1 code implementation • 21 Dec 2023 • Alex Morehead, Jeffrey Ruffolo, Aadyot Bhatnagar, Ali Madani
In this work, we introduce MMDiff, a generative model that jointly designs sequences and structures of nucleic acid and protein complexes, independently or in complex, using joint SE(3)-discrete diffusion noise.
1 code implementation • 24 May 2023 • Chaitanya K. Joshi, Arian R. Jamasb, Ramon Viñas, Charles Harris, Simon Mathis, Alex Morehead, Pietro Liò
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 geometry and conformational diversity.
3 code implementations • 8 Feb 2023 • Alex Morehead, Jianlin Cheng
However, such methods are unable to learn important geometric and physical properties of 3D molecules during molecular graph generation, as they adopt molecule-agnostic and non-geometric GNNs as their 3D graph denoising networks, which negatively impacts their ability to effectively scale to datasets of large 3D molecules.
1 code implementation • 4 Nov 2022 • Alex Morehead, Jianlin Cheng
The field of geometric deep learning has had a profound impact on the development of innovative and powerful graph neural network architectures.
1 code implementation • 26 May 2022 • Elham Soltanikazemi, Raj S. Roy, Farhan Quadir, Nabin Giri, Alex Morehead, Jianlin Cheng
Utilizing true contacts as input, DRLComplex achieved high average TM-scores of 0. 9895 and 0. 9881 and a low average interface RMSD (I_RMSD) of 0. 2197 and 0. 92 on the two datasets, respectively.
1 code implementation • 21 May 2022 • Xiao Chen, Alex Morehead, Jian Liu, Jianlin Cheng
We challenge this significant task with DProQ, which introduces a gated neighborhood-modulating Graph Transformer (GGT) designed to predict the quality of 3D protein complex structures.
1 code implementation • 20 May 2022 • Alex Morehead, Xiao Chen, Tianqi Wu, Jian Liu, Jianlin Cheng
Protein complexes are macromolecules essential to the functioning and well-being of all living organisms.
no code implementations • 18 Apr 2022 • Maged Shoman, Armstrong Aboah, Alex Morehead, Ye Duan, Abdulateef Daud, Yaw Adu-Gyamfi
Automating the product checkout process at conventional retail stores is a task poised to have large impacts on society generally speaking.
1 code implementation • 23 Mar 2022 • Alex Morehead, Watchanan Chantapakul, Jianlin Cheng
In this work, we investigate the use of dimensionality reduction techniques such as PCA, t-SNE, and UMAP to see their effect on the performance of graph neural networks (GNNs) designed for semi-supervised propagation of node labels.
2 code implementations • ICLR 2022 • Alex Morehead, Chen Chen, Jianlin Cheng
Computational methods for predicting the interface contacts between proteins come highly sought after for drug discovery as they can significantly advance the accuracy of alternative approaches, such as protein-protein docking, protein function analysis tools, and other computational methods for protein bioinformatics.
1 code implementation • 6 Jun 2021 • Alex Morehead, Chen Chen, Ada Sedova, Jianlin Cheng
In this work, we expand on a dataset recently introduced for this task, the Database of Interacting Protein Structures (DIPS), to present DIPS-Plus, an enhanced, feature-rich dataset of 42, 112 complexes for geometric deep learning of protein interfaces.