Higher-throughput approaches to crystallization and crystal structure determination

2008 ◽  
Vol 36 (4) ◽  
pp. 771-775 ◽  
Author(s):  
Mark J. Fogg ◽  
Anthony J. Wilkinson
Keyword(s):  
Crystal Structure ◽  
Structural Biology ◽  
Protein Structures ◽  
Data Bank ◽  
Structural Proteomics ◽  
Structural Determination ◽  
Ligation Independent Cloning ◽  
Structure Solution ◽  
Biology Laboratory ◽  
Automated Methods

In recent times, there has been a large increase in the number of protein structures deposited in the Protein Data Bank. Structural genomics initiatives have contributed to this expansion through their focus on high-throughput structural determination. This has fuelled advances in many of the techniques in the pipeline from gene to protein to crystal to structure. These include ligation-independent cloning methods, parallel purification systems, robotic crystallization devices and automated methods of crystal identification, data collection and, in some cases, structure solution. Some of these advances are described and discussed briefly with an emphasis on activities in the York Structural Biology Laboratory through its participation in the Structural Proteomics in Europe consortium.

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

2021 ◽  
Vol 8 ◽  
Author(s):  
Sundeep Chaitanya Vedithi ◽  
Sony Malhotra ◽  
Marta Acebrón-García-de-Eulate ◽  
Modestas Matusevicius ◽  
Pedro Henrique Monteiro Torres ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Schwann Cells ◽  
Protein Structures ◽  
Mycobacterium Leprae ◽  
Data Bank ◽  
Nerve Damage ◽  
Structural Proteomics ◽  
Bacterial Survival ◽  
Functional Sites

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.

scholarly journals Prediction of residue-residue contacts in CASP12 targets from its predicted tertiary structures

2017 ◽  
Author(s):  
Piyush Agrawal ◽  
Sandeep Singh ◽  
Gandharva Nagpal ◽  
Deepti Sethi ◽  
Gajendra P.S. Raghava
Keyword(s):  
Structural Biology ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Simple Approach ◽  
Structural Proteomics ◽  
List Size ◽  
Tertiary Structures ◽  
Residue Contact ◽  
Residue Contacts ◽  
Better Than

AbstractOne of the challenges in the field of structural proteomics is to predict residue-residue contacts in a protein. It is an integral part of CASP competitions due to its importance in the field of structural biology. This manuscript describes RRCPred 2.0 a method participated in CASP12 and predicted residue-residue contact in targets with high precision. In this approach, firstly 150 predicted protein structures were obtained from CASP12 Stage 2 tarball and ranked using clustering-based quality assessment software. Secondly, residue-residue contacts were assigned in top 10 protein structures based on distance between residues. Finally, residue-residue contacts were predicted in target protein based on consensus/average in top 10 predicted structures. This simple approach performs better than most of CASP12 methods in the categories of TBM and TBM/FM. It ranked 1st in following categories; i) TBM domain on list size L/5, ii) TBM/FM domain on list size L/5 and iii) TBM/FM domain on Top 10. These observations indicate that predicted tertiary structure of a protein can be used for predicting residue-residue contacts in protein with high accuracy.

scholarly journals Identifying, studying and making good use of macromolecular crystals

2014 ◽  
Vol 70 (8) ◽  
pp. 993-1008 ◽  
Author(s):  
Guillermo Calero ◽  
Aina E. Cohen ◽  
Joseph R. Luft ◽  
Janet Newman ◽  
Edward H. Snell
Keyword(s):  
Data Collection ◽  
Visible Light ◽  
Structural Biology ◽  
Protein Structures ◽  
Data Bank ◽  
Potential Outcomes ◽  
Structural Knowledge ◽  
X Ray ◽  
X Ray Crystallography ◽  
Molecular Scale

Structural biology has contributed tremendous knowledge to the understanding of life on the molecular scale. The Protein Data Bank, a depository of this structural knowledge, currently contains over 100 000 protein structures, with the majority stemming from X-ray crystallography. As the name might suggest, crystallography requires crystals. As detectors become more sensitive and X-ray sources more intense, the notion of a crystal is gradually changing from one large enough to embellish expensive jewellery to objects that have external dimensions of the order of the wavelength of visible light. Identifying these crystals is a prerequisite to their study. This paper discusses developments in identifying these crystals during crystallization screening and distinguishing them from other potential outcomes. The practical aspects of ensuring that once a crystal is identified it can then be positioned in the X-ray beam for data collection are also addressed.

scholarly journals Structural biology in the time of COVID-19: perspectives on methods and milestones

IUCrJ ◽  
2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Miranda L. Lynch ◽  
Edward H. Snell ◽  
Sarah E. J. Bowman
Keyword(s):  
Structural Biology ◽  
Protein Structures ◽  
50Th Anniversary ◽  
Data Bank ◽  
World Health ◽  
X Ray Crystallography ◽  
The Status ◽  
One Year ◽  
Health Organization ◽  
Structural Methods

The global COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has wreaked unprecedented havoc on global society, in terms of a huge loss of life and burden of morbidity, economic upheaval and social disruption. Yet the sheer magnitude and uniqueness of this event has also spawned a massive mobilization of effort in the scientific community to investigate the virus, to develop therapeutics and vaccines, and to understand the public health impacts. Structural biology has been at the center of these efforts, and so it is advantageous to take an opportunity to reflect on the status of structural science vis-à-vis its role in the fight against COVID-19, to register the unprecedented response and to contemplate the role of structural biology in addressing future outbreak threats. As the one-year anniversary of the World Health Organization declaration that COVID-19 is a pandemic has just passed, over 1000 structures of SARS-CoV-2 biomolecules have been deposited in the Worldwide Protein Data Bank (PDB). It is rare to obtain a snapshot of such intense effort in the structural biology arena and is of special interest as the 50th anniversary of the PDB is celebrated in 2021. It is additionally timely as it overlaps with a period that has been termed the `resolution revolution' in cryoelectron microscopy (CryoEM). CryoEM has recently become capable of producing biomolecular structures at similar resolutions to those traditionally associated with macromolecular X-ray crystallography. Examining SARS-CoV-2 protein structures that have been deposited in the PDB since the virus was first identified allows a unique window into the power of structural biology and a snapshot of the advantages of the different techniques available, as well as insight into the complementarity of the structural methods.

scholarly journals Detection of translational noncrystallographic symmetry in Patterson functions

2021 ◽  
Vol 77 (2) ◽  
pp. 131-141
Author(s):  
Iracema Caballero ◽  
Massimo D. Sammito ◽  
Pavel V. Afonine ◽  
Isabel Usón ◽  
Randy J. Read ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Protein Structures ◽  
Data Bank ◽  
Molecular Replacement ◽  
Asymmetric Unit ◽  
Intensity Factors ◽  
Patterson Function ◽  
Likelihood Functions ◽  
Structure Solution ◽  
Ranked List

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution.

scholarly journals Predicting the Shapes of Protein Complexes Through Collision Cross Section Measurements and Database Searches

2020 ◽  
Author(s):  
Michael Landreh ◽  
Cagla Sahin ◽  
Joseph Gault ◽  
Samira Sadeghi ◽  
Chester Lee Drum ◽  
...  
Keyword(s):  
Structural Biology ◽  
Cross Sections ◽  
Ion Mobility ◽  
Collision Cross Section ◽  
Protein Complexes ◽  
Protein Structures ◽  
Data Bank ◽  
Integral Membrane Protein ◽  
Specific Reference ◽  
Ion Mobility Mass Spectrometry

In structural biology, collision cross sections (CCS) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures, we find that we can distinguish oblate- and prolate-shaped protein complexes. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and an eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.

scholarly journals Visualising the Experimentally Uncharted Territories of Membrane Protein Structures inside Protein Data Bank

2020 ◽  
Author(s):  
Wei Li
Keyword(s):  
Experimental Data ◽  
Statistical Analysis ◽  
Membrane Protein ◽  
Drug Targets ◽  
Protein Structures ◽  
Hybrid Approach ◽  
Data Bank ◽  
Data Driven ◽  
Structural Determination ◽  
A Chain

As of today, there is not any direct report yet of the degree to which missing residues exist for experimentally determined membrane protein (MP) structures, which constitute more than half of current drug targets. With a chain- and position-specific visualisation and a statistical analysis of all MP structures inside PDB (as of September 25, 2019), this article argues that the experimentally uncharted territories (EUTs, i.e., consisting of missing residues) within PDB are pluggable and should be plugged with an experimental data-driven hybrid approach, and calls for continued development of MP structural determination with less and less EUTs, in light of MPs' crucial role in biological and biomedical research, both fundamental and pharmaceutical.

scholarly journals Overcoming bottlenecks in the membrane protein structural biology pipeline

2016 ◽  
Vol 44 (3) ◽  
pp. 838-844 ◽  
Author(s):  
David Hardy ◽  
Roslyn M. Bill ◽  
Anass Jawhari ◽  
Alice J. Rothnie
Keyword(s):  
Membrane Proteins ◽  
Membrane Protein ◽  
Protein Stability ◽  
Structural Biology ◽  
Protein Structures ◽  
Data Bank ◽  
Neopentyl Glycol ◽  
X Ray Crystallography ◽  
Technological Advances ◽  
Near Future

Membrane proteins account for a third of the eukaryotic proteome, but are greatly under-represented in the Protein Data Bank. Unfortunately, recent technological advances in X-ray crystallography and EM cannot account for the poor solubility and stability of membrane protein samples. A limitation of conventional detergent-based methods is that detergent molecules destabilize membrane proteins, leading to their aggregation. The use of orthologues, mutants and fusion tags has helped improve protein stability, but at the expense of not working with the sequence of interest. Novel detergents such as glucose neopentyl glycol (GNG), maltose neopentyl glycol (MNG) and calixarene-based detergents can improve protein stability without compromising their solubilizing properties. Styrene maleic acid lipid particles (SMALPs) focus on retaining the native lipid bilayer of a membrane protein during purification and biophysical analysis. Overcoming bottlenecks in the membrane protein structural biology pipeline, primarily by maintaining protein stability, will facilitate the elucidation of many more membrane protein structures in the near future.

scholarly journals Current strategies for protein production and purification enabling membrane protein structural biology

2016 ◽  
Vol 94 (6) ◽  
pp. 507-527 ◽  
Author(s):  
Aditya Pandey ◽  
Kyungsoo Shin ◽  
Robin E. Patterson ◽  
Xiang-Qin Liu ◽  
Jan K. Rainey
Keyword(s):  
Membrane Proteins ◽  
Membrane Protein ◽  
Structural Biology ◽  
Protein Production ◽  
Protein Structures ◽  
Data Bank ◽  
In Vitro Translation ◽  
Preparation Methods ◽  
Natural Hosts

Membrane proteins are still heavily under-represented in the protein data bank (PDB), owing to multiple bottlenecks. The typical low abundance of membrane proteins in their natural hosts makes it necessary to overexpress these proteins either in heterologous systems or through in vitro translation/cell-free expression. Heterologous expression of proteins, in turn, leads to multiple obstacles, owing to the unpredictability of compatibility of the target protein for expression in a given host. The highly hydrophobic and (or) amphipathic nature of membrane proteins also leads to challenges in producing a homogeneous, stable, and pure sample for structural studies. Circumventing these hurdles has become possible through the introduction of novel protein production protocols; efficient protein isolation and sample preparation methods; and, improvement in hardware and software for structural characterization. Combined, these advances have made the past 10–15 years very exciting and eventful for the field of membrane protein structural biology, with an exponential growth in the number of solved membrane protein structures. In this review, we focus on both the advances and diversity of protein production and purification methods that have allowed this growth in structural knowledge of membrane proteins through X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM).

scholarly journals Predicting the Shapes of Protein Complexes Through Collision Cross Section Measurements and Database Searches

2020 ◽  
Author(s):  
Michael Landreh ◽  
Cagla Sahin ◽  
Joseph Gault ◽  
Samira Sadeghi ◽  
Chester Lee Drum ◽  
...  
Keyword(s):  
Structural Biology ◽  
Cross Sections ◽  
Ion Mobility ◽  
Collision Cross Section ◽  
Protein Complexes ◽  
Protein Structures ◽  
Data Bank ◽  
Integral Membrane Protein ◽  
Specific Reference ◽  
Ion Mobility Mass Spectrometry

In structural biology, collision cross sections (CCS) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures, we find that we can distinguish oblate- and prolate-shaped protein complexes. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and an eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.

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