The current structural glycome landscape and emerging technologies.

Carbohydrates represent one of the building blocks of life, along with nucleic acids, proteins and lipids. Although glycans are involved in a wide range of processes from embryogenesis to protein trafficking and pathogen infection, we are still a long way from deciphering the glycocode. In this review, we aim to present a few of the challenges that researchers working in the area of glycobiology can encounter and what strategies can be utilised to overcome them. Our goal is to paint a comprehensive picture of the current saccharide landscape available in the Protein Data Bank (PDB). We also review recently updated repositories relevant to the topic proposed, the impact of software development on strategies to structurally solve carbohydrate moieties, and state-of-the-art molecular and cellular biology methods that can shed some light on the function and structure of glycans

Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae.

Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps

ProCarbDB: A Database of Carbohydrate-binding Proteins

Carbohydrate-binding proteins play crucial roles across all organisms and viruses. The complexity of carbohydrate structures, together with inconsistencies in how their three-dimensional structures are reported, has led to difficulties in characterising the protein-carbohydrate interfaces. In order to better understand protein-carbohydrate interactions, we have developed an open-access database, ProCarbDB, which, unlike the Protein Data Bank (PDB), clearly distinguishes between the complete carbohydrate ligands and their monomeric units. ProCarbDB is a comprehensive database containing over 5200 three-dimensional X-ray crystal structures of protein-carbohydrate complexes. In ProCarbDB the complete carbohydrate ligands are annotated and all their interactions are displayed. Users can also select any protein residue in the proximity of the ligand to inspect its interactions with the carbohydrate ligand and with other neighbouring protein residues. Where available, additional curated information on the binding affinity of the complex and the effects of mutations on the binding have also been provided in the database. We believe that ProCarbDB will be an invaluable resource for understanding protein-carbohydrate interfaces. The ProCarbDB web server is freely available at http://www.procarbdb.science/procarb.L.C. was supported by a Collaborative Award in Science and Engineering from Ipsen Bioinnovation Ltd. to support his Research towards a PhD. D.B.A was supported by the Jack Brockhoff Foundation [JBF 4186, 2016] and the National Health and Medical Research Council of Australia [APP1072476]. P.H.M.T. was supported by The Cystic Fibrosis Trust (SRC 010 - RG92232). D.B.A and T.L.B were supported by a Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) [MR/M026302/1]

RIBFIND2: identifying rigid bodies in protein and nucleic acid structures

Molecular structures are often fitted into cryo-EM maps by flexible fitting. When this requires large conformational changes, identifying rigid bodies can help optimize the model-map fit. Tools for identifying rigid bodies in protein structures exist, however an equivalent for nucleic acid structures is lacking. With the increase in cryo-EM maps containing RNA and progress in RNA structure prediction, there is a need for such tools. We previously developed RIBFIND, a program for clustering protein secondary structures into rigid bodies. In RIBFIND2, this approach is extended to nucleic acid structures. RIBFIND2 can identify biologically relevant rigid bodies in important groups of complex RNA structures, capturing a wide range of dynamics, including large rigid-body movements. The usefulness of RIBFIND2-assigned rigid bodies in cryo-EM model refinement was demonstrated on three examples, with two conformations each: Group II Intron complexed IEP, Internal Ribosome Entry Site and the Processome, using cryo-EM maps at 2.7–5 Å resolution. A hierarchical refinement approach, performed on progressively smaller sets of RIBFIND2 rigid bodies, was clearly shown to have an advantage over classical all-atom refinement. RIBFIND2 is available via a web server with structure visualization and as a standalone tool

TEMPy2: a Python library with improved 3D electron microscopy density-fitting and validation workflows

Structural determination of molecular complexes by cryo-EM requires large, often complex processing of the image data that are initially obtained. Here, TEMPy2, an update of the TEMPy package to process, optimize and assess cryo-EM maps and the structures fitted to them, is described. New optimization routines, comprehensive automated checks and workflows to perform these tasks are described

Cryo‐EM targets in CASP13: overview and evaluation of results

Structures of seven CASP13 targets were determined using cryo‐electron microscopy (cryo‐EM) technique with resolution between 3.0 and 4.0 å. We provide an overview of the experimentally derived structures and describe results of the numerical evaluation of the submitted models. The evaluation is carried out by comparing coordinates of models to those of reference structures (CASP‐style evaluation), as well as checking goodness‐of‐fit of modeled structures to the cryo‐EM density maps. The performance of contributing research groups in the CASP‐style evaluation is measured in terms of backbone accuracy, all‐atom local geometry and similarity of inter‐subunit interfaces. The results on the cryo‐EM targets are compared with those on the whole set of eighty CASP13 targets. A‐posteriori refinement of the best models in their corresponding cryo‐EM density maps resulted in structures that are very close to the reference structure, including some regions with better fit to the density

Publisher Correction: Structural Implications of Mutations Conferring Rifampin Resistance in Mycobacterium leprae.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper

Identification and Characterization of Genetic Determinants of Isoniazid and Rifampicin Resistance in Mycobacterium tuberculosis in Southern India

Abstract: Drug-resistant tuberculosis (TB), one of the leading causes of death worldwide, arises mainly from spontaneous mutations in the genome of Mycobacterium tuberculosis. There is an urgent need to understand the mechanisms by which the mutations confer resistance in order to identify new drug targets and to design new drugs. Previous studies have reported numerous mutations that confer resistance to anti-TB drugs, but there has been little systematic analysis to understand their genetic background and the potential impacts on the drug target stability and/or interactions. Here, we report the analysis of whole-genome sequence data for 98 clinical M. tuberculosis isolates from a city in southern India. The collection was screened for phenotypic resistance and sequenced to mine the genetic mutations conferring resistance to isoniazid and rifampicin. The most frequent mutation among isoniazid and rifampicin isolates was S315T in katG and S450L in rpoB respectively. The impacts of mutations on protein stability, protein-protein interactions and protein-ligand interactions were analysed using both statistical and machine-learning approaches. Drug-resistant mutations were predicted not only to target active sites in an orthosteric manner, but also to act through allosteric mechanisms arising from distant sites, sometimes at the protein-protein interface

Mycobacterial genomics and structural bioinformatics: opportunities and challenges in drug discovery.

Of the more than 190 distinct species of Mycobacterium genus, many are economically and clinically important pathogens of humans or animals. Among those mycobacteria that infect humans, three species namely Mycobacterium tuberculosis (causative agent of tuberculosis), Mycobacterium leprae (causative agent of leprosy) and Mycobacterium abscessus (causative agent of chronic pulmonary infections) pose concern to global public health. Although antibiotics have been successfully developed to combat each of these, the emergence of drug-resistant strains is an increasing challenge for treatment and drug discovery. Here we describe the impact of the rapid expansion of genome sequencing and genome/pathway annotations that have greatly improved the progress of structure-guided drug discovery. We focus on the applications of comparative genomics, metabolomics, evolutionary bioinformatics and structural proteomics to identify potential drug targets. The opportunities and challenges for the design of drugs for M. tuberculosis, M. leprae and M. abscessus to combat resistance are discussed

Fragment-based discovery of a new class of inhibitors targeting mycobacterial tRNA modification.

Translational frameshift errors are often deleterious to the synthesis of functional proteins and could therefore be promoted therapeutically to kill bacteria. TrmD (tRNA-(N(1)G37) methyltransferase) is an essential tRNA modification enzyme in bacteria that prevents +1 errors in the reading frame during protein translation and represents an attractive potential target for the development of new antibiotics. Here, we describe the application of a structure-guided fragment-based drug discovery approach to the design of a new class of inhibitors against TrmD in Mycobacterium abscessus. Fragment library screening, followed by structure-guided chemical elaboration of hits, led to the rapid development of drug-like molecules with potent in vitro TrmD inhibitory activity. Several of these compounds exhibit activity against planktonic M. abscessus and M. tuberculosis as well as against intracellular M. abscessus and M. leprae, indicating their potential as the basis for a novel class of broad-spectrum mycobacterial drugs