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1 change: 0 additions & 1 deletion _data/CONTRIBUTORS.yml
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Expand Up @@ -79,7 +79,6 @@ Mitchell O'Brien:

Matthew Downton:
git: mattdton
orcid: 0000-0002-4693-1965
affiliation: Associate Director - Performance Optimisation, National Computational Infrastructure (NCI)

Kisaru Liyanage:
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2 changes: 2 additions & 0 deletions _data/sidebars/main.yml
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@@ -1,6 +1,8 @@
subitems:
- title: Home
url: /index
- title: Join the conversation
url: /join_conversation
- title: Activities
url: /activities
- title: How-to Guides

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Maybe Guides > guides for consistent capitalization?

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2 changes: 1 addition & 1 deletion contributing/contributing.md
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---
title: Contributing
page_id: contributing
type: resources
#type: resources
---

{% include callout.html type="important" content="Contributing guidelines will be available soon." %}
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4 changes: 2 additions & 2 deletions pages/activities.md
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---
title: Community Activities
page_id: activities
type: resources
#type: resources
toc: false
---


## In progress
{% include section-navigation-tiles-simple.html col = "2" type="activity_inprogress" except="binder_access.md" %}
{% include section-navigation-tiles-simple.html col = "2" type="activity_in_progress" except="binder_access.md" %}


## Future
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24 changes: 12 additions & 12 deletions pages/activities/batch_structure_prediction.md
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---
title: Batch Structure Prediction Workflows
type: activity_inprogress
type: activity_in_progress
contributors: [Ziad Al-Bkhetan, Mitchell O'Brien, Joshua Storm Caley, Keiran Rowell, Cameron Hyde, Thomas Litfin]
---

### Details:
## Details

- Structure prediction software often natively supports single predictions.
- Specific workflows can re-use MSA input to massively improve efficiency over naive implementation.
Expand All @@ -15,18 +15,18 @@ contributors: [Ziad Al-Bkhetan, Mitchell O'Brien, Joshua Storm Caley, Keiran Row

This activity involves developing optimized batch workflows for structure prediction.

### Completed:
### Completed

- [x] Add support for re-using MSAs to Galaxy Australia AlphaFold2 service.
- Add support for re-using MSAs to Galaxy Australia AlphaFold2 service.

### In Progress:
### In Progress

- [ ] Add local implementation of batch colabfoldsearch to the nfcore [proteinfold](https://nf-co.re/proteinfold/1.1.1) pipeline.
- [ ] Add mmseqs-GPU support to the nfcore [proteinfold](https://nf-co.re/proteinfold/1.1.1) pipeline.
- [ ] Add boltz interaction screening workflow to screen multiple potential partners against a protein (re-using MSA for anchor protein).
- [ ] Add option for extreme replicate sampling for AlphaFold2.
- Add local implementation of batch colabfoldsearch to the nfcore **[proteinfold](https://nf-co.re/proteinfold/1.1.1)** pipeline.
- Add mmseqs-GPU support to the nfcore **[proteinfold](https://nf-co.re/proteinfold/1.1.1)** pipeline.
- Add boltz interaction screening workflow to screen multiple potential partners against a protein (re-using MSA for anchor protein).
- Add option for extreme replicate sampling for AlphaFold2.

### Future:
### Future

- [ ] Develop Galaxy workflow to take advantage of re-using MSAs.
- [ ] Add stoichiometry screening workflow to the nfcore [proteinfold](https://nf-co.re/proteinfold/1.1.1) pipeline.
- Develop Galaxy workflow to take advantage of re-using MSAs.
- Add stoichiometry screening workflow to the nfcore **[proteinfold](https://nf-co.re/proteinfold/1.1.1)** pipeline.
36 changes: 20 additions & 16 deletions pages/activities/bindcraft_access.md
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@@ -1,31 +1,35 @@
---
title: Community Access to BindCraft
type: activity_inprogress
type: activity_in_progress
contributors: [Ziad Al-Bkhetan, Thomas Litfin]
---

### Details

## Details

- [BindCraft](https://github.com/martinpacesa/BindCraft) is an end-to-end solution for protein binder design.
- BindCraft was widely used by participants in a recent blind evaluation ([Adaptyv Bio](https://www.adaptyvbio.com/blog/po104)) of protein binder design tools.
- BindCraft was widely used by participants in a recent blind evaluation (**[Adaptyv Bio](https://www.adaptyvbio.com/blog/po104)**) of protein binder design tools.
- Several independent groups generated de novo designed binders with competitive affinity to the natural ligand using the BindCraft tool.
- BindCraft tool is available within a NextFlow [workflow](https://github.com/Australian-Structural-Biology-Computing/bindflow) to support portable deployment.
- BindCraft tool is available within a NextFlow **[workflow](https://github.com/Australian-Structural-Biology-Computing/bindflow)** to support portable deployment.

{% include callout.html type="warning" content="Native BindCraft tool requires PyRosetta as a filter with non-commercial license." %}


### Completed

:warning: Native BindCraft tool requires PyRosetta as a filter with non-commercial license
- Wrap the BindCraft tool in a Nextflow workflow (**[bindflow](https://github.com/Australian-Structural-Biology-Computing/bindflow)**).
- Add support for parallel execution across multiple GPUs.
- Negotiate PyRosetta license for non-commercial use at NCI.
- Output partial results when HPC scheduler jobs time out.

### Completed:

- [x] Wrap the BindCraft tool in a Nextflow workflow ([bindflow](https://github.com/Australian-Structural-Biology-Computing/bindflow)).
- [x] Add support for parallel execution across multiple GPUs.
- [x] Negotiate PyRosetta license for non-commercial use at NCI.
- [x] Output partial results when HPC scheduler jobs time out.
### In Progress

### In Progress:
- Install workflow at NCI.
- Release BindCraft fork without PyRosetta dependency.
- Release BindCraft fork with open-source replacements for PyRosetta filters.

- [ ] Install workflow at NCI.
- [ ] Release BindCraft fork without PyRosetta dependancy.
- [ ] Release BindCraft fork with open-source replacements for PyRosetta filters.

### Future:
### Future

- [ ] OpenOnDemand app for running BindCraft from a graphical web interface.
- OpenOnDemand app for running BindCraft from a graphical web interface.
2 changes: 1 addition & 1 deletion pages/activities/binder_access.md
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@@ -1,6 +1,6 @@
---
title: Exploring how to increase access to RFdiffusion
type: activity_inprogress
type: activity_in_progress
---

A collaborative activity bringing together members of the computational structural biology community, infrastructure providers, and the Australian BioCommons, in order to determine how to increase access to binder code (e.g. RFdiffusion) for life science researchers.
29 changes: 16 additions & 13 deletions pages/activities/infrastructure_roadmap.md
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@@ -1,26 +1,29 @@
---
title: Infrastructure Roadmap
type: activity_inprogress
type: activity_in_progress
---

### Details:
## Details

The infrastructure roadmap document describes the existing national landscape, identifies and prioritizes critical research bottlenecks, and proposes a national strategy to unlock the immense potential of computational structural biology for Australian researchers.

### Completed:
### Completed

- [x] Initial draft of infrastructure roadmap.
- [x] Initial community feedback incorporated, content updated, implementation section added.
- [x] Review and updates based on feedback from co-authors and academic panel.
- [x] Review and updates based on feedback from community and BioCommons infrastructure partners.
- [x] Review and updates based on feedback from international experts.
- Initial draft of infrastructure roadmap.
- Initial community feedback incorporated, content updated, implementation section added.
- Review and updates based on feedback from co-authors and academic panel.
- Review and updates based on feedback from community and BioCommons infrastructure partners.
- Review and updates based on feedback from international experts.

### In Progress:
- [ ] Addressing final review comments.
### In Progress

### Future:
- [ ] Publication to Zenodo.
- Addressing final review comments.

### Future

- Publication to Zenodo.

### Contributors

### Contributors:
- Australian Structural Biology Computing Community
- Australian BioCommons and infrastructure partners
15 changes: 8 additions & 7 deletions pages/activities/nci_data_collections.md
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@@ -1,10 +1,10 @@
---
title: NCI Data Collection
type: activity_inprogress
type: activity_in_progress
contributors: [Matthew Downton, Kisaru Liyanage, Wenjing Xue, Joshua Storm Caley, Thomas Litfin]
---

### Details
## Details

- Structure prediction requires constructing multiple sequence alignments of homologous sequences from large reference databases.
- Different tools use different versions of the same reference databases with different naming conventions. This leads to excessive duplication and data bloat.
Expand All @@ -13,10 +13,11 @@ contributors: [Matthew Downton, Kisaru Liyanage, Wenjing Xue, Joshua Storm Caley

This activity aims to create a stable release of up-to-date reference data (with DOI) to support reproducible structure prediction workflows.

### Completed:
### Completed

- [x] Catalog latest version of reference data.
- [x] Harmonize data across different structure prediction models (AlphaFold2, AlphaFold3, Boltz, ColabFold, HelixFold3, RosettaFold-AA).
- Catalog latest version of reference data.
- Harmonize data across different structure prediction models (AlphaFold2, AlphaFold3, Boltz, ColabFold, HelixFold3, RosettaFold-AA).

### In Progress:
- [ ] NCI Data Collection EOI.
### In Progress

- NCI Data Collection EOI.
19 changes: 11 additions & 8 deletions pages/activities/nci_ood_proteinfold.md
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@@ -1,24 +1,27 @@
---
title: OpenOnDemand GUI ProteinFold app
type: activity_inprogress
type: activity_in_progress
contributors: [Matthew Downton, Kisaru Liyanage, Wenjing Xue, Joshua Storm Caley, Keiran Rowell, Thomas Litfin]
---

### Details:
## Details

- Numerous structure prediction methods are available via the command line.
- Web services with graphical interfaces are freely available with limited capacity.
- OpenOnDemand provides a simple graphical interface to HPC systems.
- Several institutional HPCs have an OpenOnDemand deployment (eg KOD @ UNSW, ARE @ NCI).
- Several institutional HPCs have an OpenOnDemand deployment (e.g. KOD @ UNSW, ARE @ NCI).

### Completed:
- [x] Pilot app developed and hosted on Katana at UNSW.
### Completed

- Pilot app developed and hosted on Katana at UNSW.

### In Progress
- [ ] Adapt pilot ProteinFold app for ARE at NCI.

### Future:
- [ ] Add support for more optional settings in web form interface.
- Adapt pilot ProteinFold app for ARE at NCI.

### Future

- Add support for more optional settings in web form interface.

<figure>
<img src= "images/activities/ood-proteinfold.png" alt="KOD-proteinfold" style="border: 4px solid black; width: 50%; height: 50%">
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26 changes: 13 additions & 13 deletions pages/activities/nfcore_proteinfold.md
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---
title: nf-core ProteinFold v2.0 Release
type: activity_inprogress
type: activity_in_progress
contributors: [Ziad Al-Bkhetan, Mitchell O'Brien, Joshua Storm Caley, Keiran Rowell, Thomas Litfin]
---

### Details:
## Details

- Molecular structure prediction tools require large reference databases and varied computational infrastructure.
- Nextflow provides the tools to standardize workflows for portable and optimized deployment.
Expand All @@ -14,17 +14,17 @@ contributors: [Ziad Al-Bkhetan, Mitchell O'Brien, Joshua Storm Caley, Keiran Row

### Completed

- [x] Config optimized for efficient utilization for Gadi at NCI.
- [x] Add RosettaFold-All-Atom.
- [x] Add HelixFold3.
- [x] Add Boltz-1.
- [x] Add AlphaFold3 (BYO weights).
- [x] Add support for local MSA search for Boltz-1.
- [x] Add standardized reporting with visualisation.
- [x] Add support for quality metrics in output reporting.
- [x] Add process labels to improve efficient use of infrastructure.
- Config optimized for efficient utilization for Gadi at NCI.
- Add RosettaFold-All-Atom.
- Add HelixFold3.
- Add Boltz-1.
- Add AlphaFold3 (BYO weights).
- Add support for local MSA search for Boltz-1.
- Add standardized reporting with visualisation.
- Add support for quality metrics in output reporting.
- Add process labels to improve efficient use of infrastructure.

### In Progress

- [ ] Add minituare reference databases for fast troubleshooting.
- [ ] De-duplicate reference datasets across different methods.
- Add minituare reference databases for fast troubleshooting.
- De-duplicate reference datasets across different methods.
27 changes: 15 additions & 12 deletions pages/activities/nfcore_proteinfold_pawsey.md
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@@ -1,24 +1,27 @@
---
title: nf-core ProteinFold at Pawsey
type: activity_inprogress
type: activity_in_progress
contributors: [Sarah Beecroft, Joshua Storm Caley]
---

### Details:
## Details

- Deep Learning models work natively with NVIDIA hardware.
- Setonix at Pawsey contains a large number of AMD GPUs.
- Models can be made to work with AMD hardware available at Pawsey.

### Completed:
- [x] Build AMD compatible container for AlphaFold2.
- [x] Build AMD compatible container for Boltz-1.
- [x] Build AMD compatible container for ESMFold.
### Completed

### In Progress:
- [ ] Adapt containers for compatibility with nfcore proteinfold.
- [ ] Test nfcore proteinfold workflow at Pawsey.
- Build AMD compatible container for AlphaFold2.
- Build AMD compatible container for Boltz-1.
- Build AMD compatible container for ESMFold.

### Future:
- [ ] Build AMD compatible container for Boltz-2.
- [ ] ProteinFold config optimized for Pawsey.
### In Progress

- Adapt containers for compatibility with nf-core proteinfold.
- Test nfcore proteinfold workflow at Pawsey.

### Future

- Build AMD compatible container for Boltz-2.
- ProteinFold config optimized for Pawsey.
6 changes: 3 additions & 3 deletions pages/activities/protein_design_seminars.md
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@@ -1,17 +1,17 @@
---
title: Protein Design Seminar Series (2025)
type: activity_inprogress
type: activity_in_progress
contributors: [Rhys Grinter, Gavin Knott, Cyntia Taveneau, Josh Hardy, Kate Michie, Johan Gustafsson, Melissa Burke]
---
<!-- TODO: Add Richard Birkinshaw -->

### Details
## Details

- Computational protein design can produce synthetic proteins that disrupt the function of a target protein.
- Australian community members are actively using protein design technology to solve biological problems.
- Community members will host a monthly seminar series to share knowledge on protein design strategies to get the best outcomes from protein design projects.

Registration is available [here](https://www.eventbrite.com.au/e/webinar-leveraging-deep-learning-to-design-custom-protein-binding-proteins-tickets-1414347163439?aff=oddtdtcreator)
Registration is **[available here](https://www.eventbrite.com.au/e/webinar-leveraging-deep-learning-to-design-custom-protein-binding-proteins-tickets-1414347163439?aff=oddtdtcreator)**.

| Date | Time | Speaker(s) | Topic |
|---------------|------------|--------------------|-------|
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2 changes: 1 addition & 1 deletion pages/contributors.md
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@@ -1,7 +1,7 @@
---
title: Community contributors
page_id: contributors
type: resources
#type: resources
---

The projects included here represent a joint effort by the following people at multiple Australian institutions:
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2 changes: 1 addition & 1 deletion pages/external_resources.md
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Expand Up @@ -2,7 +2,7 @@
title: External Resources
page_id: external_resources
#datatable: true
type: resources
#type: resources
---

<!-- {% include resource-table-all.html %} -->
2 changes: 1 addition & 1 deletion pages/guides.md
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Expand Up @@ -2,7 +2,7 @@
title: How-to Guides
description: How-to Guides for the use of deep learning methods in structural biology.
page_id: guides
type: resources
#type: resources
datatable: true
---

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