Molecular docking plays a significant role in early-stage drug discovery, from structure-based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive power is critically dependent on the protein-ligand scoring function....
Journal of chemical theory and computation
Jul 15, 2022
Existing computational methods for estimating p values in proteins rely on theoretical approximations and lengthy computations. In this work, we use a data set of 6 million theoretically determined p shifts to train deep learning models, which are sh...
Journal of chemical information and modeling
Jul 11, 2022
Accurate prediction of post-translational modifications (PTMs) is of great significance in understanding cellular processes, by modulating protein structure and dynamics. Nowadays, with the rapid growth of protein data at different "omics" levels, ma...
Journal of chemical information and modeling
Jul 6, 2022
In recent years, molecular deep generative models have attracted much attention for its application in drug design. The data-driven molecular deep generative model approximates the high dimensional distribution of the chemical space through learning...
Protein-protein interactions (PPIs) are responsible for various essential biological processes. This information can help develop a new drug against diseases. Various experimental methods have been employed for this purpose; however, their applicatio...
Calculation of protein-ligand binding affinity is a cornerstone of drug discovery. Classic implicit solvent models, which have been widely used to accomplish this task, lack accuracy compared to experimental references. Emerging data-driven models, o...
Journal of chemical information and modeling
Jun 24, 2022
Proteins interact with numerous water molecules to perform their physiological functions in biological organisms. Most water molecules act as solvent media; hence, their roles may be considered implicitly in theoretical treatments of protein structur...
Many different types of generative models for protein sequences have been proposed in literature. Their uses include the prediction of mutational effects, protein design and the prediction of structural properties. Neural network (NN) architectures h...
In the process of converting food-processing by-products to value-added ingredients, fine grained control of the raw materials, enzymes and process conditions ensures the best possible yield and economic return. However, when raw material batches lac...
Proteins play an essential role in the functioning of living organisms. The enormity of the atomic interactions in proteins is essential in controlling their spatial structures and dynamics. It can also provide scientists with valuable information th...
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