All Competitors

De novo atomic model building from cryo-EM density maps, adapting AlphaFold2 with local attention and a 3D rotary position embedding.

RNA interaction foundation model for conditional, zero-shot design of RNA sequences that bind protein, DNA, or RNA targets without retraining.

Full-precision LoRA fine-tuning of ESM-2 for per-residue binding site prediction, where low-rank constraints curb overfitting on small datasets.

Protein domain annotation model pairing an ESM-2 backbone with a probabilistic decoder, bringing language-model sensitivity to Pfam-style assignment.

Protein-ligand binding model that embeds ligands, pockets, and sequences in hyperbolic space, unifying virtual screening and affinity ranking.

Protein-protein binding affinity and interface hotspot prediction from sequence alone, using protein language models fine-tuned on SKEMPI 2.0.

Biomolecular sequence-structure co-design that plans over frozen folding and inverse-folding models with Monte Carlo tree search, training nothing.

Protein druggability classification from sequence alone, stacking a self-attentive BiLSTM and Transformer encoder on frozen ESM-2 embeddings.

Conformational ensemble generation between two anchor structures, mixing inverse-folding probabilities to prompt a frozen structure predictor.

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

Topology-guided protein backbone generation that turns hand-drawn 3D curves into designable structures by steering a diffusion sampler with a sketch.

Context-aware protein sequence search, where a genomic language model fine-tuned for retrieval lets neighboring genes shape the query embedding.

E3 ubiquitin ligase-substrate interaction prediction from a LoRA-adapted protein language model fused with structure and subcellular localization.

Geometric deep learning scoring function for protein-ligand binding affinity, pretrained on synthetic complexes and fine-tuned on PDBbind structures.

Protein motion prediction from sequence alone, mapping language model embeddings to continuous 3D displacement vectors with a lightweight CNN.

Antibody sequence-structure co-design diffusion model adding atom-level equivariant geometry to residue embeddings, raising CDR-H3 recovery to 38.9%.

All-atom 3D molecular foundation model pretrained across small molecules, proteins, and complexes with an E(3)-equivariant denoising objective.

Discrete generative model for antibody protein sequences combining MCMC walks on a smoothed energy landscape with one-step denoising jumps.

Protein language model that emulates molecular dynamics, generating equilibrium conformational ensembles and multi-timescale dynamic trajectories.

Structure-based drug design model pairing SE(3)-equivariant diffusion with retrieval of pocket-matched scaffolds to generate ligands for a target.

Equivariant heterogeneous graph network that rescores docked protein-ligand poses for virtual screening and ranks structural analogs by activity.

De novo peptide binder design framework that targets specific motifs, including disordered regions and conserved epitopes, from target sequence alone.

Uncertainty-aware diffusion model that enhances cryo-EM density maps while estimating voxel-wise confidence via Monte Carlo sampling.