arXiv AI
Jun 17
Agentic Discovery of Non-Canonical Antimicrobial Peptides with AMPGAN v3
arXiv:2606. 17127v1 Announce Type: cross Abstract: Antimicrobial resistance causes to over a million deaths annually.
OmegAMP: Targeted AMP Discovery via Biologically Informed Generation
arXiv:2504. 17247v3 Announce Type: replace Abstract: Deep learning-based antimicrobial peptide (AMP) discovery faces critical challenges such as limited controllability, lack of representations that efficiently model antimicrobial properties, and low experimental hit rates.
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arXiv AI
1d ago
RetroMPA: A Molecular Property-Aware Auxiliary Framework for Enhancing Retrosynthesis Prediction
arXiv:2608. 16111v1 Announce Type: cross Abstract: Retrosynthesis is a cornerstone of drug discovery and organic synthesis.
arXiv AI
Jul 24
Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling
arXiv:2607. 20539v1 Announce Type: cross Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited.
arXiv AI
Jun 2
Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
arXiv:2606. 01220v1 Announce Type: cross Abstract: Generating molecules that simultaneously satisfy drug-like properties and conform to the 3D structure of a target protein is a core challenge in structure-based drug design (SBDD).
arXiv Machine Learning
Aug 4
Refine Drugs, Don't Complete Them: Uniform-Source Discrete Flows for Fragment-Based Drug Discovery
arXiv:2509. 26405v2 Announce Type: replace Abstract: We introduce InVirtuoGen, a discrete flow generative model for fragmented SMILES for de novo and fragment-constrained generation, and target-property/lead optimization of small molecules.
arXiv AI
Aug 10
Genotypic Triggers: Exposing Pharmacogenomic Blind Spots via Host-Specific Backdoors in Generative Antimicrobial Peptide Models
arXiv:2608. 06779v1 Announce Type: cross Abstract: Large Language Models (LLMs) have accelerated drug discovery, particularly in the automated design of antimicrobial peptides (AMPs).
arXiv Machine Learning
Jun 11
DeepRHP: A Hybrid Variational Autoencoder for Designing Random Heteropolymers as Protein Mimics
arXiv:2606. 11651v1 Announce Type: new Abstract: Synthetic random heteropolymers (RHPs), consisting of a predefined set of monomers, offer an approach toward the design of protein-like materials.
arXiv AI
Jun 15
FlexMS: A Unified Public Benchmark for Molecule Tandem Mass Spectrum Prediction
arXiv:2602. 22822v3 Announce Type: replace Abstract: Tandem mass spectrometry (MS/MS) is central to small molecule identification, but current deep learning systems for spectrum prediction still remain difficult to evaluate and deploy in practice.
arXiv AI
Jun 9
Frequency-Domain Latent Attention Gating for Cross-Domain Token Aggregation
arXiv:2606. 08191v1 Announce Type: cross Abstract: Token aggregation is a common bottleneck in models that map token representations to sample-level predictions, yet most pooling methods operate only in the original token domain.
arXiv Machine Learning
Jun 10
Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors
arXiv:2602. 04119v2 Announce Type: replace Abstract: The application of generative models for experimental drug discovery campaigns is severely limited by the difficulty of designing molecules de novo that can be synthesized in practice.
arXiv Machine Learning
Jun 25
Why Pool When You Can Flow? Active Learning with GFlowNets
arXiv:2509. 00704v2 Announce Type: replace Abstract: The scalability of pool-based active learning is limited by the computational cost of evaluating large unlabeled datasets, a challenge that is particularly acute in virtual screening for drug discovery.
arXiv Machine Learning
Jun 9
Active Flow Expansion for Out-of-Distribution Discovery: from Theory to Molecules
arXiv:2606. 08802v1 Announce Type: new Abstract: Standard flow and diffusion pre-training matches the distribution of available data (e.