Structural coordinates: A novel approach to predict protein backbone conformation

Motivation Local protein structure is usually described via classifying each peptide to a unique class from a set of pre-defined structures. These classifications may differ in the number of structural classes, the length of peptides, or class attribution criteria. Most methods that predict the local structure of a protein from its sequence first rely on some classification and only then proceed to the 3D conformation assessment. However, most classification methods rely on homologous proteins’ existence, unavoidably lose information by attributing a peptide to a single class or suffer from a suboptimal choice of the representative classes. Results To alleviate the above challenges, we propose a method that constructs a peptide’s structural representation from the sequence, reflecting its similarity to several basic representative structures. For 5-mer peptides and 16 representative structures, we achieved the Q16 classification accuracy of 67.9%, which is higher than what is currently reported in the literature. Our prediction method does not utilize information about protein homologues but relies only on the amino acids’ physicochemical properties and the resolved structures’ statistics. We also show that the 3D coordinates of a peptide can be uniquely recovered from its structural coordinates, and show the required conditions under various geometric constraints.

CheSPI: Chemical shift Secondary structure Population Inference

NMR chemical shifts (CSs) are delicate reporters of local protein structure, and recent advances in random coil CS (RCCS) prediction and interpretation now offer the compelling prospect of inferring small populations of structure from small deviations from RCCSs. Here, we present CheSPI, a simple and efficient method that provides unbiased and sensitive aggregate measures of local structure and disorder. It is demonstrated that CheSPI can predict even very small amounts of residual structure and robustly delineate subtle differences into four structural classes for intrinsically disordered proteins. For structured regions and proteins, CheSPI can assign up to eight structural classes, which coincide with the well-known DSSP classification. The program is freely available, and can either be invoked from URL www.protein-nmr.org as a web implementation, or run locally from command line as a python program. CheSPI generates comprehensive numeric and graphical output for intuitive annotation and visualization of protein structures. A number of examples are provided.

Crystal Structures of [Fe]-Hydrogenase from Methanolacinia paynteri Suggest a Path of the FeGP-Cofactor Incorporation Process

[Fe]-hydrogenase (Hmd) catalyzes the reversible heterolytic cleavage of H2, and hydride transfer to methenyl-tetrahydromethanopterin (methenyl-H4MPT+). The iron-guanylylpyridinol (FeGP) cofactor, the prosthetic group of Hmd, can be extracted from the holoenzyme and inserted back into the protein. Here, we report the crystal structure of an asymmetric homodimer of Hmd from Methanolacinia paynteri (pHmd), which was composed of one monomer in the open conformation with the FeGP cofactor (holo-form) and a second monomer in the closed conformation without the cofactor (apo-form). In addition, we report the symmetric pHmd-homodimer structure in complex with guanosine monophosphate (GMP) or guanylylpyridinol (GP), in which each ligand was bound to the protein, where the GMP moiety of the FeGP-cofactor is bound in the holo-form. Binding of GMP and GP modified the local protein structure but did not induce the open conformation. The amino-group of the Lys150 appears to interact with the 2-hydroxy group of pyridinol ring in the pHmd–GP complex, which is not the case in the structure of the pHmd–FeGP complex. Lys150Ala mutation decreased the reconstitution rate of the active enzyme with the FeGP cofactor at the physiological pH. These results suggest that Lys150 might be involved in the FeGP-cofactor incorporation into the Hmd protein in vivo.

PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks

This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.

PBxplore: a tool to analyze local protein structure and deformability with protein Blocks

ABSTRACTProteins are highly dynamic macromolecules. A classical way to analyze their inner flexibility is to perform molecular dynamics simulations. In this context, we present the advantage to use small structural prototypes, namely the Protein Blocks (PBs). PBs give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, they allow analyzes of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is a suite of tools to analyze the dynamics and deformability of protein structures using PBs. It is able to process large amount of data such as those produced by molecular dynamics simulations. It produces various outputs with text and graphics, such as frequencies, entropy and information logo. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.

Novel Pathogenic Variant in TGFBR2 Confirmed by Molecular Modeling Is a Rare Cause of Loeys-Dietz Syndrome

Loeys-Dietz syndrome (LDS) is a connective tissue disorder characterized by vascular findings of aneurysm and/or dissection of cerebral, thoracic, or abdominal arteries and skeletal findings. We report a case of a novel pathogenic variant in TGFBR2 and phenotype consistent with classic LDS. The proband was a 10-year-old presenting to the genetics clinic with an enlarged aortic root (Z-scores 5-6), pectus excavatum, and congenital contractures of the right 2nd and 3rd digit. Molecular testing of TGFBR2 was sent to a commercial laboratory and demonstrated a novel, likely pathogenic, variant in exon 4, c.1061T>C, p.(L354P). Molecular modeling reveals alteration of local protein structure as a result of this pathogenic variant. This pathogenic variant has not been previously reported in LDS and thus expands the pathogenic variant spectrum of this condition.