Towards protein-protein docking with significant structural changes using CABS-dock
The protein-protein interactions (PPIs) are crucial for understanding the majority of cellular processes. PPIs play important role in gene transcription regulation, cellular signaling, molecular basis of immune response and more. Moreover, a disruption of hese mechanisms is frequently postulated as a possible cause of diseases such as Alzheimer's or cancer. For many of biologically relevant cases the structure of protein-protein complexes remain unknown. Therefore computational techniques, including molecular docking, have become a valuable part of drug discovery pipelines. Unfortunately, none of the widely used protein-protein docking tools is free from serious limitations. Typically, in docking simulations the protein flexibility is either completely neglected or very limited. Additionally, some knowledge of the approximate location and/or the shape of the active site is also required. Such limitations arise mostly from the enormous number of degrees of freedom of protein-protein systems. In this paper, an efficient computational method for protein-protein docking is proposed and initially tested on a single docking case. The proposed method is based on a two-step procedure. In the first step, CABS-dock web server for protein-peptide docking is used to dock a peptide, which is the appropriate protein fragment responsible for the protein-protein interaction, to the other protein partner. During peptide docking, no knowledge about the binding site, nor the peptide structure, is used and the peptide is allowed to be fully flexible. In the second step, the docked peptide is used in the structural adjustment of protein complex partners. The proposed method allowed us to obtain a high accuracy model, therefore it provides a promising framework for further advances.
Code (0)
등록된 구현이 없습니다.
Tasks
Drug DiscoveryMolecular DockingSimilar Papers 제목 키워드 기반
Fast and Accurate Blind Flexible Docking
Molecular docking that predicts the bound structures of small molecules (ligands) to their protein targets, plays a vital role in drug discovery. However, existing docking methods often face limitations: they either over…
Blind DockingComputational EfficiencyDrug DiscoveryMolecular Docking+1Highly flexible protein-peptide docking using CABS-dock
Protein-peptide molecular docking is a difficult modeling problem. It is even more challenging when significant conformational changes that may occur during the binding process need to be predicted. In this chapter, we d…
Molecular DockingDiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models
Understanding how proteins structurally interact is crucial to modern biology, with applications in drug discovery and protein design. Recent machine learning methods have formulated protein-small molecule docking as a g…
Drug DiscoveryProtein DesignPROflow: An iterative refinement model for PROTAC-induced structure prediction
Proteolysis targeting chimeras (PROTACs) are small molecules that trigger the breakdown of traditionally ``undruggable'' proteins by binding simultaneously to their targets and degradation-associated proteins. A key chal…
The Docking Game: Loop Self-Play for Fast, Dynamic, and Accurate Prediction of Flexible Protein-Ligand Binding
Molecular docking is a crucial aspect of drug discovery, as it predicts the binding interactions between small-molecule ligands and protein pockets. However, current multi-task learning models for docking often show infe…
Multi-Task LearningDrug Discovery