#Protein-protein interaction

[cbirt]

The molecular surface of a protein is represented in the form of geometric and chemical attributes that create the unique fingerprint for identifying protein interaction. Geometric deep-learning-based algorithms can be used to analyze these fingerprints, which can help researchers design new computational tools to study Protein interactions.

Inferring protein-protein interactions (PPIs) solely from their structural information remains a major issue in the field of proteomics. The unavailability of tools and techniques to understand the mechanism of protein interaction has been a great hindrance in designing antibodies and regents with an affinity for selected target proteins.

One of the problems faced by researchers studying protein-protein interactions is generating a protein sequence that can bind to the target protein and form a complex structure. The synthesized protein sequence is known as a protein binder. The availability of several tools like AlphaFold has helped researchers design and predict protein-protein interactions to some extent. But protein binder design is a relatively less researched field.

Scientists have tried to overcome this problem by developing a neural network-based tool that considers proteins as surfaces and learns from the geometric and chemical attributes present on the protein surface. It can determine the probability of an interaction between two protein molecules. The recognition of a molecular surface is based on its geometric and chemical constraints, which are interdependent but reciprocal in nature. Geometric constraints result from van der Waals interactions, and chemical constraints arise due to hydrophobic and electrostatics interactions within the protein complex structure.

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[golden--doodler]

These two were so silly in the latest episode, so I had to draw them. I just absolutely loved Jimmy Jr. offering Tina a nugget, so I had to make him even more aggressive about it 😭

[ID]: Digital fanart of Tina Belcher and Jimmy Pesto Jr. from Bob’s Burgers. They can be seen from the waist-up in a lineless style. Jimmy Jr. is leaning slightly forward with one hand on his hip and the other holding a chicken nugget. He has an angry, an almost determined expression on his face. He has short, fluffy red hair, bright green eyes, a bright yellow shirt with a blue vest, and blue shorts. Tina is rolling her eyes with a fond smile on her face. She has short, fluffy black hair, bright blue eyes, a light blue shirt, and a dark blue skirt with a dark purple bow. Her arms are also crossed. She also has large black glasses and a small yellow barrette in her hair. They are standing in front of their school, Wagstaff.

[qoldenskies]

Something about how Raph would have the most to return to when it comes to being helpful—there’s only so much Donnie can eat, and there’s only so much Leo can physically heal before having to face the fact that most of the wounds are emotional. Raph can keep going though, the way he always has, he can keep going, he can be better this time, he can be the big brother he was supposed to be for all of them and this will never happen again never never never never

[clingylilhoneybee]

Spilled protein coffee on my pants and now it looks like they have a jizz stain

[bunnihearted]

🐁

[wayti-blog]

"Researchers at the University Medical Center Göttingen (UMG) have discovered a new quality control mechanism that regulates energy production in human cells. This process takes place in mitochondria, the power plants of the cell."

"Mitochondria play a central role for cellular metabolism. Therefore, malfunctions of the mitochondria lead to serious, often fatal, heart, muscle or nerve diseases. Mitochondria are surrounded by two membranes, an outer and an inner one, which separate them from the surrounding cell. The final conversion of food into energy takes place in the inner membrane. Proteins are involved in this process.

Central proteins for energy production are formed in the mitochondria, transported to the inner membrane and inserted there. The protein OXA1L is mainly responsible for the insertion of proteins into the membrane, where larger complex structures are formed with other proteins that interact with each other and ensure energy production. How the incorporation and assembly of these structures works in detail has been poorly investigated thus far."

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[chipped-chimera]

FOR THE TIRED PEOPLE: Some new research about Chronic + ADHD(inattentive) related fatigue, and BCAAs

[DISCLAIMER // I AM NOT A DOCTOR. I AM NOT A MEDICAL PRACTITIONER. I AM NOT A DIETICIAN. I'm just a big tired nerd with way too much time on my hands who likes science. I am however, sharing this because this could potentially help others and BCAAs are already safe for human consumption, widely used and easily accessible. If you are uncertain about adding BCAAs to your diet please talk to your doctor first. There are also some medications which interact negatively with BCAA's. Do your research. Also generally be careful about taking medical advice from the internet! ]

I was going to post about something else but I went down the rabbit hole of explaining this study I read and decided that no, this needed it's own thing or it's gonna be a mile long.

So in one of my usual weekly fatigue breakdowns where I was scraping the internet for any kind of information that might point out something I've SURELY missed to explain why I feel the way I do, I stumbled across this study published last year (2022) -

[ The relationship between central fatigue and Attention Deficit/Hyperactivity Disorder of the inattentive type ]

The TL;DR on the paper - our previous assumptions about the tryptophan-serotonin system might be wrong (tryptophan being the precursor for a bunch of stuff, including melatonin which is the sleepy chemical - aka why people say drink warm milk before bed to help sleep, that's tryptophan) what was previously assumed was reducing tryptophan = bad because it could affect serotonin production.

Testing in rats (so grain of salt here) indicated that higher levels of tryptophan =/= higher levels of serotonin and when reducing the level of free tryptophan in the bloodstream it returned to baseline. High levels of tryptophan were associated with fatigue and inattention, and rats on a tryptophan deficient diet by contrast took longer to reach a state of exhaustion. I'm skipping over a bunch of stuff but basically - research is now pointing to both Chronic Fatigue and ADHD related fatigue being related to Central Nervous System Fatigue which up until now, has only really been associated with the fatigue athletes experience when exercising really hard (now just picture me doing jack shit and feeling like that every day. Yeah). I've only just stared to see bits and pieces pop up about this recently but nothing in relation to this tryptophan study.

Anyway, the thing about BCAAs: BCAAs (Branched Chain Amino Acids) are currently used to reduce the uptake of tryptophan in the brain for better performance in athletes, help with reduction of exercise fatigue (CNS fatigue) and muscle building. You can pretty easily find BCAA's added to protein-shakes or in it's own kind of supplement. It also occurs naturally in some foods (Beef, Chicken, Eggs, Lentils, Chickpeas, Brown Rice etc.) so it is absolutely safe to consume. It's also generally fairly affordable (especially compared to the lengthy process of treatment + medications that might not even work and you have to keep changing them, yes I am talking from personal experience).

Again, this is all very new and absolutely needs so much more research because up until now, no one has really been sure what causes Chronic Fatigue Syndrome, but tests have shown that those suffering CFS demonstrate similar activation of their muscles as fatigued athletes - as in they could activate them but not to their full capacity. This connection is only considered 'possible' and it might take a good few years before we can say anything with certainty.

But as an extremely tired bitch who is extremely tired of being extremely fucking tired, I am sharing this because it's easy to get, safe, and affordable and if you're like me you're about ready to try anything. And it's not another goddamn pill (I'm on 14 a day).

Also for the ADHDers specifically: protein rich diets are usually advised for us because it helps with the metabolism of stimulants, and can help with softening medication crashes when they wear off. So adding a protein shake with BCAAs to your morning routine might be a good idea. Or just any protein shake in general.

There can be side effects to taking BCAAs, but it is considered rare and this depends entirely on the person. Cross check existing medications, talk to your doc etc. if you are not 100% certain adding BCAAs to your diet is possible. Stay safe peeps.

[noknowshame]

honestly what's not to get

[ardentpoop]

the show THINKS sam is the “healthy” eater btwn the two of them but that doesn’t mean it’s true lol

[cbirt]

Predicting protein structures has been transformed by artificial intelligence. However, rather than competence, accessibility, and ease of use are increasingly becoming limiting issues for end users as more sophisticated and powerful software is developed. In order to simplify the process of medium-scale protein-protein interaction prediction, the author Thomas C. McLean, from John Innes Centre, UK, presents a pipeline based on Google Colaboratory called LazyAF. This pipeline integrates the current ColabFold BATCH. Using LazyAF, he predicts the interactome of the 76 proteins encoded on a multi-drug resistance 20 plasmid with a large host range, showcasing the convenience and accessibility of the pipeline.

AlphaFold2 and RoseTTAFold, two AI-based programs for protein structure prediction, have been incorporated by Google Colaboratory into notebook services like ColabFold BATCH. Because of this integration, big or complex protein structure predictions may now be made more quickly and with greater accessibility thanks to powerful graphics processing units (GPUs). From single protein structure predictions to screening huge datasets for novel protein-protein interactions (PPIs), the potential scope of protein structure prediction has grown. 

Designed to operate with ColabFold BATCH, a Google Colaboratory-based LazyAF pipeline makes it easier for individuals with less bioinformatics background to screen huge datasets for novel PPIs. The pipeline lowers the entrance barrier for medium-scale PPI prediction and enables more wet-bench researchers to incorporate in silico modeling into their workflow by performing automatic medium-throughput prediction of protein complexes in an all-versus-all scenario.

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[opens-up-4-nobody]

...

[fractallogic]

Look at this cat, who had been snoring right in my ear before I turned to admire her

I’m gonna shake up a protein shake and start a load of laundry before I go to the gym (and then come back and switch the laundry and change my clothes and eat some real food and go to campus for a couple hours)

I really fucked up last night by playing with notion until ONE IN THE FUCKING MORNING and then reading The Hacienda for another hour (it’s pretty good, it’s pretty creepy, but the prose bugs me… but the creepiness so far bumps it up from (say) a 3.75/5 to a 4/5)

I’m very unmotivated to continue doing the tedious fucking work on my data that I have been doing and WHICH THE RAS SHOULD HAVE DONE A BETTER JOB OF ASKING ME QUESTIONS ABOUT, but every time I asked them “does that make sense? Do you have any questions? Can you highlight the ones you have questions about or aren’t sure about?” they were like nope it’s all fine here’s a Google sheet with no highlighting and no questions and needing to change well over half of the coding because WHY ASK FUCKING QUESTIONS WHEN YOU’RE CONFUSED

SIGH

I need to just like. Put on my pomodoro timer and a long podcast. Make some tea. Remember that I have snacks in my office. You know. The usual.

[newsepick]

Semaglutide enhances cognitive abilities and reduces Alzheimer’s pathology in mice and human brain models

A study in *Biomedicine & Pharmacotherapy* explored the effects of Semaglutide on Alzheimer's Disease (AD) in mouse and human brain organoid models. Researchers found that Semaglutide improved cognitive function, reduced amyloid plaque and Tau protein levels, and decreased neuroinflammation in APP/PS1 mice. Behavioral tests indicated enhanced learning and memory, while biochemical assessments showed modulation of key neuroprotective pathways. Additionally, Semaglutide increased oxytocin levels in human models, suggesting its therapeutic potential through GLP-1 receptor and oxytocin interaction. These findings point to Semaglutide as a promising candidate in AD treatment, warranting further research.

[mysticalpeacenut]

Advancements in PPI Targeted Drug Discovery

In the ever-evolving international of drug discovery, concentrated on protein-protein interactions (PPIs) has emerged as a groundbreaking method with massive healing capacity. While traditional drug discovery has largely focused on focused on single proteins or enzymes, the point of interest is shifting toward the intricate networks fashioned by using protein interactions. These networks are critical to expertise disorder mechanisms and growing innovative treatments. This blog delves into the modern day advancements in PPI targeted drug discovery, highlighting the transformative impact of Protein-Protein Interactions Magna™ technology and different modern tactics.

Understanding Protein-Protein Interactions

Protein-protein interactions are essential to almost each biological manner. Proteins not often function in isolation; as a substitute, they interact with different proteins to carry out their functions. These interactions can manipulate cell signaling pathways, adjust gene expression, and influence cell responses to environmental changes. Disruptions or malfunctions in those interactions are frequently implicated in diseases which include cancer, neurodegenerative problems, and infectious diseases.

PPI Targeted Drug Discovery makes a speciality of designing drugs which could especially modulate these protein interactions. Unlike conventional capsules that focus on a single protein, PPI-centered pills purpose to persuade the interactions among multiple proteins, thereby imparting a greater nuanced approach to therapeutic intervention.

Key Advancements in PPI Targeted Drug Discovery

Protein-Protein Interactions Magna™ Technology

One of the maximum giant advancements in PPI-focused drug discovery is the development of Protein-Protein Interactions Magna™ technology via Depixus. This modern day era gives a complete platform for analyzing and manipulating protein interactions with remarkable precision.

Magna™ generation uses advanced techniques to seize and examine how proteins engage within a cellular surroundings. By offering special insights into these interactions, Magna™ permits researchers to become aware of ability drug goals and design molecules that may in particular disrupt or decorate those interactions. This method is vital for growing healing procedures that focus on complicated sicknesses wherein conventional drug discovery methods may additionally fall brief.

High-Throughput Screening

High-throughput screening (HTS) has revolutionized PPI-centered drug discovery via permitting the rapid evaluation of lots of compounds for their capability to modulate protein interactions. HTS structures use automated structures to test big libraries of molecules against particular PPIs, identifying promising applicants for further development.

Recent improvements in HTS technology have expanded the speed and accuracy of screening processes. Innovations consisting of miniaturized assays, stepped forward detection techniques, and sophisticated statistics analysis gear have substantially better the efficiency of PPI-targeted drug discovery.

Structural Biology Techniques

Structural biology strategies, together with X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy, have supplied vital insights into the three-dimensional structures of protein complexes. Understanding the ideal structure of protein-protein interactions is essential for designing drugs which could in particular goal those interactions.

Recent traits in structural biology have enabled researchers to visualize protein interactions at atomic resolution, facilitating the design of small molecules and biologics which could efficiently disrupt or stabilize those interactions. This structural records is invaluable for growing centered treatment options with high specificity and decreased off-goal outcomes.

Computational Approaches

Computational methods, which includes molecular docking and molecular dynamics simulations, have end up necessary gear in PPI-targeted drug discovery. These techniques use pc algorithms to predict how small molecules or peptides will interact with protein complexes, guiding the layout of recent drugs.

Advancements in computational techniques have improved the accuracy of predictions and the efficiency of digital screening techniques. By simulating protein interactions and drug binding, researchers can pick out ability drug applicants and optimize their homes earlier than conducting experimental research.

Biologics and Peptide-Based Therapies

Biologics, along with monoclonal antibodies and peptide-based totally remedies, constitute a growing vicinity of hobby in PPI-focused drug discovery. These cures are designed to specially bind to protein interactions and modulate their activity.

Recent advancements in biologics and peptide design have caused the development of novel drugs that concentrate on PPIs with excessive specificity. For instance, bispecific antibodies which could simultaneously bind to two exclusive proteins are being explored as potential cures for numerous sicknesses.

The Future of PPI Targeted Drug Discovery

The subject of PPI focused drug discovery is swiftly advancing, with ongoing research aimed toward overcoming current challenges and increasing the range of druggable objectives. The integration of new technology, which includes Protein-Protein Interactions Magna™, structural biology, excessive-throughput screening, and computational strategies, is riding innovation and opening up new possibilities for therapeutic intervention.

As researchers hold to explore the complexities of protein interactions, the capability for growing novel treatments that concentrate on previously undruggable sicknesses grows. The capability to especially modulate protein-protein interactions offers a brand new stage of precision in drug development, paving the way for extra effective and focused remedies.

Conclusion

PPI focused drug discovery represents a paradigm shift in how we technique drug development, shifting beyond traditional single-protein objectives to focus on the tricky networks of protein interactions. With advancements which include Protein-Protein Interactions Magna™ era and other present day tactics, the sector is poised for great breakthroughs so one can remodel the landscape of medicine. At Depixus, we're at the leading edge of this thrilling field, providing innovative solutions and technologies that aid researchers of their quest to broaden the next generation of centered healing procedures. To study extra approximately how our Protein-Protein Interactions Magna™ generation can decorate your research and pressure innovation contact us at Depixus.

Reposted Blog Post URL: https://petrickzagblogger.wordpress.com/2024/09/04/advancements-in-ppi-targeted-drug-discovery/

[abigailspinach]

There you have it - what are you most interested in, dear leader? Artificial intelligence, the blockchain, or quantum computing?6 They know exactly what their target market is - people who have been given power of other people's money because they've learned how to smile at everything, and know that you can print money by hitching yourself to the next speculative bandwagon. No competent person in security that I know - that is, working day-to-day cybersecurity as opposed to an institution dedicated to bleeding-edge research - cares about any of this. They're busy trying to work out if the firewalls are configured correctly, or if the organization is committing passwords to their repositories. Yes, someone needs to figure out what the implications of quantum computing are for cryptography, but I guarantee you that it is not Synergy Greg, who does not have any skill that you can identify other than talking very fast and increasing headcount. Synergy Greg should not be consulted on any important matters, ranging from machine learning operations to tying shoelaces quickly. The last time I spoke to one of the many avatars of Synergy Greg, he insisted that I should invest most of my money into a cryptocurrency called Monero, because "most of these coins are going to zero but the one is going to one". This is the face of corporate AI. Behold its ghastly visage and balk, for it has eyes bloodshot as a demon and is pretending to enjoy cigars.

My consultancy has three pretty good data scientists - in fact, two of them could probably reasonably claim to be amongst the best in the country outside of groups doing experimental research, though they'd be too humble to say this. Despite this we don't sell AI services of any sort. The market is so distorted that it's almost as bad as dabbling in the crypto space. It isn't as bad, meaning that I haven't yet reached the point where I assume that anyone who has ever typed in import tensorflow is a scumbag, but we're well on our way there.