Jianfeng Pei
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View article: MGTbind: a comprehensive database of molecular glue ternary interactome
MGTbind: a comprehensive database of molecular glue ternary interactome Open
Molecular glues (MGs) are an emerging class of small molecules capable of inducing or enhancing protein–protein interactions, leading to reprograming of cellular events. In recent years, MG discovery has gained significant attention in dru…
View article: Unveiling optimal molecular features for hERG insights with automatic machine learning
Unveiling optimal molecular features for hERG insights with automatic machine learning Open
View article: Effects of replacing soybean meal with an equivalent amount of fermented feed on the production performance and egg and meat quality of laying hens during the late laying period
Effects of replacing soybean meal with an equivalent amount of fermented feed on the production performance and egg and meat quality of laying hens during the late laying period Open
This study aimed to investigate the effects of replacing soybean meal with an equivalent amount of fermented feed on the production performance of laying hens. A total of 480 healthy, 70-week-old Hy-Line Sonia laying hens were divided into…
View article: Comparative assessment of co-folding methods for molecular glue ternary structure prediction
Comparative assessment of co-folding methods for molecular glue ternary structure prediction Open
Molecular glues (MGs) represent an emerging therapeutic paradigm capable of inducing or stabilizing protein-protein interactions, with broad applications in creating neomorphic interactomes and targeted protein degradation. However, curren…
View article: Author Correction: Accelerating discovery of bioactive ligands with pharmacophore-informed generative models
Author Correction: Accelerating discovery of bioactive ligands with pharmacophore-informed generative models Open
View article: Artificial intelligence guided Raman spectroscopy in biomedicine: Applications and prospects
Artificial intelligence guided Raman spectroscopy in biomedicine: Applications and prospects Open
View article: Accelerating discovery of bioactive ligands with pharmacophore-informed generative models
Accelerating discovery of bioactive ligands with pharmacophore-informed generative models Open
View article: RefineScore: Improving Ligand Docking Accuracy and Interpretability by Predicting MDN Corrective Physical Interactions
RefineScore: Improving Ligand Docking Accuracy and Interpretability by Predicting MDN Corrective Physical Interactions Open
Precisely evaluating the protein-ligand interaction is crucial in drug screening and optimization. There are significant advances in the application of machine learning approaches to developing protein-ligand scoring functions in recent ye…
View article: RefineScore: Improving Ligand Docking Accuracy and Interpretability by Predicting MDN Corrective Physical Interactions
RefineScore: Improving Ligand Docking Accuracy and Interpretability by Predicting MDN Corrective Physical Interactions Open
Precisely evaluating the protein-ligand interaction is crucial in drug screening and optimization. There are significant advances in the application of machine learning approaches to developing protein-ligand scoring functions in recent ye…
View article: DeepRLI: a multi-objective framework for universal protein–ligand interaction prediction
DeepRLI: a multi-objective framework for universal protein–ligand interaction prediction Open
DeepRLI is a multi-objective deep learning framework for universal protein–ligand interaction prediction, applicable to binding affinity prediction, molecular docking, and virtual screening tasks, offering better guidance for drug discover…
View article: Structure-Based Screening and Optimization of PafA Inhibitors with Potent Anti-Tuberculosis Activity
Structure-Based Screening and Optimization of PafA Inhibitors with Potent Anti-Tuberculosis Activity Open
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global health challenge, primarily due to the increasing prevalence of drug resistance. Consequently, the development of drugs with novel modes of action (MOAs)…
View article: Reacon: a template- and cluster-based framework for reaction condition prediction
Reacon: a template- and cluster-based framework for reaction condition prediction Open
Reacon is a valuable tool for reaction condition prediction.
View article: Incidence trends and specific risk factors of ischemic heart disease and stroke: An ecological analysis based on the Global Burden of Disease 2019
Incidence trends and specific risk factors of ischemic heart disease and stroke: An ecological analysis based on the Global Burden of Disease 2019 Open
Distribution of risk factors for cardiovascular diseases has been changing globally, which may account for the discrepant temporal trends of ischemic heart disease (IHD) and stroke. To test the hypothesis and identify potential contributin…
View article: DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking Open
Molecular docking, a technique for predicting ligand binding poses, is crucial in structure-based drug design for understanding protein-ligand interactions. Recent advancements in docking methods, particularly those leveraging geometric de…
View article: Unveiling Optimal Molecular Features for hERG Insights with Automatic Machine Learning
Unveiling Optimal Molecular Features for hERG Insights with Automatic Machine Learning Open
We have developed MaxQsaring, a novel universal framework integrating molecular descriptors, fingerprints, and deep-learning pretrained representations, to predict the properties of compounds. Applied to a case study of hERG (human Ether-à…
View article: COASY variant as a new genetic cause of riboflavin-responsive lipid storage myopathy
COASY variant as a new genetic cause of riboflavin-responsive lipid storage myopathy Open
View article: DeepRLI: A Multi-objective Framework for Universal Protein--Ligand Interaction Prediction
DeepRLI: A Multi-objective Framework for Universal Protein--Ligand Interaction Prediction Open
Protein (receptor)--ligand interaction prediction is a critical component in computer-aided drug design, significantly influencing molecular docking and virtual screening processes. Despite the development of numerous scoring functions in …
View article: Accelerating Discovery of Novel and Bioactive Ligands With Pharmacophore-Informed Generative Models
Accelerating Discovery of Novel and Bioactive Ligands With Pharmacophore-Informed Generative Models Open
Deep generative models have gained significant advancements to accelerate drug discovery by generating bioactive chemicals against desired targets. Nevertheless, most generated compounds that have been validated for potent bioactivity ofte…
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Contents list Open
View article: DiffBindFR: an SE(3) equivariant network for flexible protein–ligand docking
DiffBindFR: an SE(3) equivariant network for flexible protein–ligand docking Open
DiffBindFR, a diffusion model based flexible full-atom protein–ligand docking tool, demonstrates its superior docking and side-chain refinement accuracy with reliable physical plausibility.
View article: In silico protein function prediction: the rise of machine learning-based approaches
In silico protein function prediction: the rise of machine learning-based approaches Open
Proteins function as integral actors in essential life processes, rendering the realm of protein research a fundamental domain that possesses the potential to propel advancements in pharmaceuticals and disease investigation. Within the con…
View article: DiffBindFR: An SE(3) Equivariant Network for Flexible Protein-Ligand Docking
DiffBindFR: An SE(3) Equivariant Network for Flexible Protein-Ligand Docking Open
Molecular docking, a key technique in structure-based drug design, plays pivotal roles in protein-ligand interaction modeling, hit identification and optimization, in which accurate prediction of protein-ligand binding mode is essential. C…
View article: Toward <i>In Silico</i> Design of Protein–Protein Interaction Stabilizers
Toward <i>In Silico</i> Design of Protein–Protein Interaction Stabilizers Open
ADVERTISEMENT RETURN TO ISSUEPREVFirst ReactionsNEXTToward In Silico Design of Protein–Protein Interaction StabilizersSystematic binding free energy analysis reveals a dual binding mechanism as a protein-protein interaction stabilizer desi…
View article: Specific pupylation as IDEntity reporter (SPIDER) for the identification of protein-biomolecule interactions
Specific pupylation as IDEntity reporter (SPIDER) for the identification of protein-biomolecule interactions Open
View article: Anxiety prevalence and its association with physical activity in patients with non-communicable diseases during COVID-19 lockdown: a cross-sectional study in Shanghai, China
Anxiety prevalence and its association with physical activity in patients with non-communicable diseases during COVID-19 lockdown: a cross-sectional study in Shanghai, China Open
View article: Synthesis-driven design of 3D molecules for structure-based drug discovery using geometric transformers
Synthesis-driven design of 3D molecules for structure-based drug discovery using geometric transformers Open
Finding drug-like compounds with high bioactivity is essential for drug discovery, but the task is complicated by the high cost of chemical synthesis and validation. With their outstanding performance in de novo drug design, deep generativ…
View article: <scp>QuoteTarget</scp>: A sequence‐based transformer protein language model to identify potentially druggable protein targets
<span>QuoteTarget</span>: A sequence‐based transformer protein language model to identify potentially druggable protein targets Open
The development of efficient computational methods for drug target protein identification can compensate for the high cost of experiments and is therefore of great significance for drug development. However, existing structure‐based drug t…
View article: miDruglikeness: Subdivisional Drug-Likeness Prediction Models Using Active Ensemble Learning Strategies
miDruglikeness: Subdivisional Drug-Likeness Prediction Models Using Active Ensemble Learning Strategies Open
The drug development pipeline involves several stages including in vitro assays, in vivo assays, and clinical trials. For candidate selection, it is important to consider that a compound will successfully pass through these stages. Using g…
View article: A NR2E1‐interacting peptide of LSD1 inhibits the proliferation of brain tumour initiating cells
A NR2E1‐interacting peptide of LSD1 inhibits the proliferation of brain tumour initiating cells Open
Objectives Elimination of brain tumour initiating cells (BTICs) is important for the good prognosis of malignant brain tumour treatment. To develop a novel strategy targeting BTICs, we studied NR2E1(TLX) involved self‐renewal mechanism of …
View article: A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins
A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins Open
How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyn…