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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...
Elucidating allosteric signal disruption in PBP2a: impact of N146K/E150K mutations on ceftaroline resistance in methicillin-resistant
Elucidating allosteric signal disruption in PBP2a: impact of N146K/E150K mutations on ceftaroline resistance in methicillin-resistant
Ceftaroline (CFT) effectively combats methicillin-resistant Staphylococcus aureus (MRSA) by binding to the allosteric site...
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 ...
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...
Convolidine as potent BACE1 inhibitor for Alzheimer’s disease; in-silico coupled with in-vitro assessment
Convolidine as potent BACE1 inhibitor for Alzheimer’s disease; in-silico coupled with in-vitro assessment
Alzheimer’s Disease is a chronic progressive neurodegenerative disorder characterized by impaired intellect and cogn...
Synthesis, TD-DFT calculations, molecular docking and ADME studies of new spiro-oxindole derivatives containing 5(4H)-oxazolone as anti-viral and anti-bacterial agents
Synthesis, TD-DFT calculations, molecular docking and ADME studies of new spiro-oxindole derivatives containing 5(4H)-oxazolone as anti-viral and anti-bacterial agents
Spiro pyrrolidine oxindole and oxazolone compounds have been widely used in medicinal chemistry. They can show anti-viral,...
Exploring the anti-diabetic potential of the using in vitro, in vivo and computational models
Exploring the anti-diabetic potential of the using in vitro, in vivo and computational models
Vigna sesquipedalis is traditionally used for the treatment of various disorders including diabetes but without scientific...
Deciphering the sequence-dependent unfolding pathways of an RNA pseudoknot with steered molecular dynamics
Deciphering the sequence-dependent unfolding pathways of an RNA pseudoknot with steered molecular dynamics
Programmed ribosomal frameshifting in Simian retrovirus-1 (SRV-1) is sensitive to the mechanical properties of an RNA pseu...
MiR-146/TNF-α/IL-6/osteocalcin crosstalk in anti-rheumatic potential of hemolymph from computational molecular modeling to in-vivo validation
MiR-146/TNF-α/IL-6/osteocalcin crosstalk in anti-rheumatic potential of hemolymph from computational molecular modeling to in-vivo validation
Rheumatoid arthritis (RA) is an inflammatory autoimmune illness that persistently and recurrently affects joints. In RA, m...
Rational molecular design of novel class-III peptidic antagonists to competitively disrupt human PPARδ self-binding peptide
Rational molecular design of novel class-III peptidic antagonists to competitively disrupt human PPARδ self-binding peptide
Human peroxisome proliferator-activated receptor-δ (PPARδ) belongs to the nuclear receptor PPAR family that play...
Structure-based discovery of novel non-covalent small molecule inhibitors of USP30
Structure-based discovery of novel non-covalent small molecule inhibitors of USP30
Ubiquitin-specific proteases (USPs) are crucial regulators of protein degradation pathways, influencing diverse cellular p...
OPTUNA optimization for predicting chemical respiratory toxicity using ML models
OPTUNA optimization for predicting chemical respiratory toxicity using ML models
Predicting molecular toxicity is an important stage in the process of drug discovery. It is directly related to medical de...
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...
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which...
Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals
Improving the accuracy of the FMO binding affinity prediction of ligand-receptor complexes containing metals
Polarization and charge transfer strongly characterize the ligand-receptor interaction when metal atoms are present, as fo...
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