Help find a cure for COVID-19, Cancer, Ebola, AIDS, and other stuff

Is Rogers Cable their ISP??? :crazy_face:

Show’s over, folks! Move along! Nothing to see here!

Smash it with your hulk hands!!!

text and diagram

Research update from the SCC team

A short research update from the Smash Childhood Cancer team


Project: Smash Childhood Cancer

Published on: 27 Jul 2022


Dear volunteers, we have received some insightful research news from the Smash Childhood Cancer team that we would like to share with you! During the restart process, the researchers at SCC have been hard at work discovering more ways to prevent cancer among children, and we can’t wait to assist them in their research soon. Here is what they shared with us:

“β-catenin (CTNNB1) is an important part of the Wnt/β-catenin signaling pathway, which is involved in the regulation of embryonic development and maintenance of organs and tissues. Activation of Wnt/β-catenin signaling cascade inhibits degradation of β-catenin, which in turn stimulates transcription of downstream target genes.

Abnormal activation of β-catenin signaling is found in >70% of colorectal cancers and several pediatric tumors such as hepatoblastoma and craniopharyngioma. Activated β-catenin promotes cancer cell proliferation, survival and migration.
Therefore, targeting β-catenin strategies have been attempted by researchers but no definite effective options are available yet. Identifying specific inhibitors against β-catenin protein binding domains is one of our projects in Smash Childhood Cancers program. Tyuji Hoshino has synthesized >150 chemical compounds targeting β-catenin binding sites based on the information generated by the massive computer network donated by the volunteers. Ching Lau and Godfrey Chan have been verifying the in vitro and in vivo activities of some of the novel compounds generated, with the intention of possible clinical translation in the future.”

Adapted from Bubus 12, Wikipedia (June 2013)
Adapted from Bubus 12, Wikipedia (June 2013)

Thanks for reading!

The World Community Grid team

1 Like

Rain in Africa
Posts on Facebook

Just because I like you guys so much and don’t want you to injure a finger clicking on that link, I’ll post the text of it here:

Here’s the monthly update on World Community Grid points:

Statistics last updated: 2/27/22 23:59:59 (UTC) [3,690 hour(s) ago]

#N/A

Available WCG Projects

#NULL!

WCG discussion forums can be found here .

Here’s the monthly update on Folding@Home points:

                          Monthly
Name            Credit     Change
1695814     23,506,151  2,145,069
Celalta      6,419,290  1,353,412
Breadmaker   3,414,429     57,983
GoA_Kenny    3,177,692    613,789

Typical Folding@Home Projects

COVID-19
Alzheimer’s
Cancer
Huntington’s
Parkinson’s
For a comprehensive list see https://apps.foldingathome.org/psummary

If you’d like to join us in finding a cure for COVID-19, Cancer, Ebola, AIDS, and other stuff, see the OP ( <-- clicky clicky! ) for links to get the downloads

Help Stop TB update…

full article text

Interview with Help Stop TB team

Learn about the current state and future plans of Help Stop TB through this brief interview


Project: Help Stop TB

Published on: 4 Aug 2022


Dear volunteers, Help Stop Tuberculosis team has been collaborating with World Community Grid for nearly two years, and has produced life-saving research results thanks to you. We hope you find this interview-style article informative and answer all of the questions you may have about their research!


What does your project aim to do?

Our project aims to study the structural and organizational properties of Mycolic Acids: very long fatty acids integral to TB’s drug resistance. Mycolic Acids are far longer than many other lipids, allowing them to fold into complex structures that a regular fatty acid could not. Mycobacterium tuberculosis bacteria use these complex structures to create a near impenetrable cell wall by fitting Mycolic Acids together like puzzle pieces, preventing drugs and our immune cells from doing their jobs effectively.

We create simulations of Mycolic Acids folding over time to map out their folding behavior and understand how the shapes they adopt change the properties they display - however, to do this we need to generate hundreds of potential combinations of different acids, under different temperature and solvent conditions. This is where the World Community Grid is essential, as such large-scale simulations and analysis would not be possible without the help of many volunteers to provide the computing power.

Our work comes with a range of exciting potential future applications: Firstly, understanding how Mycolic Acids strengthen the cell wall will enable more informed drug design. If we know how it works, we can learn how to break it! Secondly, we can use the knowledge gained on the Mycolic Acids to design our own resilient cell walls (for example in industrially-used microbes to make them more robust), and more broadly to benefit research into other highly flexible and “bendy” molecules.

How was the project affected by the WCG downtime period?

The downtime has allowed us to consolidate the data computed by WCG thus far, and allowed us to further develop the ideas for new aspects of the research, including our own “wiggle parameter” to describe the flexibility of the molecules. We’ve also had an integral and valued team-member, Christof Jäger, leave the project for new pastures, so we have been carefully planning our next steps to accommodate this loss.

What has your research achieved so far?

Through the volunteers’ help, we have one of the largest flexible molecular dynamics data sets and have made rapid progress on understanding highly challenging dynamic systems. This opens up new uses for machine learning and provides different perspectives on the problem of clustering data - a major difficulty at present. It offers us the potential for new perspectives on other exciting chemical systems that have been to date difficult to analyze due to their dynamics, such as intrinsically disordered proteins.

What can the volunteers do?

We appreciate the support and enthusiasm of the volunteers in the forums - the moral support is invaluable when the science gets challenging. Volunteers can always help further when they raise awareness in the community of the valuable WCG projects and their wider impact. This is particularly important for our project as we are seeing a resurgence of TB worldwide on the back of the COVID pandemic. Here, education on how harmful the disease can be, why we are seeing antibiotic resistance, and the importance of global vaccination programmes is key.

Are there any expansions or new projects being considered for the near future?

On the back of the new analytical tools we have been developing with the current dataset, we are considering expanding our molecules to the pathogenetically important cord-factors - medically important derivatives of the mycolic acids we have already looked at. This will provide additional insight into how the chemical coupling of mycolic acids changes their behavior and allows us to further develop our ideas around cell-wall models for TB.


Thank you to Dr. Anna K. Croft for your contribution, as well as the rest of the HSTB team for their part in building a better world.

The World Community Grid team

While waiting for this thing to go somewhere, I decided to shift priority and help find amicable numbers.
However I started noticing that at times when I was watching youtube or even a movie in my computer’s DVD, occasionally the video would lag. My bro-in-law advised I watch on Task manager and sure enough the next time it happened a program named Amicable v3_03 popped up and hogged all my CPU resources for about 10 seconds. This was annoying so I uninstalled BOINC; perhaps I will reinstall it when things get moving, but I thought this was odd.

1 Like

From the big book of faces:

In addition to the bug report, that link basically tells you that they’re sending out projects in small batches…artisanally crafted…

[brings up boinc…ctrl+shift+esc…]

Holy enya, I have work units running.

Makin’ it :cloud_with_rain:…makin’ it :cloud_with_lightning_and_rain:…in :earth_africa:!!!

1 Like

Another “be patient “ update…

https://www.worldcommunitygrid.org/forums/wcg/viewthread_thread,44260

1 Like

OOOOH!!! OOOOOOH!!! IT’S LETTING ME DOWNLOAD SOME WORK UNITS!!!

ETA: Download was not completely successful. Prolly gonna have to delete what I did get. Me sad.

ETA: Download was successful: it was just a wee bit s-l-o-ww… :slight_smile:

1 Like

I was in my cool basement as usual and wondered why the thermometer in my office area was registering 74 degrees instead of the 71 I was used to seeing recently; lo and behold sometime in the last 24-48 hours I was running tasks again. I forgot that my computer seconds as a space heater!

1 Like

Got some more work units on the weekend. I sent back an ARP ‘cause it was gonna take waaaay too fluffin’ long!!

1 Like

Yeah, I’ve got ARP & Cov19 from WCG on the ol’ laptop…nothing on my desktop, but that one’s cranking away on foldingathome.

epic beard...okay, maybe not "epic" but it's a beard.

Project 18402

Disease Type: cancer

Can molecular simulation be used for virtual affinity-maturation of de novo designed protein binders? That’s the question this project aims to address. The Bahl Lab at the Institute for Protein Innovation has had some amazing success using computational design to develop high-affinity mini-proteins that can inhibit protein targets by tightly binding to them. In practice, the current approach requires the experimental screening of thousands of computational designs to discover a few tight binders, and similarly expensive experimental screens to optimize their binding (i.e. “affinity maturation”). If we can make more accurate predictions of how sequence mutations affect binding affinity, we may be able to offload this expensive task to computers, boosting the efficiency of these efforts considerably.

In this project, we use relative free energy calculations to predict how single-point mutations of a computationally designed mini-protein alter the binding affinity to the periplasmic protease LapG, an important regulator of bacterial biofilm formation. These predictions will be compared to high-throughput experimental measurements of binding affinity provided by the Bahl lab. An important end goal of this work is to develop new classes of inhibitors to make antibiotic therapies more successful.

This project is managed by at Temple University.

![](data:;base64, 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)

Dr. Voelz’s research focuses on using new simulation methods to understand and design molecular function, by modeling the folding and binding properties of proteins, peptides, and peptidomimetics. The Voelz Lab participates in the Folding@home project, hosting eight servers at Temple University.

Thanks for starting this great thread! Speaking about cancer, I’ve recently ran into an interesting article about a deworming drug that is believed to have good results in cancer treatment. Fenbendazole, also known as Panacur C, is an anti-parasitic drug used to treat a variety of parasites in dogs, including cancer. There is a lot of potential for fenbendazole (fenbendazole.org) to be used as an anticancer medication in humans. The findings from the studies done so far are very promising and suggest that this drug could be used to enhance current cancer treatments or even help develop new ones. This is an exciting area of research that warrants further exploration.

2 Likes

Here’s the monthly update on World Community Grid points:

Statistics last updated: 8/30/22 23:59:59 (UTC) [26 hour(s) ago]

#N/A

Available WCG Projects

#NULL!

Even though my computer is running some WCG tasks right now, I don’t seem to be collecting points, so I’ll leave the above summary as-is until that changes.

WCG discussion forums can be found here .

Here’s the monthly update on Folding@Home points:

                          Monthly
Name            Credit     Change
1695814     25,007,411  1,501,260
Celalta      7,579,641  1,160,351
Breadmaker   3,468,298     53,869
GoA_Kenny    3,492,253    314,561

Typical Folding@Home Projects

COVID-19
Alzheimer’s
Cancer
Huntington’s
Parkinson’s
For a comprehensive list see https://apps.foldingathome.org/psummary

If you’d like to join us in finding a cure for COVID-19, Cancer, Ebola, AIDS, and other stuff, see the OP ( <-- clicky clicky! ) for links to get the downloads

Obviously, not a gif certificate:

The World Community Grid website is temporarily down due to an expired security certificate. We will notify you when the issue has been resolved.

tweet tweet

The computer that was running folding tasks was a laptop that I’m not using much anymore and as a result it’s no longer completing tasks. My desktops are up and running on WCG tasks now that the migration to Krembil is complete.

2 Likes

From the WCG forum:
https://www.worldcommunitygrid.org/forums/wcg/viewthread_thread,44311_offset,0#676412

text of the post

Hi everyone,

Some good news to share before the weekend. Our data centre was able to fix some of the networking issues that should help us to stabilize the flow of workunits from the data centre to your devices. We ultimately aim to prevent the transient issues that have been the most commonly reported bug from volunteers during the testing phase and prevent further interruptions to the supply of workunits available to our volunteers.

Working with personnel at the data centre, our engineers were able to find a temporary workaround for the networking issue whereby migrating VMs to dedicated physical hosts with a previously configured virtualized interface to the VLAN; thus, the switch that provides access to the storage layer of the WCG was successful in connecting additional VMs to the storage layer. Oversubscribing some of these new VMs that will join the production Aurora/Mesos cluster to the physical resources of the bare metal hosts allowed us to fit the VMs, and will increase the overall capacity of the workunit processing backend by roughly ~45%. This will provide an additional upload/download server to help mediate the issues reported by volunteers in awaiting download/upload of workunits (and reduce the manual workarounds we had to do to make workunits available again).

Currently, we are running diagnostics on these servers, and will put them into service as part of the production Aurora/Mesos cluster as soon as we are finished. The oversubscription to the physical resources of the host should not affect the performance of the VMs, as the newly migrated VMs we are putting into service were co-located specifically with VMs that use those resources intermittently or sparingly (Build Servers, DevOps, internally hosted apps, etc.)

It may seem like a small advance - but besides directly helping with the workunit management - this will also free up some time for our tech team to finish other pressing challenges, and brings us closer to a more stable WCG.

Thank you for your support, patience and understanding.

  • WCG team
what I actually read/heard

Charlie Brown Teacher Speaking - YouTube

1 Like

From email:

Dear 1695814,

We hope you’re keeping up with everything that’s happened recently with World Community Grid projects. And we hope you’re able to begin contributing soon!

You can contact us at support@worldcommunitygrid.org with any questions.

Thanks for your support!

The World Community Grid team

…but I don’t see any “breaking news “ so I’m not sure what that was all about.