AIMC Topic: Drug Design

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Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors.

Journal of computer-aided molecular design Aug 20, 2024
The development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thomas et al. Clinical Development Success Rates and Contributing Factors 2011-2020, 2021). To increase the probability of success a...
Humans Machine Learning Algorithms Computer Simulation Proteins Drug Design Drug Discovery
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Novel molecular inhibitor design for Plasmodium falciparum Lactate dehydrogenase enzyme using machine learning generated library of diverse compounds.

Molecular diversity Aug 20, 2024
Generative machine learning models offer a novel strategy for chemogenomics and de novo drug design, allowing researchers to streamline their exploration of the chemical space and concentrate on specific regions of interest. In cases with limited inh...
Small Molecule Libraries Drug Design Plasmodium falciparum Enzyme Inhibitors L-Lactate Dehydrogenase Machine Learning Antimalarials
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Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Molecular diversity Aug 17, 2024
Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell prolifer...
Molecular Dynamics Simulation Ligands Models, Molecular Phosphatidylinositol 3-Kinases Class Ib Phosphatidylinositol 3-Kinase Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Molecular Docking Simulation Drug Design Antineoplastic Agents Protein Binding Machine Learning Neoplasms Humans
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Perspectives on current approaches to virtual screening in drug discovery.

Expert opinion on drug discovery Aug 12, 2024
INTRODUCTION: For the past two decades, virtual screening (VS) has been an efficient hit finding approach for drug discovery. Today, billions of commercially accessible compounds are routinely screened, and many successful examples of VS have been re...
Humans Machine Learning High-Throughput Screening Assays Small Molecule Libraries Drug Design Drug Discovery
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Actionable Predictions of Human Pharmacokinetics at the Drug Design Stage.

Molecular pharmaceutics Aug 12, 2024
We present a novel computational approach for predicting human pharmacokinetics (PK) that addresses the challenges of early stage drug design. Our study introduces and describes a large-scale data set of 11 clinical PK end points, encompassing over 2...
Pharmacokinetics Humans Machine Learning Drug Design Pharmaceutical Preparations
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Active learning approaches in molecule pKi prediction.

Molecular informatics Aug 6, 2024
During the early stages of drug design, identifying compounds with suitable bioactivities is crucial. Given the vast array of potential drug databases, it's feasible to assay only a limited subset of candidates. The optimal method for selecting the c...
Drug Design Supervised Machine Learning
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Generative artificial intelligence for small molecule drug design.

Current opinion in biotechnology Aug 5, 2024
In recent years, the rapid advancement of generative artificial intelligence (GenAI) has revolutionized the landscape of drug design, offering innovative solutions to potentially expedite the discovery of novel therapeutics. GenAI encompasses algorit...
Artificial Intelligence Algorithms Humans Small Molecule Libraries Drug Design Drug Discovery
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AI-guided few-shot inverse design of HDP-mimicking polymers against drug-resistant bacteria.

Nature communications Jul 26, 2024
Host defense peptide (HDP)-mimicking polymers are promising therapeutic alternatives to antibiotics and have large-scale untapped potential. Artificial intelligence (AI) exhibits promising performance on large-scale chemical-content design, however, ...
Microbial Sensitivity Tests Bacteria Artificial Intelligence Drug Resistance, Bacterial Polymers Drug Design Anti-Bacterial Agents Antimicrobial Peptides
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Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design.

Journal of chemical information and modeling Jul 24, 2024
Computational molecular generation methods that generate chemical structures from gene expression profiles have been actively developed for de novo drug design. However, most omics-based methods involve complex models consisting of multiple neural ne...
Drug Design Gene Expression Profiling Humans Neural Networks, Computer Ligands Transcription, Genetic
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HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery.

Journal of chemical information and modeling Jul 22, 2024
We propose HydraScreen, a deep-learning framework for safe and robust accelerated drug discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network designed for the effective representation of molecular structures and interactio...
Proteins Ligands Deep Learning Protein Binding Neural Networks, Computer Drug Design Drug Discovery
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