Designing Pharmaceuticals Through Ligand-Centric Approaches DOI

Spoorthi R Kulkarni,

Vidya Niranjan,

Shradha Anand Mulimani

и другие.

Advances in medical technologies and clinical practice book series, Год журнала: 2024, Номер unknown, С. 217 - 246

Опубликована: Окт. 25, 2024

The chapter explores the integration of fragment-based drug design (FBDD) and diffusion-based models, exemplified by ProteinReDiff, in advancing ligand-centric approaches to discovery. FBDD provides a strategic framework for identifying potential candidates, while ProteinReDiff streamlines redesign process through innovative computational techniques. discusses effectiveness both methodologies optimizing ligand binding affinity enhancing efficacy, as evidenced experimental validations. It highlights paradigm shift brought about models like which depart from traditional reliance on structural data, making more accessible efficient. abstract emphasizes promise accelerating therapeutic development driving innovation biomedical research, with focus transparency credibility scientific endeavors.

Язык: Английский

Convergent Protocols for Computing Protein–Ligand Interaction Energies Using Fragment-Based Quantum Chemistry DOI
Paige E. Bowling, Dustin R. Broderick, John M. Herbert

и другие.

Journal of Chemical Theory and Computation, Год журнала: 2025, Номер unknown

Опубликована: Янв. 2, 2025

Fragment-based quantum chemistry methods offer a means to sidestep the steep nonlinear scaling of electronic structure calculations so that large molecular systems can be investigated using high-level methods. Here, we use fragmentation compute protein-ligand interaction energies in with several thousand atoms, new software platform for managing fragment-based implements screened many-body expansion. Convergence tests minimal-basis semiempirical method (HF-3c) indicate two-body calculations, single-residue fragments and simple hydrogen caps, are sufficient reproduce obtained conventional supramolecular within 1 kcal/mol at about 1% computational cost. We also demonstrate HF-3c results illustrative trends density functional theory basis sets up augmented quadruple-ζ quality. Strategic deployment facilitates converged biomolecular model alongside high-quality sets, bringing

Язык: Английский

Процитировано

5

Integrated Molecular Modeling and Machine Learning for Drug Design DOI Creative Commons
Song Xia, Eric Chen, Yingkai Zhang

и другие.

Journal of Chemical Theory and Computation, Год журнала: 2023, Номер 19(21), С. 7478 - 7495

Опубликована: Окт. 26, 2023

Modern therapeutic development often involves several stages that are interconnected, and multiple iterations usually required to bring a new drug the market. Computational approaches have increasingly become an indispensable part of helping reduce time cost research drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling machine learning develop computational tools for modulator design, including pocket-guided rational design approach based AlphaSpace target protein-protein interactions, delta scoring functions protein-ligand docking as well virtual screening, state-of-the-art deep models predict calculated experimental properties mechanics optimized geometries. Meanwhile, discuss remaining challenges promising directions further use retrospective example FDA approved kinase inhibitor Erlotinib demonstrate these newly developed tools.

Язык: Английский

Процитировано

32

Progress of machine learning in the application of small molecule druggability prediction DOI
Junyao Li, Jianmei Zhang, Rui Guo

и другие.

European Journal of Medicinal Chemistry, Год журнала: 2025, Номер 285, С. 117269 - 117269

Опубликована: Янв. 10, 2025

Язык: Английский

Процитировано

2

Top 20 influential AI-based technologies in chemistry DOI Creative Commons
Valentine P. Ananikov

Artificial Intelligence Chemistry, Год журнала: 2024, Номер 2(2), С. 100075 - 100075

Опубликована: Июль 27, 2024

The beginning and ripening of digital chemistry is analyzed focusing on the role artificial intelligence (AI) in an expected leap chemical sciences to bring this area next evolutionary level. analytic description selects highlights top 20 AI-based technologies 7 broader themes that are reshaping field. It underscores integration tools such as machine learning, big data, twins, Internet Things (IoT), robotic platforms, smart control processes, virtual reality blockchain, among many others, enhancing research methods, educational approaches, industrial practices chemistry. significance study lies its focused overview how these innovations foster a more efficient, sustainable, innovative future sciences. This article not only illustrates transformative impact but also draws new pathways chemistry, offering broad appeal researchers, educators, industry professionals embrace advancements for addressing contemporary challenges

Язык: Английский

Процитировано

9

Subpocket Similarity-Based Hit Identification for Challenging Targets: Application to the WDR Domain of LRRK2 DOI
Merveille Eguida, Guillaume Bret,

François Sindt

и другие.

Journal of Chemical Information and Modeling, Год журнала: 2024, Номер 64(13), С. 5344 - 5355

Опубликована: Июнь 25, 2024

ou non, émanant des établissements d'enseignement et de recherche français étrangers, laboratoires publics privés.

Процитировано

5

Allo-targeting of the kinase domain: Insights from in silico studies and comparison with experiments DOI
Ji Young Lee, Emma Gebauer, Markus A. Seeliger

и другие.

Current Opinion in Structural Biology, Год журнала: 2024, Номер 84, С. 102770 - 102770

Опубликована: Янв. 11, 2024

Язык: Английский

Процитировано

3

GENEOnet: statistical analysis supporting explainability and trustworthiness DOI
Giovanni Bocchi, Patrizio Frosini, Alessandra Micheletti

и другие.

Statistics, Год журнала: 2025, Номер unknown, С. 1 - 26

Опубликована: Март 17, 2025

Язык: Английский

Процитировано

0

Artificial intelligence in drug development for delirium and Alzheimer’s disease DOI Creative Commons
Ruixue Ai, Xianglu Xiao,

Shuling Deng

и другие.

Acta Pharmaceutica Sinica B, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Python tools for structural tasks in chemistry DOI
Fedor V. Ryzhkov, Yuliya E. Ryzhkova, Michaïl N. Elinson

и другие.

Molecular Diversity, Год журнала: 2024, Номер unknown

Опубликована: Май 14, 2024

Язык: Английский

Процитировано

2

AutoTarget: Disease-Associated druggable target identification via node representation learning in PPI networks DOI Creative Commons
Hyunseung Kong, Inyoung Kim,

Byoung-Tak Zhang

и другие.

Current Research in Biotechnology, Год журнала: 2024, Номер 8, С. 100260 - 100260

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0