Computational Enzymology on Sulfur-Containing Enzymes: From Method to Application

Sulfur-containing biomolecules display incredible functional diversity. Indeed, in addition to thiols and thioethers, S-nitrosothiols, 3,4-coordinate, sulfoxides, persulfides and now even polysulfides are commonly observed intermediates. Unfortunately, however, their biological synthesis and roles remain poorly understood. In addition, sulfur-containing species can access a broad range of oxidation states and thus can act as either an electrophile or nucleophile giving rise to an even more diverse set of sulfur-derived functional groups. However, these unique properties can lead to difficulties in characterizing such compounds experimentally and reinforces the need for computational studies to reliably predict their structural and energetic properties. In this dissertation, we have applied a broad range of computational methodologies to important sulfur-containing biomolecules to assess their applicability and to elucidate the chemistry of such species. The first two chapters highlight some of the roles of sulfur and challenges associated with studying sulfur systems. We detail current methods in computational enzymology, discussing examples of their application and outline the next generation of approaches. In Chapter 3, we demonstrate the importance of selecting a proper computational method for application to biorelevant sulfur/selenium-containing molecules. We conduct a detailed benchmark study and find that sulfur-sulfur bonds in particular are sensitive to changes in basis set. The ωB97XD/6-311G(2d,p) level of theory is found to be the most accurate and reliable for obtaining geometries and energetics. We apply the knowledge gained from these benchmark studies in Chapter 4 to study biological persulfide/polysulfide formation pathways. Radical-containing charged intermediates are commonly proposed which can prove challenging for DFT methods to accurately describe. These species were found to be transient due to small contributions towards their stability from high-energy Rydberg states. Extending to an active site model showed that sulfur-sulfur bond formation is favoured with radical intermediates, particularly when electron transfer cofactors such as FAD are involved. Chapter 5 examines the catalytic mechanism of maleamate amidohydrolase (NicF) which converts an amide substrate to a carboxylic acid with assistance of a cysteine nucleophile. The reaction took place in two stages: a stepwise pathway for release of ammonia by concerted attack of a water molecule to form the acid product. Stabilization of the oxyanion hole by a critical threonyl is thought to facilitate the reaction instead of a metal ion. Then, in Chapter 6, several approaches for selecting a suitable structure from molecular dynamics simulations for use in QM/MM calculations were examined. Building upon our mechanistic studies on NicF in Chapter 5, we show that poor structure selection can result in problematic surfaces due to the erroneous energetic contributions from the MM layer. To help alleviate some of the user burden, Chapter 7 builds upon the conclusions of Chapter 6 to investigate the ability of artificial intelligence to guide the structure selection process. The program “Pose Selector” was created which uses agglomerative machine learning to select a set of structures for analysis. Evaluation of this approach was done on the NicF system and revealed that this approach can be used to select a structure, and that different catalytic pathways may be identified. Finally, in Chapter 8, we apply these combined learnings to the enzyme cysteine desulfurase (SufS) and examine how the active site prepares for sulfur transfer to an active site cysteinyl to produce an enzyme-bound persulfide. Protonation states of the key active site residues were clarified with dynamic pKa calculations on these residues. Throughout this dissertation we developed new protocols and demonstrated their application to sulfur-containing biomolecular systems. These insights can be extended beyond the realm of computational enzymology and may have impact in other fields such as the design of sulfa-drugs and calculating their properties using these approaches

Computational Enzymology on Sulfur-Containing Enzymes: From Method to Application

Sulfur-containing biomolecules display incredible functional diversity. Indeed, in addition to thiols and thioethers, S-nitrosothiols, 3,4-coordinate, sulfoxides, persulfides and now even polysulfides are commonly observed intermediates. Unfortunately, however, their biological synthesis and roles remain poorly understood. In addition, sulfur-containing species can access a broad range of oxidation states and thus can act as either an electrophile or nucleophile giving rise to an even more diverse set of sulfur-derived functional groups. However, these unique properties can lead to difficulties in characterizing such compounds experimentally and reinforces the need for computational studies to reliably predict their structural and energetic properties. In this dissertation, we have applied a broad range of computational methodologies to important sulfur-containing biomolecules to assess their applicability and to elucidate the chemistry of such species. The first two chapters highlight some of the roles of sulfur and challenges associated with studying sulfur systems. We detail current methods in computational enzymology, discussing examples of their application and outline the next generation of approaches. In Chapter 3, we demonstrate the importance of selecting a proper computational method for application to biorelevant sulfur/selenium-containing molecules. We conduct a detailed benchmark study and find that sulfur-sulfur bonds in particular are sensitive to changes in basis set. The ωB97XD/6-311G(2d,p) level of theory is found to be the most accurate and reliable for obtaining geometries and energetics. We apply the knowledge gained from these benchmark studies in Chapter 4 to study biological persulfide/polysulfide formation pathways. Radical-containing charged intermediates are commonly proposed which can prove challenging for DFT methods to accurately describe. These species were found to be transient due to small contributions towards their stability from high-energy Rydberg states. Extending to an active site model showed that sulfur-sulfur bond formation is favoured with radical intermediates, particularly when electron transfer cofactors such as FAD are involved. Chapter 5 examines the catalytic mechanism of maleamate amidohydrolase (NicF) which converts an amide substrate to a carboxylic acid with assistance of a cysteine nucleophile. The reaction took place in two stages: a stepwise pathway for release of ammonia by concerted attack of a water molecule to form the acid product. Stabilization of the oxyanion hole by a critical threonyl is thought to facilitate the reaction instead of a metal ion. Then, in Chapter 6, several approaches for selecting a suitable structure from molecular dynamics simulations for use in QM/MM calculations were examined. Building upon our mechanistic studies on NicF in Chapter 5, we show that poor structure selection can result in problematic surfaces due to the erroneous energetic contributions from the MM layer. To help alleviate some of the user burden, Chapter 7 builds upon the conclusions of Chapter 6 to investigate the ability of artificial intelligence to guide the structure selection process. The program “Pose Selector” was created which uses agglomerative machine learning to select a set of structures for analysis. Evaluation of this approach was done on the NicF system and revealed that this approach can be used to select a structure, and that different catalytic pathways may be identified. Finally, in Chapter 8, we apply these combined learnings to the enzyme cysteine desulfurase (SufS) and examine how the active site prepares for sulfur transfer to an active site cysteinyl to produce an enzyme-bound persulfide. Protonation states of the key active site residues were clarified with dynamic pKa calculations on these residues. Throughout this dissertation we developed new protocols and demonstrated their application to sulfur-containing biomolecular systems. These insights can be extended beyond the realm of computational enzymology and may have impact in other fields such as the design of sulfa-drugs and calculating their properties using these approaches

An Assessment of Computational Methods for Calculating Accurate Structures and Energies of Bio-Relevant Polysulfur/Selenium-Containing Compounds

The heavier chalcogens sulfur and selenium are important in organic and inorganic chemistry, and the role of such chalcogens in biological systems has recently gained more attention. Sulfur and, to a lesser extent selenium, are involved in diverse reactions from redox signaling to antioxidant activity and are considered essential nutrients. We investigated the ability of the DFT functionals (B3LYP, B3PW91, ωB97XD, M06-2X, and M08-HX) relative to electron correlation methods MP2 and QCISD to produce reliable and accurate structures as well as thermochemical data for sulfur/selenium-containing systems. Bond lengths, proton affinities (PA), gas phase basicities (GPB), chalcogen–chalcogen bond dissociation enthalpies (BDE), and the hydrogen affinities (HA) of thiyl/selenyl radicals were evaluated for a range of small polysulfur/selenium compounds and cysteine per/polysulfide. The S–S bond length was found to be the most sensitive to basis set choice, while the geometry of selenium-containing compounds was less sensitive to basis set. In mixed chalcogens species of sulfur and selenium, the location of the sulfur atom affects the S–Se bond length as it can hold more negative charge. PA, GPB, BDE, and HA of selenium systems were all lower, indicating more acidity and more stability of radicals. Extending the sulfur chain in cysteine results in a decrease of BDE and HA, but these plateau at a certain point (199 kJ mol−1 and 295 kJ mol−1), and PA and GPB are also decreased relative to the thiol, indicating that the polysulfur species exist as thiolates in a biological system. In general, it was found that ωB97XD/6-311G(2d,p) gave the most reasonable structures and thermochemistry relative to benchmark calculations. However, nuances in performance are observed and discussed

Reply to Sopek Merkaš, I.; Lakušić, N. Comment on “von Känel et al. Early Trauma-Focused Counseling for the Prevention of Acute Coronary Syndrome-Induced Posttraumatic Stress: Social and Health Care Resources Matter. J. Clin. Med. 2022, 11, 1993”

We thank Merkaš and Lakušić for commenting on our recently published paper; in the paper, we suggested that resources in a patient’s social environment may moderate the benefit of one single-session trauma-focused counseling in the prevention of acute coronary syndrome (ACS)-induced posttraumatic stress disorder (PTSD) symptoms [1]. Their comment gives a comprehensive summary on the topic of ACS-induced PTSD and its treatment [2]. We agree with the authors that guidelines and standards regarding the identification and treatment of patients at high risk for developing PTSD after ACS remain lacking. We designed the MI-SPRINT study to test whether trauma-focused psychological counseling is more effective than stress-focused counseling in preventing PTSD symptoms after acute ACS [3]. Our study showed no beneficial effect of trauma-focused counseling on PTSD symptoms; after 3 and 12 months, we found no difference in the severity of PTSD symptoms between patients with early trauma-focused counseling and those with stress-focused counseling in the total sample. However, our results suggested that psychological counseling in general might help distressed patients to prevent posttraumatic psychological responses compared with no intervention [4,5]. Importantly, PTSD symptoms that had developed after 3 months were shown to have been persistent up to 12 months after ACS, despite the delivery of one session of early psychological counseling [6]. Furthermore, as alluded to above, we showed that social support and cardiac rehabilitation act as moderators of the intervention; specifically, trauma-focused counseling was associated with fewer PTSD symptoms compared with stress-focused counseling in patients with high social support and with longer participation in cardiac rehabilitation [1]. Moreover, the data of MI-SPRINT showed that several factors contribute to identifying patients at risk for ACS-induced PTSD symptoms, such as high perceived distress during ACS [6], perception of higher harmful consequences of the illness [7], perception of a hectic hospital environment [8], sleep problems [9], and low trait resilience [10]. Screening for risk factors or specific symptoms—e.g., in the cardiac rehabilitation setting, as indicated by the Merkaš and Lakušić [1]—is important. However, we believe that screening alone may have little clinical benefit. It will be much more crucial to offer effective treatment to patients identified at high risk of developing PTSD or patients with established PTSD symptoms. In summary, further studies are needed to develop a standardized approach for the screening of patients at risk of clinically relevant, ACS-induced PTSD symptoms and to establish efficacious interventions that can be applied in a clinical setting. For instance, multisession early counseling could be elaborated and tested based on our findings to prevent the development of PTSD symptoms in patients at risk

Reply to Sopek Merkaš, I.; Lakušić, N. Comment on "von Känel et al. Early Trauma-Focused Counseling for the Prevention of Acute Coronary Syndrome-Induced Posttraumatic Stress: Social and Health Care Resources Matter. J. Clin. Med. 2022, 11, 1993".

We thank Merkaš and Lakušić for commenting on our recently published paper; in the paper, we suggested that resources in a patient's social environment may moderate the benefit of one single-session trauma-focused counseling in the prevention of acute coronary syndrome (ACS)-induced posttraumatic stress disorder (PTSD) symptoms [...]

Early Trauma-Focused Counseling for the Prevention of Acute Coronary Syndrome-Induced Posttraumatic Stress: Social and Health Care Resources Matter.

BACKGROUND A one-size-fits-all approach might explain why early psychological interventions are largely ineffective in preventing the development of posttraumatic stress disorder (PTSD) symptoms triggered by acute medical events. We examined the hypothesis that social and health care resources are moderators of an intervention effect. METHODS Within 48 h of hospital admission, 129 patients (mean age 58 years, 83% men) with acute coronary syndrome (ACS) self-rated their social support and were randomized to one single session of trauma-focused counseling (TFC) or stress-focused counseling (SFC) (active control intervention). Clinician-rated PTSD symptoms, use of cardiac rehabilitation (CR) and use of psychotherapy were assessed at 3 and 12 months. Random mixed regression multivariable models were used to analyze associations with PTSD symptoms over time. RESULTS TFC did not prevent ACS-induced PTSD symptom onset better than SFC; yet, there were significant and independent interactions between "intervention" (TFC or SFC) and social support (p = 0.013) and between "intervention" and duration of CR in weeks (p = 0.034). Patients with greater social support or longer participation in CR had fewer PTSD symptoms in the TFC group compared with the SFC group. The number of psychotherapy sessions did not moderate the intervention effect. CONCLUSIONS Early psychological intervention after ACS with a trauma-focused approach to prevent the development of PTSD symptoms may be beneficial for patients who perceive high social support or participate in CR for several weeks

Relationship between a Self-Reported History of Depression and Persistent Elevation in C-Reactive Protein after Myocardial Infarction.

BACKGROUND Elevated levels of C-reactive protein (CRP) are associated with both an increased risk of cardiovascular disease (CVD) and depression. We aimed to test the hypothesis that a self-report history of depression is associated with a smaller decrease in CRP levels from hospital admission to 3-month follow-up in patients with acute myocardial infarction (MI). METHODS We assessed 183 patients (median age 59 years; 84% men) with verified MI for a self-report history of lifetime depression and plasma CRP levels within 48 h of an acute coronary intervention and again for CRP levels at three months. CRP values were categorized according to their potential to predict CVD risk at hospital admission (acute inflammatory response: 0 to <5 mg/L, 5 to <10 mg/L, 10 to <20 mg/L, and ≥20 mg/L) and at 3 months (low-grade inflammation: 0 to <1 mg/L, 1 to <3 mg/L, and ≥3 mg/L). Additionally, in a subsample of 84 patients showing admission CRP levels below 20 mg/L, changes in continuous CRP values over time were also analyzed. RESULTS After adjustment for a range of potentially important covariates, depression history showed a significant association with a smaller decrease in both CRP risk categories (r = 0.261, p < 0.001) and log CRP levels (r = 0.340, p = 0.005) over time. CONCLUSIONS Self-reported history of depression may be associated with persistently elevated systemic inflammation three months after MI. This finding warrants studies to test whether lowering of inflammation in patients with an acute MI and a history of depression may improve prognosis

Relationship between a Self-Reported History of Depression and Persistent Elevation in C-Reactive Protein after Myocardial Infarction

Background: Elevated levels of C-reactive protein (CRP) are associated with both an increased risk of cardiovascular disease (CVD) and depression. We aimed to test the hypothesis that a self-report history of depression is associated with a smaller decrease in CRP levels from hospital admission to 3-month follow-up in patients with acute myocardial infarction (MI). Methods: We assessed 183 patients (median age 59 years; 84% men) with verified MI for a self-report history of lifetime depression and plasma CRP levels within 48 h of an acute coronary intervention and again for CRP levels at three months. CRP values were categorized according to their potential to predict CVD risk at hospital admission (acute inflammatory response: 0 to <5 mg/L, 5 to <10 mg/L, 10 to <20 mg/L, and ≥20 mg/L) and at 3 months (low-grade inflammation: 0 to <1 mg/L, 1 to <3 mg/L, and ≥3 mg/L). Additionally, in a subsample of 84 patients showing admission CRP levels below 20 mg/L, changes in continuous CRP values over time were also analyzed. Results: After adjustment for a range of potentially important covariates, depression history showed a significant association with a smaller decrease in both CRP risk categories (r = 0.261, p < 0.001) and log CRP levels (r = 0.340, p = 0.005) over time. Conclusions: Self-reported history of depression may be associated with persistently elevated systemic inflammation three months after MI. This finding warrants studies to test whether lowering of inflammation in patients with an acute MI and a history of depression may improve prognosis

Antitumor Activity of Pembrolizumab in Biomarker-Unselected Patients With Recurrent and/or Metastatic Head and Neck Squamous Cell Carcinoma: Results From the Phase Ib KEYNOTE-012 Expansion Cohort.

Purpose Treatment with pembrolizumab, an anti-programmed death-1 antibody, at 10 mg/kg administered once every 2 weeks, displayed durable antitumor activity in programmed death-ligand 1 (PD-L1) -positive recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) in the KEYNOTE-012 trial. Results from the expansion cohort, in which patients with HNSCC, irrespective of biomarker status, received a fixed dose of pembrolizumab at a less frequent dosing schedule, are reported. Patients and Methods Patients with R/M HNSCC, irrespective of PD-L1 or human papillomavirus status, received pembrolizumab 200 mg intravenously once every 3 weeks. Imaging was performed every 8 weeks. Primary end points were overall response rate (ORR) per central imaging vendor (Response Evaluation Criteria in Solid Tumors v1.1) and safety. Secondary end points included progression-free survival, overall survival, and association of response and PD-L1 expression. Patients who received one or more doses of pembrolizumab were included in analyses. Results Of 132 patients enrolled, median age was 60 years (range, 25 to 84 years), 83% were male, and 57% received two or more lines of therapy for R/M disease. ORR was 18% (95% CI, 12 to 26) by central imaging vendor and 20% (95% CI, 13 to 28) by investigator review. Median duration of response was not reached (range, ≥ 2 to ≥ 11 months). Six-month progression-free survival and overall survival rates were 23% and 59%, respectively. By using tumor and immune cells, a statistically significant increase in ORR was observed for PD-L1-positive versus -negative patients (22% v 4%; P = .021). Treatment-related adverse events of any grade and grade ≥ 3 events occurred in 62% and 9% of patients, respectively. Conclusion Fixed-dose pembrolizumab 200 mg administered once every 3 weeks was well tolerated and yielded a clinically meaningful ORR with evidence of durable responses, which supports further development of this regimen in patients with advanced HNSCC