Artificial intelligence for science in quantum, atomistic, and continuum systems

X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y **e… - arxiv preprint arxiv …, 2023 - arxiv.org
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery

D Trisciuzzi, BO Villoutreix, L Siragusa… - Expert Opinion on …, 2023 - Taylor & Francis
ABSTRACT Introduction Protein-protein interactions (PPIs) have been often considered
undruggable targets although they are attractive for the discovery of new therapeutics. The …

Modelling peptide–protein complexes: docking, simulations and machine learning

A Mondal, L Chang, A Perez - QRB discovery, 2022 - cambridge.org
Peptides mediate up to 40% of protein interactions, their high specificity and ability to bind in
places where small molecules cannot make them potential drug candidates. However …

A manager's guide to using eDNA metabarcoding in marine ecosystems

Z Gold, AR Wall, TM Schweizer, ND Pentcheff, EE Curd… - PeerJ, 2022 - peerj.com
Environmental DNA (eDNA) metabarcoding is a powerful tool that can enhance marine
ecosystem/biodiversity monitoring programs. Here we outline five important steps managers …

Target-Specific De Novo Peptide Binder Design with DiffPepBuilder

F Wang, Y Wang, L Feng, C Zhang… - Journal of Chemical …, 2024 - ACS Publications
Despite the exciting progress in target-specific de novo protein binder design, peptide
binder design remains challenging due to the flexibility of peptide structures and the scarcity …

Full-atom peptide design with geometric latent diffusion

X Kong, Y Jia, W Huang, Y Liu - arxiv preprint arxiv:2402.13555, 2024 - arxiv.org
Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to
leverage target binding sites that are previously undruggable. Most existing methods are …

Propedia v2. 3: A novel representation approach for the peptide-protein interaction database using graph-based structural signatures

P Martins, D Mariano, FC Carvalho, LL Bastos… - Frontiers in …, 2023 - frontiersin.org
Propedia is a web database of peptide-protein interactions, which introduced a clustering
approach based on three methods:(i) sequences,(ii) structure interface, and (iii) binding …

An approach for engineering peptides for competitive inhibition of the sars-cov-2 spike protein

AP de Abreu, FC Carvalho, D Mariano, LL Bastos… - Molecules, 2024 - mdpi.com
SARS-CoV-2 is the virus responsible for a respiratory disease called COVID-19 that
devastated global public health. Since 2020, there has been an intense effort by the …

Growing ecosystem of deep learning methods for modeling protein–protein interactions

JR Rogers, G Nikolényi… - … Engineering, Design and …, 2023 - academic.oup.com
Numerous cellular functions rely on protein–protein interactions. Efforts to comprehensively
characterize them remain challenged however by the diversity of molecular recognition …

Design of peptide-based protein degraders via contrastive deep learning

K Palepu, M Ponnapati, S Bhat, E Tysinger, T Stan… - bioRxiv, 2022 - biorxiv.org
Therapeutic modalities targeting pathogenic proteins are the gold standard of treatment for
multiple disease indications. Unfortunately, a significant portion of these proteins are …