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Article ; Online: Exploring the effects of missense mutations on protein thermodynamics through structure-based approaches: findings from the CAGI6 challenges.

Rodrigues, Carlos H M / Portelli, Stephanie / Ascher, David B

2024

Abstract: Missense mutations are known contributors to diverse genetic disorders, due to their subtle, single amino acid changes imparted on the resultant protein. Because of this, understanding the impact of these mutations on protein stability and function is ... ...

Abstract	Missense mutations are known contributors to diverse genetic disorders, due to their subtle, single amino acid changes imparted on the resultant protein. Because of this, understanding the impact of these mutations on protein stability and function is crucial for unravelling disease mechanisms and developing targeted therapies. The Critical Assessment of Genome Interpretation (CAGI) provides a valuable platform for benchmarking state-of-the-art computational methods in predicting the impact of disease-related mutations on protein thermodynamics. Here we report the performance of our comprehensive platform of structure-based computational approaches to evaluate mutations impacting protein structure and function on 3 challenges from CAGI6: Calmodulin, MAPK1 and MAPK3. Our stability predictors have achieved correlations of up to 0.74 and AUCs of 1 when predicting changes in ΔΔG for MAPK1 and MAPK3, respectively, and AUC of up to 0.75 in the Calmodulin challenge. Overall, our study highlights the importance of structure-based approaches in understanding the effects of missense mutations on protein thermodynamics. The results obtained from the CAGI6 challenges contribute to the ongoing efforts to enhance our understanding of disease mechanisms and facilitate the development of personalised medicine approaches.
Language	English
Publishing date	2024-01-16
Publishing country	Germany
Document type	Journal Article
ZDB-ID	223009-4
ISSN	1432-1203 ; 0340-6717
ISSN (online)	1432-1203
ISSN	0340-6717
DOI	10.1007/s00439-023-02623-4
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Article ; Online: AI-Driven Enhancements in Drug Screening and Optimization.

Serghini, Adam / Portelli, Stephanie / Ascher, David B

Methods in molecular biology (Clifton, N.J.)

2023 Volume 2714, Page(s) 269–294

Abstract: The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, ...

Abstract	The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, and efficacy of the end product, streamlining these efforts toward compounds with success potential is pivotal for a more efficient and cost-effective process. The use of artificial intelligence (AI) within the pharmaceutical industry aims at just this, and has applications in preclinical screening for biological activity, optimization of pharmacokinetic properties for improved drug formulation, early toxicity prediction which reduces attrition, and pre-emptively screening for genetic changes in the biological target to improve therapeutic longevity. Here, we present a series of in silico tools that address these applications in small molecule development and describe how they can be embedded within the current pharmaceutical development pipeline.
MeSH term(s)	Drug Evaluation, Preclinical ; Artificial Intelligence ; Drug Development ; Drug Discovery ; Drug Industry
Language	English
Publishing date	2023-09-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-3441-7_15
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Article ; Online: Identifying Innate Resistance Hotspots for SARS-CoV-2 Antivirals Using In Silico Protein Techniques.

Portelli, Stephanie / Heaton, Ruby / Ascher, David B

Genes

2023 Volume 14, Issue 9

Abstract: The development and approval of antivirals against SARS-CoV-2 has further equipped clinicians with treatment strategies against the COVID-19 pandemic, reducing deaths post-infection. Extensive clinical use of antivirals, however, can impart additional ... ...

Abstract	The development and approval of antivirals against SARS-CoV-2 has further equipped clinicians with treatment strategies against the COVID-19 pandemic, reducing deaths post-infection. Extensive clinical use of antivirals, however, can impart additional selective pressure, leading to the emergence of antiviral resistance. While we have previously characterized possible effects of circulating SARS-CoV-2 missense mutations on proteome function and stability, their direct effects on the novel antivirals remains unexplored. To address this, we have computationally calculated the consequences of mutations in the antiviral targets: RNA-dependent RNA polymerase and main protease, on target stability and interactions with their antiviral, nucleic acids, and other proteins. By analyzing circulating variants prior to antiviral approval, this work highlighted the inherent resistance potential of different genome regions. Namely, within the main protease binding site, missense mutations imparted a lower fitness cost, while the opposite was noted for the RNA-dependent RNA polymerase binding site. This suggests that resistance to nirmatrelvir/ritonavir combination treatment is more likely to occur and proliferate than that to molnupiravir. These insights are crucial both clinically in drug stewardship, and preclinically in the identification of less mutable targets for novel therapeutic design.
MeSH term(s)	Humans ; SARS-CoV-2/genetics ; Antiviral Agents/pharmacology ; Antiviral Agents/therapeutic use ; COVID-19/genetics ; Pandemics ; Peptide Hydrolases
Chemical Substances	Antiviral Agents ; Peptide Hydrolases (EC 3.4.-)
Language	English
Publishing date	2023-08-26
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes14091699
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Article ; Online: Characterization on the oncogenic effect of the missense mutations of p53 via machine learning.

Pan, Qisheng / Portelli, Stephanie / Nguyen, Thanh Binh / Ascher, David B

Briefings in bioinformatics

2023 Volume 25, Issue 1

Abstract: Dysfunctions caused by missense mutations in the tumour suppressor p53 have been extensively shown to be a leading driver of many cancers. Unfortunately, it is time-consuming and labour-intensive to experimentally elucidate the effects of all possible ... ...

Abstract	Dysfunctions caused by missense mutations in the tumour suppressor p53 have been extensively shown to be a leading driver of many cancers. Unfortunately, it is time-consuming and labour-intensive to experimentally elucidate the effects of all possible missense variants. Recent works presented a comprehensive dataset and machine learning model to predict the functional outcome of mutations in p53. Despite the well-established dataset and precise predictions, this tool was trained on a complicated model with limited predictions on p53 mutations. In this work, we first used computational biophysical tools to investigate the functional consequences of missense mutations in p53, informing a bias of deleterious mutations with destabilizing effects. Combining these insights with experimental assays, we present two interpretable machine learning models leveraging both experimental assays and in silico biophysical measurements to accurately predict the functional consequences on p53 and validate their robustness on clinical data. Our final model based on nine features obtained comparable predictive performance with the state-of-the-art p53 specific method and outperformed other generalized, widely used predictors. Interpreting our models revealed that information on residue p53 activity, polar atom distances and changes in p53 stability were instrumental in the decisions, consistent with a bias of the properties of deleterious mutations. Our predictions have been computed for all possible missense mutations in p53, offering clinical diagnostic utility, which is crucial for patient monitoring and the development of personalized cancer treatment.
MeSH term(s)	Humans ; Mutation, Missense ; Tumor Suppressor Protein p53/genetics ; Mutation ; Neoplasms/genetics ; Machine Learning
Chemical Substances	Tumor Suppressor Protein p53
Language	English
Publishing date	2023-11-29
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbad428
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Article ; Online: Identifying the molecular drivers of ALS-implicated missense mutations.

Portelli, Stephanie / Albanaz, Amanda / Pires, Douglas Eduardo Valente / Ascher, David Benjamin

Journal of medical genetics

2022 Volume 60, Issue 5, Page(s) 484–490

Abstract: Background: Amyotrophic lateral sclerosis (ALS) is a progressively fatal, neurodegenerative disease associated with both motor and non-motor symptoms, including frontotemporal dementia. Approximately 10% of cases are genetically inherited (familial ALS), ...

Abstract	Background: Amyotrophic lateral sclerosis (ALS) is a progressively fatal, neurodegenerative disease associated with both motor and non-motor symptoms, including frontotemporal dementia. Approximately 10% of cases are genetically inherited (familial ALS), while the majority are sporadic. Mutations across a wide range of genes have been associated; however, the underlying molecular effects of these mutations and their relation to phenotypes remain poorly explored. Methods: We initially curated an extensive list (n Results: Compared with previous ALS-dedicated databases, we have curated the most extensive missense mutation database to date and observed a twofold increase in unique implicated genes, and almost a threefold increase in the number of mutations. Our gene-specific analysis identified distinct molecular drivers across the different proteins, where SOD1 mutations primarily reduced protein stability and dimer formation, and those in FUS and TDP-43 were present within disordered regions, suggesting different mechanisms of aggregate formation. Conclusion: Using our three genes as case studies, we identified distinct insights which can drive further research to better understand ALS. The information curated in our database can serve as a resource for similar gene-specific analyses, further improving the current understanding of disease, crucial for the development of treatment strategies.
MeSH term(s)	Humans ; Amyotrophic Lateral Sclerosis/genetics ; Amyotrophic Lateral Sclerosis/metabolism ; Amyotrophic Lateral Sclerosis/pathology ; Mutation, Missense/genetics ; Superoxide Dismutase-1/genetics ; Neurodegenerative Diseases ; Mutation
Chemical Substances	Superoxide Dismutase-1 (EC 1.15.1.1)
Language	English
Publishing date	2022-09-30
Publishing country	England
Document type	Journal Article
ZDB-ID	220881-7
ISSN	1468-6244 ; 0022-2593
ISSN (online)	1468-6244
ISSN	0022-2593
DOI	10.1136/jmg-2022-108798
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Article ; Online: Using long, sequence-specific dsRNA to knockdown inducible protein expression and virus production via an RNAi-like mechanism.

Au, Sarah K W / Portelli, Iliana V / DeWitte-Orr, Stephanie J

Fish & shellfish immunology

2022 Volume 131, Page(s) 945–957

Abstract: RNA interference (RNAi) is a powerful innate immune mechanism to knock down translation of specific proteins whose machinery is conserved from plants to mammals. The template used to determine which mRNA's translation is inhibited is dsRNA, whose origin ... ...

Abstract	RNA interference (RNAi) is a powerful innate immune mechanism to knock down translation of specific proteins whose machinery is conserved from plants to mammals. The template used to determine which mRNA's translation is inhibited is dsRNA, whose origin can range from viruses (long dsRNA, ∼100-1000s bp) to host (micro(mi)RNA, ∼20mers). While miRNA-mediated RNAi is well described in vertebrates, the ability of long dsRNA to guide RNAi-mediated translation inhibition in vertebrates is controversial. Indeed, as long dsRNA is so effective at inducing type I interferons (IFNs), and IFNs down-regulate RNAi machinery, it is believed that IFN-competent cells are not capable of using long dsRNA for RNAi. In the present study the ability of long, sequence specific dsRNA to knock down both host protein expression and viral replication is investigated in IFN-competent rainbow trout cells. Before exploring RNAi effects, the optimal dsRNA concentration that would funnel into RNAi without triggering the IFN response was determined. After which, the ability of sequence specific long dsRNA to target knockdown via RNAi was evaluated in: (1) uninfected host cells using inducible luciferase gene expression and (2) host cells infected with chum salmon reovirus (CSV), frog virus 3 (FV3) or viral hemorrhagic septicemia virus genotype IVa (VHSV-IVa). Induced expression studies utilized RTG-P1, a luciferase reporter cell line, and dsRNA containing luciferase sequence (dsRNA-Luc) or a mis-matched sequence (dsRNA-GFP), and subsequent luminescence intensity was measured. Anti-CSV studies used dsRNA-CSVseg7 and dsRNA-CSVseg10 to target CSV segment 7 and CSV segment 10 respectively. Inhibition of virus replication was measured by viral titration and RT-qPCR. Taking advantage of the fact that long dsRNA can accommodate more sequences than miRNAs, the antiviral capability of dsRNA molecules containing both CSV segment 7 and segment 10 simultaneously was also measured. Target sequence appears important, as dsRNA-FV3MCP did not knock down FV3 titres, and while dsRNA-VHSV-N knocked down VHSV-IVa, dsRNA-VHSV-G and dsRNA-VHSV-M did not. This is the first study in fish to provide evidence that sequence specific long dsRNA induces potent gene expression silencing and antiviral responses in vitro via an RNAi-like mechanism instead of an IFN-dependent response.
Language	English
Publishing date	2022-11-11
Publishing country	England
Document type	Journal Article
ZDB-ID	1067738-0
ISSN	1095-9947 ; 1050-4648
ISSN (online)	1095-9947
ISSN	1050-4648
DOI	10.1016/j.fsi.2022.10.061
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Article ; Online: toxCSM: comprehensive prediction of small molecule toxicity profiles.

de Sá, Alex G C / Long, Yangyang / Portelli, Stephanie / Pires, Douglas E V / Ascher, David B

Briefings in bioinformatics

2022 Volume 23, Issue 5

Abstract: Drug discovery is a lengthy, costly and high-risk endeavour that is further convoluted by high attrition rates in later development stages. Toxicity has been one of the main causes of failure during clinical trials, increasing drug development time and ... ...

Abstract	Drug discovery is a lengthy, costly and high-risk endeavour that is further convoluted by high attrition rates in later development stages. Toxicity has been one of the main causes of failure during clinical trials, increasing drug development time and costs. To facilitate early identification and optimisation of toxicity profiles, several computational tools emerged aiming at improving success rates by timely pre-screening drug candidates. Despite these efforts, there is an increasing demand for platforms capable of assessing both environmental as well as human-based toxicity properties at large scale. Here, we present toxCSM, a comprehensive computational platform for the study and optimisation of toxicity profiles of small molecules. toxCSM leverages on the well-established concepts of graph-based signatures, molecular descriptors and similarity scores to develop 36 models for predicting a range of toxicity properties, which can assist in developing safer drugs and agrochemicals. toxCSM achieved an Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of up to 0.99 and Pearson's correlation coefficients of up to 0.94 on 10-fold cross-validation, with comparable performance on blind test sets, outperforming all alternative methods. toxCSM is freely available as a user-friendly web server and API at http://biosig.lab.uq.edu.au/toxcsm.
MeSH term(s)	Agrochemicals ; Drug Discovery/methods ; Humans ; ROC Curve
Chemical Substances	Agrochemicals
Language	English
Publishing date	2022-08-20
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbac337
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Article ; Online: Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease.

Serghini, Adam / Portelli, Stephanie / Troadec, Guillaume / Song, Catherine / Pan, Qisheng / Pires, Douglas E V / Ascher, David B

Human molecular genetics

2023 Volume 33, Issue 3, Page(s) 224–232

Abstract: Background: Mutations within the Von Hippel-Lindau (VHL) tumor suppressor gene are known to cause VHL disease, which is characterized by the formation of cysts and tumors in multiple organs of the body, particularly clear cell renal cell carcinoma ( ... ...

Abstract	Background: Mutations within the Von Hippel-Lindau (VHL) tumor suppressor gene are known to cause VHL disease, which is characterized by the formation of cysts and tumors in multiple organs of the body, particularly clear cell renal cell carcinoma (ccRCC). A major challenge in clinical practice is determining tumor risk from a given mutation in the VHL gene. Previous efforts have been hindered by limited available clinical data and technological constraints. Methods: To overcome this, we initially manually curated the largest set of clinically validated VHL mutations to date, enabling a robust assessment of existing predictive tools on an independent test set. Additionally, we comprehensively characterized the effects of mutations within VHL using in silico biophysical tools describing changes in protein stability, dynamics and affinity to binding partners to provide insights into the structure-phenotype relationship. These descriptive properties were used as molecular features for the construction of a machine learning model, designed to predict the risk of ccRCC development as a result of a VHL missense mutation. Results: Analysis of our model showed an accuracy of 0.81 in the identification of ccRCC-causing missense mutations, and a Matthew's Correlation Coefficient of 0.44 on a non-redundant blind test, a significant improvement in comparison to the previous available approaches. Conclusion: This work highlights the power of using protein 3D structure to fully explore the range of molecular and functional consequences of genomic variants. We believe this optimized model will better enable its clinical implementation and assist guiding patient risk stratification and management.
MeSH term(s)	Humans ; Carcinoma, Renal Cell/genetics ; Carcinoma, Renal Cell/metabolism ; Kidney Neoplasms/metabolism ; Mutation, Missense/genetics ; von Hippel-Lindau Disease/genetics ; von Hippel-Lindau Disease/pathology ; Von Hippel-Lindau Tumor Suppressor Protein/genetics ; Von Hippel-Lindau Tumor Suppressor Protein/chemistry ; Von Hippel-Lindau Tumor Suppressor Protein/metabolism ; Machine Learning
Chemical Substances	Von Hippel-Lindau Tumor Suppressor Protein (EC 2.3.2.27)
Language	English
Publishing date	2023-10-26
Publishing country	England
Document type	Journal Article
ZDB-ID	1108742-0
ISSN	1460-2083 ; 0964-6906
ISSN (online)	1460-2083
ISSN	0964-6906
DOI	10.1093/hmg/ddad181
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Article ; Online: Cues to care: Chronic disease diagnosis in young adult trauma patients.

Adams, Ursula / Portelli Tremont, Jaclyn / Yohann, Avital / Aldridge, Joshua / Riggins, Stephanie / Brownstein, Michelle / Charles, Anthony / Udekwu, Pascal Osita

The journal of trauma and acute care surgery

2023 Volume 96, Issue 1, Page(s) 70–75

Abstract: Background: Prevention of chronic disease necessitates early diagnosis and intervention. In young adults, a trauma admission may be an early contact with the health care system, representing an opportunity for screening and intervention. This study ... ...

Abstract	Background: Prevention of chronic disease necessitates early diagnosis and intervention. In young adults, a trauma admission may be an early contact with the health care system, representing an opportunity for screening and intervention. This study estimates the prevalence of previously diagnosed disease and undiagnosed disease (UD)-diabetes mellitus, hypertension, obesity, and alcohol and substance use-in a young adult trauma population. We determine factors associated with UD and examine outcomes in patients with UD. Methods: This is a multicenter, retrospective cohort study of adult trauma patients 18 to 40 years old admitted to participating Level I trauma centers between January 2018 and December 2020. Three Level 1 trauma centers in a single state participated in the study. Trauma registry data and chart review were examined for evidence of previously diagnosed disease or UD. Patient demographics and outcomes were compared between cohorts. Multivariable regression modeling was performed to assess risk factors associated with any UD. Results: The analysis included 6,307 admitted patients. Of these, 4,843 (76.8%) had evidence of at least 1 UD, most commonly hypertension and obesity. In multivariable models, factors most associated with risk of UD were age (adjusted odds ratio [aOR], 0.98; 95% confidence interval [CI], 0.98-0.99), male sex (aOR, 1.43; 95% CI, 1.25-1.63), and uninsured status (aOR, 1.57; 95% CI, 1.38-1.80). Only 24.5% of patients had evidence of a primary care provider (PCP), which was not associated with decreased odds of UD. Clinical outcomes were significantly associated with the presence of chronic disease. Of those with UD and no PCP, only 11.2% were given a referral at discharge. Conclusion: In the young adult trauma population, the UD burden is high, especially among patients with traditional sociodemographic risk factors and even in patients with a PCP. Because of short hospital stays in this population, the full impact of UD may not be visible during a trauma admission. Early chronic disease diagnosis in this population will require rigorous, standard screening measures initiated within trauma centers. Level of evidence: Prognostic and Epidemiological; Level IV.
MeSH term(s)	Humans ; Male ; Young Adult ; Adolescent ; Adult ; Retrospective Studies ; Cues ; Diabetes Mellitus/epidemiology ; Obesity ; Hypertension/epidemiology ; Chronic Disease
Language	English
Publishing date	2023-10-03
Publishing country	United States
Document type	Multicenter Study ; Journal Article
ZDB-ID	2651070-4
ISSN	2163-0763 ; 2163-0755
ISSN (online)	2163-0763
ISSN	2163-0755
DOI	10.1097/TA.0000000000004149
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Article ; Online: Delving deeper into disparity: The impact of health literacy on the surgical care of breast cancer patients.

Portelli Tremont, Jaclyn N / Downs-Canner, Stephanie / Maduekwe, Ugwuji

American journal of surgery

2020 Volume 220, Issue 4, Page(s) 806–810

Abstract: Background: Breast surgical oncology is a unique field that involves complex cancer management and longstanding patient interactions with the healthcare system, making it potentially challenging for patients with low health literacy. The purpose of this ...

Abstract	Background: Breast surgical oncology is a unique field that involves complex cancer management and longstanding patient interactions with the healthcare system, making it potentially challenging for patients with low health literacy. The purpose of this review is to summarize the current knowledge regarding health literacy in breast cancer and identify future directions for research and potential intervention in breast surgical oncology. Data sources: A search of relevant literature querying PubMed and Science Direct was performed and included the following keywords: health literacy, breast cancer, breast surgical oncology, surgery, outcomes, prevention, screening, healthcare utilization, chronic disease. Conclusions: Limited health literacy may detrimentally affect understanding and outcomes in breast surgical oncology. Identifying ways providers can improve patient understanding and utilization of health information is important, and surgeons may have a pivotal role. Further studies addressing health literacy in breast surgical oncology is needed in order to better optimize care of patients.
MeSH term(s)	Breast Neoplasms/surgery ; Female ; Health Literacy ; Healthcare Disparities ; Humans
Language	English
Publishing date	2020-05-12
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2953-1
ISSN	1879-1883 ; 0002-9610
ISSN (online)	1879-1883
ISSN	0002-9610
DOI	10.1016/j.amjsurg.2020.05.009
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