The transformative power of transformers in protein structure prediction
Bernard Moussad, Rahmatullah Roche, Debswapna Bhattacharya
Abstract
Transformer neural networks have revolutionized structural biology with the ability to predict protein structures at unprecedented high accuracy. Here, we report the predictive modeling performance of the state-of-the-art protein structure prediction methods built on transformers for 69 protein targets from the recently concluded 15th Critical Assessment of Structure Prediction (CASP15) challenge. Our study shows the power of transformers in protein structure modeling and highlights future areas of improvement.
Topics & Concepts
Protein structure predictionTransformerTransformative learningArtificial neural networkComputer sciencePredictive powerProtein structureArtificial intelligenceMachine learningEngineeringBiologyElectrical engineeringPsychologyPhysicsVoltageBiochemistryPedagogyQuantum mechanicsProtein Structure and DynamicsMachine Learning in BioinformaticsEnzyme Structure and Function