Alex Morehead
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View article: Flow matching for generative modeling in bioinformatics and computational biology
Flow matching for generative modeling in bioinformatics and computational biology Open
View article: GCP-VQVAE: A Geometry-Complete Language for Protein 3D Structure
GCP-VQVAE: A Geometry-Complete Language for Protein 3D Structure Open
Converting protein tertiary structure into discrete tokens via vector-quantized variational autoencoders (VQ-VAEs) creates a language of 3D geometry and provides a natural interface between sequence and structure models. While pose invaria…
View article: How to go with the flow: flow matching in bioinformatics and computational biology
How to go with the flow: flow matching in bioinformatics and computational biology Open
View article: How to go with the flow: flow matching in bioinformatics and computational biology
How to go with the flow: flow matching in bioinformatics and computational biology Open
View article: Assessing the potential of deep learning for protein-ligand docking.
Assessing the potential of deep learning for protein-ligand docking. Open
The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning …
View article: RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design.
RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design. Open
We introduce RNA-FrameFlow, the first generative model for 3D RNA backbone design. We build upon flow matching for protein backbone generation and establish protocols for data preparation and evaluation to address unique challenges p…
View article: How to go with the flow: flow matching in bioinformatics and computational biology
How to go with the flow: flow matching in bioinformatics and computational biology Open
View article: <scp>FlowDock</scp>: Geometric flow matching for generative protein–ligand docking and affinity prediction
<span>FlowDock</span>: Geometric flow matching for generative protein–ligand docking and affinity prediction Open
Motivation Powerful generative AI models of protein–ligand structure have recently been proposed, but few of these methods support both flexible protein–ligand docking and affinity estimation. Of those that do, none can directly model mult…
View article: MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction Models
MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction Models Open
Protein structure prediction models such as AlphaFold3 (AF3) push the frontier of biomolecular modeling by incorporating science-informed architectural changes to the transformer architecture. However, these advances come at a steep system…
View article: Protein‐Ligand Structure and Affinity Prediction in <scp>CASP16</scp> Using a Geometric Deep Learning Ensemble and Flow Matching
Protein‐Ligand Structure and Affinity Prediction in <span>CASP16</span> Using a Geometric Deep Learning Ensemble and Flow Matching Open
Predicting the structure of ligands bound to proteins is a foundational problem in modern biotechnology and drug discovery, yet little is known about how to combine the predictions of protein‐ligand structure (poses) produced by the latest…
View article: FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction.
FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction. Open
In this work, we propose FlowDock, the first deep geometric generative model based on conditional flow matching that learns to directly map unbound (apo) structures to their bound (holo) counterparts for an arbitrary number of binding liga…
View article: Geometry-complete diffusion for 3D molecule generation and optimization
Geometry-complete diffusion for 3D molecule generation and optimization Open
View article: Evaluating representation learning on the protein structure universe
Evaluating representation learning on the protein structure universe Open
We introduce ProteinWorkshop, a comprehensive benchmark suite for representation learning on protein structures with Geometric Graph Neural Networks. We consider large-scale pre-training and downstream tasks on both experimental and predic…
View article: gRNAde: Geometric Deep Learning for 3D RNA inverse design
gRNAde: Geometric Deep Learning for 3D RNA inverse design Open
Computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D conformational diversity. We introduce gRNAde , a g eometric RNA…
View article: Protein structure accuracy estimation using geometry‐complete perceptron networks
Protein structure accuracy estimation using geometry‐complete perceptron networks Open
Estimating the accuracy of protein structural models is a critical task in protein bioinformatics. The need for robust methods in the estimation of protein model accuracy (EMA) is prevalent in the field of protein structure prediction, whe…
View article: Protein Structure Accuracy Estimation using Geometry-Complete Perceptron Networks
Protein Structure Accuracy Estimation using Geometry-Complete Perceptron Networks Open
Estimating the accuracy of protein structural models is a critical task in protein bioinformatics. The need for robust methods in the estimation of protein model accuracy (EMA) is prevalent in the field of protein structure prediction, whe…
View article: Geometry-complete perceptron networks for 3D molecular graphs
Geometry-complete perceptron networks for 3D molecular graphs Open
Motivation The field of geometric deep learning has recently had a profound impact on several scientific domains such as protein structure prediction and design, leading to methodological advancements within and outside of the realm of tra…
View article: Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusion
Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusion Open
Generative models of macromolecules carry abundant and impactful implications for industrial and biomedical efforts in protein engineering. However, existing methods are currently limited to modeling protein structures or sequences, indepe…
View article: Impact of <scp>AlphaFold</scp> on structure prediction of protein complexes: The <scp>CASP15‐CAPRI</scp> experiment
Impact of <span>AlphaFold</span> on structure prediction of protein complexes: The <span>CASP15‐CAPRI</span> experiment Open
We present the results for CAPRI Round 54, the 5th joint CASP‐CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo‐trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7…
View article: Accurate prediction of protein tertiary structural changes induced by single-site mutations with equivariant graph neural networks
Accurate prediction of protein tertiary structural changes induced by single-site mutations with equivariant graph neural networks Open
Predicting the change of protein tertiary structure caused by singlesite mutations is important for studying protein structure, function, and interaction. Even though computational protein structure prediction methods such as AlphaFold can…
View article: PreMut Datasets
PreMut Datasets Open
This dataset contains the PDB files used in the work PreMut. Also the CSV files containing the information about the wild-mutant pairs in the test data.
View article: PreMut Datasets
PreMut Datasets Open
This dataset contains the PDB files used in the work PreMut. Also the CSV files containing the information about the wild-mutant pairs in the test data. We also provide the predicted pdb files by PreMut and AlphaFold for evaluation purpose…
View article: PreMut Datasets
PreMut Datasets Open
This dataset contains the PDB files used in the work PreMut. Also the CSV files containing the information about the wild-mutant pairs in the test data.
View article: PreMut Datasets
PreMut Datasets Open
This dataset contains the PDB files used in the work PreMut. Also the CSV files containing the information about the wild-mutant pairs in the test data. We also provide the predicted pdb files by PreMut and AlphaFold for evaluation purpose…
View article: DIPS-Plus: The enhanced database of interacting protein structures for interface prediction
DIPS-Plus: The enhanced database of interacting protein structures for interface prediction Open
View article: Impact of AlphaFold on Structure Prediction of Protein Complexes: The CASP15-CAPRI Experiment
Impact of AlphaFold on Structure Prediction of Protein Complexes: The CASP15-CAPRI Experiment Open
We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homo-dimers, 3 homo-trimers, 13 hetero-dimers including 3 antibody-antigen complexes, and…
View article: DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data)
DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data) Open
This dataset contains supplementary replication data for the paper titled "DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction". In particular, it contains a new version of our `final_raw_dips.tar.gz…
View article: DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data)
DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data) Open
This dataset contains supplementary replication data for the paper titled "DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction". In particular, it contains a new version of our `final_raw_dips.tar.gz…
View article: DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data)
DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data) Open
This dataset contains supplementary replication data for the paper titled "DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction". In particular, it contains a new version of our `final_raw_dips.tar.gz…
View article: A gated graph transformer for protein complex structure quality assessment and its performance in CASP15
A gated graph transformer for protein complex structure quality assessment and its performance in CASP15 Open
Motivation Proteins interact to form complexes to carry out essential biological functions. Computational methods such as AlphaFold-multimer have been developed to predict the quaternary structures of protein complexes. An important yet la…