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Computational design and experimental confirmation of a disulfide-stapled YAP helix-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 helix-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...
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...
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...
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...
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...
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...
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....
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 ...
Promoter recognition specificity of stress response sigma factors σ and σ deciphered using computer modeling and point mutagenesis
Promoter recognition specificity of stress response sigma factors σ and σ 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...
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 ...
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...
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...
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...
In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry
In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry
The COVID-19 pandemic, caused by SARS-CoV-2, has underscored the urgent need for effective antiviral therapies, particular...
Discovering promising drug candidates for Parkinson’s disease: integrating miRNA and DEG analysis with molecular dynamics and MMPBSA
Discovering promising drug candidates for Parkinson’s disease: integrating miRNA and DEG analysis with molecular dynamics and MMPBSA
Parkinson’s disease (PD) is a progressive neurological disorder with an increasing prevalence in aging populations. ...
Computational investigation to identify multi-targeted anti-hyperglycemic potential of substituted 2-Mercaptobenzimidazole derivatives and synthesis of new α-glucosidase inhibitors
Computational investigation to identify multi-targeted anti-hyperglycemic potential of substituted 2-Mercaptobenzimidazole derivatives and synthesis of new α-glucosidase inhibitors
One of the most widespread diseases recognized all over the world is diabetes, accounting for 1.5 million deaths ...
Multi-targeted benzylpiperidine–isatin hybrids: Design, synthesis, biological and in silico evaluation as monoamine oxidases and acetylcholinesterase inhibitors for neurodegenerative disease therapies
Multi-targeted benzylpiperidine–isatin hybrids: Design, synthesis, biological and in silico evaluation as monoamine oxidases and acetylcholinesterase inhibitors for neurodegenerative disease therapies
Neurodegenerative diseases (NDDs) like Alzheimer’s and Parkinson’s, characterized by gradual loss of neuronal ...
Molecular docking, dynamics simulations, and in vivo studies of gallic acid in adenine-induced chronic kidney disease: targeting KIM-1 and NGAL
Molecular docking, dynamics simulations, and in vivo studies of gallic acid in adenine-induced chronic kidney disease: targeting KIM-1 and NGAL
Gallic acid (GA), a naturally occurring compound with antioxidant, anti-inflammatory, anti-apoptotic, and regenerative pro...
From closed to open: three dynamic states of membrane-bound cytochrome P450 3A4
From closed to open: three dynamic states of membrane-bound cytochrome P450 3A4
Cytochrome P450 3A4 (CYP3A4) is a membrane bound monooxygenase. It metabolizes the largest proportion of all orally ingest...
Open-ComBind: harnessing unlabeled data for improved binding pose prediction
Open-ComBind: harnessing unlabeled data for improved binding pose prediction
Determination of the bound pose of a ligand is a critical first step in many in silico drug discovery tasks. Molecular doc...
Correction: Exploring DrugCentral: from molecular structures to clinical effects
Correction: Exploring DrugCentral: from molecular structures to clinical effects
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, whi...
Binding of small molecule inhibitors to RNA polymerase-Spt5 complex impacts RNA and DNA stability
Binding of small molecule inhibitors to RNA polymerase-Spt5 complex impacts RNA and DNA stability
Spt5 is an elongation factor that associates with RNA polymerase II (Pol II) during transcription and has important functi...
Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information
Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information
In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attent...
Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study
Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study
Correction to: Journal of Computer-Aided Molecular Design In the original publication of the articl...
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state
In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to...
Mur ligase F as a new target for the flavonoids quercitrin, myricetin, and (–)-epicatechin
Mur ligase F as a new target for the flavonoids quercitrin, myricetin, and (–)-epicatechin
MurC, D, E, and F are ATP-dependent ligases involved in the stepwise assembly of the tetrapeptide stem of forming peptidog...
The in silico identification of novel broad-spectrum antidotes for poisoning by organophosphate anticholinesterases
The in silico identification of novel broad-spectrum antidotes for poisoning by organophosphate anticholinesterases
Owing to their potential to cause serious adverse health effects, significant efforts have been made to develop antidotes ...
MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling
MASSA Algorithm: an automated rational sampling of training and test subsets for QSAR modeling
QSAR models capable of predicting biological, toxicity, and pharmacokinetic properties were widely used to search lead bio...
TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection
TeM-DTBA: time-efficient drug target binding affinity prediction using multiple modalities with Lasso feature selection
Drug discovery, especially virtual screening and drug repositioning, can be accelerated through deeper understanding and p...
Cooperative and structural relationships of the trimeric Spike with infectivity and antibody escape of the strains Delta (B.1.617.2) and Omicron (BA.2, BA.5, and BQ.1)
Cooperative and structural relationships of the trimeric Spike with infectivity and antibody escape of the strains Delta (B.1.617.2) and Omicron (BA.2, BA.5, and BQ.1)
Herein, we conducted simulations of trimeric Spike from several SARS-CoV-2 variants of concern (Delta and Omicron sub-vari...
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