Science Pool

This article forms a book chapter in Quantum Mechanics In Drug Discovery which is part of the Methods in Molecular Biology book series.

In this article, we discuss the use of quantum mechanics in understanding receptor-ligand interactions and chemical reactions.

The chapter includes:

• an overview of the use of quantum mechanics methods in drug design and drug discovery
• presentation of the most popular quantum mechanics methods and software packages
• discussion of recent representative applications in drug design and drug discovery

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This article forms a book chapter in Artificial Intelligence in Drug Design.

In this review article, we discuss the use of artificial intelligence, machine learning, and deep learning in computational drug discovery.

The chapter includes:

• an overview of the current state-of-the-art artificial intelligence methods which are applied in drug discovery
• a focus on structure-based and ligand-based virtual screening, library design and high throughput analysis
• further discussion on drug repurposing, de novo design, chemical reactions and synthetic accessibility, ADMET and quantum mechanics
• real life drug design case studies

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This article forms a book chapter in Artificial Intelligence in Drug Design.

In this review article, we discuss artificial intelligence and deep learning, and its application in computational chemistry.

The chapter includes:

• a comparison of deep learning and other machine learning approaches
• the advantages of deep learning including the facile incorporation of multitask learning and the enhancement of generative modelling
• the impact of deep learning on computational chemistry

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This article forms a book chapter in Artificial Intelligence in Drug Design.

In this review article, we provide the latest insights into fighting COVID-19 with technologies such as artificial intelligence.

It includes:

• an overview of the ongoing demand for efficacious drugs to treat potential vaccine-resistant COVID-19 variants in the future
• how identifying and repurposing marketed drugs for the treatment of COVID-19 plays an important role in this process 
• how artificial intelligence can be employed to speed up the drug discovery process by facilitating the selection of potential drug candidates as well as monitoring the pandemic and enabling faster diagnosis in patients
• a focus on the impact and challenges associated with artificial intelligence for drug repurposing of therapies for the treatment of COVD-19

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This article forms a book chapter in Artificial Intelligence in Drug Design.

In this review article, we provide the latest insights into de novo design approaches based on  artificial intelligence (AI) algorithms with a specific focus on ligand-based methods.

It includes:

• a background to de novo design approaches developed prior to the use of AI
• an overview of AI and commonly employed neural network architectures used in ligand based de novo design
• a list of more than 100 deep generative models reported in the literature from 2017-2020
• current applications of deep generative approaches in the drug discovery context
• an insight into future applications of deep generative models in de novo drug design 

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Learn more about Human iPSC-Derived Mixed CNS Cells and their advantages including:

• Highly physiological neural networks
• Long term synchronous network activity
• Suitable as seizure liability mode

Learn more about the advantages of human iPSC-derived cardiomyocytes including:

• Predictive and physiological cell model
• Applicable for drug development, preclinical research, and cardiac safety assessment
• Quantity, consistency and efficiency for HTS

Learn more about in Vitro iPSC research services at Evotec including:

• Robust differentiation protocols or adaptation of client protocols
• High-quality production of iPSC-derived cells at large scale
• Disease-relevant phenotypic read-outs for exploratory research and compound profiling/HTS
• Proprietary iPSC patent portfolio in tissue and disease modeling