From these comparisons, N-protein active site residue(s) that were responsible for each domain showed a significant functional change in terms of N-protein activity when removed and showed N-protein activity prediction capability and significant structural change in the N-protein when altered were ...
The latter uses a negative electrostatic surface around the entrance to the active site gorge for the fast binding of its positively charged substrate (Radic et al., 1997, Zhou et al., 1998). In other cases, such as in complexes formed by WASp and Cdc42 (Abdul-Manan et al., 1999) ...
a statement that assigns a function to a protein) is true in all of them. For each subontology of GO we train up to ten models and aggregate the prediction scores using three different strategies. First, we take the maximum of the selected scores which means...
compared to other approaches, there are still significant challenges in interpreting the learning mechanisms within PhiGnet. For instance, a protein might have more than one active or functionally relevant sites. The activation score does not allow to discern active site a given residue is part of...
Method development for RBP binding-site prediction is an active area of research in the domain of computational RNA biology and an abundance of RBP binding-site prediction methods have been developed in recent years [8, 9, 10]. Development of new methods further accelerated with the advent of ...
The recently proposed DoGSite method investigated the concept of subpockets and the difference of Gaussian approach (DoG) is found to be able to improve the prediction rates of protein active sites [35]. Except for the efforts to find the discriminative features of interaction sites and their ...
Antibody Complementarity-Determining Region Sequence Design using AlphaFold2 and Binding Affinity Prediction Model Takafumi Ueki, Masahito Ohue bioRxiv 2023.06.02.543382 Context-Dependent Design of Induced-fit Enzymes using Deep Learning Generates Well Expressed, Thermally Stable and Active Enzymes Lior Zimmerm...
In the third experiment we study the impact of using bidirectional constraints between pairs of levels; the level not appearing in the rules is predicted independently, as above. In theP⇔Dcase, both theP→DandD→Prules are active, meaning that the protein and domain levels are enforced to ...
Interestingly, COH000 binds to a cryptic pocket within SUMO E1 that is separate from its active site and which had been observed to be buried in previous structures of the enzyme. It was hypothesized that the SUMO E1 is in constant structural flux and that COH000 could lock the enzyme into...
the impact of the molecular flexibility using a machine learning algorithm, we successfully distinguished the most overestimated association rates from the non-overestimated ones and were thus able to correct the overestimated rate constants and improve the final prediction in a cross-validation test set...