Systematic enumeration for describing the IDP and IDR conformations landscape

Therese Malliavin (CNRS, Université de Lorraine, France)

LinkedIn: @Therese Malliavin

Abstract: Intrinsically disordered proteins (IDP) and intrinsically disordered regions (IDR) are at the center of numerous regulation and control pathways in the cell, and attract consequently extreme interest nowadays in structural biology. Nevertheless, it is difficult to characterize the conformational landscape of IDP,
as they sample highly variable conformations of similar energy. Thus, the structural convergence criterion used in classical NMR structure determination does not apply here. Therefore, the analysis of IDP conformational spaces classically relies on the use of Monte Carlo and molecular dynamics simulations. We present here the use of the  geometric Threading-Augmented interval Branch-and-Prune (TAiBP) approach which permits to enumerate systematically the possible conformations verifying a set of NMR chemical shifts. The combinatorial explosion due to the enumeration is alleviated by partitioning the input instances into consecutive peptide fragments and by systematic solutions clustering using self-organizing maps. The obtained sets of protein conformations can be further filtered using Small Angle X-ray Scattering (SAXS) curves or Residual Dipolar Coupling (RDC) values. Several applications will be presented.
References:
Huang, Shih, Jeng, Chang, Lin, Malliavin. pH Sensitivity of the SERF1a Conformational Ensemble. ACS Omega 2026 11:2614-2627. doi: 10.1021/acsomega.5c07620 Förster, Idier, Liberti, Mucherino, Lin, Malliavin. Low-resolution description of the conformational space for intrinsically disordered proteins. Sci Rep 2022 12:19057. doi: 10.1038/s41598-022-21648-9
Malliavin. Tandem domain structure determination based on a systematic enumeration of conformations. Sci Rep 2021 11:16925. doi: 10.1038/s41598-021-96370-z
Malliavin, Mucherino, Lavor, Liberti. Systematic Exploration of Protein Conformational Space Using a Distance Geometry Approach. J Chem Inf Model 2019 59:4486-4503
doi: 10.1021/acs.jcim.9b00215