We are thrilled to announce that PEACCEL has been awarded the prestigious French DeepTech label by BPI France, the public investment bank dedicated to innovation. This recognition is a testament to our commitment to pushing the boundaries of biotechnology with our groundbreaking AI discovery platform for Biologics.
Continue reading “Unlocking the Future of Pharma: PEACCEL’s Breakthrough AI Platform for Biologics Wins French DeepTech Label.”
Protein engineering in the context of metabolic engineering has a growing impact in industrial biotechnology and synthetic biology. Epistasis is a crucial issue: Non-Linear responses can hinder drug target identification or optimization of industrial production processes.
Discover our Editorial for a special issue of Frontiers in Molecular Biosciences: Machine learning, epistasis, and protein engineering: From sequence-structure-function relationships to regulation of metabolic pathways VOL I.
Read more: https://www.readcube.com/articles/10.3389/fmolb.2022.1098289
For more information:
PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/
Maximize your next value creation opportunity for peptides, proteins, enzymes, antibodies & VHHs. Stand out of the reach of your competitors.
EPI_technology™ (Epistasis Processing Inside): Unique on the market, better & quicker for protein design & optimization
Meet Peaccel’s delegates Jean-Marie Vallet and Jacob Weintraub at the Synthetic Biology-Based Therapies Summit, December 14-15 2022, Boston, US: https://synthetic-biology-therapeutics-summit.com
For more information:
PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/
The recent development of structure prediction deep learning (DL) tools such as Alphafold2 (DeepMind), ESMfold (Meta) or ProteinMPNN (David Baker’s team) has revolutionized this area. Nevertheless, these DL tools are not suitable for predicting how individual amino acid changes alter protein function: they can’t predict epistaticeffects.
After protein folding powered by DeepMind and Meta the next challenge is to accurately predict epistasis ie. the impact of non-linear interactions of mutations within the protein sequence on the function.
Our recent review of Machine Learning (ML) and Deep Learning (DL) strategies examines how epistatic effects influence the success rate of protein engineering projects by comparing 15 state-of-the-art approaches (see Table 4: https://link.springer.com/protocol/10.1007/978-1-0716-2152-3_15/tables/4) and provides a general workflow for non-experts when using such learning strategies.
Read more: https://link.springer.com/protocol/10.1007/978-1-0716-2152-3_15#Abs1
For more information:
PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/
Epistasis dramatically influences the success of drug discovery projects: The real lead drug candidate is missed if epistasis is not taken into account.
After protein folding powered by Meta and DeepMind , the next challenge is to accurately predict epistasis ie. the impact of non-linear interactions of mutations within the protein sequence. PEACCEL’s founder, co-authored in ACS Catalysis a critical review on epistasis with its partners at Leibniz Institute of Plant Biochemistry.
Read more: https://pubs.acs.org/doi/10.1021/acscatal.2c01426#
For more information :
PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/
PEACCEL (Paris, Fr) and JWIP & Patent Services, LLC (Boston, USA) have signed a strategic partnership agreement.
As of October 2022, PEACCEL – The AI company for life sciences in Paris, and JWIP & Patent Services, LLC a Leading IP Firm in Boston, USA, combine their know-how and expertise to address the increasing needs of emerging AI-based drug discovery challenges for their large portfolio of customers and partners.
Combining the innov’SAR industrial AI platform developed by PEACCEL and the legal counsel provided by JWIP to accelerate critical collaborations and licensing between PEACCEL and key players in the pharmaceutical and chemical industries.
PEACCEL and partners underline in the June 2022 issue of the peer-
reviewed journal Frontiers in Artificial intelligence how non-linearity is crucial when
modeling metabolic pathways for the identification of biomarkers of diseases or
optimizing industrial production processes.
Exemplified for:
VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. Unfortunately, most VHHs do not have 3D structures. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.
PEACCEL and SYNTHELIS have signed a strategic partnership to offer their clients and partners a one-stop shop combining Artificial Intelligence (AI) and Cell-Free lead expression for accelerated drug discovery.
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PEACCEL and SYNTHELIS have signed a strategic partnership to offer their clients and partners a one-stop shop combining Artificial Intelligence (AI) and Cell-Free lead expression for accelerated drug discovery.
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