A Unified Peptide Generative Framework via a Weakly Order-Dependent Autoregressive Language Model and Lifelong Learning.

Bioactive peptides have become strong candidates for a variety of clinical therapies due to their diverse advantages, which promote the development of deep generative models for peptide generation. Considering that existing methods cannot effectively deal with the conformational flexibility of peptides and find it difficult to capture accurate residue-to-residue interaction dependencies, we propose a unified peptide generative framework, PepGenWL, via a weakly order-dependent autoregressive language model and lifelong learning. PepGenWL introduces tolerance for out-of-order input as an inductive bias into the autoregressive language model, coupled with Mixture-of-Experts-style plugins to maintain the optimal trade-off between memory stability and learning plasticity across multiple rounds of fine-tuning.

Electro-oxidative amination of benzylic C(sp³)-C(sp³) bonds in aromatic hydrocarbons.

C(sp)-C(sp) amination represents a promising approach for synthesizing various amines, facilitating applications from late-stage scaffold hopping to the degradation of polymers and biomass. However, it remains challenging due to the inertness of the C-C bond and difficulties in controlling regio- and chemo-selectivity. Herein, we report an electro-oxidative benzylic C(sp)-C(sp) amination reaction of aromatic hydrocarbons using nitriles, amides, and sulfonamides as nucleophiles.

Divergent Upcycling of Polystyrene into Phenol and Hydroquinone Derivatives by Photocatalysis and Electrocatalysis.

The selective upcycling of polystyrene (PS) waste into value-added aromatics has emerged as a compelling strategy toward sustainable plastic valorization, drawing significant scientific and industrial interest. While most existing methods involved oxidative C─C bond cleavage predominantly yield benzoic acid, the direct conversion of waste PS into phenolic compounds remains largely unexplored. Herein, we report the first example of photocatalytic upcycling of PS into phenol derivatives with high chemoselectivity.

Supervised Screening of EGFR Inhibitors Validated through Computational Structural Biology Approaches.

One of the prominent challenges in breast cancer (BC) treatment is human epidermal growth factor receptor (EGFR) overexpression, which facilitates tumor proliferation and presents a viable target for anticancer therapies. This study integrates multiomics data to pinpoint promising therapeutic compounds and employs a machine learning (ML)-based similarity search to identify effective alternatives. We used BC cell line data from the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) databases and single-cell RNA sequencing (scRNA-seq) information that established afatinib as an efficacious candidate demonstrating superior IC values.

Intelligent identification of foodborne pathogenic bacteria by self-transfer deep learning and ensemble prediction based on single-cell Raman spectrum.

Foodborne pathogenic infections pose a significant threat to human health. Accurate detection of foodborne diseases is essential in preventing disease transmission. This study proposed an AI model for precisely identifying foodborne pathogenic bacteria based on single-cell Raman spectrum.

Screening and design of PARP12 inhibitors from traditional Chinese medicine small molecules using computational modeling and simulation.

The poly (ADP-ribose) polymerase (PARP) family of enzymes plays a pivotal role in orchestrating a multitude of cellular processes, including DNA repair mechanisms, transcriptional regulation, and modulation of immune responses. Within this family, PARP12 emerges as a noteworthy candidate for targeted cancer therapeutics. Consequently, this investigation endeavors to screen and design potential PARP12 inhibitors derived from traditional Chinese medicinal compounds by employing sophisticated molecular modeling and computational medicinal chemistry approaches.

Paired electrocatalysis enabled oxidative coupling of styrenes with alkyl radicals.

A paired electrocatalysis strategy for intermolecular oxidative cross-dehydrocoupling between styrenes and ethers or -methylphenol derivatives using ketone as a mild oxidant is described. This approach enables the generation of Csp carbon-centered radicals through anodic oxidation, followed by reductive coupling of ketones at the cathode, ultimately yielding valuable oxidative alkylation products.

AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network.

The structural stability of proteins is an important topic in various fields such as biotechnology, pharmaceuticals, and enzymology. Specifically, understanding the structural stability of protein is crucial for protein design. Artificial design, while pursuing high thermodynamic stability and rigidity of proteins, inevitably sacrifices biological functions closely related to protein flexibility.

Unveiling the Therapeutic Potential of Paclitaxel Combinations Against Breast Carcinoma and Identification of In Vivo Biomarkers.

Breast cancer (BC) is one of the leading causes of high mortality rates in women worldwide. Although advancements have been made in the design of therapeutic strategies and drug discovery, drug resistance remains one of the key challenges. One of the ways to overcome drug resistance is finding potential drug combinations since the efficacy of combined drugs is higher than their individual efficacies if the combination is a synergistic pair.

Molecular dynamic simulation reveals spider antimicrobial peptide Latarcin-1 and human eosinophil cationic protein as peptide inhibitors of SARS-CoV-2 variants.

COVID-19 has rapidly proliferated around 180 countries, and new cases are reported frequently. No peptide medication has been developed that can reliably block SARS-CoV-2 infection. The investigation focuses on the crucial host receptors angiotensin-converting enzyme 2 (ACE2) , which can bind receptor-binding domain (RBD) on the SARS-CoV-2 spike protein (S).

16S rRNA gene sequencing and machine learning reveal correlation between drug abuse and human host gut microbiota.

Over the past few years, there has been increasing evidence highlighting the strong connection between gut microbiota and overall well-being of the host. This has led to a renewed emphasis on studying and addressing substance use disorder from the perspective of brain-gut axis. Previous studies have suggested that alcohol, food, and cigarette addictions are strongly linked to gut microbiota and faecal microbiota transplantation or the use of probiotics achieved significant efficacy.

Comparative binding analysis of WGX50 and Alpha-M with APP family proteins APLP1 and APLP2 using structural-dynamics and free energy calculation approaches.

A.D. is a common disease among other neurodegenerative disorders primarily developing due to amyloid-β (Aβ) neurotoxicity derived from the amyloid-β protein precursor (AβPP).

[Preparation of luciferase-expressing mRNA and expression characteristics of mRNA delivered by electroporation ].

In this study, we aimed to construct a non-replication mRNA platform and explore the side effects of electroporation-mediated delivery of mRNA on the mice as well as the expression features of the mRNA. With luciferase gene as a marker, transcription with T7 RNA polymerase was carried out for the synthesis of luciferase-expressed mRNA, followed by enzymatic capping and tailing. The mRNA was delivered by electroporation via an gene delivery system, and the expression intensity and duration of luciferase in mice were observed via an imaging system.

Investigating the stabilisation of IFN-α2a by replica exchange molecular dynamics simulation.

Current biopharmaceutical drugs are mainly a class of peptides or proteins that play an essential role in the treatment of many diseases. Such peptides/proteins are usually thermally unstable and may lose their bioactivity when exposed to ambient conditions. Therefore, they are not suitable for long-term storage.

Insight into substrate-assisted catalytic mechanism and stereoselectivity of bifunctional nocardicin thioesterase.

The inversion from L- to D-stereochemistry endows peptides improved bioactivity and enhanced resistance to many proteases and peptidases. To strengthen the biostability and bioavailability of peptide drugs, enzymatic epimerization becomes an important way to incorporate D-amino acid into peptide backbones. Recently, a bifunctional thioesterase NocTE, which is responsible for the epimerization and hydrolysis of the C-terminal (p-hydroxyphenyl)glycine residue of β-lactam antibiotic nocardicin A, exclusively directs to the generation of D-diastereomers.

Improved thermostability of proteinase K and recognizing the synergistic effect of Rosetta and FoldX approaches.

Proteinase K (PRK) is a proteolytic enzyme that has been widely used in industrial applications. However, poor stability has severely limited the uses of PRK. In this work, we used two structure-guided rational design methods, Rosetta and FoldX, to modify PRK thermostability.

Deep learning analysis and age prediction from shoeprints.

Human gaits are the patterns of limb movements which involve both the upper and lower body parts. These patterns in terms of step rate, gait speed, stance widening, stride, and bipedal forces are influenced by different factors including environmental (such as social, cultural, and behavioral traits) and physical changes (such as age and health status). These factors are reflected on the imprinted shoeprints generated with body forces, which in turn can be used to predict age, a problem not systematically addressed using any computational approach.

Discovery of a Natural Product with Potent Efficacy Against SARS-CoV-2 by Drug Screening.

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide for almost 2 years. It starts from viral adherence to host cells through an interaction between spike glycoprotein 1 (S1) containing a receptor-binding domain (RBD) and human angiotensin-converting enzyme-2 (ACE2). One of the useful strategies to prevent SARS-CoV-2 infection is to inhibit the attachment of RBD to ACE2.

HD5 and LL-37 Inhibit SARS-CoV and SARS-CoV-2 Binding to Human ACE2 by Molecular Simulation.

The coronavirus (COVID-19) pandemic is still spreading all over the world. As reported, angiotensin-converting enzyme-2 (ACE2) is a receptor of SARS-CoV-2 spike protein that initializes viral entry into host cells. Previously, the human defensin 5 (HD5) has been experimentally confirmed to be functional against the SARS-CoV-2.

Human Cathelicidin Inhibits SARS-CoV-2 Infection: Killing Two Birds with One Stone.

SARS-CoV-2 infection begins with the association of its spike 1 (S1) protein with host angiotensin-converting enzyme-2 (ACE2). Targeting the interaction between S1 and ACE2 is a practical strategy against SARS-CoV-2 infection. Herein, we show encouraging results indicating that human cathelicidin LL37 can simultaneously block viral S1 and cloak ACE2.

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level.

Rapid detection of food-borne pathogens in early food contamination is a permanent topic to ensure food safety and prevent public health problems. Raman spectroscopy, a label-free, highly sensitive and dependable technology has attracted more and more attention in the field of diagnosing food-borne pathogens in recent years. In the research, 15,890 single-cell Raman spectra of 23 common strains from 7 genera were obtained at the single cell level.

Complete sequences of two new KPC-harbouring plasmids in Klebsiella pneumoniae ST11 strains in China.

Objectives: Klebsiella pneumoniae carbapenemase (KPC) has spread across the world. The present study focused on exploring the sequences of two new KPC-harbouring plasmids in K. pneumoniae.