2. Biomolecular Design Tools

AF2_seq-MPNN: A protocol, based on AF2_seq and ProteinMPNN, for the computational design of topologically complex protein folds and soluble analogues of membrane proteins.
Published: June 19, 2024
Paper | Preprint | AF2_seq Code (GitHub) | Colab Notebook 1 | Colab Notebook 2

CarbonDesign: A protein sequence design method that adapts the success ingredients of AF2. CarbonDesign utilizes Inverseformer, a network architecture adapted from AlphaFold’s Evoformer. Based on scTM score, sequence recovery rate, and BLOSUM score, CarbonDesign outperformed other published methods, including versions of ProteinMPNN and ESM-IF, on CAMEO and CASP15 test sets, as well as RFdiffusion-generated backbones. CarbonDesign is also capable of predicting the effects of mutations on protein function.
Published: May 23, 2024
Paper | Preprint | Code (GitHub) | Code (Code Ocean)

AntiFold: An inverse folding model for antibody sequence design based on ESM-IF1.
Posted: May 06, 2024
Preprint | Code (GitHub) | Webserver | Colab Notebook

SPDesign: A method that combines structural sequence profile, fast shape recognition, and pre-trained language models for protein sequence design.
Published: April 09, 2024
Paper | Webserver | Code

Evo: A long-context foundation model that generalizes across the central dogma of biology: DNA, RNA, and proteins. Evo is a 7 billion parameter model trained to generate DNA sequences and is capable of prediction and generative tasks, from molecules to whole genomes.
Posted: March 06, 2024
Preprint | Code (GitHub) | Code (PyPI) | Blog | Playground | Colab Notebook

PocketGen: A method for generating full-atom ligand-binding pockets to design small molecule-binding proteins. PocketGen uses a co-design strategy that, given the ligand and the scaffold, simultaneously designs the sequence and structure of the protein pocket.
Posted: Feb 28, 2024
Preprint | Code (GitHub) | Blog

CoVES: A “simple” model to design functional and diverse combinatorial protein variants.
Published: Feb 22, 2024
Published: Jan 06, 2024
Paper | Code (GitHub) | Code (Zenodo)

Multiflow: A generative model for protein sequence and structure co-design based on the DFM and FrameFlow models.
Posted: Feb 07, 2024
Preprint | Code (GitHub)

Protpardelle: A generative model for structure-based protein design that sets a new state-of-the-art by outperforming existing models on various metrics. Genie 2 builds on Genie (version 1) to expand the structure space (size and diversity) captured by the model.
Published: Jun 25, 2024
Paper | Code (GitHub) | Preprint | Web Demo (HuggingFace)

Genie 2: A generative model for structure-based protein design that sets a new state-of-the-art by outperforming existing models on various metrics. Genie 2 builds on Genie (version 1) to expand the structure space (size and diversity) captured by the model.
Posted: May 24, 2024
Preprint | Code (GitHub)

Proteus: A diffusion model for de novo protein backbone generation that, based on multiple metrics, surpasses other leading methods, including RFdiffusion, Genie, FrameDiff, and Chroma.
Posted: Feb 12, 2024
Preprint | Code (GitHub)

Multiflow: A generative model for protein sequence and structure co-design based on the DFM and FrameFlow models.
Posted: Feb 07, 2024
Preprint | Code (GitHub)

FrameFlow: FrameFlow is an SE(3) flow matching model for fast protein backbone generation, adapted from the diffusion-based FrameDiff model. FrameFlow has also been extended to the motif-scaffolding task. Posted: Jan 08, 2024 | Oct 10, 2023
Preprint 1 | Preprint 2 | Code (GitHub)

RFdiffusion All-Atom (RFdiffusionAA): A diffusion model that generates de novo protein structures around small molecules and other non-protein targets. RFdiffusionAA was developed by fine-tuning RosettaFold All-Atom (RFAA) on structure denoising.
Published: March 07, 2024
Paper | Code (GitHub)

PepFlow: A method to predict structures of peptides, including single-state and ensembles of conformations. PepFlow is also capable of generating structures of macrocycles.
Published: Jun 27, 2024
Paper | Preprint | Code (GitLab)

EvoBind2: A method for designing novel linear and cyclic protein-binding peptides using just the amino acid sequence of the target protein as input. EvoBind2, similar to EvoBind (v1), presents as an in silico directed evolution method using a strategy analogous to the "diversify-screen/select(-amplify)" cycle of experimental directed evolution.
Posted: Jun 22, 2024
Preprint | Code (GitHub) | EvoBind v1 Paper | EvoBind v1 Code (GitHub) | EvoBind v1 Colab Notebook

HELM-GPT: A generative model for de novo design of macrocyclic peptides.
Published: Jun 12, 2024
Paper | Code (GitHub)

AfCycDesign: An AlphaFold2-based approach for accurate structure prediction and design of cyclic peptides. AfCycDesign is capable of fixed backbone and de novo design of cyclic peptides, outperforming Rosetta on cyclic peptide design tasks.
Posted: Feb 26, 2023
Preprint | Colab Notebook

RNAFlow: A flow-matching model for simultaneous design of RNA structure and sequence conditioned on protein structure and sequence. The denoising network of RNAFlow comprises: 1. an RNA inverse folding model, and 2. a pre-trained RosettaFold2NA network. In each design cycle, RNAFlow first designs a RNA sequence for a given noised protein-RNA complex, and then uses RosettaFold2NA to predict a denoised RNA structure.
Posted: May 29, 2024
Preprint | Code (GitHub)

gRNAde: The “ProteinMPNN for RNA sequence design”. gRNAde is a geometric DL-based model for computational design of RNA sequences given 3D RNA backbone structures. gRNAde enables both single- and multi-state fixed-bb sequence design by generating candidates RNA sequences conditioned on one or more bb 3D conformations.
Posted: April 01, 2024
Preprint | Code (GitHub) | Colab Notebook 1 | Colab Notebook 2

Evo: A long-context foundation model that generalizes across the central dogma of biology: DNA, RNA, and proteins. Evo is a 7 billion parameter model trained to generate DNA sequences and is capable of prediction and generative tasks, from molecules to whole genomes.
Posted: March 06, 2024
Preprint | Code (GitHub) | Code (PyPI) | Blog | Playground | Colab Notebook

GenerRNA: A generative pre-trained language model for de novo RNA design. Posted: Feb 08, 2024
Preprint | Code (GitHub)

RfamGen: A generative model for designing functional RNA family sequences. RfamGen incorporates alignment and consensus secondary structure information and generates novel and functional RNA family sequences.
Published: Jan 18, 2024
Paper | Code (GitHub)

Evo: A long-context foundation model that generalizes across the central dogma of biology: DNA, RNA, and proteins. Evo is a 7 billion parameter model trained to generate DNA sequences and is capable of prediction and generative tasks, from molecules to whole genomes.
Posted: March 06, 2024
Preprint | Code (GitHub) | Code (PyPI) | Blog | Playground | Colab Notebook

DNA-Diffusion: A diffusion model to generate context-/cell type-specific DNA regulatory sequences.
Posted: Feb 01, 2024
Preprint | Code (GitHub) | Documentation

GeoAB: A method for computational design and optimization (affinity maturation) of antibody. GeoAB utilizes a co-design strategy, predicting the structure of a CDR and optimized 1D sequences for structure.
Posted: May 17, 2024
Preprint | Code (GitHub)

IgDiff: A model for de novo antibody design (structure generation) that adapted FrameDiff (a diffusion-based model for protein backbone generation) by fine-tuning it on artificial antibody structures.
Posted: May 13, 2024
Preprint | Code (Zenodo)

AntiFold: An inverse folding model for antibody sequence design based on ESM-IF1.
Posted: May 06, 2024
Preprint | Code (GitHub) | Webserver | Colab Notebook

tFold-Ab and tFold-Ag: Methods for antibody and antibody-antigen complex modelling and design by Tencent.
Posted: Feb 08, 2024
Preprint | Code (GitHub)