Williams et al. 2018). Summarized information is available in both the HTML and PDF reports. Detailed information is available for download as csv files, both from the HTML and the PDF reports. Please refer to the PDB user guide for details.

    +

    5.1b. MolProbity Analysis : MolProbity analysis for atomic structures reported is consistent with PDB standards for X-ray structures (Williams et al. 2018). Summarized information is available in both the HTML and PDF reports. Detailed information is available for download as csv files, both from the HTML and the PDF reports. Please refer to the PDB user guide for details.