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 2021-08-01 to 2025-08-01.)
ArticleCitations
Computational investigation of functional water molecules in GPCRs bound to G protein or arrestin139
Computational peptide discovery with a genetic programming approach54
GPCRLigNet: rapid screening for GPCR active ligands using machine learning40
A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios23
Enhancing sampling of water rehydration upon ligand binding using variants of grand canonical Monte Carlo23
Obtaining QM/MM binding free energies in the SAMPL8 drugs of abuse challenge: indirect approaches22
PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams19
QM assisted ML for 19F NMR chemical shift prediction19
Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host–guest binding: II. regression and dielectric constant17
In silico exploration of natural xanthone derivatives as potential inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication and cellular entry16
FastGrow: on-the-fly growing and its application to DYRK1A16
Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery16
Design of new imidazole derivatives with anti-HCMV activity: QSAR modeling, synthesis and biological testing16
COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge16
“Heptadecanol” a phytochemical multi-target inhibitor of SMYD3 & GFPT2 proteins in non-small cell lung cancer: an in-silico & in-vitro investigation15
Correction to: Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory14
pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants14
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 study13
Unveiling a novel ellagic acid derivative as a potent lipoxygenase (LOX) inhibitor: integration of computational modeling and experimental validation12
Mechanistic insights into PROTAC-mediated degradation through an integrated framework of molecular dynamics, free energy landscapes, and quantum mechanics: A case study on kinase degraders11
Evaluating computational and experimental approaches in early-stage Alzheimer’s drug discovery: a systematic review11
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 activity11
An overview of the SAMPL8 host–guest binding challenge11
Imputation of sensory properties using deep learning10
User-centric design of a 3D search interface for protein-ligand complexes10
Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange10
Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation10
Improvement of multi-task learning by data enrichment: application for drug discovery10
On the NS-DSSB unidirectional estimates in the SAMPL6 SAMPLing challenge9
Integrated machine learning and deep learning-based virtual screening framework identifies novel natural GSK-3β inhibitors for Alzheimer’s disease9
Modeling receptor flexibility in the structure-based design of KRASG12C inhibitors9
Extended continuous similarity indices: theory and application for QSAR descriptor selection9
From closed to open: three dynamic states of membrane-bound cytochrome P450 3A49
Protein-ligand co-design: a case for improving binding affinity between type II NADH:quinone oxidoreductase and quinones9
Molecular docking, dynamics simulations, and in vivo studies of gallic acid in adenine-induced chronic kidney disease: targeting KIM-1 and NGAL9
Multitarget neuroprotective effects of β-sitosterol in diabetes-associated neurodegeneration: a coupled experimental/computational study9
Contact networks in RNA: a structural bioinformatics study with a new tool9
De novo drug design through gradient-based regularized search in information-theoretically controlled latent space9
DeepCubist: Molecular Generator for Designing Peptidomimetics based on Complex three-dimensional scaffolds8
Multi-Omics Analysis of the virulence factors and designing of next-generation multi-epitopes Vaccines against Rickettsia prowazekii: a computer-aided vaccine designing approach8
Comparing classification models—a practical tutorial8
Comparison of logP and logD correction models trained with public and proprietary data sets8
Molecular and thermodynamic insights into interfacial interactions between collagen and cellulose investigated by molecular dynamics simulation and umbrella sampling8
CoBdock-2: enhancing blind docking performance through hybrid feature selection combining ensemble and multimodel feature selection approaches8
Molecular dynamics simulations reveal the inhibition mechanism of Cdc42 by RhoGDI18
MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics8
Reliable gas-phase tautomer equilibria of drug-like molecule scaffolds and the issue of continuum solvation8
Benchmarking ANI potentials as a rescoring function and screening FDA drugs for SARS-CoV-2 Mpro8
Exploring DrugCentral: from molecular structures to clinical effects8
Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model7
Turbo prediction: a new approach for bioactivity prediction7
In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes7
Exploring the anti-diabetic potential of the Vigna sesquipedalis using in vitro, in vivo and computational models7
Comparative assessment of physics-based in silico methods to calculate relative solubilities7
Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT7
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