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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...
SpaceGrow: efficient shape-based virtual screening of billion-sized combinatorial fragment spaces
SpaceGrow: efficient shape-based virtual screening of billion-sized combinatorial fragment spaces
The growing size of make-on-demand chemical libraries is posing new challenges to cheminformatics. These ultra-large chemi...
Correction: Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design
Correction: Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, whic...
Molecular dynamics simulations as a guide for modulating small molecule aggregation
Molecular dynamics simulations as a guide for modulating small molecule aggregation
Small colloidally aggregating molecules (SCAMs) can be problematic for biological assays in drug discovery campaigns. Howe...
Molecule auto-correction to facilitate molecular design
Molecule auto-correction to facilitate molecular design
Ensuring that computationally designed molecules are chemically reasonable is at best cumbersome. We present a molecule co...
Rethinking the applicability domain analysis in QSAR models
Rethinking the applicability domain analysis in QSAR models
Notwithstanding the wide adoption of the OECD principles (or best practices) for QSAR modeling, disparities between in sil...
Deciphering the molecular choreography of Janus kinase 2 inhibition via Gaussian accelerated molecular dynamics simulations: a dynamic odyssey
Deciphering the molecular choreography of Janus kinase 2 inhibition via Gaussian accelerated molecular dynamics simulations: a dynamic odyssey
The Janus kinases (JAK) are crucial targets in drug development for several diseases. However, accounting for the impact o...
A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat
A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat
An important aspect in the development of small molecules as drugs or agrochemicals is their systemic availability after i...
Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface
Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface
SARS-CoV-2, the virus that causes COVID-19, led to a global health emergency that claimed the lives of millions. Despite t...
Molecular dynamics study on micelle-small molecule interactions: developing a strategy for an extensive comparison
Molecular dynamics study on micelle-small molecule interactions: developing a strategy for an extensive comparison
Theoretical predictions of the solubilizing capacity of micelles and vesicles present in intestinal fluid are important fo...
QM assisted ML for 19F NMR chemical shift prediction
QM assisted ML for 19F NMR chemical shift prediction
Ligand-observed 19F NMR detection is an efficient method for screening libraries of fluorinated molecules in fragment-base...
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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