Digital Discovery
Overview
Digital Discovery is a scientific journal, published by Royal Society of Chemistry since 2022 in English. The journal's country of origin is United Kingdom.
Details
Details
Abbr.
Digit Discov
Publisher
Royal Society of Chemistry
Start
2022
End
Continuing
e-ISSN
2635-098X
Country
United Kingdom
Language
English
Metrics
Metrics
h-index / Ranks: 13991
12
SJR / Ranks: 2701
1238
Recent Articles
1.
Pinheiro Jr M, de Oliveira Bispo M, Mattos R, Telles do Casal M, Chandra Garain B, Toldo J, et al.
Digit Discov
. 2025 Jan;
4(3):666-682.
PMID: 39885946
The analysis of nonadiabatic molecular dynamics (NAMD) data presents significant challenges due to its high dimensionality and complexity. To address these issues, we introduce ULaMDyn, a Python-based, open-source package designed...
2.
Alshehri A, Bergman M, You F, Hall C
Digit Discov
. 2025 Jan;
4(2):561-571.
PMID: 39882101
Plastic pollution, particularly microplastics (MPs), poses a significant global threat to ecosystems and human health, necessitating innovative remediation strategies. Biocompatible and biodegradable plastic-binding peptides (PBPs) offer a potential solution through...
3.
Ulanov E, Qadir G, Riedmiller K, Friederich P, Grater F
Digit Discov
. 2025 Jan;
4(2):513-522.
PMID: 39850148
Predicting reaction barriers for arbitrary configurations based on only a limited set of density functional theory (DFT) calculations would render the design of catalysts or the simulation of reactions within...
4.
Ai Q, Meng F, Wang R, Klein J, Godfrey A, Coley C
Digit Discov
. 2025 Jan;
4(2):486-499.
PMID: 39829711
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on...
5.
Cree B, Bieniek M, Amin S, Kawamura A, Cole D
Digit Discov
. 2025 Jan;
4(2):438-450.
PMID: 39816163
FEgrow is an open-source software package for building congeneric series of compounds in protein binding pockets. For a given ligand core and receptor structure, it employs hybrid machine learning/molecular mechanics...
6.
Ozcelik R, Grisoni F
Digit Discov
. 2024 Dec;
4(2):316-325.
PMID: 39726698
Deep learning has significantly accelerated drug discovery, with 'chemical language' processing (CLP) emerging as a prominent approach. CLP approaches learn from molecular string representations (, Simplified Molecular Input Line Entry...
7.
Haas B, Hardy M, Sowndarya S V S, Adams K, Coley C, Paton R, et al.
Digit Discov
. 2024 Dec;
4(1):222-233.
PMID: 39664609
Data-driven reaction discovery and development is a growing field that relies on the use of molecular descriptors to capture key information about substrates, ligands, and targets. Broad adaptation of this...
8.
Lee J, Mulay P, Tamasi M, Yeow J, Stevens M, Gormley A
Digit Discov
. 2024 Dec;
2:219-233.
PMID: 39650094
Oxygen tolerant polymerizations including Photoinduced Electron/Energy Transfer-Reversible Addition-Fragmentation Chain-Transfer (PET-RAFT) polymerization allow for high-throughput synthesis of diverse polymer architectures on the benchtop in parallel. Recent developments have further increased throughput...
9.
Clark J, Mi X, Mitchell D, Shukla D
Digit Discov
. 2024 Dec;
4(2):343-354.
PMID: 39649639
Ribosomally synthesized and post-translationally modified peptide (RiPP) biosynthetic enzymes often exhibit promiscuous substrate preferences that cannot be reduced to simple rules. Large language models are promising tools for predicting the...
10.
PolyCL: contrastive learning for polymer representation learning explicit and implicit augmentations
Zhou J, Yang Y, Mroz A, Jelfs K
Digit Discov
. 2024 Dec;
4(1):149-160.
PMID: 39649638
Polymers play a crucial role in a wide array of applications due to their diverse and tunable properties. Establishing the relationship between polymer representations and their properties is crucial to...