Generative artificial intelligence for small molecule drug design
Highlights•Brief history and background of Generative AI (GenAI).•Applications of GenAI in
drug design.•Representations of molecules in GenAI.•Importance of databases in …
drug design.•Representations of molecules in GenAI.•Importance of databases in …
Deep reinforcement learning in chemistry: A review
Reinforcement learning (RL) has been applied to various domains in computational
chemistry and has found wide‐spread success. In this review, we first motivate the …
chemistry and has found wide‐spread success. In this review, we first motivate the …
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning
Rapid determination of molecular structures can greatly accelerate workflows across many
chemical disciplines. However, elucidating structure using only one-dimensional (1D) NMR …
chemical disciplines. However, elucidating structure using only one-dimensional (1D) NMR …
Spiers Memorial Lecture: How to do impactful research in artificial intelligence for chemistry and materials science
Machine learning has been pervasively touching many fields of science. Chemistry and
materials science are no exception. While machine learning has been making a great …
materials science are no exception. While machine learning has been making a great …
Spectra to structure: contrastive learning framework for library ranking and generating molecular structures for infrared spectra
Inferring complete molecular structure from infrared (IR) spectra is a challenging task. In this
work, we propose SMEN (Spectra and Molecule Encoder Network), a framework for scoring …
work, we propose SMEN (Spectra and Molecule Encoder Network), a framework for scoring …
Lmm spectrometric determination of an organic compound
K Kawchak - 2024 - chemrxiv.org
Many machine learning models used in academia and industry that identify organic
compounds typically lack the ability to converse over prompts and results, and also require …
compounds typically lack the ability to converse over prompts and results, and also require …
Spectro: A multi-modal approach for molecule elucidation using IR and NMR data
E Chacko, R Sondhi, A Praveen, KL Luska… - 2024 - chemrxiv.org
Molecular structure elucidation is a crucial but fundamentally challenging step in the
characterization of materials given the large number of possible structures. Here, we …
characterization of materials given the large number of possible structures. Here, we …
TorRNA-Improved Prediction of Backbone Torsion Angles of RNA by Leveraging Large Language Models
S Devata, D Priyakumar - 2024 - chemrxiv.org
RNA molecules play a significant role in many biological pathways and have diverse
functional roles, which is a result of their structural flexibility to fold into diverse …
functional roles, which is a result of their structural flexibility to fold into diverse …
[PDF][PDF] Rethinking Structure Prediction in Computational Chemistry: The Role of Machine Learning in Replacing Database Searches
S Devata - 2024 - web2py.iiit.ac.in
Well designed search algorithms can be used to search databases in computational
chemistry to identify unknown compounds and their structures based on their observable …
chemistry to identify unknown compounds and their structures based on their observable …