GenPharmaChain
Revolutionizing Drug Discovery with AI-Driven Protein Engineering and Decentralized Computing
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Current issues in the pharmaceutical industry
Protein prediction is crucial in modern medicine, particularly in precision medicine and drug development. Proteins are key molecules that perform various functions in organisms, and protein prediction uses computer modeling to predict their 3D structure and interactions, helping to understand their roles in cells and the body. This process offers valuable insights into the causes of diseases.
Protein ® / drug develop / Trials
Our goal is to build a global decentralized platform where everyone can contribute their computational resources to help with complex protein structure prediction and functional studies.
200M+
Database entire
47+
key organisms proteomes
Reference：Cheng, J et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science (2023).
Jumper, J et al. Highly accurate protein structure prediction with AlphaFold. Nature (2021).Varadi, M et al. AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences. Nucleic Acids Research (2024).
Protein 3D structure
Protein design
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De novo design of protein topological structures
Applying Deep Learning Frameworks (such as AlphaFold, RoseTTAFold) for Large-Scale Fast Modeling of Immunoglobulin Variable Region 3D Structures
Develop an automated pipeline capable of processing antibody, TCR, and nanobody sequence datasets on the scale of 10510^5105, efficiently translating them into accurate three-dimensional structural models.
GAN-based nanobody scaffold design platform to explore hypervariable region (HCDR) 3D structures, engineer non-classical disulfide bonds, and optimize pH-dependent affinity maturation.
Protein topological structures
By generating new structures for motif scaffolds, it supports existing motifs on proteins. The platform also incorporates partial diffusion, allowing for the diversification of part or all of the protein to optimize various properties like solubility, thermal stability, and others.
Generate sequences for a given protein scaffold, or upload multiple structures for batch submission.
Choose the protein residues to be designed or fixed.
Protein topological structures
Predict how small molecules or candidate drugs bind to a known protein binding site, with the site specified by the coordinates of the binding pocket.
Predict the binding affinity (kcal/mol) and the ligand pose.
Simulate protein-peptide systems to find optimal binding modes Predict solubility, membrane permeability, and physicochemical characteristics
Drug molecular properties
ADME represents the acronym for Absorption, Distribution, Metabolism, and Excretion - the fundamental pharmacokinetic processes governing the dynamic disposition of drug compounds within biological systems.
Absorption: Oral bioavailability prediction (Fa% ± 5% accuracy) Distribution: Volume of distribution (Vd) modeling with PPB adjustments Metabolism: CYP450 isoform profiling (IC50 determinations) Excretion: Renal/hepatic clearance simulations
Protein research / PRECISION SERVICERE / Drug Production
Genpharamachain
Our Advantages
CONSITIT US
GenPharmaChain
Protein ® / drug develop / Trials
Our goal is to build a global decentralized platform where everyone can contribute their computational resources to help with complex protein structure prediction and functional studies.
200M+
Database entire
47+
key organisms proteomes
Reference：Cheng, J et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science (2023).
Jumper, J et al. Highly accurate protein structure prediction with AlphaFold. Nature (2021).Varadi, M et al. AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences. Nucleic Acids Research (2024).
Signal sequences (SignalP)
 Transmembrane regions (Phobius)
Coiled coils (Coils)
Intrinsically disordered regions
Protein research / PRECISION SERVICERE / Drug Production
Genpharamachain
Our Advantages
Protein Structure Prediction and Optimization
Our project focuses on predicting the structures of immune proteins at massive scale and speed. This capability allows us to redesign and optimize complementarity-determining regions (CDRs) for specific antigens, enhancing the precision and efficacy of protein-based therapies.
Binding Pose and Sequence Optimization
We specialize in predicting the binding poses of antibody-antigen complexes, crucial for understanding and improving protein interactions. Additionally, we optimize protein sequences to enhance properties such as thermostability, solubility, and overall developability, ensuring that the proteins we design are both effective and practical for therapeutic use.
De Novo Design of Nanobody Binders
Leveraging advanced computational tools, we design de novo nanobody binders tailored for specific antigens. This cutting-edge approach allows us to create highly specific and potent binders, expanding the possibilities for innovative treatments and diagnostics in the biomedical field.
CONSITIT US