楼主: vmzy

[独立平台] [生命科学类] Folding@Home

发表于 2020-7-1 13:59:33 | 显示全部楼层
Related Articles
The SARS-CoV-2 nucleocapsid protein is dynamic, disordered, and phase separates with RNA.
bioRxiv. 2020 Jun 18;:
Authors: Cubuk J, Alston JJ, Incicco JJ, Singh S, Stuchell-Brereton MD, Ward MD, Zimmerman MI, Vithani N, Griffith D, Wagoner JA, Bowman GR, Hall KB, Soranno A, Holehouse AS
The SARS-CoV-2 nucleocapsid (N) protein is an abundant RNA binding protein that plays a variety of roles in the viral life cycle including replication, transcription, and genome packaging. Despite its critical and multifunctional nature, the molecular details that underlie how N protein mediates these functions are poorly understood. Here we combine single-molecule spectroscopy with all-atom simulations to uncover the molecular details that contribute to the function of SARS-CoV-2 N protein. N protein contains three intrinsically disordered regions and two folded domains. All three disordered regions are highly dynamic and contain regions of transient helicity that appear to act as local binding interfaces for protein-protein or protein-RNA interactions. The two folded domains do not significantly interact with one another, such that full-length N protein is a flexible and multivalent RNA binding protein. As observed for other proteins with similar molecular features, we found that N protein undergoes liquid-liquid phase separation when mixed with RNA. Polymer models predict that the same multivalent interactions that drive phase separation also engender RNA compaction. We propose a simple model in which symmetry breaking through specific binding sites promotes the formation of metastable single-RNA condensate, as opposed to large multi-RNA phase separated droplets. We speculate that RNA compaction to form dynamic single-genome condensates may underlie the early stages of genome packaging. As such, assays that measure how compounds modulate phase separation could provide a convenient tool for identifying drugs that disrupt viral packaging.
PMID: 32587966 [PubMed]

 楼主| 发表于 2020-9-2 10:49:54 | 显示全部楼层
New CPU GRO_A8 core for FAH with p16810
Postby sperezconesa » Tue Sep 01, 2020 5:42 pm

We have just released CPU FahCore_a8 0.0.6 to FAH!

This new CPU FahCore_a8 updates the FahCore from GROMACS 5 (FahCore_a7) to GROMACS 2020. This will provide substantial gains in efficiency of WU production! Specifically, we have been observing that FahCore_a8 runs noticeably faster than FahCore_a7; in tests, FahCore_a8 runs about 50% faster on recent CPUs that support AVX2 and FMA, and still 5-15% on older ones, with the bigger boosts seen in Windows. These are big optimizations that should make a significant difference for our research while better utilizing donor's existing hardware!

Testing this core will help new future CPU Projects such that researcher's science output will be increased significantly on existing hardware. It is a project based on the SARS-CoV-2 E protein which is an ion channel for which we will computationally study its electrophysiology.

- Improvements in MD algorithm with going to GROMACS 2020: update groups for neighbour lists, optimized SIMD, dual list dynamic pruning, use of OMP threading...
- Production of xtc rather than trrs to save space and potentially change to tng in the future.
- Boosts in TPF ranging from 7%-60% depending on project and system.
- Improvements in hardware accelerators: New FahCore_a8 has been updated to latest GROMACS code which now makes use of AVX2 instructions on modern CPUs.
- New way of generating gens in project.xml.

- Problems with pause/unpause.
- The viewer only showed a single chain, now it solves them all.
- For the moment, the core only supports ntmpi=1. We have found some problems with ntmpi > 1 which we hope to fix in the near future.
In addition to this, the hybrid CPU/GPU MD strategy of GROMACS could potentially enable a mixed CPU/GPU core in the future.
Please post here if you notice any issues!
发布新cpu计算内核FahCore_a8 0.0.6
 楼主| 发表于 2020-11-25 10:09:37 | 显示全部楼层
November 23, 2020
by Emma

Hello Folders! We’ve been made aware of a potential issue for users who are using certain advanced manual configuration options for remote client management using fah-control. We actively recommend against this sort of remote management, so the issue affects less than 1% of our user base, and only under very specific conditions. Even so, in the interest of being transparent and not alarming our users, we are making this blog post to prevent confusion.

The issue is limited to the small subset of users that manually configured the client and their network to allow remote client management, and are using fah-control to connect over an untrusted network to a remotely accessible client port.

In those specific circumstances, if an attacker on the untrusted network could perform a PITM (person-in-the-middle) attack and actively manipulate network traffic, they would be able to remotely execute code in the context of the user running the fah-control GUI. The actual Folding@home client on the remote machine would not be affected, but the system running the fah-control GUI itself could be affected.

If you currently perform the manual steps described and may be affected, we recommend you update to client version v7.6.20 or later. These versions have the fix applied and are no longer affected.

It is also important to point out that manually configuring fah-control to manage remote clients is not recommended when used over an untrusted network. If you need to do this remotely over the public internet, we recommend using a VPN or similar method of extending a trusted network between two locations.

We would also like to thank the researchers that brought this to our attention.

Thanks to Rutger Beltman:

Also to Axel Koolhaas:

We greatly appreciate you both taking time to review some of our open source code and help us through responsible and coordinated disclosure practices.

For anyone else out there who would like to report any potential security concerns, please refer to our contact page at the below link. We may be updating it in the near future with improved security contact information, and our policies and preferences around reporting security vulnerabilities.

Folding@home Security Contact Details:
 楼主| 发表于 2021-11-15 09:37:07 | 显示全部楼层
本帖最后由 vmzy 于 2021-11-27 18:56 编辑

core22 0.0.18 widespread rollout on Mon 15 Nov
by JohnChodera » Sun Nov 14, 2021 1:22 pm

Hi all!

We're planning to roll out core22 0.0.18 to all FAH projects on Mon 15 Nov.

This version is built from OpenMM 7.6.0, the latest and most performant release of OpenMM:

We have used CUDA Toolkit 11.2 for these builds in order to support the latest, fastest NVIDIA GPUs. This may result in older GPUs or drivers that are no longer supported by CUDA 11.2 to fall back to OpenCL instead; you may need to update your NVIDIA driver to one that supports CUDA 11.2 (linux >= 460.32.03, windows >=461.09) if this happens.

We broke CUDA support for the Linux core build in 0.0.16 by not including trailing version digits on shipped CUDA shared libraries. This has now been fixed.

Huge thanks to David Dotson, Peter Eastman, and all the FAH volunteers who helped us test this release!

~ John Chodera // MSKCC
GPU计算内核core22,将在11月15号(周一)正式升级至0.0.18版。该版本将OpenMM内核升级至最新的7.6.0版,支持CUDA Toolkit 11.2。
请大家注意升级驱动(linux >= 460.32.03,linux glibc>=2.17, windows >=461.09),否则计算内核会因为驱动问题,自动退出cuda模式切至OpenCL模式。
 楼主| 发表于 2022-8-1 09:46:09 | 显示全部楼层
AMD RX6000+ family GPU owners, please update to 22.7.1 drivers for optimal F@H performanceby muziqaz » Wed Jul 27, 2022 5:42 pm ... 673252c6c548bcaeec0

as cs9k already reported in another thread, AMD finally fixed OpenCL performance with their latest driver version (22.7.1).
Until today majority of RX6000 series GPUs were folding at ~50% of it's capabilities and the last driver which was still offering good performance was 21.3.2, which was not compatible with majority of RX6000 series GPUs. Now your RDNA2 GPUs can match nVidia OpenCL performance with 22.7.1.

If you have older AMD GPUs, you can keep folding on 21.3.2 or older.

For those wondering how much you will gain? Your PPD pretty much will double, or even triple in certain scenarios.
If you are seeing 2.5-5m PPD with your 6800/6900xt GPUs, that means new driver is working for you.

Good luck, and thank you for your contribution
 楼主| 发表于 5 天前 | 显示全部楼层
November 30, 2023
by Greg Bowman

When it comes to designing novel drugs, achieving specificity is a major challenge. An effective drug must bind tightly to its target protein while avoiding unwanted side effects that can result from interactions with other proteins. This challenge becomes even more complex when targeting specific members of protein families with similar structures. Additionally, some enzymes share substrates, like ATP, across various protein families, making it difficult to design compounds that compete with endogenous ligands without causing off-target effects.

One innovative approach to drug design is targeting allosteric sites rather than active sites. Allosteric compounds can enhance desirable protein functions, offering a unique way to achieve specificity. These sites are often less conserved than active sites, making it easier to develop specific drugs. In recent years, highly specific allosteric compounds have been serendipitously discovered through high-throughput screens, targeting various proteins such as G-protein-coupled receptors, myosins, kinases, and β-lactamases. Despite these successes, designing drugs that target allosteric sites from scratch is challenging because experimental structural studies often provide limited insights into a protein’s conformational landscape.

One specific area of interest is myosins, a superfamily of ATPases that play crucial roles in various cellular processes. Myosins have the potential to be valuable drug targets for numerous diseases, but their complexity and the existence of multiple isoforms make targeting specific myosin variants extremely difficult. For instance, there are 38 myosin genes in the human genome, and individual cells express about 20 different myosin isoforms. Compounds like mavacamten have shown promise in clinical trials for heart-related conditions, but there is a need for more myosin modulators to address a broader range of diseases. However, the challenge lies in targeting specific myosin isoforms due to their highly conserved motor domain fold and active site structure.

Figure caption: Structure of a myosin protein highlighting the binding sites of some known allosteric modulators, including blebbistatin.
Blebbistatin, a myosin-II specific allosteric inhibitor, has been a subject of study to understand the molecular mechanisms governing drug specificity. It was discovered in a high-throughput screen targeting nonmuscle myosin IIs and was found to broadly inhibit various myosin-II isoforms while sparing other myosin families. The key to its selectivity lies in the dynamics of the blebbistatin pocket and the conformations myosin isoforms adopt in solution.

Through all-atom molecular dynamics simulations, this study has shown that the probability of the blebbistatin pocket opening is higher in more sensitive myosin isoforms, which explains differences in drug potency. This finding, along with differences in the pocket’s residue composition, provides insights into the factors contributing to drug specificity. These results demonstrate the role of pocket dynamics and conformational selection in achieving drug specificity and highlight the potential for precision medicine through computational modeling.

In conclusion, the study of blebbistatin sheds light on the intricate world of drug specificity in the realm of myosin inhibitors. It emphasizes the importance of understanding the dynamic interplay between drug molecules and protein structures. This knowledge has the potential to open doors to more precise drug design, allowing us to target specific isoforms and improve the effectiveness of therapeutic interventions. As the field of precision medicine advances, computational modeling and simulations like the ones used in this study offer promising opportunities to tailor treatments to individual patients and address a wide range of diseases with unprecedented specificity.

WCG Team
作者 格雷格·鲍曼





通过全原子分子动力学模拟, 这项研究结果表明,在更敏感的肌球蛋白异形体中,布比他汀口袋开口的概率更高,这解释了药物效力的差异。这个发现,以及口袋里残基成分的差异,提供了对药物特异性的因素的深入了解。这些结果说明了口袋动力学和构象选择在实现药物特异性方面的作用,并通过计算建模强调了精密医学的潜力。

您需要登录后才可以回帖 登录 | 新注册用户



小黑屋|手机版|Archiver|中国分布式计算总站 ( 沪ICP备05042587号 )

GMT+8, 2023-12-6 08:24

Powered by Discuz! X3.4

© 2001-2017 Comsenz Inc.

快速回复 返回顶部 返回列表