Molecular Similarity: Theory, Applications, and Perspectives DOI Creative Commons

Kenneth López Pérez,

Juan Avellaneda Tamayo,

Lexin Chen

и другие.

Опубликована: Ноя. 24, 2023

Molecular similarity pervades much of our understanding and rationalization chemistry. This has become particularly evident in the current data-intensive era chemical research, with measures serving as backbone many Machine Learning (ML) supervised unsupervised procedures. Here, we present a discussion on role molecular drug design, space exploration, “art” generation, representations, more. We also discuss more recent topics similarity, like ability to efficiently compare large libraries.

Язык: Английский

Chemoinformatic characterization of NAPROC-13: A database for natural product 13C-RMN dereplication DOI Creative Commons
Juan F. Avellaneda-Tamayo, Naicolette A. Agudo-Muñoz, Javier E. Sánchez-Galán

и другие.

Опубликована: Май 7, 2024

Natural products (NPs) are secondary metabolites of natural origin with broad applications across various human activities, particularly discovering bioactive compounds. Structural elucidation new NPs entails significant cost and effort. On the other hand, dereplication known compounds is crucial for early exclusion irrelevant in contemporary pharmaceutical research. NAPROC-13 stands out as a publicly accessible database, providing structural 13C NMR spectroscopic information over 25,000 compounds, rendering it pivotal resource product (NP) research, favoring open science. This study seeks to quantitatively analyze chemical content, diversity, space coverage within NAPROC-13, compared FDA-approved drugs very diverse subset NPs, UNPD-A. Findings indicated that exhibit comparable properties those UNPD-A, albeit showcasing notably array scaffolds, ring systems interest, molecular fragments. covers specific region multiverse regarding physicochemical UNPD-A terms features represented by fingerprints.

Язык: Английский

Процитировано

1

Molecular Similarity: Theory, Applications, and Perspectives DOI Creative Commons

Kenneth López Pérez,

Juan Avellaneda Tamayo,

Lexin Chen

и другие.

Опубликована: Ноя. 24, 2023

Molecular similarity pervades much of our understanding and rationalization chemistry. This has become particularly evident in the current data-intensive era chemical research, with measures serving as backbone many Machine Learning (ML) supervised unsupervised procedures. Here, we present a discussion on role molecular drug design, space exploration, “art” generation, representations, more. We also discuss more recent topics similarity, like ability to efficiently compare large libraries.

Язык: Английский

Процитировано

2