high-throughput-screening-to-obtain-crystal-hits-for-protein

High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography

X-ray crystallography is the most commonly employed technique to discern macromolecular structures, but the crucial step of crystallizing a protein into ...

Hauptman-Woodward Medical Research Institute

Nearly 90% of structural models in the Protein Data Bank (PDB), the central resource worldwide for three-dimensional structural information, are currently derived from macromolecular crystallography (MX). A major bottleneck in determining MX structures is finding conditions in which a biomolecule will crystallize. Here, we present a searchable database of the chemicals associated with successful crystallization experiments from the PDB. We use these data to examine the relationship between protein secondary structure and average molecular weight of polyethylene glycol and to investigate patterns in crystallization conditions. Our analyses reveal striking patterns of both redundancy of chemical compositions in crystallization experiments and extreme sparsity of specific chemical combinations, underscoring the challenges faced in generating predictive models for  optimal crystallization experiments.

A Searchable Database of Crystallization Cocktails in the PDB: Analyzing the Chemical Condition Space.

Ewing sarcoma is an aggressive pediatric tumor of the bone and soft tissue. The current standard of care is radiation and chemotherapy, and patients generally lack targeted therapies. One of the defining molecular features of this tumor type is the presence of significantly elevated levels of replication stress as compared with both normal cells and many other types of cancers, but the source of this stress is poorly understood. Tumors that harbor elevated levels of replication stress rely on the replication stress and DNA damage response pathways to retain viability. Understanding the source of the replication stress in Ewing sarcoma may reveal novel therapeutic targets. Ewing sarcomagenesis is complex, and in this review, we discuss the current state of our knowledge regarding elevated replication stress and the DNA damage response in Ewing sarcoma, one contributor to the disease process. We will also describe how these pathways are being successfully targeted therapeutically in other tumor types, and discuss possible novel, evidence-based therapeutic interventions in Ewing sarcoma. We hope that this consolidation will spark investigations that uncover new therapeutic targets and lead to the development of better treatment options for patients with Ewing sarcoma. IMPLICATIONS: This review uncovers new therapeutic targets in Ewing sarcoma and highlights replication stress as an exploitable vulnerability across multiple cancers.

Exploiting Replication Stress as a Novel Therapeutic Intervention.

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 crystallo-graphy. 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.

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

Iron, the most abundant metal in human brain, is an essential microelement that regulates numerous cellular mechanisms. Some key physiological roles of iron include oxidative phosphorylation and ATP production, embryonic neuronal development, formation of iron-sulfur clusters, and the regulation of enzymes involved in DNA synthesis and repair. Because of its physiological and pathological importance, iron homeostasis must be tightly regulated by balancing its uptake, transport, and storage. Endosomes and lysosomes (endolysosomes) are acidic organelles known to contain readily releasable stores of various cations including iron and other metals. Increased levels of ferrous (Fe) iron can generate reactive oxygen species (ROS) via Fenton chemistry reactions and these increases can damage mitochondria and genomic DNA as well as promote carcinogenesis. Accumulation of iron in the brain has been linked with aging, diet, disease, and cerebral hemorrhage. Further, deregulation of brain iron metabolism has been implicated in carcinogenesis and may be a contributing factor to the increased incidence of brain tumors around the world. Here, we provide insight into mechanisms by which iron accumulation in endolysosomes is altered by pH and lysosome membrane permeabilization. Such events generate excess ROS resulting in mitochondrial DNA damage, fission, and dysfunction, as well as DNA oxidative damage in the nucleus; all of which promote carcinogenesis. A better understanding of the roles that endolysosome iron plays in carcinogenesis may help better inform the development of strategic therapeutic options for cancer treatment and prevention.

Role of endolysosome function in iron metabolism and brain carcinogenesis.

Comparative functional analysis of the dynamic interactions between various  mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. A multi-agent classifier successfully identified functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Conserved dynamics regions of ACE2 involve both the N-terminal helices, as well as a region of more transient dynamics encompassing residues K353, Q325 and a novel motif AAQPFLL 386-92 that appears to coordinate their dynamic interactions with the viral RBD at N501. We also demonstrate that the functional evolution of  zoonotic spillovers involving ACE2 interaction dynamics are likely pre-adapted from two precise and stable binding sites involving the viral bat progenitor strain's interaction with CD26 at SAMLI 291-5 and SS 333-334. Our analyses further indicate that the human endemic strains hCoV-HKU1 and hCoV-OC43 have evolved more stable N-terminal helix interactions through enhancement of an interfacing loop region on the viral RBD, whereas the highly transmissible SARS-CoV-2 variants (B.1.1.7, B.1.351 and P.1) have evolved more stable viral binding via more focused interactions between the viral N501 and ACE2 K353 alone.Communicated by Ramaswamy H. Sarma.

Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent  strains.

Ewing sarcoma is the second most common bone malignancy in children and adolescents. In recent years, a large body of evidence has emerged that suggests Ewing tumors harbor large amounts of replication stress (RS). CDC7, also known as DDK (DBF4-dependent kinase), is a serine/threonine kinase that is involved in a diverse array of cellular functions including the regulation of DNA replication initiation and activation of the RS response. Due to DDK's diverse roles during replication, coupled with the fact that there is an increased level of RS within Ewing tumors, we hypothesized that Ewing sarcoma cells would be particularly vulnerable to DDK inhibition. Here, we report that DDK inhibition resulted a significant reduction in cell viability and the induction of apoptosis, specifically in Ewing sarcoma cells. Treatment with DDK inhibitors dramatically reduced the rate of replication, prolonged S-phase, and led to a pronounced increase in phospho-CDC2 (Y15), indicating delay of mitotic entry. The induction of cell death corresponded to mitotic exit and G1 entry, suggesting improper mitotic progression. In accordance with this, we find that DDK inhibition caused premature mitotic entry resulting in mitotic abnormalities such as anaphase bridges, lagging chromosomes, and cells with >2 poles in Ewing sarcoma cells. This abnormal progression through mitosis resulted in mitotic catastrophe as evidenced by the formation of micronuclei and induction of DNA damage. Together, these findings suggest that DDK activity is required for the faithful and timely completion of DNA replication in Ewing cells and that DDK inhibition may present a viable therapeutic strategy for the treatment of Ewing sarcoma.

CDC7 kinase (DDK) inhibition disrupts DNA replication leading to mitotic catastrophe in Ewing sarcoma.

This paper describes an ensemble cluster analysis of bivariate profiles of HIV biomarkers, viral load and CD4 cell counts, which jointly measure disease progression. Data are from a prevalent cohort of HIV positive participants in a clinical trial of vitamin supplementation in Botswana. These individuals were HIV positive upon enrollment, but with unknown times of infection. To categorize groups of participants based on their patterns of progression of HIV infection using both biomarkers, we combine univariate shape-based cluster results for multiple biomarkers through the use of ensemble clustering methods. We first describe univariate clustering for each of the individual biomarker profiles, and make use of shape-respecting distances for clustering the longitudinal profile data. In our data, profiles are subject to either missing or irregular measurements as well as unobserved initiation times of the process of interest. Shape-respecting distances that can handle such data issues, preserve time-ordering, and identify similar profile shapes are useful in identifying patterns of disease progression from longitudinal biomarker data. However, their performance with regard to clustering differs by severity of the data issues mentioned above. We provide an empirical investigation of shape-respecting distances (Fréchet and dynamic time warping (DTW)) on benchmark shape data, and use DTW in cluster analysis of biomarker profile observations. These reveal a primary group of 'typical progressors,' as well as a smaller group that shows relatively rapid progression. We then refine the analysis using ensemble clustering for both markers to obtain a single classification. The information from joint evaluation of the two biomarkers combined with ensemble clustering reveals subgroups of patients not identifiable through univariate analyses; noteworthy subgroups are those that appear to represent recently and chronically infected subsets.

Ensemble clustering of longitudinal bivariate HIV biomarker profiles to group patients by patterns of disease progression.

Diffraction-based structural methods contribute a large fraction of the biomolecular structural models available, providing a critical understanding of macromolecular architecture. These methods require crystallization of the target molecule, which remains a primary bottleneck in crystal-based structure determination. The National High-Throughput Crystallization Center at Hauptman-Woodward Medical Research Institute has focused on overcoming obstacles to crystallization through a combination of robotics-enabled high-throughput screening and advanced imaging to increase the success of finding crystallization conditions. This paper will describe the lessons learned from over 20 years of operation of our high-throughput crystallization services. The current experimental pipelines, instrumentation, imaging capabilities and software for image viewing and crystal scoring are detailed. New developments in the field and opportunities for further improvements in biomolecular crystallization are reflected on.

Article	Year
A Searchable Database of Crystallization Cocktails in the PDB: Analyzing the Chemical Condition Space. Patterns (New York, N.Y.)\| PubMed ID: 32776019	2020
Exploiting Replication Stress as a Novel Therapeutic Intervention. Molecular cancer research : MCR\| PubMed ID: 33020173	2021
Structural biology in the time of COVID-19: perspectives on methods and milestones. IUCrJ\| PubMed ID: 33953920	2021
Role of endolysosome function in iron metabolism and brain carcinogenesis. Seminars in cancer biology\| PubMed ID: 34139350	2021
Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent strains. Journal of biomolecular structure & dynamics\| PubMed ID: 34286673	2022
CDC7 kinase (DDK) inhibition disrupts DNA replication leading to mitotic catastrophe in Ewing sarcoma. Cell death discovery\| PubMed ID: 35220396	2022
Ensemble clustering of longitudinal bivariate HIV biomarker profiles to group patients by patterns of disease progression. International journal of data science and analytics\| PubMed ID: 35528805	2022
20 years of crystal hits: progress and promise in ultrahigh-throughput crystallization screening. Acta crystallographica. Section D, Structural biology\| PubMed ID: 36876429	2023

Miranda L. Lynch

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