LambdaPP: Fast and accessible protein-specific phenotype predictions

Abstract

AbstractThe availability of accurate and fast Artificial Intelligence (AI) solutions predicting aspects of proteins are revolutionizing experimental and computational molecular biology. The webserverLambdaPPaspires to supersede PredictProtein, the first internet server making AI protein predictions available in 1992. Given a protein sequence as input,LambdaPPprovides easily accessible visualizations of protein 3D structure, along with predictions at the protein level (GeneOntology, subcellular location), and the residue level (binding to metal ions, small molecules, and nucleotides; conservation; intrinsic disorder; secondary structure; alpha-helical and beta-barrel transmembrane segments; signal-peptides; variant effect) in seconds. The structure prediction provided byLambdaPP- leveragingColabFold and computed in minutes- is based onMMseqs2multiple sequence alignments. All other feature prediction methods are based on the pLMProtT5. Queried by a protein sequence,LambdaPPcomputes protein and residue predictions almost instantly for various phenotypes, including 3D structure and aspects of protein function.Accessibility StatementLambdaPP is freely available for everyone to use underembed.predictprotein.org, the interactive results for the case study can be found underhttps://embed.predictprotein.org/o/Q9NZC2. The frontend of LambdaPP can be found on GitHub (github.com/sacdallago/embed.predictprotein.org), and can be freely used and distributed under the academic free use license (AFL-2). For high-throughput applications, all methods can be executed locally via the bio-embeddings (bioembeddings.com) python package, or docker image atghcr.io/bioembeddings/bio_embeddings, which also includes the backend of LambdaPP.Impact StatementWe introduce LambdaPP, a webserver integrating fast and accurate sequence-only protein feature predictions based on embeddings from protein Language Models (pLMs) available in seconds along with high-quality protein structure predictions. The intuitive interface invites experts and novices to benefit from the latest machine learning tools. LambdaPP’s unique combination of predicted features may help in formulating hypotheses for experiments and as input to bioinformatics pipelines.