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JCIM & JCTC Journals @JCIM_JCTC

Tweets from Journal of Chemical Information and Modeling (JCIM) and Journal of Chemical Theory and Computation (JCTC) from @ACSPublications

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JCIM & JCTC Journals@JCIM_JCTC
Jun 29
📢 Check the new Volume 66 Issue 11 of #JCIM pubs.acs.org/toc/jcisd8/66/1…
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Constrained Low-Dimensional Parametrization of Coarse-Grained Force Fields for Structural and Thermodynamic Consistency pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #compchem

Constrained Low-Dimensional Parametrization of Coarse-Grained Force Fields for Structural and...

For complex multicomponent condensed-phase systems, coarse-grained (CG) molecular dynamics often struggles to simultaneously achieve structural fidelity and thermodynamic consistency. Using base...

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B–Z DNA Transitions under Z–DNA-Favoring Conditions: Benchmarking the OL21-vdW7 Force Field pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #compchem

B–Z DNA Transitions under Z–DNA-Favoring Conditions: Benchmarking the OL21-vdW7 Force Field

The B–Z DNA transition provides a rigorous benchmark for all-atom DNA force fields because it arises from a finely balanced free-energy competition between conformational states with distinct...

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Fast Fourier Transform Enables Automated Parametrization of Complex Dihedral Potentials in All-Atom and Coarse-Grained Force Fields pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #compchem

Fast Fourier Transform Enables Automated Parametrization of Complex Dihedral Potentials in All-Atom...

Torsional parametrization remains one of the most persistent challenges and weaknesses of modern force fields, particularly for dihedrals whose asymmetry and multimodality evade traditional Fourier...

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Large-Scale Collaborative Assessment of Binding Free Energy Calculations for Drug Discovery Using OpenFE pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #compchem

Large-Scale Collaborative Assessment of Binding Free Energy Calculations for Drug Discovery Using...

Accurately measuring compound binding affinities is key to driving the pharmaceutical development process. Rigorous physics-based in silico approaches, particularly alchemical free energy methods,...

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Efficient and Precise Force Field Optimization for Biomolecules Using DPA-3 pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #ChemicalInformation

Efficient and Precise Force Field Optimization for Biomolecules Using DPA-3

Molecular simulations are essential tools in computational chemistry, enabling the prediction and understanding of molecular interactions and thermodynamic properties of biomolecules. However,...

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Overcoming Shortcut Learning in RNA-Small Molecule Modeling via Bias-Matched Decoys and Structure-Aware Network Design pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #ChemicalInformation

Overcoming Shortcut Learning in RNA-Small Molecule Modeling via Bias-Matched Decoys and Structure...

Targeting RNA with small molecules represents a promising frontier in drug discovery, yet current computational models are often hindered by the physicochemical property misalignment within available...

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3DOpt: Benchmark for Automated Design of 3D Molecular Structures across the Periodic Table pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #ChemicalInformation

3DOpt: Benchmark for Automated Design of 3D Molecular Structures across the Periodic Table

The automated design of three-dimensional (3D) molecular structures is a rapidly advancing field with major applications in drug discovery, catalysis, and materials science. Despite this progress,...

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MotifLeadDB: A Hierarchical Structural Data Set for Congeneric Ligand Binding Activity Change pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #ChemicalInformation

MotifLeadDB: A Hierarchical Structural Data Set for Congeneric Ligand Binding Activity Change

Predicting ligand binding free energy change by chemical substitutions is a critical task in drug optimization studies. Despite many efforts, existing computational methods show limited prediction...

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Toward Lab-Ready AI Synthesis Plans with Protection Strategies and Route Scoring pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

Toward Lab-Ready AI Synthesis Plans with Protection Strategies and Route Scoring

AI-driven synthesis planning tools are developed to automatically create synthesis routes and thereby aid chemists in making novel molecules. However, these tools frequently produce reaction trees...

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Reliability-Aware Deep Learning Framework for Chemical Genotoxicity Prediction with Uncertainty Quantification pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

Reliability-Aware Deep Learning Framework for Chemical Genotoxicity Prediction with Uncertainty...

Genotoxicity assessment is crucial for drug development and chemical safety evaluation. However, traditional experimental approaches are time-consuming, resource-intensive, and raise ethical concerns...

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ProtSATT: An Advanced Protein Solubility Predictor Based on Attention Mechanism pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

ProtSATT: An Advanced Protein Solubility Predictor Based on Attention Mechanism

Protein solubility is an important factor affecting the production efficiency and downstream utility in biologics development. However, conventional expression systems often suffer from insoluble...

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When Trees Guide Molecules: Multiobjective Search inde NovoDrug Design pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

When Trees Guide Molecules: Multiobjective Search in de Novo Drug Design

Seen as a problem of guided exploration with multiple objectives, molecular design requires carefully elaborated decision-tree–based strategies for traversing vast chemical space. Among main challe...

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NMR-Challenge for LLMs: Evaluating Chemical Reasoning in Humans and AI pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

NMR-Challenge for LLMs: Evaluating Chemical Reasoning in Humans and AI

Nuclear magnetic resonance (NMR) structure determination is an important problem in education, industry, and research. Solving NMR spectra requires expert knowledge, critical thinking, and careful...

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Per-MOF Mechanistic Attribution Reveals Context-Dependent Stability Mechanisms in Metal–Organic Frameworks pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

Per-MOF Mechanistic Attribution Reveals Context-Dependent Stability Mechanisms in Metal–Organic...

Water stability remains a critical barrier to the practical deployment of metal–organic frameworks (MOFs) in aqueous and industrial environments. While recent machine-learning studies have achieved...

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CLIMBS: Assessing Carbohydrate–Protein Interactions through a Graph Neural Network Classifier Using Synthetic Negative Data pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

CLIMBS: Assessing Carbohydrate–Protein Interactions through a Graph Neural Network Classifier Using...

Carbohydrate–protein interactions are essential for biological processes, such as cellular signaling and metabolism, and represent a large pool of untapped targets for diagnostics and therapeutics....

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The Tsetlin Machine: A “Third Way” in QSAR Modeling pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #MachineLearning #DeepLearning

The Tsetlin Machine: A “Third Way” in QSAR Modeling

Advances in Quantitative Structure Activity Relationship (QSAR) are led by two core paradigms, (1) descriptor engineering, where complex fixed-length vectors of compounds are generated and conventi...

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Comprehensive Review of Contrastive and Generative Self-Supervised Learning for Small Molecular Representation pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #Review

Comprehensive Review of Contrastive and Generative Self-Supervised Learning for Small Molecular...

Drug discovery is a complex and resource-intensive process, where developing effective computational tools to analyze vast and heterogeneous molecular data is paramount. In this landscape, contrast...

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Are We Underestimating Overfitting? pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #Perspective

Are We Underestimating Overfitting?

It is a well-established dogma in quantitative structure–activity relationships (QSAR) that parsimonious models generalize best and that overfitting must be avoided. As the number of fitted paramet...

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Pep2MARS: Automated Cyclic Peptide Parameterization for Molecular Dynamics and Compound Design pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #ApplicationNote

Pep2MARS: Automated Cyclic Peptide Parameterization for Molecular Dynamics and Compound Design

Cyclic peptide represents an attractive drug modality with its advantages in targeting proteins that were traditionally considered “undruggable”. Molecular dynamics (MD) simulation remains a powerful...

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PDBTools.jl: A Lightweight and High-Performance Julia Package for Molecular Structure File Handling and Analysis pubs.acs.org/doi/10.1021/acs… #JCIM Vol66 Issue11 #ApplicationNote

PDBTools.jl: A Lightweight and High-Performance Julia Package for Molecular Structure File Handling...

We present PDBTools.jl, a lightweight and high-performance Julia package for reading, writing, selecting, and analyzing molecular structure data stored in PDB and mmCIF (PDBx) file formats. The...

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