Integrative data fusion for comprehensive assessment of a novel CHEK2 variant using combined genomics, imaging, and functional-structural assessments via protein informatics

Management of individuals with germline pathogenic/likely pathogenic variants in CHEK2: A clinical practice resource of the American College of Medical Genetics and Genomics (ACMG)

PURPOSE

Although the role of CHEK2 germline pathogenic variants in cancer predisposition is well known, resources for managing CHEK2 heterozygotes in clinical practice are limited.

METHODS

An international workgroup developed guidance on clinical management of CHEK2 heterozygotes informed by peer-reviewed publications from PubMed.

RESULTS

Although CHEK2 is considered a moderate penetrance gene, cancer risks may be considered as a continuous variable, which are influenced by family history and other modifiers. Consequently, early cancer detection and prevention for CHEK2 heterozygotes should be guided by personalized risk estimates. Such estimates may result in both downgrading lifetime breast cancer risks to those similar to the general population or upgrading lifetime risk to a level at which CHEK2 heterozygotes are offered high-risk breast surveillance according to country-specific guidelines. Risk-reducing mastectomy should be guided by personalized risk estimates and shared decision making. Colorectal and prostate cancer surveillance should be considered based on assessment of family history. For CHEK2 heterozygotes who develop cancer, no specific targeted medical treatment is recommended at this time.

CONCLUSION

Systematic prospective data collection is needed to establish the spectrum of CHEK2-associated cancer risks and to determine yet-unanswered questions, such as the outcomes of surveillance, response to cancer treatment, and survival after cancer diagnosis.

Statistical Mechanics Metrics in Pairing and Parsing In Silico and Phenotypic Data of a Novel Genetic NFκB1 (c.T638A) Variant

(1) Background: Mutations in NFκB1, a transcriptional regulator of immunomodulating proteins, are a known cause of inborn errors of immunity. Our proband is a 22-year-old male with a diagnosis of common variable immunodeficiency (CVID), cytopenias with massive splenomegaly, and nodular regenerative hyperplasia of the liver. Genetic studies identified a novel, single-point mutation variant in NFκB1, c. T638A p. V213E. (2) Methods: Next-generation panel sequencing of the patient uncovered a novel single-point mutation in the NFκB1 gene that was modeled using the I-TASSER homology-modeling software, and molecular dynamics were assessed using the YASARA2 software (version 20.14.24). (3) Results: This variant replaces valine with glutamic acid at position 213 in the NFκB1 sequence. Molecular modeling and molecular dynamic studies showed altered dynamics in and around the rel homology domain, ankyrin regions, and death domain of the protein. We postulate that these changes alter overall protein function. (4) Conclusions: This case suggests the pathogenicity of a novel variant using protein-modeling techniques and molecular dynamic simulations.

Protein structure-based in-silico approaches to drug discovery: Guide to COVID-19 therapeutics

With more than 5 million fatalities and close to 300 million reported cases, COVID-19 is the first documented pandemic due to a coronavirus that continues to be a major health challenge. Despite being rapid, uncontrollable, and highly infectious in its spread, it also created incentives for technology development and redefined public health needs and research agendas to fast-track innovations to be translated. Breakthroughs in computational biology peaked during the pandemic with renewed attention to making all cutting-edge technology deliver agents to combat the disease. The demand to develop effective treatments yielded surprising collaborations from previously segregated fields of science and technology. The long-standing pharmaceutical industry's aversion to repurposing existing drugs due to a lack of exponential financial gain was overrun by the health crisis and pressures created by front-line researchers and providers. Effective vaccine development even at an unprecedented pace took more than a year to develop and commence trials. Now the emergence of variants and waning protections during the booster shots is resulting in breakthrough infections that continue to strain health care systems. As of now, every protein of SARS-CoV-2 has been structurally characterized and related host pathways have been extensively mapped out. The research community has addressed the druggability of a multitude of possible targets. This has been made possible due to existing technology for virtual computer-assisted drug development as well as new tools and technologies such as artificial intelligence to deliver new leads. Here in this article, we are discussing advances in the drug discovery field related to target-based drug discovery and exploring the implications of known target-specific agents on COVID-19 therapeutic management. The current scenario calls for more personalized medicine efforts and stratifying patient populations early on for their need for different combinations of prognosis-specific therapeutics. We intend to highlight target hotspots and their potential agents, with the ultimate goal of using rational design of new therapeutics to not only end this pandemic but also uncover a generalizable platform for use in future pandemics.

Phenotypic screening models for rapid diagnosis of genetic variants and discovery of personalized therapeutics

Precision medicine strives for highly individualized treatments for disease under the notion that each individual's unique genetic makeup and environmental exposures imprints upon them not only a disposition to illness, but also an optimal therapeutic approach. In the realm of rare disorders, genetic predisposition is often the predominant mechanism driving disease presentation. For such, mostly, monogenic disorders, a causal gene to phenotype association is likely. As a result, it becomes important to query the patient's genome for the presence of pathogenic variations that are likely to cause the disease. Determining whether a variant is pathogenic or not is critical to these analyses and can be challenging, as many disease-causing variants are novel and, ergo, have no available functional data to help categorize them. This problem is exacerbated by the need for rapid evaluation of pathogenicity, since many genetic diseases present in young children who will experience increased morbidity and mortality without rapid diagnosis and therapeutics. Here, we discuss the utility of animal models, with a focus mainly on C. elegans, as a contrast to tissue culture and in silico approaches, with emphasis on how these systems are used in determining pathogenicity of variants with uncertain significance and then used to screen for novel therapeutics.

Molecular Modeling and Phenotypic Description of a Patient with a Novel Exonic Deletion of GALNS with Resultant Morquio Syndrome with Two Successful Pregnancies

In this report, we describe phenotypic features of a patient with mucopolysaccharidosis type IVA (Morquio syndrome) harboring a novel exon 1 deletion in GALNS with enzymatic confirmation consistent with Morquio syndrome. To our knowledge, this is the first reported case of this variant. Additionally, we protein modelled wild-type GALNS and the pathogenic variant with an exon 1 deletion for comparative analysis using statistical mechanics methods described herein. We demonstrate that, even when the protein is translated, the mutation would affect protein stability and function via homodimer interaction modifications. Lastly, given the patient's 2 successful pregnancies, data about the management of pregnancies in mucopolysaccharidoses are reviewed, and we discuss the management of pregnancy in patients with Morquio syndrome.

Structural Models for the Dynamic Effects of Loss-of-Function Variants in the Human SIM1 Protein Transcriptional Activation Domain

Single-minded homologue 1 (SIM1) is a transcription factor with numerous different physiological and developmental functions. SIM1 is a member of the class I basic helix-loop-helix-PER-ARNT-SIM (bHLH-PAS) transcription factor family, that includes several other conserved proteins, including the hypoxia-inducible factors, aryl hydrocarbon receptor, neuronal PAS proteins, and the CLOCK circadian regulator. Recent studies of HIF-a-ARNT and CLOCK-BMAL1 protein complexes have revealed the organization of their bHLH, PASA, and PASB domains and provided insight into how these heterodimeric protein complexes form; however, experimental structures for SIM1 have been lacking. Here, we describe the first full-length atomic structural model for human SIM1 with its binding partner ARNT in a heterodimeric complex and analyze several pathogenic variants utilizing state-of-the-art simulations and algorithms. Using local and global positional deviation metrics, deductions to the structural basis for the individual mutants are addressed in terms of the deleterious structural reorganizations that could alter protein function. We propose new experiments to probe these hypotheses and examine an interesting SIM1 dynamic behavior. The conformational dynamics demonstrates conformational changes on local and global regions that represent a mechanism for dysfunction in variants presented. In addition, we used our ab initio hybrid model for further prediction of variant hotspots that can be engineered to test for counter variant (restoration of wild-type function) or basic research probe.

Structural And Computational Perspectives of Selectively Targeting Mutant Proteins

Diseases are often caused by mutant proteins. Many drugs have limited effectiveness and/or toxic side effects because of a failure to selectively target the disease-causing mutant variant, rather than the functional wild type protein. Otherwise, the drugs may even target different proteins with similar structural features. Designing drugs that successfully target mutant proteins selectively represents a major challenge. Decades of cancer research have led to an abundance of potential therapeutic targets, often touted to be "master regulators". For many of these proteins, there are no FDA-approved drugs available; for others, off-target effects result in dose-limiting toxicity. Cancer-related proteins are an excellent medium to carry the story of mutant-specific targeting, as the disease is both initiated and sustained by mutant proteins; furthermore, current chemotherapies generally fail at adequate selective distinction. This review discusses some of the challenges associated with selective targeting from a structural biology perspective, as well as some of the developments in algorithm approach and computational workflow that can be applied to address those issues. One of the most widely researched proteins in cancer biology is p53, a tumor suppressor. Here, p53 is discussed as a specific example of a challenging target, with contemporary drugs and methodologies used as examples of burgeoning successes. The oncogene KRAS, which has been described as "undruggable", is another extensively investigated protein in cancer biology. This review also examines KRAS to exemplify progress made towards selective targeting of diseasecausing mutant proteins. Finally, possible future directions relevant to the topic are discussed.

Computational analysis of high-risk SNPs in human CHK2 gene responsible for hereditary breast cancer: A functional and structural impact

Nowadays CHK2 mutation is studied frequently in hereditary breast and ovarian cancer patients in addition to BRCA1/BRCA2. CHK2 is a tumor suppressor gene that encodes a serine/threonine kinase, also involved in pathways such as DNA repair, cell cycle regulation and apoptosis in response to DNA damage. CHK2 is a well-studied moderate penetrance gene that correlates with third high risk susceptibility gene with an increased risk for breast cancer. Hence before planning large population study, it is better to scrutinize putative functional SNPs of CHK2 using different computational tools. In this study, we have used various computational approaches to identify nsSNPs which are deleterious to the structure and/or function of CHK2 protein that might be causing this disease. Computational analysis was performed by different in silico tools including SIFT, Align GVGD, SNAP-2, PROVEAN, Poly-Phen-2, PANTHER, PhD-SNP, MUpro, iPTREE-STAB, Consurf, InterPro, NCBI Conserved Domain Search tool, ModPred, SPARKS-X, RAMPAGE, Verify-3D, FT Site, COACH and PyMol. Out of 78 nsSNP of human CHK2 gene, seven nsSNPs were predicted functionally most significant SNPs. Among these seven nsSNP, p.Arg160Gly, p.Gly210Arg and p.Ser415Phe are highly conserved residues with conservation score of 9 and three nsSNP were predicted to be involved in post translational modification. The p.Arg160Gly and p.Gly210Arg may interfere in phosphopeptide binding site on FHA conserved domain. The p.Ser415Phe may interfere in formation of activation loop of protein-kinase domain and might interfere in interactions of CHK2 with ligand. The study concludes that mutation of serine to phenylalanine at position 415 is a major mutation in native CHK2 protein which might contribute to its malfunction, ultimately causing disease. This is the first comprehensive study, where CHK2 gene variants are analyzed using in silico tools hence it will be of great help while considering large scale studies and also in developing precision medicines related to these polymorphisms in the era of personalized medicine.

Genomic Observations of a Rare/Pathogenic SMAD3 Variant in Loeys⁻Dietz Syndrome 3 Confirmed by Protein Informatics and Structural Investigations

Background and objectives: Loeys–Dietz syndrome 3, also known as aneurysms-–osteoarthritis syndrome, is an autosomal dominant genetic connective tissue disease caused by pathogenic variants in SMAD3, a transcription factor involved in TGF-β signaling. This disorder is characterized by early-onset osteoarthritis and arterial aneurysms. Common features include scoliosis, uvula abnormalities, striae, and velvety skin. Materials and Methods: The pathogenicity of a variant of uncertain significance in the SMAD3 gene was evaluated (variant c.220C > T) through personalized protein informatics and molecular studies. Results: The case of a 44-year-old male, who was originally presumed to have Marfan syndrome, is presented. An expanded gene panel determined the probable cause to be a variant in SMAD3, c.220C > T (p.R74W). His case was complicated by a history of stroke, but his phenotype was otherwise characteristic for Loeys–Dietz syndrome 3. Conclusion: This case emphasizes the importance of comprehensive genetic testing to evaluate patients for connective tissue disorders, as well as the potential benefit of utilizing a protein informatics platform for the assessment of variant pathogenicity.