Journal of Computer-Aided Molecular Design

Papers
(The TQCC of Journal of Computer-Aided Molecular Design is 7. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-06-01 to 2025-06-01.)
ArticleCitations
Energy-entropy prediction of octanol–water logP of SAMPL7 N-acyl sulfonamide bioisosters124
Computational investigation of functional water molecules in GPCRs bound to G protein or arrestin60
Computational peptide discovery with a genetic programming approach49
In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry38
GPCRLigNet: rapid screening for GPCR active ligands using machine learning38
Enhancing sampling of water rehydration upon ligand binding using variants of grand canonical Monte Carlo23
A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios22
Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host–guest binding: II. regression and dielectric constant21
QM assisted ML for 19F NMR chemical shift prediction21
Obtaining QM/MM binding free energies in the SAMPL8 drugs of abuse challenge: indirect approaches18
Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery17
PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams17
COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge17
FastGrow: on-the-fly growing and its application to DYRK1A16
pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants15
Design of new imidazole derivatives with anti-HCMV activity: QSAR modeling, synthesis and biological testing15
The FMO2 analysis of the ligand-receptor binding energy: the Biscarbene-Gold(I)/DNA G-Quadruplex case study14
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory14
SAMPL7 physical property prediction from EC-RISM theory14
Identification of potential inhibitors of Mycobacterium tuberculosis shikimate kinase: molecular docking, in silico toxicity and in vitro experiments14
Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation13
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 activity13
Imputation of sensory properties using deep learning13
An overview of the SAMPL8 host–guest binding challenge13
Improvement of multi-task learning by data enrichment: application for drug discovery12
Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange12
Insight into the sequence-specific elements leading to increased DNA bending and ligase-mediated circularization propensity by antitumor trabectedin11
User-centric design of a 3D search interface for protein-ligand complexes11
Contact networks in RNA: a structural bioinformatics study with a new tool11
Modeling receptor flexibility in the structure-based design of KRASG12C inhibitors11
De novo drug design through gradient-based regularized search in information-theoretically controlled latent space11
From closed to open: three dynamic states of membrane-bound cytochrome P450 3A410
Molecular docking, dynamics simulations, and in vivo studies of gallic acid in adenine-induced chronic kidney disease: targeting KIM-1 and NGAL10
On the NS-DSSB unidirectional estimates in the SAMPL6 SAMPLing challenge10
DeepCubist: Molecular Generator for Designing Peptidomimetics based on Complex three-dimensional scaffolds9
Benchmarking ANI potentials as a rescoring function and screening FDA drugs for SARS-CoV-2 Mpro9
Reliable gas-phase tautomer equilibria of drug-like molecule scaffolds and the issue of continuum solvation9
Comparing classification models—a practical tutorial9
Molecular and thermodynamic insights into interfacial interactions between collagen and cellulose investigated by molecular dynamics simulation and umbrella sampling9
Extended continuous similarity indices: theory and application for QSAR descriptor selection9
MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics8
In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes8
Comparative assessment of physics-based in silico methods to calculate relative solubilities8
Exploring DrugCentral: from molecular structures to clinical effects8
Multi-Omics Analysis of the virulence factors and designing of next-generation multi-epitopes Vaccines against Rickettsia prowazekii: a computer-aided vaccine designing approach8
Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model8
Comparison of logP and logD correction models trained with public and proprietary data sets8
Prediction of n-octanol/water partition coefficients and acidity constants (pKa) in the SAMPL7 blind challenge with the IEFPCM-MST model8
Exploring the anti-diabetic potential of the Vigna sesquipedalis using in vitro, in vivo and computational models8
Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays8
Molecular dynamics simulations reveal the inhibition mechanism of Cdc42 by RhoGDI18
Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal7
Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT7
Development of human lactate dehydrogenase a inhibitors: high-throughput screening, molecular dynamics simulation and enzyme activity assay7
Turbo prediction: a new approach for bioactivity prediction7
Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors7
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state7
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