VDP-152 [Funding] Project TransFidelity

Proposals
1

One-liner

Project TransFidelity aims to develop small molecules and peptides that enhance translation fidelity to prevent harmful protein misfolding, thereby addressing neurodegenerative diseases (NDDs) like Alzheimer’s and Parkinson’s from their root cause.

  1. Join Molecule’s Discord
  2. View Pitch Deck

Team

Principal Investigator: Dr. Dimitri Scherbakov

Project Managers: Ella McCarthy-Page, Kishore Kumar, Amine Chaherli, Benji Leibowitz

Sourcer: Michele Gallia

Key Researchers and Collaborators: Dr. Rashid Akbergenov, Prof. Dr. David Wolfer, Prof. Dr. Dennis Gillingham

Simple Summary

Project TransFidelity focuses on preventing neurodegenerative diseases by improving the accuracy of protein synthesis, thereby reducing the formation of harmful protein aggregates. This approach targets the root cause of these diseases, aiming to provide a novel treatment strategy that goes beyond symptom management. This proposal is to provide $50k USD in (ETH) funding for the project.

Problem

Neurodegenerative diseases (NDDs) like Alzheimer’s and Parkinson’s are devastating conditions that affect millions worldwide. These diseases are driven by the misfolding and aggregation of proteins, which leads to brain cell death and cognitive decline. Project TransFidelity aims to solve this by improving the accuracy of protein synthesis, preventing harmful protein misfolding from the start.

Solution

Project TransFidelity proposes a novel approach to treating NDDs by improving the fidelity of protein translation. This strategy addresses the core problem of protein misfolding at its source. By identifying compounds that enhance translation fidelity, we aim to prevent the formation of toxic protein aggregates. Think of it as upgrading the factory’s quality control system to ensure that only correctly assembled proteins are made.

Opportunity

By improving the accuracy of ribosomes, we can reduce the production of faulty proteins. Here’s how our approach works:

  • Small Molecules and Peptides: Screen molecules that help ribosomes print proteins more accurately.
  • Reducing Misfolded Proteins: Once the protein has been printed, it needs to be folded into its correct form. With fewer errors, folding accuracy improves. It reduces the working load to the cell’s cleanup system and decreases protein aggregation with its negative consequences such as chronic inflammation.
  • Easing Cellular Stress: Reducing the rate of misfolded proteins eases the burden on our cell systems, granting them the ability to spend more energy on cell vital functions, resulting in cells that function better and stay healthy longer.

The ultimate goal is to develop new treatments that halt or reverse the progression of NDDs,

providing new hope for millions of patients.

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Utility of drug modality to exploit mechanism of action

The small molecules and peptides screened through this project enhance the accuracy of protein synthesis. They act like quality control inspectors, ensuring that proteins are built correctly, which reduces toxic protein aggregates. Current treatments for NDDs primarily manage symptoms without addressing the underlying cause. Existing therapies like Levodopa and dopamine agonists provide symptomatic relief, while lifestyle changes are recommended as preventative measures. Experimental treatments targeting protein aggregates, such as monoclonal antibodies or proteolysis (protein degradation) activators, are also in development. However, no existing or developing therapy aims to prevent protein misfolding from the outset. TransFidelity’s approach of enhancing protein synthesis accuracy is unique, aiming to prevent harmful aggregation and halt disease progression, rather than merely managing symptoms.

Therapeutic relevance of biological mechanism of action

Improving translation fidelity is crucial because misfolded and aggregated proteins are among the major causes of NDDs like Alzheimer’s and Parkinson’s. In simple terms, our body’s cells can sometimes make mistakes when creating proteins, leading to “faulty” proteins that clump together and damage brain cells. By enhancing the precision with which proteins are made, our approach aims to prevent these damaging clumps from forming in the first place. This method has the potential not just to slow down the progression of these diseases, but possibly even reverse some of their effects, offering new hope where current treatments fall short. Essentially, we’re working on a way to make our cellular machinery more error-proof, protecting brain health at the source of the problem.

Relevance to Longevity

Existing research underscores the importance of accurate protein synthesis in longevity. Longer-lived species have evolved mechanisms to ensure higher fidelity in protein translation, which helps maintain proteostasis and prevent the accumulation of damaging protein aggregates. By targeting and improving translation fidelity, it may be possible to develop therapies that mitigate age-related diseases and extend healthy lifespan, making it a promising area for longevity research.

In addition, increased translational efficiency has improved longevity markers in several model organisms. Please see the figure below.

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References:

  1. Ke Z, et al. Aging Cell. 2017; 16:988–93. PMC
  2. Azpurua J, et al. Proc Natl Acad Sci USA. 2013; 110:17350–55. PMC
  3. Martinez-Miguel VE, et al. Cell Metab. 2021; 33(11):2288-2300. PMC

IP Roadmap

We will secure patents for our lead compounds, ensuring their unique composition of matter and method of use are protected. Additionally, we are obtaining a patent for our “in vitro” translation fidelity measuring system, which we may license to other companies for large-scale screening. We plan to patent our “in cell” screening system once its sensitivity is optimized and secure a patent for our “in vivo” translation fidelity measuring mouse model, pending agreements with collaborating research groups.

Therapeutic Optionality

Broader Applications: Potential to apply the technology to other protein misfolding disorders, such as Type 2 Diabetes and Huntington’s disease.

Experimental Plan

Phase Item Description and Rationale Performed by Desired Outcome and Milestone
1a Basic Med Chem to check for red flags Initial medicinal chemistry to identify potential issues early in the process. Consultant Identification of any red flags in the chemical structure of the compounds.
1b Cell lines This control enables estimates of the comparable efficiency of the compounds (in terms of improved fidelity and anti-aggregation activity) to published results In-house Develop positive control for HEK cell lines
1b iPSC assays Test two indirect compounds in neuron-specific aggregation assays using iPSC-derived neuronal cell lines. In-house Milestone 1: Reduction in protein aggregates in human-origin cell lines. Reduction of ~20-30% to justify further development.
Go/No-Go Decision based on Basic Med Chem and iPSC assay results Evaluate data from Basic Med Chem and iPSC assays to decide whether to continue. Research team and sponsor Decision to proceed or halt based on initial data. Criteria: - Reduction in protein aggregates (target ~20-30%) - No red flags in chemistry. - Hits can be modified cost-effectively.
2a PISA Assay Use PISA assay to identify interacting cellular counterparts and pathways affected by hit compounds. In-house Milestone 2: Identification of pathways and cellular counterparts.
2b Proteomics & Transcriptomics Verification with RNAi experiments, transcriptome, and proteome technology. In-house Milestone 3: Verification of 2a results with RNAi experiments, transcriptome, and proteome technology.
2c TPP with Med Chemist Define requirements for drug development (Target Product Profile). Consultant Establishment of a clear target product profile.
Next Fundraise Secure additional funding based on validated hits and target pathways. Research team and sponsor Sufficient funding for further development.

Gantt chart

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Milestones, Deliverables, and Budget

Item Deliverables Expected due date Responsible person Cost (CHF)
Milestone 1 Ppt summarizing experimental setup and results. Raw data files (excel files, images) Jan 2025 Researcher 1 & 2 + Consultant 12,000
Milestone 2 Ppt summarizing experimental setup and results. Raw data files (excel) August 2025 Researcher 1 & 2 26,000
Milestone 3 Report from Medicinal chemist August 2025 Consultant 30,000
Final report Written word document signed off by sponsor and researcher summarizing all experiments performed in project plan. All accompanying raw data from previous milestones. Sep 2025 Researcher 1 & 2 NA

Budget and costs

Item Amount (CHF) Amount (USD)
Personnel costs
Senior Postdoc salary (100% for 1 year) 118,000 132,000
Consumables and reagents
In vitro experiments 12,000 13,400
Cell lines (HEK) 5,000 5,580
PISA, Proteomic and transcriptomics analysis 26,000 29,000
External consultants and partnerships
Medicinal Chemistry Analysis 18,000 20,000
University overhead costs
20% of total cost (excluding med chemist) 33,200 37,000
Bench fees 5000 5,580
Total 217,200 242,560

Proposed project scope for a subsequent fundraise

  1. Depending on the success of the initial two hits and elaborations by the med chem consultant, screen another library of commercially available 800 biologically active compounds (4000-5000 CHF; 3-4 months).
  2. Perform SAR studies using the existing in vitro assay formats to pave the way for a hit-to-lead campaign with the promise of yielding novel IP. (unknown)
  3. Evaluate the efficacy of the new compounds in a C. elegans-based aggregation and longevity assays in vivo, once we are closer to final chemistry. It would be worthwhile further evaluating translationally relevant animal models. (8000-12000 CHF, 4-6 months).
  4. Identify downstream members of affected pathways as targets for guided development of more specific and efficient compounds increasing translation fidelity, develop the new compounds, potentially affecting identified targets, screen them for fidelity modulating activity (price and time frame depends on the nature of proposed compounds, currently unpredictable)

Planning flow-chart

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Financing and VitaDAO Funding Terms

This proposal is to provide the project $50k, ~20% of the $242k needed to complete the milestones. The remaining funding will come from other DAOs, and individuals in the DeSci community. Funding will be open and welcome to all via Molecule’s platform: Catalyst. The project. Tokenomics will be split such that 95% of the IP Tokens will go to the funders, and 5% will go to a liquidity pool.

The licensing terms are not yet finalized. We are currently in conversations with the relevant technology transfer office (TTO), and are looking to secure funding prior to negotiating the terms. If an agreement is not reached, and the funders do not approve of the terms of the IP, the funding will be returned to both VitaDAO and individual funders.

Budget

This proposal, if passed, will allocate $50k (in ETH) of the $100k allocated to Catalyst projects as part of VDP-147. Again, if the terms are not agreed upon by the funders, then the ETH will be returned to VitaDAO.

Note

We have provided the current Project Pitch Deck, along with a Discord channel where questions regarding the project will be answered. As this is a preview before the project is launched, we hope to see this as a collaborative exercise, meaning project changes can be made based on feedback.

Senior Review Digest - Quantitative

The project was reviewed by four reviewers: a scientist, an entrepreneur, a VC, and a professor.

Below is the average scores from the reviewers out of 5 per category.

Average Scores

  • Team Expertise: 3.5
  • Feasibility & Data: 3.0
  • Commercial Potential & Impact: 4.3
  • Novelty & Market Advantage: 3.5
  • IP Defensibility: 2.8
  • Relevance to Longevity: 4.5
  • Deal Terms: N/A (the terms have not yet been set)
  • General Conviction Score 3.0 (for reference, the average score of past funded projects is 3.7)

The majority of the reviewers think that this project is a moonshot.

Two reviewers recommended that the project should be advanced for token-holders vote, one that it should be followed-up with the applicant for more information, one that it should be denied outright giving constructive feedback.

Senior Review Digest - Qualitative

Each reviewer was asked whether they would endorse the project, as well as the pros and cons they see: below are their answers.

Reviewer 1
Until the group can find new chemical entities there is limited commercial viability and I would not endorse the project. Also, data are contradictory regarding enhancing/reducing translation and the researchers have no drug target in mind other than a biological process. Systemically changing anything in the body is a bad idea.

Pros

  • Dysregulation of translation is known in a lot of diseases. Targeting it might be beneficial.

Cons

  • No molecular target and no viable IP.
  • Systemically targeting translation is likely dangerous and the literature suggesting enhancing/decreasing has both positive/negative consequences.
  • Team lacks any BD/Development experience.

Reviewer 2
I am familiar with most of the past potential projects that VitaDAO has brought to the table, and this is one of the strongest so far. It has my clear endorsement.

Pros

  • Known mode-of-action, allowing to deploy the typical paths to bring a target/drug to market.
  • Evolutionarily conserved and robust lifespan extension in invertebrates and unicellular models.
  • Disruptive potential of a huge market.

Cons

  • Mammalian pro-longevity results lacking.
  • Aggravating this mode-of-action clearly shortens lifespan and compromises health, but breaking a system is dissimilar and easier than improving upon it.

Reviewer 3
I’d put this in the top 50% of project i’ve reviewed, but not top 10%. The research seems interesting and worth supporting; likely a reasonable project for VitaDAO to fund.

Pros

  • Solid academic foundation.
  • Conceptually promising approach.
  • Feasible patent plan.

Cons

  • Lack of clinical/regulatory experience.
  • Crowded market concerns.
  • Indirect alignment with longevity mission.

Reviewer 4
At this stage I would endorse the idea behind the project but not the project itself. This is a very early stage research which is likely to fail within the timeframe of the proposed project as a lot more research is required to improve feasibility. Nevertheless, the idea is exciting and I would be happy to discuss it publicly or even become involved scientifically.

Pros

  • Novelty of the approach.
  • Evidence of chemistry with apparently desired biological effect.
  • Good expertise in biology with support from medicinal chemist.

Cons

  • very early stage project with uncertainties about whether improving translation fidelity would have any benefit for health/longevity/disease prevention.
  • research programme is broad with no guarantee of success.

Vote

  • Agree
  • Revisions Requested [Details in Comments]
  • Disagree
0 voters
3 Likes
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The protein aggregates in Alzheimer’s arise from proteolytic processing after translation. So it’s unclear to me why targeting translation is expected to work in this disease at all. Why not target diseases where translational misreading is the major mechanism of action? Cystic fibrosis seems the obvious choice here, or some of the muscular dystrophies.

Based on the pitch deck, it sounds like claiming impact on Alzheimer’s is a huge stretch. What AD mouse model was used?

Most of the data presented are correlational and in the negative sense: if translation is broken, there is a problem, but that doesn’t mean translation breaks during aging. That the drugs may fix artificially induced damage may or may not be relevant. I think it would be important to show that the drugs enhance lifespan in an otherwise healthy model, or a standard disease model.

I think it is important to validate that the hits work at all in vivo before going to all the mechanistic work to identify a target, etc. Also not convinced that PISA, proteomic and transcriptomic analysis will get you the mechanism.

There’s also some basic solubility/delivery/tox questions. I would prioritize those above mechanism, too.

The postdoc salary seems inflated, even if fringe is included. Base NIH salary for a 7 year postdoc is $74k/year, which is about half of the requested $132k/year. Also, who pays for patent costs? How do ‘cell lines’ differ from ‘in vitro experiments’?

There is potential overlap with ArtanBio. I presume any potential COI is being managed. I mention it because I’m not sure how the DAO wants to balance different mechanisms of action vs several shots in a similar direction.

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Thank you for the questions at always @bowtiedshrike. Will try answering them piece by piece

  • Cystic fibrosis is caused by mutations, not translational misreadings (RNA → protein)
  • Yes there is translational readthrough, but this is due to mutations in CFTR
  • Could be wrong on this, but not sure why this is necessarily a better application of enhancement of translational fidelity. Even if a CF patient had perfect translational fidelity, their CFTR protein would still be mutated
  • The mouse model used in the proposal is designed to derive the causal effect of translation fidelity on aging. Specifically, the researchers have created heterozygous knock-in mice that express the ribosomal ambiguity mutation RPS9 D95N, resulting in genome-wide error-prone translation. This model is not directly linked to AD but is intended to provide causal evidence that translation errors accelerate aging in vivo and limit lifespan. We propose that AD could be one use case, given the broader implications of translation fidelity on protein quality and cellular health. Parkinson’s could be another potential target.
  • Attached is their publication ‘Premature aging in mice with error-prone protein synthesis’
  • From this paper: “Both the overall rate of protein synthesis and the fidelity of translation decreases with age. These two observations are distinct and reproducible across numerous studies and model organisms (Anisimova et al., 2018)”
  • Increased fidelity of protein synthesis extends lifespan: In vivo testing has not been performed on the compounds, but studies have been done that show increased healthspan / lifespan in healthy animal models
    • RPS23 K60R is a mutation that enhances translation fidelity
    • Improves yeast, worm, and fly lifespans
  • Confirming hits in vivo is time/resource intensive and not necessarily the best/only way forward at this stage. Important to note is that the PISA work is not an in depth target identification work package, but rather a first step towards that direction. Fully agreed it doesn’t make sense to do PISA, proteomics, transcriptomic in a full work package here - important to just start with the one that makes the most amount of sense and go from there. The final candidate may also work via a different target, so until further work has been done on hit to lead, this work serves as more of a guiding direction, as opposed to trying to definitively find the target. This is a function of starting with a phenotypic screen.
  • Point taken though - there’s always a balance about which direction to take. We’d suggest discussing with researchers what they want to get out of PISA/transcriptomics, what the natural stopping point is, and when they see in vivo work commencing. Would be curious to know what your opinion is on when this moment should occur?
  • Agreed, the med chemist will review to see if there are any immediate red flags and solubility/delivery will need to be defined in line with preferred route of administration.
  • In general though, the thought process of having a med chemist do an early review is that for phenotypic screening, when moving from hit to lead, it’s important to know whether the hits are acting via the same or different pathways - the goal is to just get an understanding of whether these hits have more functional overlap or not, to support which one to prioritize. Once one can be prioritized, you can work more on solubility/delivery and keep the other as a back up to be most capital efficient.

The salary is for one senior postdoc (25+ yrs experience) in Switzerland. It is lucky in the sense that Dimitri’s salary is already partially covered by the University of Zurich and so Dimtri and Rashid have agreed to both work on the project for a single salary. How they decide to split that amount is at their discretion.

Patent costs fall under the purview of the patent owner, i.e. the university in this case. In line with previous projects, the research will be funded via a Sponsored Research Agreement, granting the IPT holders licensing rights.

They do not - apologies this is my mistake. Will update the project plan accordingly.

  • Though both projects technically target translation, Artan is trying to correct nonsense mutations, while this project is trying to prevent translation errors not reflected at the genetic level
  • Artan is going after DMD, CF, SMA, and cancer, while Transfidelity is targeting protein aggregation diseases of the brain, minimizing potential COIs both at the mechanistic and target indication level

Here is a google drive folder with all the supporting papers provided by the research team.

6 Likes
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With the mandate approved a few months ago it was decided to accomplish our mission with the model of sustainable biotech financing that we pioneered with VITA-FAST, which includes the generation of cash flow with trading fees and liquidity provision. Would this project be compliant with this?

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This is completely up to VitaDAO.

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Thanks, it is important to clarify this point.

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The senior review has been completed and a digest of the results has been added to the proposal at the end.

You have until August 1st EOB to

  • vote, in case you did not vote yet, or to
  • revise your vote based on the new information, in case you already voted
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As requested in the longevity pod Discord channel, I have just added to the senior review digest the pros and cons seen by each reviewer.

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Thank you, Paolo, for sharing senior reviews. I am still inclined to fund the project, however based on the feedback of senior reviewers it might be sensible to adjust the research plan. Here are my thoughts.

Benefits of improving translational fidelity are unclear
It is true that in the past several papers have shown that improving translational fidelity does not impact lifespan but the latest developments seem to indicate that it does indeed extend lifespan. From my blog:
the jury is still out on whether improving translational fidelity has the potential to extend lifespan. In the 60s, the “error catastrophe theory of aging” proposed by British chemist Leslie Orgel posited that exponentially increasing accumulation of translational error rates was the cause of aging. Later studies in rodents seemed to disprove this theory, and indeed, it is the case that in these animals, there is no age-dependent decrease in the quality of protein synthesis. However, recently, a paper by, among others, Vadim Gladyshev and Vera Gorbunova found a significant correlation between species’ lifespan and their translational error rate. On top, in 2021, a paper from Bjiedov and colleagues showed that a mutation in conserved protein, RPS23, led to a reduction in translational errors, heat shock resistance, and longer lifespan. These later findings are leading to renewed interest in improving translational fidelity as an anti-aging intervention.

these are the kind of moonshot projects that VitaDAO could and should fund if we are indeed after moonshots

Lack of experience bla bla
Refuse to even comment on these cons. These are outstanding researchers and they are focused as they should on science. Catalyst and DAOs can provide funding and support to cover these gaps

Concerns about research plan and IP
Point taken. we can maybe adjust the research plan to ensure that target identification come before everything else. Then we can optimize the discovered compounds with a medchem. My understanding is that these optimized compound, if optimization is possible, can be patentable. If not, once we have identified target and MoA, what is preventing us from screening for novel compounds?
One of the senior reviewers mentioned that the research plan is broad. Based on their feedback, let’s adjust it.

All in all, this is a very interesting and understudied area that is picking up attention recently - it is up to VitaDAO to decide whether we want to be risk-taking leaders or risk-averse laggards

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Michele, could you please share the references of the papers you mention on longevity?

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Translation fidelity coevolves with longevity

Increased fidelity of protein synthesis extends lifespan

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Exciting research project and great questions and answers @bowtiedshrike @benji !!

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Thank you. I was also curious about the longevity potential of this intervention. However, the first paper you cite shows correlation not causation, and the second one is where the lifespan data in the proposal comes from. That paper shows an interesting improvement in drosophila, but a small one in c elegans. As I mentioned at the pitch that preceded this VDP, I was hoping to find more data to confirm the relevance of this biology in a longevity context.

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Think this needs to be done in an AD model if they want to claim AD. Claiming AD because you can find brain problems in a mouse feels disingenuous to me.

Big problem with most of the CF mutations is the failure of CFTR to fold properly and get to the surface. Anything that gets more CFTR to the surface will improve disease. For example, if we could get humans to run at 25 C, we could fix CF because enough of the mutant protein would get folded and reach the surface to function. Historically, this is why ice baths were used to relieve CF.

Multi-pass transmembrane proteins are where most of the waste in protein synthesis occurs. So I would expect protein errors to have the biggest impact here and in proteins that last forever in the cell. Amyloid beta is neither of these.

I think the activity assay is more important than worrying about mechanism at all. Pick a lead and then worry about how it acts. Otherwise, the risk of studying an artifact or something that doesn’t work is too high.

I disagree here. If you have multiple hits, try combining the two leads. If there is an extra benefit, then maybe different MoA. If no additive effects, probably same pathway.

What is the %effort from Dimitri proposed for this project? Assuming $90k/year for the salary+fringe of a postdoc w/7+ years experience, $42k would still represent a significant % effort from the PI.

Most of these will lead to protein misfolding and/or nonsense mediated decay. And I think the translation clinical targets will be similar between both.

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As I said "the jury is still out on whether improving translational fidelity has the potential to extend lifespan. These later findings are leading to renewed interest in improving translational fidelity as an anti-aging intervention.

As I said “All in all, this is a very interesting and understudied area that is picking up attention recently - it is up to VitaDAO to decide whether we want to be risk-taking leaders or risk-averse laggards”

Let’s see what tokenholders think of it

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Thank you @bowtiedshrike

I think the activity assay is more important than worrying about mechanism at all. Pick a lead and then worry about how it acts. Otherwise, the risk of studying an artifact or something that doesn’t work is too high.

One of our experts (see senior reviewer 1) instead think that it is more important to first define target and MOA. What are your thoughts on it?

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I get it, it’s just that “the jury is still out” for longevity is in my view not good enough if we want to fund impactful work. I was hoping to see more data, because, indeed, the longevity relevance of translation - which comes downstream of transcription, the epigenome, and DNA, which also become faulty with aging - is not obvious to me.

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Reviewer 1 did NOT endorse the proposal. I agree with the reviewer on that aspect.

I further agree that they need to get more data on their two leads that fix “translational fidelity” before this is worth funding.

I would also want to see some indication that fixing “translational fidelity” with the lead compound increases longevity in some healthy organism, or fixes some protein folding disease (CF model, etc).

Without that, who cares about MoA?

Identifying the target and MoA are also challenging tasks that may not be successful. Figuring out if the compound has a physiological effect is straightforward, and critical to bringing this to market.

There are many drugs that get approved when we have little to no idea how they convey therapeutic effects. For example, what’s the analgesic mechanism for acetominophen?

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The project is devoted to increasing translation fidelity. None of the hit compounds affect the global translation rate. And when the reviewer says the data are contradictory, I would love to know exactly what is meant here. I have ideas what the contradiction might be, but knowing what the reviewer’s line of thought is could be helpful. Given the unclear terminology and vague standard wording, I want to rule out the possibility that the reviewer didn’t understand the proposal.

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You have as much information as I do here. I was not in direct correspondence with the senior reviewer and I believe that we all have the same level of information from the senior reviewer. I agree that this review is poor and decreases its credibility.