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In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes
In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes
Diabetes represents a significant global health challenge associated with substantial healthcare costs and therapeutic com...
ConoDL: a deep learning framework for rapid generation and prediction of conotoxins
ConoDL: a deep learning framework for rapid generation and prediction of conotoxins
Conotoxins, being small disulfide-rich and bioactive peptides, manifest notable pharmacological potential and find extensi...
MolGraph: a Python package for the implementation of molecular graphs and graph neural networks with TensorFlow and Keras
MolGraph: a Python package for the implementation of molecular graphs and graph neural networks with TensorFlow and Keras
Molecular machine learning (ML) has proven important for tackling various molecular problems, such as predicting molecular...
Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays
Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays
Although small molecule superposition is a standard technique in drug discovery, a rigorous performance assessment of the ...
Promoter recognition specificity of Corynebacterium glutamicum stress response sigma factors σD and σH deciphered using computer modeling and point mutagenesis
Promoter recognition specificity of Corynebacterium glutamicum stress response sigma factors σD and σH deciphered using computer modeling and point mutagenesis
This study aimed to reveal interactions of the stress response sigma subunits (factors) σD and σH of RNA polymer...
Understanding the relationship between preferential interactions of peptides in water-acetonitrile mixtures with protein-solvent contact surface area
Understanding the relationship between preferential interactions of peptides in water-acetonitrile mixtures with protein-solvent contact surface area
The influence of polar, water-miscible organic solvents (POS) on protein structure, stability, and functional activity is ...
Identification of novel inhibitors targeting PI3Kα via ensemble-based virtual screening method, biological evaluation and molecular dynamics simulation
Identification of novel inhibitors targeting PI3Kα via ensemble-based virtual screening method, biological evaluation and molecular dynamics simulation
PIK3CA gene encoding PI3K p110α is one of the most frequently mutated and overexpressed in majority of human cancers....
Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model
Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model
Therapeutic monoclonal antibodies are an effective method of treating acute infectious diseases. However, knowing which of...
Comparative assessment of physics-based in silico methods to calculate relative solubilities
Comparative assessment of physics-based in silico methods to calculate relative solubilities
Relative solubilities, i.e. whether a given molecule is more soluble in one solvent compared to others, is a critical para...
Computational Identification and Illustrative Standard for Representation of Unimolecular G-Quadruplex Secondary Structures (CIIS-GQ)
Computational Identification and Illustrative Standard for Representation of Unimolecular G-Quadruplex Secondary Structures (CIIS-GQ)
G-quadruplexes refer to a large group of nucleic acid–based structures. In recent years, they have been attracting a...
Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands
Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands
So-called “cross-docking” is the prediction of the bound configuration of small-molecule ligands that differ f...
De novo drug design through gradient-based regularized search in information-theoretically controlled latent space
De novo drug design through gradient-based regularized search in information-theoretically controlled latent space
Over the last decade, automatic chemical design frameworks for discovering molecules with drug-like properties have signif...
Computational design and experimental confirmation of a disulfide-stapled YAP helixα1-trap derived from TEAD4 helical hairpin to selectively capture YAP α1-helix with potent antitumor activity
Computational design and experimental confirmation of a disulfide-stapled YAP helixα1-trap derived from TEAD4 helical hairpin to selectively capture YAP α1-helix with potent antitumor activity
Human Hippo signaling pathway is an evolutionarily conserved regulator network that controls organ development and has bee...
Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors
Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors
The development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thom...
FitScore: a fast machine learning-based score for 3D virtual screening enrichment
FitScore: a fast machine learning-based score for 3D virtual screening enrichment
Enhancing virtual screening enrichment has become an urgent problem in computational chemistry, driven by increasingly lar...
Development of human lactate dehydrogenase a inhibitors: high-throughput screening, molecular dynamics simulation and enzyme activity assay
Development of human lactate dehydrogenase a inhibitors: high-throughput screening, molecular dynamics simulation and enzyme activity assay
Lactate dehydrogenase A (LDHA) is highly expressed in many tumor cells and promotes the conversion of pyruvate to lactic a...
Development of QSARs for cysteine-containing di- and tripeptides with antioxidant activity:influence of the cysteine position
Development of QSARs for cysteine-containing di- and tripeptides with antioxidant activity:influence of the cysteine position
Antioxidants agents play an essential role in the food industry for improving the oxidative stability of food products. In...
From mundane to surprising nonadditivity: drivers and impact on ML models
From mundane to surprising nonadditivity: drivers and impact on ML models
Nonadditivity (NA) in Structure-Activity and Structure-Property Relationship (SAR) data is a rare but very information ric...
MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics
MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics
Molecular dynamics (MD) simulation is a powerful tool for characterizing ligand–protein conformational dynamics and ...
Structural impacts of two disease-linked ADAR1 mutants: a molecular dynamics study
Structural impacts of two disease-linked ADAR1 mutants: a molecular dynamics study
Adenosine deaminases acting on RNA (ADARs) are pivotal RNA-editing enzymes responsible for converting adenosine to inosine...
User-centric design of a 3D search interface for protein-ligand complexes
User-centric design of a 3D search interface for protein-ligand complexes
In this work, we present the frontend of GeoMine and showcase its application, focusing on the new features of its latest ...
Correlation of protein binding pocket properties with hits’ chemistries used in generation of ultra-large virtual libraries
Correlation of protein binding pocket properties with hits’ chemistries used in generation of ultra-large virtual libraries
Although the size of virtual libraries of synthesizable compounds is growing rapidly, we are still enumerating only tiny f...
Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design
Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design
Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully...
De novo drug design as GPT language modeling: large chemistry models with supervised and reinforcement learning
De novo drug design as GPT language modeling: large chemistry models with supervised and reinforcement learning
In recent years, generative machine learning algorithms have been successful in designing innovative drug-like molecules. ...
From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product
From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product
Scaffold replacement as part of an optimization process that requires maintenance of potency, desirable biodistribution, m...
On the relevance of query definition in the performance of 3D ligand-based virtual screening
On the relevance of query definition in the performance of 3D ligand-based virtual screening
Ligand-based virtual screening (LBVS) methods are widely used to explore the vast chemical space in the search of novel co...
Computational peptide discovery with a genetic programming approach
Computational peptide discovery with a genetic programming approach
The development of peptides for therapeutic targets or biomarkers for disease diagnosis is a challenging task in protein e...
Identifying and characterising promising small molecule inhibitors of kinesin spindle protein using ligand-based virtual screening, molecular docking, molecular dynamics and MM‑GBSA calculations
Identifying and characterising promising small molecule inhibitors of kinesin spindle protein using ligand-based virtual screening, molecular docking, molecular dynamics and MM‑GBSA calculations
The kinesin spindle protein (Eg5) is a mitotic protein that plays an essential role in the formation of the bipolar spindl...
Benchmarking ANI potentials as a rescoring function and screening FDA drugs for SARS-CoV-2 Mpro
Benchmarking ANI potentials as a rescoring function and screening FDA drugs for SARS-CoV-2 Mpro
Here, we introduce the use of ANI-ML potentials as a rescoring function in the host–guest interaction in molecular d...
The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations
The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations
Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico designed molecules ad...
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