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Ease of Use
Protein - Ligand docking is a multi-step process. Researchers should prepare structures, choose the binding site, adjust parameters, dock and then score.
Usually, this process requires the use of a few different software and approaches. It also requires manual interventions like defining protonation states of residues, identifying the binding site, optimizing the parameters. In addition to experience and skill required, one also need computing resources which makes these calculations inaccessible to experimental scientists. Drugitt simplifies the whole workflow with all-in-one solutions and automatically performs all these steps for you while providing the computing resources through the web interface. Users can also choose the in-house versions of the tools.
An ideal protein - ligand docking approach is expected to provide high accuracy and consistency among different protein families and different ligand classes.
Artifical Intelligence empowered docking algorithm predicts the near-native binding poses without any user intervention such as defining the binding site or adjusting grid parameters. At this step, a significant number of possible protein and ligand conformations are sampled. Followed by docking, Drugitt's unparalleled hybrid scoring function offers the scoring power over 90% measured by Pearson’s R by incorporating the contributions to enthalpy and entropy of the system. High Throughput Scanning (HTS) option allows the systematic investigation of the target(s) and ligands in question while researchers enjoy the near-perfect accuracy levels.
Predicting the binding free energy of a protein-ligand complex requires a delicate balance between time and accuracy.
Protein-ligand binding process consists of many steps. One should not only consider the bound complex (enthalpic contributions) but should also examine the free state conformations of both protein and ligand (entropic contributions) separately. This time-consuming process is accelerated in an unmatched manner with the unique sampling algorithms of Drugitt. CUDA Graphic Processing Units (GPUs) provide the desired computing power in comparison to a traditional CPU with a few cores. At this step, optimization of calculations on different cores is performed meticulously for maximum efficiency so that HTS is enabled.