Cover Image

QSAR-Guided Generative Framework for the Discovery of Synthetically Viable Odorants

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pearce, Tim C., Ibrahim, Ahmed
Format:	Preprint
Published:	2025
Subjects:	Chemical Physics Machine Learning Biomolecules Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Designing the Haystack: Programmable Chemical Space for Generative Molecular Discovery
by: Zhu, Yuchen, et al.
Published: (2026)

ProtSCAPE: Mapping the landscape of protein conformations in molecular dynamics
by: Viswanath, Siddharth, et al.
Published: (2024)

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
by: Min, Yaosen, et al.
Published: (2022)

LICO: Large Language Models for In-Context Molecular Optimization
by: Nguyen, Tung, et al.
Published: (2024)

RNAGenScape: Property-Guided, Optimized Generation of mRNA Sequences with Manifold Langevin Dynamics
by: Liao, Danqi, et al.
Published: (2025)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models
by: Kulytė, Paulina, et al.
Published: (2024)

ImmunoAI: Accelerated Antibody Discovery Using Gradient-Boosted Machine Learning with Thermodynamic-Hydrodynamic Descriptors and 3D Geometric Interface Topology
by: Shivakumar, Shawnak, et al.
Published: (2025)

Curiosity as a Self-Supervised Method to Improve Exploration in De novo Drug Design
by: Chadi, Mohamed-Amine, et al.
Published: (2023)

Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling
by: Lu, Jiarui, et al.
Published: (2023)

Conditioning Protein Generation via Hopfield Pattern Multiplicity
by: Varner, Jeffrey D.
Published: (2026)

DDoS: A Graph Neural Network based Drug Synergy Prediction Algorithm
by: Schwarz, Kyriakos, et al.
Published: (2022)

A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation
by: Wang, Yongkang, et al.
Published: (2023)

Generative power of a protein language model trained on multiple sequence alignments
by: Sgarbossa, Damiano, et al.
Published: (2022)

NPGPT: Natural Product-Like Compound Generation with GPT-based Chemical Language Models
by: Sakano, Koh, et al.
Published: (2024)

Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders
by: Abeer, A N M Nafiz, et al.
Published: (2024)

NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
by: Liu, Zhiyuan, et al.
Published: (2025)

Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks
by: Ünlü, Atabey, et al.
Published: (2023)

Molecular dynamics simulations with grand-canonical reweighting suggest cooperativity effects in RNA structure probing experiments
by: Calonaci, Nicola, et al.
Published: (2022)

Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules versus Therapeutic Peptides
by: Wang, Yiquan, et al.
Published: (2025)

Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction
by: Weitzman, Ruben, et al.
Published: (2025)

Differentiable Folding for Nearest Neighbor Model Optimization
by: Krueger, Ryan K., et al.
Published: (2025)

Classifying the Stoichiometry of Virus-like Particles with Interpretable Machine Learning
by: Zhang, Jiayang, et al.
Published: (2025)

Exploring zero-shot structure-based protein fitness prediction
by: Sharma, Arnav, et al.
Published: (2025)

IgCraft: A versatile sequence generation framework for antibody discovery and engineering
by: Greenig, Matthew, et al.
Published: (2025)

Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives
by: Liu, Xiaokun, et al.
Published: (2025)

PocketVina Enables Scalable and Highly Accurate Physically Valid Docking through Multi-Pocket Conditioning
by: Sarigun, Ahmet, et al.
Published: (2025)

Protein Fold Classification at Scale: Benchmarking and Pretraining
by: Chen, Dexiong, et al.
Published: (2026)

Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation
by: Wang, Zhiwei, et al.
Published: (2024)

TriFit: Trimodal Fusion with Protein Dynamics for Mutation Fitness Prediction
by: Cho, Seungik
Published: (2026)

Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations
by: Lu, Jiarui, et al.
Published: (2024)

Accurate RNA 3D structure prediction using a language model-based deep learning approach
by: Shen, Tao, et al.
Published: (2022)

Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space
by: Lee, Minji, et al.
Published: (2024)

ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution
by: Cheng, Lixue, et al.
Published: (2022)

Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
by: Gu, Siyi, et al.
Published: (2024)

Is novelty predictable?
by: Fannjiang, Clara, et al.
Published: (2023)

Improving Protein Optimization with Smoothed Fitness Landscapes
by: Kirjner, Andrew, et al.
Published: (2023)

Drug Repurposing for Parkinson's Disease Using Random Walk With Restart Algorithm and the Parkinson's Disease Ontology Database
by: Kankariya, Pratham, et al.
Published: (2024)

Optimizing Convolutional Neural Networks for Identifying Invasive Pollinator Apis Mellifera and Finding a Ligand drug to Protect California's Biodiversity
by: Swaroop, Arnav
Published: (2024)

Biologically-Grounded Multi-Encoder Architectures as Developability Oracles for Antibody Design
by: Crouzet, Simon J.
Published: (2026)

gRNAde: Geometric Deep Learning for 3D RNA inverse design
by: Joshi, Chaitanya K., et al.
Published: (2023)