All Competitors

Predicts the radius of gyration of intrinsically disordered proteins from 23 physics-derived sequence features, screening missense mutants in bulk.

Structure-based mutational effect prediction from local atomic environments, scoring how substitutions change protein stability and binding affinity.

Lightweight AlphaFlow variant that fine-tunes only AlphaFold's structure module, keeping the Evoformer frozen to cut conformational sampling cost.

Generative biological foundation model placing DNA, RNA, and protein in one shared vocabulary, spanning genomic, proteomic, and cross-molecule tasks.

Multimodal generative protein language model reasoning jointly over protein sequence, structure, and function, trained at 98B parameters.

Blind peptide binder design from a protein sequence alone, evolving linear or cyclic binders against a frozen AlphaFold2 with no binding site given.

Multimodal model fusing pre-trained DNA, RNA, and protein encoders through cross-attention to predict tissue-specific transcript isoform expression.

Scaling-law study of protein language models identifying compute-optimal training for causal and masked objectives on 939 million protein sequences.

Essential-protein prediction for prokaryotic genomes, pairing a frozen ESM-2 encoder with a bi-LSTM ensemble that generalizes to unseen species.

Structure-based molecular design that samples a quantum electron cloud in the protein pocket, then decodes it into ligands with a Llama-style model.

Multi-task protein framework recasting function, binding site, and structure prediction as autoregressive next-token prediction over ESM2 embeddings.

Full-atom peptide binder design against a target pocket, generating backbone frames, side-chain torsions and residue types in one joint flow.

Protein function prediction model that conditions a T5 encoder-decoder on retrieved homologs to assign EC numbers, GO terms and Pfam families.

Neural ab initio reconstruction for cryo-EM and cryo-ET that jointly infers particle poses and a continuous landscape of conformational states.

Tri-modal protein language model aligning sequence, structure, and text in one embedding space for natural-language search over billions of proteins.

Multimodal protein language model extending ESM-2 and SaProt with a Structure Adapter over residue torsion angles for protein function prediction.

Generative antibody language model for antigen-binding prediction and de novo paired heavy-light chain design, scaled to 2.4 billion parameters.

Homology-aware but alignment-free protein language model using the Mamba state space architecture to condition on hundreds of unaligned homologs.

Protein conformation sampler that rebuilds AlphaFold2 as a structural diffusion model, generating alternative folded states from sequence alone.

Structure-conditioned protein language model aligned to experimental stability data, scoring variant stability and generating stabilized sequences.

Efficient protein language model library from Prescient Design enabling high-quality sequence representations and fitness prediction in 24 GPU hours.

Trainable, open-source reimplementation of AlphaFold2 for protein structure prediction that matches its accuracy and runs 3-5x faster.

Deep learning framework predicting equilibrium distributions of molecular systems, enabling efficient ensemble generation and conformation sampling.