AIMC Topic: Drug Design

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AIScaffold: A Web-Based Tool for Scaffold Diversification Using Deep Learning.

Journal of chemical information and modeling Dec 28, 2020
Molecular scaffolds are widely used in drug design. Many methods and tools have been developed to utilize the information in scaffolds. Scaffold diversification is frequently used by medicinal chemists in tasks such as lead compound optimization, but...
Deep Learning Internet Drug Design
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Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.

International journal of molecular sciences Dec 26, 2020
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...
Deep Learning Genome-Wide Association Study Diabetes Mellitus, Type 2 Drug Discovery Case-Control Studies Computational Biology Systems Biology Epigenomics Gene Regulatory Networks Genetic Predisposition to Disease Biomarkers Drug Design Humans Hypoglycemic Agents
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Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors.

Bioorganic chemistry Dec 19, 2020
Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inp...
Carbonic Anhydrase IX Carbonic Anhydrase Inhibitors Triazines Carbonic Anhydrase II Antigens, Neoplasm Sulfonamides Neural Networks, Computer Drug Design Humans
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Scaffold-Constrained Molecular Generation.

Journal of chemical information and modeling Dec 10, 2020
One of the major applications of generative models for drug discovery targets the lead-optimization phase. During the optimization of a lead series, it is common to have scaffold constraints imposed on the structure of the molecules designed. Without...
Drug Design Drug Discovery Probability Neural Networks, Computer Algorithms
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An integrated computational methodology with data-driven machine learning, molecular modeling and PBPK modeling to accelerate solid dispersion formulation design.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V Dec 7, 2020
Drugs in solid dispersion (SD) take advantage of fast and extended dissolution, thus attains a higher bioavailability than the crystal form. However, current development of SD relies on a random large-scale formulation screening method with low effic...
Biological Availability Datasets as Topic Intestinal Absorption Solubility Drug Liberation Drug Design Machine Learning Data Science Molecular Dynamics Simulation Models, Biological Administration, Oral
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Target-Specific Drug Design Method Combining Deep Learning and Water Pharmacophore.

Journal of chemical information and modeling Nov 30, 2020
Following identification of a target protein, hit identification, which finds small organic molecules that bind to the target, is an important first step of a structure-based drug design project. In this study, we demonstrate a target-specific drug d...
Algorithms Proteins Molecular Docking Simulation Ligands Deep Learning Drug Design Water
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AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks.

International journal of molecular sciences Nov 10, 2020
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient and successful rational drug design. Therefore, many binding affinity prediction methods have been developed. In recent years, since deep learning tech...
Neural Networks, Computer Molecular Docking Simulation Drug Design Drug Discovery Molecular Dynamics Simulation Computer-Aided Design Protein Binding Deep Learning Proteins Humans Ligands User-Computer Interface Databases, Protein
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REINVENT 2.0: An AI Tool for De Novo Drug Design.

Journal of chemical information and modeling Oct 29, 2020
In the past few years, we have witnessed a renaissance of the field of molecular de novo drug design. The advancements in deep learning and artificial intelligence (AI) have triggered an avalanche of ideas on how to translate such techniques to a var...
Drug Discovery Artificial Intelligence Drug Design
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A Turing Test for Molecular Generators.

Journal of medicinal chemistry Oct 12, 2020
Machine learning approaches promise to accelerate and improve success rates in medicinal chemistry programs by more effectively leveraging available data to guide a molecular design. A key step of an automated computational design algorithm is molecu...
Machine Learning Algorithms Drug Design Humans Molecular Structure Chemistry, Pharmaceutical
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Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.

Journal of computer-aided molecular design Oct 9, 2020
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in...
Drug Design Ligands Drug Discovery Machine Learning Pharmaceutical Preparations Quantum Theory Models, Molecular
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