Journal of Computer-Aided Molecular Design

Papers
(The TQCC of Journal of Computer-Aided Molecular Design is 8. 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 2021-05-01 to 2025-05-01.)
ArticleCitations
Energy-entropy prediction of octanol–water logP of SAMPL7 N-acyl sulfonamide bioisosters120
Computational investigation of functional water molecules in GPCRs bound to G protein or arrestin59
Computational peptide discovery with a genetic programming approach53
GPCRLigNet: rapid screening for GPCR active ligands using machine learning45
In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry38
Enhancing sampling of water rehydration upon ligand binding using variants of grand canonical Monte Carlo35
A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios22
PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams21
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 approaches20
Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery18
COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge17
FastGrow: on-the-fly growing and its application to DYRK1A17
pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants16
Design of new imidazole derivatives with anti-HCMV activity: QSAR modeling, synthesis and biological testing15
SAMPL7 physical property prediction from EC-RISM theory14
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory14
Identification of potential inhibitors of Mycobacterium tuberculosis shikimate kinase: molecular docking, in silico toxicity and in vitro experiments14
The FMO2 analysis of the ligand-receptor binding energy: the Biscarbene-Gold(I)/DNA G-Quadruplex case study14
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 activity14
Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation13
An overview of the SAMPL8 host–guest binding challenge13
De novo drug design through gradient-based regularized search in information-theoretically controlled latent space13
Imputation of sensory properties using deep learning12
User-centric design of a 3D search interface for protein-ligand complexes12
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 trabectedin12
Improving virtual screening results with MM/GBSA and MM/PBSA rescoring11
Development and interpretation of a QSAR model for in vitro breast cancer (MCF-7) cytotoxicity of 2-phenylacrylonitriles11
Contact networks in RNA: a structural bioinformatics study with a new tool11
Modeling receptor flexibility in the structure-based design of KRASG12C inhibitors11
Fine-tuning of a generative neural network for designing multi-target compounds11
Benchmarking ANI potentials as a rescoring function and screening FDA drugs for SARS-CoV-2 Mpro10
On the NS-DSSB unidirectional estimates in the SAMPL6 SAMPLing challenge10
Molecular docking, dynamics simulations, and in vivo studies of gallic acid in adenine-induced chronic kidney disease: targeting KIM-1 and NGAL10
From closed to open: three dynamic states of membrane-bound cytochrome P450 3A410
DeepCubist: Molecular Generator for Designing Peptidomimetics based on Complex three-dimensional scaffolds9
Extended continuous similarity indices: theory and application for QSAR descriptor selection9
Comparing classification models—a practical tutorial9
Molecular dynamics simulations reveal the inhibition mechanism of Cdc42 by RhoGDI19
Molecular and thermodynamic insights into interfacial interactions between collagen and cellulose investigated by molecular dynamics simulation and umbrella sampling8
Prediction of n-octanol/water partition coefficients and acidity constants (pKa) in the SAMPL7 blind challenge with the IEFPCM-MST model8
Comparative assessment of physics-based in silico methods to calculate relative solubilities8
Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model8
Development of human lactate dehydrogenase a inhibitors: high-throughput screening, molecular dynamics simulation and enzyme activity assay8
Reliable gas-phase tautomer equilibria of drug-like molecule scaffolds and the issue of continuum solvation8
Exploring DrugCentral: from molecular structures to clinical effects8
In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes8
Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays8
Comparison of logP and logD correction models trained with public and proprietary data sets8
MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics8
Exploring the anti-diabetic potential of the Vigna sesquipedalis using in vitro, in vivo and computational models8
Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal8
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