Mutant Complexes Research Articles

Analysis of damaging non-synonymous SNPs in GPx1 gene associated with the progression of diverse cancers through a comprehensive in silico approach

Glutathione Peroxidase 1 (GPx1) gene has been reported for its role in cellular redox homeostasis, and the dysregulation of its expression is linked with the progression of diverse cancers. Non-synonymous single nucleotide polymorphism (nsSNPs) have been emerged as the crucial factors, playing their role in GPx1 overexpression. To understand the deleterious mutational effects on the structure and function of GPx1 enzyme, we delved deeper into the exploration of possibly damaging nsSNPs using in-silico based approaches. Eight widely utilized computational tools were employed to roughly shortlist the deleterious nsSNPs. Their damaging effects on structure and function of the genes were evaluated by using different bioinformatics tools. Subsequently, the three final proposed deleterious mutants including mutations rs373838463, rs2107818892, and rs763687242, were docked with their reported binder, TNF receptor-associated factor 2 (TRAF2). The lowest binding affinity and stability of the docked mutant complexes as compared to the wild type GPx1 were validated by molecular dynamic simulation. Finally, the comparison of RMSD, RMSF, RoG and hydrogen bond analyses between wild-type and mutant’s complexes validated the deleterious effects of proposed nsSNPs. This study successfully identified and verified the possibly damaging nsSNPs in GPx1 enzyme, which may be linked the progression of various types of cancer. Our findings underscore the value of in-silico approaches in mutational analysis and encourage further preclinical and clinical trials.

In silico mutagenesis on active site residues of Acinetobacter haemolyticus lipase KV1 for improved binding to polyethylene terephthalate (PET)

Polyethylene terephthalate (PET) pollution is an emerging environmental hazard because of its recalcitrance to degradation. This study proposes an in silico mutagenesis of LipKV1 from Acinetobacter haemolyticus for improved lipase-PET interaction, using the PET-degrading Thermobifida cutinase (TfCut2) as the structural benchmark. Results revealed that lid deletion on LipKV1 (LipKV1_LE) facilitated the entry of PET into the active site. The mutation of several predicted amino acids into alanine expanded the LipKV1 active site for better PET binding. Docking results indicated that the LipKV1_LE mutants, Var9 (-6.2 kcal/mol), Var18 (-6.0 kcal/mol), and Var181 (-6.0 kcal/mol), produced higher binding affinities with PET than the wild-type LipKV1 (-2.5 kcal/mol) and TfCut2 (-4.6 kcal/mol), attesting that the selected mutation sites played prominent role in altering the abilities of LipKV1_LE mutants to bind to PET. Our molecular dynamics (MD) simulation results corroborated the variant-PET complexes’ improved binding, mirrored by their improved conformations (RMSD ∼0.35 nm). The RMSF results also showed acceptable fluctuation limits of the LipKV1_PET mutant complexes (RMSF < 0.5 nm). Rg data of the complexes showed that they are conformationally stable, with a maximum of three H-bonds in their interaction with PET. SASA results showed that the mutations did not profoundly alter the hydrophobicity of the amino acid residues. MM-PBSA calculations on the LipKV1_PET mutant complexes estimated binding free energies between −28.29 kcal/mol to −23.25 kcal/mol, comparable to the molecular docking data. Thus, the MD data conveyed the practicality of the above-said site mutations in rationally designing the LipKV1 active site for better PET degradation.

Mutations in Mig6 reduce inhibition of the epidermal growth factor receptor.

Mitogen-inducible gene 6 (Mig6) is a cellular inhibitor of epidermal growth factor receptor (EGFR) that binds directly to the EGFR kinase domain and interferes with signaling. Reduced Mig6 expression is correlated with increased EGFR activity in multiple cancer models. Here, we investigated whether disease-associated point mutations could reduce the inhibitory potency of Mig6. We show that several cancer-associated mutations, and a mutation derived from Alzheimer's Disease patients, diminish the ability of Mig6 to bind and inhibit EGFR invitro. In mammalian cells, the mutations decreased the Mig6-induced suppression of basal and EGF-stimulated autophosphorylation, MAP kinase phosphorylation, and cell migration. To probe the mechanisms by which the mutations could lead to reduced Mig6 inhibition, we constructed atomic-level computational models of Mig6 complexed with the EGFR catalytic domain, and performed molecular dynamics simulations for wild-type and mutant complexes.

Exploring the Dynamic Interplay of Deleterious Variants on the RAF1-RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics.

The RAF1-RAP1A interaction activates the MAPK/ERK pathway which is very crucial in the carcinogenesis process. This protein complex influences tumor formation, proliferation, and metastasis. Understanding aberrant interactions driven by clinical mutations is vital for targeted therapies. Hence, the current study focuses on the screening of clinically reported substitutions in the RAF1 and RAP1A genes using predictive algorithms integrated with all-atoms simulation, essential dynamics, and binding free energy methods. Survival analysis results revealed a strong association between RAF1 and RAP1A expression levels and diminished survival rates in cancer patients across different cancer types. Integrated machine learning algorithms showed that among the 134 mutations reported for these 2 proteins, only 13 and 35 were classified as deleterious mutations in RAF1 and RAP1P, respectively. Moreover, one mutation in RAF1 reported elevated levels of binding between RAF1 and RAP1P while in RAP1A, 7 mutations were reported to increase the binding affinity. The high-binding mutations, P34Q and V60F, were subjected to protein-protein coupling which confirmed the increase in the binding affinity. Wild-type and mutant RAF1-RAP1P bound complexes were subjected to molecular simulation investigation, revealing enhanced structural stability, increased compactness, and stabilized residue fluctuations of the mutant systems in contrast to the wild-type. In addition, hydrogen bonding analysis revealed a variation in the binding paradigm which further underscores the impact of these substitutions on the coupling of RAF1 and RAP1A. Principal component analysis (PCA) and free energy landscape (FEL) evaluation further determined dynamical variations in the wild-type and mutant complexes. Finally, the Gibbs free energy for each complex was estimated and found to be -71.94 ± 0.38 kcal/mol for the wild-type, -95.57 ± 0.37 kcal/mol for the V60F, and -85.76 ± 0.72 kcal/mol for P34Q complex. These findings confirm the effect of these variants on increasing the binding affinity of RAF1 to RAP1P. These mutations can therefore be targeted for cancer therapy to modulate the activity of the MAPK/ERK signaling pathway.

SAAMBE-MEM: a sequence-based method for predicting binding free energy change upon mutation in membrane protein-protein complexes.

Mutations in protein-protein interactions can affect the corresponding complexes, impacting function and potentially leading to disease. Given the abundance of membrane proteins, it is crucial to assess the impact of mutations on the binding affinity of these proteins. Although several methods exist to predict the binding free energy change due to mutations in protein-protein complexes, most require structural information of the protein complex and are primarily trained on the SKEMPI database, which is composed mainly of soluble proteins. A novel sequence-based method (SAAMBE-MEM) for predicting binding free energy changes (ΔΔG) in membrane protein-protein complexes due to mutations has been developed. This method utilized the MPAD database, which contains binding affinities for wild-type and mutant membrane protein complexes. A machine learning model was developed to predict ΔΔG by leveraging features such as amino acid indices and position-specific scoring matrices (PSSM). Through extensive dataset curation and feature extraction, SAAMBE-MEM was trained and validated using the XGBoost regression algorithm. The optimal feature set, including PSSM-related features, achieved a Pearson correlation coefficient of 0.64, outperforming existing methods trained on the SKEMPI database. Furthermore, it was demonstrated that SAAMBE-MEM performs much better when utilizing evolution-based features in contrast to physicochemical features. The method is accessible via a web server and standalone code at http://compbio.clemson.edu/SAAMBE-MEM/. The cleaned MPAD database is available at the website.

RNA interacts with topoisomerase I to adjust DNA topology

Topoisomerase I (TOP1) is an essential enzyme that relaxes DNA to prevent and dissipate torsional stress during transcription. However, the mechanisms underlying the regulation of TOP1 activity remain elusive. Using enhanced cross-linking and immunoprecipitation (eCLIP) and ultraviolet-cross-linked RNA immunoprecipitation followed by total RNA sequencing (UV-RIP-seq) in human colon cancer cells along with RNA electrophoretic mobility shift assays (EMSAs), biolayer interferometry (BLI), and invitro RNA-binding assays, we identify TOP1 as an RNA-binding protein (RBP). We show that TOP1 directly binds RNA invitro and in cells and that most RNAs bound by TOP1 are mRNAs. Using a TOP1 RNA-binding mutant and topoisomerase cleavage complex sequencing (TOP1cc-seq) to map TOP1 catalytic activity, we reveal that RNA opposes TOP1 activity as RNA polymerase II (RNAPII) commences transcription of active genes. We further demonstrate the inhibitory role of RNA in regulating TOP1 activity by employing DNA supercoiling assays and magnetic tweezers. These findings provide insight into the coordinated actions of RNA and TOP1 in regulating DNA topological stress intrinsic to RNAPII-dependent transcription.

Finite Difference Model of Substrate Channeling in TCA Cycle Enzymes

The Tricarboxylic Acid (TCA) cycle is a highly optimized metabolic pathway. Of particular interest in the TCA cycle is the malate dehydrogenase—citrate synthase (MDH-CS) complex, which accomplishes citrate production from malate with an oxaloacetate intermediate. This complex was studied experimentally by Bulutoglu et al, who showed that mutation of positively-charged residues on the complex surface effected the dynamic response of citrate production as measured by lag time experiments.1 More recently, we have created a Markov State model that was used to predict the transfer efficiency of each complex and determine the reaction pathways on the surface.2 Utilizing the kinetic parameters of both the recombinant and mutant complexes determined experimentally1and Markov state transition matrix produced by previous modeling2, we report a finite difference model to calculate time trajectories of the surface and bulk occupancies by OAA. Solution of a system of differential mass balance equations, based on the transient matrix, provide the occupancy probability at each node in the network. The lag time of MDH-CS was determined computationally to be comparable to experiment for both the recombinant and mutant complex with lag times of 0.44 and 2.1 seconds, respectively.1 Using the model, the dynamics of each of the four possible reaction pathways between the the two source (MDH) active sites and the two sink (CS) sites could be studied independently. This analysis provides a dynamic model for intermediate transport in an electrostatically channeled system, and can be used as a predictive tool to provide mechanistic insight into pathway dominance. We gratefully acknowledge support from the Army Research Office MURI (#W911NF1410263) via The University of Utah. References B. Bulutoglu, K. E. Garcia, F. Wu, S. D. Minteer, and S. Banta, ACS Chemical Biology, 11, 2847–53 (2016). doi:10.1021/acschembio.6b00523Y. Xie, S. D. Minteer, S. Banta, and S. Calabrese Barton, ACS Nanoscience Au, 2, 414-421 (2022). doi:10.1021/acsnanoscienceau.2c00011 Figure 1

TFIIB-Termination Factor Interaction Affects Termination of Transcription on Genome-Wide Scale.

Apart from its well-established role in the initiation of transcription, the general transcription factor TFIIB has been implicated in the termination step as well. The ubiquity of TFIIB involvement in termination as well as mechanistic details of its termination function, however, remain largely unexplored. Using GRO-seq analyses, we compared the terminator readthrough phenotype in the sua7-1 mutant (TFIIBsua7-1) and the isogenic wild type (TFIIBWT) strains. Approximately 74% of genes analyzed exhibited a 2-3-fold increase in readthrough of the poly(A)-termination signal in the TFIIBsua7-1 mutant compared to TFIIBWT cells. To understand the mechanistic basis of TFIIB's role in termination, we performed the mass spectrometry of TFIIB-affinity purified from chromatin and soluble cellular fractions-from TFIIBsua7-1 and TFIIBWT cells. TFIIB purified from the chromatin fraction of TFIIBWT cells exhibited significant enrichment of CF1A and Rat1 termination complexes. There was, however, a drastic decrease in TFIIB interaction with CF1A and Rat1 complexes in the TFIIBsua7-1 mutant. ChIP assays revealed about a 90% decline in the recruitment of termination factors in the TFIIBsua7-1 mutant compared to wild type cells. The overall conclusion of these results is that TFIIB affects the termination of transcription on a genome-wide scale, and the TFIIB-termination factor interaction plays a crucial role in the process.

Application of Bioinformatics and Molecular Dynamics Simulation for Designing FGF7 Mutants Stable in Urea Solution

Background: FGF7 is a potent cytoprotective and regenerative protein on the injured epithelial tissues, indicating its potential therapeutic effect in conditions such as mucositis, ulcerative colitis, and cutaneous wound formation induced by chemotherapy or radiotherapy. However, FGF7 low stability prevents its usability as a pharmaceutical product, necessitating the design and production of stable FGF7 mutants. Methods: In the current study, bioinformatics and MD simulations approaches were used for identifying potential stable mutants of FGF7. For this, the model structure of FGF7 was constructed and subjected to MAESTROweb service to identify stability conferring mutations. The identified potential mutants of FGF7 were MD simulated in an explicit denaturant condition and their stabilities were evaluated. The complexes of FGF7 mutants with FGFR2 receptor were also examined to investigate the receptor binding ability of proposed mutants. Results: Investigation of stability parameters showed that introducing A104S mutations in FGF7 may greatly improve its stability in urea solution. Calculation of binding energies indicated that A104S mutant interacts better then wild type FGF7 with the receptor. The structural stability and binding capability of A104S were comparable to that of A120C mutation, as an experimentally determined stability conferring mutation, which was used in whole process to indicate the validity of employed MD simulation for predicting the effect of mutation on FGF7 stability. Conclusion: The results of current study showed that A104S mutant of FGF7 has a potential to be evaluated further for the purpose of presenting a therapeutic agent effective in conditions such as mucositis, ulcerative colitis, and cutaneous wound formation induced by chemotherapy or radiotherapy.

Genome-wide analysis of TFIIB's role in termination of transcription.

This study provides evidence that the role of TFIIB extends beyond initiation to include the termination step of transcription. Using GRO-seq analyses, we compared terminator readthrough phenotype in sua7-1 mutant (TFIIB sua7-1 ) and the isogenic wild type (TFIIB WT ) strains. Approximately 74% of genes analyzed exhibited a 2-3-fold increase in readthrough of the poly(A)-termination signal in the TFIIB sua7-1 mutant compared to TFIIB WT cells. Mass spectrometry of affinity purified TFIIB from chromatin fraction found TFIIB exhibiting interaction with CF1A and Rat1 termination complexes in TFIIB WT cells. There was, however, a drastic decrease in TFIIB interaction with CF1A and Rat1 termination complexes in the TFIIB sua7-1 mutant. ChIP assays revealed about 90% decline in recruitment of termination factors in TFIIB sua7-1 mutant compared to wild type cells. The overall conclusion of these results is that TFIIB affects termination of transcription on a genome-wide scale, and TFIIB-termination factor interaction may play a crucial role in the process.

Mutations in LIFR rewire the JAK/STAT signaling pathway: A study unveiling mechanistic details of Stüve-Wiedemann syndrome

Stüve-Wiedemann syndrome (SWS), a rare autosomal recessive disorder, characterized by diminutive size, curvature of the elongated bones, bent fingers, episodes of heightened body temperature, respiratory distress or periods of breath-holding, and challenges with feeding, especially causes fatality in infants. SWS is an outcome of potential missense mutations in the leukemia inhibitory factor receptor gene reflected as numerous amino acid mutations at protein level. Employing in silico tools and techniques like mutational screening with Pred_MutHTP, I-Mutant2.0, PANTHER.db, PolyPhen, to classify mutations as deleterious/destabilizing, in conjunction with experimental data analysis, P136A and S279P emerged as ‘effect’-causing mutations. Pre-existing knowledge suggests, SWS progression is effectuated conformationally altered and dysfunctional LIFR, unable to bind to LIF and further form the LIF/LIFR/gp130 signalling complex. To gain functional insights into the effect of the said mutations on the wild type protein, an all-atom, explicit, solvent molecular dynamics simulation was performed following docking approaches. Consequently, referring to the RMSD, RMSF, protein dynamic network analysis, energy landscape plots and domain motion analysis, it was revealed that unbound LIFR_WT was more prone to LIF binding as usual whereas the mutants exhibited considerable domain closure to inhibit LIF binding. We conducted binding affinity analysis via MM/GBSA and dissociation constant estimation after LIFR-LIF docking and found the WT_complex to be more stable and compact as a whole when compared to the flexible mutant complexes thus being associated with SWS. Our study offers a route for understanding molecular level implications upon LIFR mutations which opens an avenue for therapeutic interventions.

Genome-wide analysis of TFIIB's role in termination of transcription.

Apart from its well-established role in initiation of transcription, the general transcription factor TFIIB has been implicated in the termination step as well. The ubiquity of TFIIB involvement in termination as well as mechanistic details of its termination function, however, remains largely unexplored. To determine the prevalence of TFIIB's role in termination, we performed GRO-seq analyses in sua7-1 mutant (TFIIB sua7-1 ) and the isogenic wild type (TFIIB WT ) strains of yeast. Almost a three-fold increase in readthrough of the poly(A)-termination signal was observed in TFIIB sua7-1 mutant compared to the TFIIB WT cells. Of all genes analyzed in this study, nearly 74% genes exhibited a statistically significant increase in terminator readthrough in the mutant. To gain an understanding of the mechanistic basis of TFIIB involvement in termination, we performed mass spectrometry of TFIIB, affinity purified from chromatin and soluble cellular fractions, from TFIIB sua7-1 and TFIIB WT cells. TFIIB purified from the chromatin fraction of TFIIB WT cells exhibited significant enrichment of CF1A and Rat1 termination complexes. There was, however, a drastic decrease in TFIIB interaction with both CF1A and Rat1 termination complexes in TFIIB sua7-1 mutant. ChIP assay revealed that the recruitment of Pta1 subunit of CPF complex, Rna15 subunit of CF1 complex and Rat1 subunit of Rat1 complex registered nearly 90% decline in the mutant over wild type cells. The overall conclusion of these results is that TFIIB affects termination of transcription on a genome-wide scale, and TFIIB-termination factor interaction may play a crucial role in the process.

An interaction network in the polymerase active site is a prerequisite for Watson-Crick base pairing in Pol γ.

The replication accuracy of DNA polymerase gamma (Pol γ) is essential for mitochondrial genome integrity. Mutation of human Pol γ arginine-853 has been linked to neurological diseases. Although not a catalytic residue, Pol γ arginine-853 mutants are void of polymerase activity. To identify the structural basis for the disease, we determined a crystal structure of the Pol γ mutant ternary complex with correct incoming nucleotide 2'-deoxycytidine 5'-triphosphate (dCTP). Opposite to the wild type that undergoes open-to-closed conformational changes when bound to a correct nucleotide that is essential for forming a catalytically competent active site, the mutant complex failed to undergo the conformational change, and the dCTP did not base pair with its Watson-Crick complementary templating residue. Our studies revealed that arginine-853 coordinates an interaction network that aligns the 3'-end of primer and dCTP with the catalytic residues. Disruption of the network precludes the formation of Watson-Crick base pairing and closing of the active site, resulting in an inactive polymerase.

Computational analysis of affinity dynamics between the variants of SARS-CoV-2 spike protein (RBD) and human ACE-2 receptor

The novel coronavirus SARS-CoV-2 resulted in a significant worldwide health emergency known as the COVID-19 pandemic. This crisis has been marked by the widespread of various variants, with certain ones causing notable apprehension. In this study, we harnessed computational techniques to scrutinize these Variants of Concern (VOCs), including various Omicron subvariants. Our approach involved the use of protein structure prediction algorithms and molecular docking techniques, we have investigated the effects of mutations within the Receptor Binding Domain (RBD) of SARS-CoV-2 and how these mutations influence its interactions with the human angiotensin-converting enzyme 2 (hACE-2) receptor. Further we have predicted the structural alterations in the RBD of naturally occurring SARS-CoV-2 variants using the tr-Rosetta algorithm. Subsequent docking and binding analysis employing HADDOCK and PRODIGY illuminated crucial interactions occurring at the Receptor-Binding Motif (RBM). Our findings revealed a hierarchy of increased binding affinity between the human ACE2 receptor and the various RBDs, in the order of wild type (Wuhan-strain) < Beta < Alpha < Gamma < Omicron-B.1.1.529 < Delta < Omicron-BA.2.12.1 < Omicron-BA.5.2.1 < Omicron-BA.1.1. Notably, Omicron-BA.1.1 demonstrated the highest binding affinity of -17.4 kcal mol−1 to the hACE2 receptor when compared to all the mutant complexes. Additionally, our examination indicated that mutations occurring in active residues of the Receptor Binding Domain (RBD) consistently improved the binding affinity and intermolecular interactions in all mutant complexes. Analysis of the differences among variants has laid a foundation for the structure-based drug design targeting the RBD region of SARS-CoV-2.

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region’s significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Molecular dynamics simulation guided analysis of the interaction between delafloxacin and Staphylococcus aureus gyrase mutants

ABSTRACT Staphylococcus aureus is a highly virulent nosocomial pathogen producing a wide array of virulence factors to orchestrate a deadly disease. Delafloxacin is a fluoroquinolone antibiotic targeting gyrase to confer its antibacterial properties by stabilising DNA breakage. Due to the presence of certain mutations in gyrase A (GyrA), fluoroquinolone resistance has been reported. In this paper, the computational basis of delafloxacin resistance in S. aureus is studied. Computational techniques including molecular dynamics simulations simulation were applied to observe the effects of delafloxacin binding to gyrase coupled with MM-PBSA-based binding energy calculation and PCA to further ascertain the stability of the complexes. The mutation in gyrase did not cause any significant structural perturbation owing to delafloxacin binding. A significant change in free binding energy was seen in mutant–delafloxacin complexes in contrast to wild-type counterparts. The lowest (most negative) binding free energy obtained in the WT–delafloxacin complex indicated a better affinity and more stable interaction than the mutant complexes. The key residues of GyrA involved in interaction with delafloxacin were identified using their contribution to binding energy through the implementation of per-residue MM-PBSA decomposition. Delafloxacin failed to maintain stable interaction when bound to a mutant binding pocket and trans-located to an alternate site.

Abstract 5596: Exploring BRCA1-Y1853ter and potential therapeutic targets in BRCA1-BRCT mutated cancers

Abstract The breast cancer gene BRCA1 plays a pivotal role as a tumor suppressor gene. Despite the use of poly (ADP-ribose) polymerase inhibitors (PARPi) in treating BRCA1 mutation carriers, the lack of response or the development of acquired drug resistance underscores the pressing need for new therapeutic targets. One intriguing BRCA1 mutation, BRCA1-Y1853ter, characterized by a minimal truncation, has been identified in multiple individuals with Hereditary Breast and Ovarian Cancer (HBOC) syndrome. We have developed a Halo Tag and adenovirus-based system where wild-type BRCA1 (WT BRCA1) and mutant BRCA1 protein complexes can be studied in multiple cell types. Here, we used this system to affinity purify BRCA1 wild-type and mutant complexes, followed by label-free quantitative proteomics to investigate the dynamic interactome variations between WT BRCA1 and BRCA1 mutant. Contrary to the assumed loss of function, our preliminary findings suggest a potential gain of function, as a significant number of candidate proteins exhibit enhanced binding affinity with the mutant BRCA1. We are currently exploring whether these distinct binding characteristics are shared among various BRCA1-BRCT mutants, which may hint at a common tumorigenesis mechanism. Our overarching hypothesis is that identifying a specific binding partner, shared among various BRCA-BRCT mutants, could unveil a novel therapeutic target with broader applicability in treating BRCA1-related malignancies. Citation Format: Jingjing Chen. Exploring BRCA1-Y1853ter and potential therapeutic targets in BRCA1-BRCT mutated cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5596.

Photoautotrophic cultivation of a Chlamydomonas reinhardtii mutant with zeaxanthin as the sole xanthophyll

BackgroundPhotosynthetic microalgae are known for their sustainable and eco-friendly potential to convert carbon dioxide into valuable products. Nevertheless, the challenge of self-shading due to high cell density has been identified as a drawback, hampering productivity in sustainable photoautotrophic mass cultivation. To address this issue, mutants with altered pigment composition have been proposed to allow a more efficient light diffusion but further study on the role of the different pigments is still needed to correctly engineer this process.ResultsWe here investigated the Chlamydomonas reinhardtii Δzl mutant with zeaxanthin as the sole xanthophyll. The Δzl mutant displayed altered pigment composition, characterized by lower chlorophyll content, higher chlorophyll a/b ratio, and lower chlorophyll/carotenoid ratio compared to the wild type (Wt). The Δzl mutant also exhibited a significant decrease in the light-harvesting complex II/Photosystem II ratio (LHCII/PSII) and the absence of trimeric LHCIIs. This significantly affects the organization and stability of PSII supercomplexes. Consequently, the estimated functional antenna size of PSII in the Δzl mutant was approximately 60% smaller compared to that of Wt, and reduced PSII activity was evident in this mutant. Notably, the Δzl mutant showed impaired non-photochemical quenching. However, the Δzl mutant compensated by exhibiting enhanced cyclic electron flow compared to Wt, seemingly offsetting the impaired PSII functionality. Consequently, the Δzl mutant achieved significantly higher cell densities than Wt under high-light conditions.ConclusionsOur findings highlight significant changes in pigment content and pigment–protein complexes in the Δzl mutant compared to Wt, resulting in an advantage for high-density photoautotrophic cultivation. This advantage is attributed to the decreased chlorophyll content of the Δzl mutant, allowing better light penetration. In addition, the accumulated zeaxanthin in the mutant could serve as an antioxidant, offering protection against reactive oxygen species generated by chlorophylls.

DeePNAP: A Deep Learning Method to Predict Protein-Nucleic Acid Binding Affinity from Their Sequences.

Predicting the protein-nucleic acid (PNA) binding affinity solely from their sequences is of paramount importance for the experimental design and analysis of PNA interactions (PNAIs). A large number of currently developed models for binding affinity prediction are limited to specific PNAIs while also relying on the sequence and structural information of the PNA complexes for both training and testing, and also as inputs. As the PNA complex structures available are scarce, this significantly limits the diversity and generalizability due to the small training data set. Additionally, a majority of the tools predict a single parameter, such as binding affinity or free energy changes upon mutations, rendering a model less versatile for usage. Hence, we propose DeePNAP, a machine learning-based model built from a vast and heterogeneous data set with 14,401 entries (from both eukaryotes and prokaryotes) from the ProNAB database, consisting of wild-type and mutant PNA complex binding parameters. Our model precisely predicts the binding affinity and free energy changes due to the mutation(s) of PNAIs exclusively from their sequences. While other similar tools extract features from both sequence and structure information, DeePNAP employs sequence-based features to yield high correlation coefficients between the predicted and experimental values with low root mean squared errors for PNA complexes in predicting KD and ΔΔG, implying the generalizability of DeePNAP. Additionally, we have also developed a web interface hosting DeePNAP that can serve as a powerful tool to rapidly predict binding affinities for a myriad of PNAIs with high precision toward developing a deeper understanding of their implications in various biological systems. Web interface: http://14.139.174.41:8080/.

Analysis of E2F1 single-nucleotide polymorphisms reveals deleterious non-synonymous substitutions that disrupt E2F1-RB protein interaction in cancer

Cancer is a medical condition that is caused by the abnormal growth and division of cells, leading to the formation of tumors. The E2F1 and RB pathways are critical in regulating cell cycle, and their dysregulation can contribute to the development of cancer. In this study, we analyzed experimentally reported SNPs in E2F1 and assessed their effects on the binding affinity with RB. Out of 46, nine mutations were predicted as deleterious, and further analysis revealed four highly destabilizing mutations (L206W, R232C, I254T, A267T) that significantly altered the protein structure. Molecular docking of wild-type and mutant E2F1 with RB revealed a docking score of −242 kcal/mol for wild-type, while the mutant complexes had scores ranging from −217 to −220 kcal/mol. Molecular simulation analysis revealed variations in the dynamics features of both mutant and wild-type complexes due to the acquired mutations. Furthermore, the total binding free energy for the wild-type E2F1-RB complex was −64.89 kcal/mol, while those of the L206W, R232C, I254T, and A267T E2F1-RB mutants were −45.90 kcal/mol, −53.52 kcal/mol, −55.67 kcal/mol, and −61.22 kcal/mol, respectively. Our study is the first to extensively analyze E2F1 gene mutations and identifies candidate mutations for further validation and potential targeting for cancer therapeutics.