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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...
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...
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 ...
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...
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...
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...
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...
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...
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...