AIMC Journal:
Journal of chemical information and modeling

Showing 261 to 270 of 934 articles

Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design.

Journal of chemical information and modeling Jun 6, 2024
Determining the viability of a new drug molecule is a time- and resource-intensive task that makes computer-aided assessments a vital approach to rapid drug discovery. Here we develop a machine learning algorithm, iMiner, that generates novel inhibit...
Data Mining Ligands Molecular Dynamics Simulation Molecular Docking Simulation Algorithms Proteins Drug Design Artificial Intelligence Machine Learning
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Graphormer-IR: Graph Transformers Predict Experimental IR Spectra Using Highly Specialized Attention.

Journal of chemical information and modeling Jun 6, 2024
Infrared (IR) spectroscopy is an important analytical tool in various chemical and forensic domains and a great deal of effort has gone into developing methods for predicting experimental spectra. A key challenge in this regard is generating highly ...
Spectrophotometry, Infrared Neural Networks, Computer
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Identification of Family-Specific Features in Cas9 and Cas12 Proteins: A Machine Learning Approach Using Complete Protein Feature Spectrum.

Journal of chemical information and modeling Jun 5, 2024
The recent development of CRISPR-Cas technology holds promise to correct gene-level defects for genetic diseases. The key element of the CRISPR-Cas system is the Cas protein, a nuclease that can edit the gene of interest assisted by guide RNA. Howeve...
CRISPR-Associated Proteins CRISPR-Associated Protein 9 CRISPR-Cas Systems Machine Learning
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ChatGPT Combining Machine Learning for the Prediction of Nanozyme Catalytic Types and Activities.

Journal of chemical information and modeling Jun 3, 2024
The design of nanozymes with superior catalytic activities is a prerequisite for broadening their biomedical applications. Previous studies have exerted significant effort in theoretical calculation and experimental trials for enhancing the catalytic...
Catalysis Machine Learning Decision Trees Humans Enzymes
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Raman Spectra of Amino Acids and Peptides from Machine Learning Polarizabilities.

Journal of chemical information and modeling Jun 3, 2024
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides, and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations, which can n...
Density Functional Theory Machine Learning Peptides Spectrum Analysis, Raman Neural Networks, Computer Amino Acids Molecular Dynamics Simulation
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RhoMax: Computational Prediction of Rhodopsin Absorption Maxima Using Geometric Deep Learning.

Journal of chemical information and modeling Jun 3, 2024
Microbial rhodopsins (MRs) are a diverse and abundant family of photoactive membrane proteins that serve as model systems for biophysical techniques. Optogenetics utilizes genetic engineering to insert specialized proteins into specific neurons or br...
Models, Molecular Amino Acid Sequence Rhodopsin Deep Learning Rhodopsins, Microbial Optogenetics Protein Conformation
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Application of Transformers in Cheminformatics.

Journal of chemical information and modeling May 30, 2024
By accelerating time-consuming processes with high efficiency, computing has become an essential part of many modern chemical pipelines. Machine learning is a class of computing methods that can discover patterns within chemical data and utilize this...
Cheminformatics Machine Learning
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Coordinate-Free and Low-Order Scaling Machine Learning Model for Atomic Partial Charge Prediction for Any Size of Molecules.

Journal of chemical information and modeling May 17, 2024
The atomic partial charge is of great importance in many fields, such as chemistry and drug-target recognition. However, conventional quantum-based computing of atomic charges is relatively slow, limiting further applications of atomic charge analysi...
Neural Networks, Computer Static Electricity Machine Learning Models, Molecular
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Guided Docking as a Data Generation Approach Facilitates Structure-Based Machine Learning on Kinases.

Journal of chemical information and modeling May 15, 2024
Drug discovery pipelines nowadays rely on machine learning models to explore and evaluate large chemical spaces. While including 3D structural information is considered beneficial, structural models are hindered by the availability of protein-ligand ...
Ligands Protein Kinases Protein Kinase Inhibitors Protein Conformation Drug Discovery Phosphotransferases Neural Networks, Computer Molecular Docking Simulation Machine Learning Protein Binding
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Improving Anticancer Drug Selection and Prioritization via Neural Learning to Rank.

Journal of chemical information and modeling May 13, 2024
Personalized cancer treatment requires a thorough understanding of complex interactions between drugs and cancer cell lines in varying genetic and molecular contexts. To address this, high-throughput screening has been used to generate large-scale dr...
Antineoplastic Agents Humans Neural Networks, Computer Cell Line, Tumor Drug Discovery
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