This article provides a comprehensive analysis of the current landscape of AI-driven molecular optimization for drug discovery.
The exploration of high-dimensional chemical space is a fundamental challenge in modern drug discovery, crucial for identifying novel therapeutic candidates.
Accurate energy functions are the cornerstone of reliable computational protein design, enabling the creation of novel therapeutics, enzymes, and materials.
This article provides a comprehensive framework for validating molecular dynamics (MD) simulations, a critical step for ensuring the reliability and reproducibility of computational studies in drug development and biomedical research.
This comprehensive guide addresses the critical challenges researchers face in heterologous protein expression, a cornerstone technique in biotechnology and drug development.
This article provides a comprehensive guide for researchers and drug development professionals on optimizing molecular similarity thresholds in Quantitative Structure-Activity Relationship (QSAR) modeling.
Molecular optimization in drug discovery and materials science often operates in data-sparse regimes where extensive experimental data is unavailable.
This article provides a comprehensive guide for researchers and drug development professionals on overcoming the challenge of silent biosynthetic gene clusters (BGCs).
This article provides a comprehensive guide for researchers and drug development professionals on improving the accuracy of Molecular Dynamics (MD) simulations.
Scaling molecular engineering processes from laboratory discovery to industrial and clinical application presents a complex set of interdisciplinary challenges.