Kieran Didi
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View article: GPU-accelerated homology search with MMseqs2
GPU-accelerated homology search with MMseqs2 Open
View article: <i>De novo</i> Design of All-atom Biomolecular Interactions with RFdiffusion3
<i>De novo</i> Design of All-atom Biomolecular Interactions with RFdiffusion3 Open
Deep learning has accelerated protein design, but most existing methods are restricted to generating protein backbone coordinates and often neglect interactions with other biomolecules. We present RFdiffusion3 (RFD3), a diffusion model tha…
View article: Accelerating Biomolecular Modeling with AtomWorks and RF3
Accelerating Biomolecular Modeling with AtomWorks and RF3 Open
Deep learning methods trained on protein structure databases have revolutionized biomolecular structure prediction, but developing and training new models remains a considerable challenge. To facilitate the development of new models, we pr…
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: A universal model for drug-receptor interactions
A universal model for drug-receptor interactions Open
The modern AI models promise decoding of the genomic landscape that holds, in principle, the information required for rational therapeutic design. Genes encode proteins whose functions are mediated by their three-dimensional structures via…
View article: La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching
La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching Open
Recently, many generative models for de novo protein structure design have emerged. Yet, only few tackle the difficult task of directly generating fully atomistic structures jointly with the underlying amino acid sequence. This is challeng…
View article: Proteina: Scaling Flow-based Protein Structure Generative Models
Proteina: Scaling Flow-based Protein Structure Generative Models Open
Recently, diffusion- and flow-based generative models of protein structures have emerged as a powerful tool for de novo protein design. Here, we develop Proteina, a new large-scale flow-based protein backbone generator that utilizes hierar…
View article: MotifBench: A standardized protein design benchmark for motif-scaffolding problems
MotifBench: A standardized protein design benchmark for motif-scaffolding problems Open
The motif-scaffolding problem is a central task in computational protein design: Given the coordinates of atoms in a geometry chosen to confer a desired biochemical function (a motif), the task is to identify diverse protein structures (sc…
View article: Predicting PROTAC off-target effects via warhead involvement levels in drug–target interactions using graph attention neural networks
Predicting PROTAC off-target effects via warhead involvement levels in drug–target interactions using graph attention neural networks Open
Proteolysis-targeting chimeras (PROTACs) represent an emerging modality for targeted protein degradation with broad therapeutic potential. However, the risk of off-target protein degradation remains a major concern in the development of PR…
View article: Structure-based drug design with equivariant diffusion models
Structure-based drug design with equivariant diffusion models Open
View article: GPU-accelerated homology search with MMseqs2
GPU-accelerated homology search with MMseqs2 Open
Rapidly growing protein databases demand faster sensitive sequence similarity detection. We present GPU-accelerated search utilizing intra-query parallelization delivering 6x faster single-protein searches compared to state-of-the-art CPU …
View article: BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery Open
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increasingly relies on computational scale, with recent protein la…
View article: Synsor: a tool for alignment-free detection of engineered DNA sequences
Synsor: a tool for alignment-free detection of engineered DNA sequences Open
DNA sequences of nearly any desired composition, length, and function can be synthesized to alter the biology of an organism for purposes ranging from the bioproduction of therapeutic compounds to invasive pest control. Yet despite offerin…
View article: DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised $h$-transform
DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised $h$-transform Open
Generative modelling paradigms based on denoising diffusion processes have emerged as a leading candidate for conditional sampling in inverse problems. In many real-world applications, we often have access to large, expensively trained unc…
View article: MISATO: machine learning dataset of protein–ligand complexes for structure-based drug discovery
MISATO: machine learning dataset of protein–ligand complexes for structure-based drug discovery Open
View article: Assessing antibody and nanobody nativeness for hit selection and humanization with AbNatiV
Assessing antibody and nanobody nativeness for hit selection and humanization with AbNatiV Open
View article: A framework for conditional diffusion modelling with applications in motif scaffolding for protein design
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design Open
Many protein design applications, such as binder or enzyme design, require scaffolding a structural motif with high precision. Generative modelling paradigms based on denoising diffusion processes emerged as a leading candidate to address …
View article: Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models?
Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models? Open
Deep generative models for structure-based drug design (SBDD), where molecule generation is conditioned on a 3D protein pocket, have received considerable interest in recent years. These methods offer the promise of higher-quality molecule…
View article: BioModelsML: Building a FAIR and reproducible collection of machine learning models in life sciences and medicine for easy reuse
BioModelsML: Building a FAIR and reproducible collection of machine learning models in life sciences and medicine for easy reuse Open
Machine learning (ML) models are widely used in life sciences and medicine; however, they are scattered across various platforms and there are several challenges that hinder their accessibility, reproducibility and reuse. In this manuscrip…
View article: AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for hit selection, humanisation, and engineering
AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for hit selection, humanisation, and engineering Open
Monoclonal antibodies have emerged as key therapeutics, and nanobodies are rapidly gaining momentum following the approval of the first nanobody drug in 2019. Nonetheless, the development of these biologics as therapeutics remains a challe…
View article: On How AI Needs to Change to Advance the Science of Drug Discovery
On How AI Needs to Change to Advance the Science of Drug Discovery Open
Research around AI for Science has seen significant success since the rise of deep learning models over the past decade, even with longstanding challenges such as protein structure prediction. However, this fast development inevitably made…
View article: Biomolecular condensate phase diagrams with a combinatorial microdroplet platform
Biomolecular condensate phase diagrams with a combinatorial microdroplet platform Open
View article: High Resolution Biomolecular Condensate Phase Diagrams with a Combinatorial Microdroplet Platform
High Resolution Biomolecular Condensate Phase Diagrams with a Combinatorial Microdroplet Platform Open
The assembly of intracellular proteins into biomolecular condensates is a fundamental process underlying the organisation of intracellular space and the regulation of many cellular processes. Mapping and characterising phase behaviour of b…