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Protein Engineering

Accelerate Protein Design

Rational design of proteins can aid a multitude of translational R&D efforts. Models like AlphaFold have been used forin silico SARS-CoV-2 antigen predictions, de novo protein design, and characterizing agents of antibiotic resistance. However usage is blocked by access to GPUs and ease of use for scientists. Latch offers efficient GPU access for running hundreds of protein-ML applications.

Flowchart of protein design workflow with screening, candidate identification, and PDB storage using Latch Workflow and Latch Data
1

Launch AlphaFold, ColabFold, or custom models to predict 3D protein structure

Predict 3D protein structures using ready-to-run LLMs.

User friendly interface accessed through Latch Workflow for AlphaFold2 showing text box with example amino acid sequences

Anyone can use the Latch Verified AlphaFold or ColabFold workflow to 3D protein structure from amino acid inputs. Define GPU resources for efficient and rapid LLM inference.

AlphaFold

DeepMind’s highly accurate protein structure prediction model

ColabFold

Sergey O’s work to increase the speed of AlphaFold2

OmegaFold

Enables accurate prediction of orphan proteins

2

Visualize a .pdb on Latch, or import into a Pod for further investigation

Armed with 3D protein structures, infer functional properties of proteins and explore annotations.

3D ribbon model of a protein structure with additional visualization options

Or anyone familiar with code can run custom downstream analysis in pods to look at molecular dynamics, binding affinities, and other protein attributes using tools like Bio3D.