Information-driven modeling of biomolecular complexes

Modelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases

“…Therefore, our protocol combines this final step with the key preliminary assessment of the isoform mapping correctly the mutation of interest. Importantly, all steps of our protocol yield results that can be used at different stages by the user: the identification of specific isoforms containing residues involved in selected mutations is per se a remarkable clue for genetic assessment of the impact of isoforms, especially by handling a large number of proteins and point mutations; the set of the templates eventually identified by MoNvIso with the section of the target protein covered by them are made available to the user; finally, the structural predictions represent a valuable starting point for additional refinements and investigations, such as molecular dynamics simulations ( Raval et al, 2012 ; Hollingsworth and Dror, 2018 ; Lazim et al, 20202020 ; Miller and Phillips, 2021 ; Itoh and Okumura, 2022 ), hot spots evaluation ( Murakami et al, 2017 ; Liu et al, 20182018 ; Rosell and Fernández-Recio, 2018 ; Rosensweig et al, 2018 ), protein-protein docking ( Kangueane and Nilofer, 2018 ; van Noort et al, 2021 ) and more ( Poelwijk et al, 2016 ; Rivoire et al, 2016 ; Salinas and Ranganathan, 2018 ). Finally, note that for isoforms without good quality-templates, users could choose to use predicted structures such as those provided by AF and RosettaFold ( Baek et al, 2021 ) or other modelling packages and/or protocols to build their own structural models using the isoform(s) correctly associated with the selected point mutations.…”

Bismuth Drugs Reverse Tet(X)-Conferred Tigecycline Resistance in Gram-Negative Bacteria

“…The homology modeling of Tet(X4) protein and template protein 2XYO was performed using SwissModel ( 35 ). Molecular docking between Bi(NO 3 ) 3 molecules, bismuth atom, and Tet(X4)-FAD complex system was carried using Autodock with random blind docking methods ( 36 , 37 ). The related operations of molecular dynamics simulation were conducted using the Desmond module in the Schrodinger software package ( 38 ).…”

Protein–protein interaction prediction methods: from docking-based to AI-based approaches

“…In the last 10 years, sophisticated high-precision docking methods such as HADDOCK (van Zundert et al 2015 ), ClusPro (Desta et al 2020 ), ZDOCK (Pierce et al 2014 ), and LightDock (Jiménez-García et al 2018 ) have been developed and continually improved. To sample conformations more efficiently, they have used not only three-dimensional structural information in both modeling and scoring steps, but also evolutionary information and information obtained from experiments of several types (van Noort et al 2021 ). Evolutionary information has been used for the prediction of PPIs based on the idea that mutations of the residues involved in the interaction on a protein engender mutations of the interface residues on the partner protein (Jothi et al 2006 ).…”

“…Recently, data of low-resolution shapes obtained by small-angle scattering methods such as SAXS, were also used for the filtering of docked models in several docking methods (van Noort et al 2021 ), e.g., pyDockSAXS (Jiménez-García et al 2015 ) and HADDOCK (van Zundert et al 2015 ).…”