ΔΔG Values Research Articles

Quantitative assessment of early caries lesion activity using novel dye-enhanced fluorescence imaging

ObjectivesThis study aimed to evaluate the validity of the dye-enhanced quantitative light-induced fluorescence (DEQLF) method for assessing early enamel caries activity. MethodsSeventy extracted human teeth with early enamel caries on smooth surfaces were included. Two dentists evaluated the caries activity using the Nyvad system followed by the DEQLF method. The teeth were hydrated with distilled water for 60 s, dehydrated with compressed air for 10 s, and stained with 100 μM fluorescein sodium solution for 10 s. White and fluorescent images were captured using a QLF-D 2+ Billuminator. The change in fluorescence (ΔΔG) was calculated using image analysis software. Independent-sample t-tests were performed to evaluate the difference in ΔΔG between active and inactive lesions for both DEQLF and conventional quantitative light-induced fluorescence (QLF) methods. Receiver operating characteristic (ROC) curve analysis was used to assess the validity of ΔΔG for distinguishing lesion activity using the area under the ROC curve (AUROC). ResultsAmong the 70 caries lesions, 33 were active and 37 were inactive. Using the DEQLF method, the ΔΔG for active lesions (3.8 ± 5.6) was significantly higher than that for inactive lesions (1.0 ± 2.5) (P < 0.05). With the conventional QLF method, there was no significant difference in ΔΔG between active (-1.1 ± 1.7) and inactive (-1.3 ± 1.7) lesions. DEQLF-derived ΔΔG demonstrated an AUROC of 0.72, a sensitivity of 0.67, and a specificity of 0.76. ConclusionsApplying the DEQLF method to human teeth enabled the quantitative assessment of lesion activity based on dye penetration. DEQLF-derived ΔΔG values showed significant differences based on lesion activity status and demonstrated high validity in distinguishing lesion activity. Clinical significanceClinicians can use the DEQLF method, which involves applying a fluorescent dye for 10 s prior to conventional QLF, to objectively quantify and distinguish the activity status of early enamel caries, potentially replacing the traditional reliance on subjective visual assessments.

A novel heuristic of rigid docking scores positively correlates with full-length nuclear receptor LRH-1 regulation

The nuclear receptor Liver Receptor Homolog-1 (LRH-1, NR5A2) is a ligand-regulated transcription factor and validated drug target for several human diseases. LRH-1 activation is regulated by small molecule ligands, which bind to the ligand binding domain (LBD) within the full-length LRH-1. We recently identified 57 compounds that bind LRH-1, and unexpectedly found these compounds regulated either the isolated LBD, or the full-length LRH-1 in cells, with little overlap. Here, we correlated compound binding energy from a single rigid-body scoring function with full-length LRH-1 activity in cells. Although docking scores of the 57 hit compounds did not correlate with LRH-1 regulation in wet lab assays, a subset of the compounds had large differences in binding energy docked to the isolated LBD vs. full-length LRH-1, which we used to empirically derive a new metric of the docking scores we call "ΔΔG". Initial regressions, correlations and contingency analyses all suggest compounds with high ΔΔG values more frequently regulated LRH-1 in wet lab assays. We then docked all 57 compounds to 18 separate crystal structures of LRH-1 to obtain averaged ΔΔG values for each compound, which robustly and reproducibly associated with full-length LRH-1 activity in cells. Network analyses on the 18 crystal structures of LRH-1 suggest unique communication paths exist between the subsets of LRH-1 crystal structures that produced high vs. low ΔΔG values, identifying a structural relationship between ΔΔG and the position of Helix 6, a previously established regulatory helix important for LRH-1 regulation. Together, these data suggest rigid-body computational docking can be used to quickly calculate ΔΔG, which positively correlated with the ability of these 57 hit compounds to regulate full-length LRH-1 in cell-based assays. We propose ΔΔG as a novel computational tool that can be applied to LRH-1 drug screens to prioritize compounds for resource-intense secondary screening.

Transcending Lifshitz Theory: Reliable Prediction of Adhesion Forces between Hydrocarbon Surfaces in Condensed Phases Using Molecular Contact Thermodynamics.

Lifshitz theory is widely used to calculate interfacial interaction energies and underpins established approaches to the interpretation of measurement data from experimental methods including the surface forces apparatus and the atomic force microscope. However, a significant limitation of Lifshitz theory is that it uses the bulk dielectric properties of the medium to predict the work of adhesion. Here, we demonstrate that a different approach, in which the interactions between molecules at surfaces and in the medium are described by a set of surface site interaction points (SSIPs), yields interaction free energies that are correlated better with experimentally determined values. The work of adhesion W(Lifshitz) between hydrocarbon surfaces was calculated in 260 liquids using Lifshitz theory and compared with interaction free energies ΔΔG calculated using the SSIP model. The predictions of these models diverge in significant ways. In particular, ΔΔG values for hydrocarbon surfaces are typically small and vary little, but in contrast, W(Lifshitz) values span 4 orders of magnitude. Moreover, the SSIP model yields significantly different ΔΔG values in some liquids for which Lifshitz theory predicts similar values of W(Lifshitz). These divergent predictions were tested using atomic force microscopy. Experimentally determined works of adhesion were closer to the values predicted using the SSIP model than Lifshitz theory. In mixtures of methanol and benzyl alcohol, even greater differences were found in the interaction energies calculated using the two models: the value of ΔΔG calculated using the SSIP model declines smoothly as the benzyl alcohol concentration increases, and values are well correlated with experimental data; however, W(Lifshitz) decreases to a minimum and then increases, reaching a larger value for benzyl alcohol than for methanol. We conclude that the SSIP model provides more reliable estimates of the work of adhesion than Lifshitz theory.

Ligand Binding Affinity Prediction for Membrane Proteins with Alchemical Free Energy Calculation Methods.

Alchemical relative binding free energy (ΔΔG) calculations have shown high accuracy in predicting ligand binding affinity and have been used as important tools in computer-aided drug discovery and design. However, there has been limited research on the application of ΔΔG methods to membrane proteins despite the fact that these proteins represent a significant proportion of drug targets, play crucial roles in biological processes, and are implicated in numerous diseases. In this study, to predict the binding affinity of ligands to G protein-coupled receptors (GPCRs), we employed two ΔΔG calculation methods: thermodynamic integration (TI) with AMBER and the alchemical transfer method (AToM) with OpenMM. We calculated ΔΔG values for 53 transformations involving four class A GPCRs and evaluated the performance of AMBER-TI and AToM-OpenMM. In addition, we conducted tests using different numbers of windows and varying simulation times to achieve reliable ΔΔG results and to optimize resource utilization. Overall, both AMBER-TI and AToM-OpenMM show good agreement with the experimental data. Our results validate the applicability of AMBER-TI and AToM-OpenMM for optimization of lead compounds targeting membrane proteins.

Prediction and assessment of deleterious and disease causing nonsynonymous single nucleotide polymorphisms (nsSNPs) in human FOXP4 gene: An in-silico study

In humans, FOXP gene family is involved in embryonic development and cancer progression. The FOXP4 (Forkhead box protein P4) gene belongs to this FOXP gene family. FOXP4 gene plays a crucial role in oncogenesis. Single nucleotide polymorphisms are biological markers and common determinants of human diseases. Mutations can largely affect the function of the corresponding protein. Therefore, the molecular mechanism of nsSNPs in the FOXP4 gene needs to be elucidated. Initially, the SNPs of the FOXP4 gene were extracted from the dbSNP database and a total of 23124 SNPs was found, where 555 nonsynonymous, 20525 intronic, 1114 noncoding transcript, 334 synonymous were obtained and the rest were unspecified. Then, a series of bioinformatics tools (SIFT, PolyPhen2, SNAP2, PhD SNP, PANTHER, I-Mutant2.0, MUpro, GOR IV, ConSurf, NetSurfP 2.0, HOPE, DynaMut2, GeneMANIA, STRING and Schrodinger) were used to explore the effect of nsSNPs on FOXP4 protein function and structural stability. First, 555 nsSNPs were analyzed using SIFT, of which 57 were found as deleterious. Following, PolyPhen2, SNAP2, PhD SNP and PANTHER analyses, 10 nsSNPs (rs372762294, rs141899153, rs142575732, rs376938850, rs367607523, rs112517943, rs140387832, rs373949416, rs373949416 and rs376160648) were common and observed as deleterious, damaging and diseases associated. Following that, using I-Mutant2.0 and MUpro servers, 7 nsSNPs were found to be the most unstable. GOR IV predicted that these seven nsSNPs affect protein structure by altering the protein contents of alpha helixes, extended strands, and random coils. Following DynaMut2, 5 nsSNPs showed a decrease in the ΔΔG value compared with the wild-type and were found to be responsible for destabilizing the corresponding protein. GeneMANIA and STRING network revealed interaction of FOXP4 with other genes. Finally, molecular dynamics simulation analysis revealed consistent fluctuation in RMSD and RMSF values, Rg and hydrogen bonds in the mutant proteins compared with WT, which might alter the functional and structural stability of the corresponding protein. As a result, the aforementioned integrated comprehensive bioinformatic analyses provide insight into how various nsSNPs of the FOXP4 gene change the structural and functional properties of the corresponding protein, potentially proceeding with the pathophysiology of human diseases.

The two-step strategy for enhancing the specific activity and thermostability of alginate lyase AlyG2 with mechanism for improved thermostability

To overcome the trade-off challenge encountered in the engineering of alginate lyase AlyG2 from Seonamhaeicola algicola Gy8T and to expand its potential industrial applications, we devised a two-step strategy encompassing activity enhancement followed by thermal stability engineering. To enhance the specific activity of efficient AlyG2, we strategically substituted residues with bulky steric hindrance proximal to the active pocket with glycine or alanine. This led to the generation of three promising positive mutants, with particular emphasis on the T91S mutant, exhibiting a 1.91-fold specific activity compared to the wild type. To mitigate the poor thermal stability of T91S, mutants with negative ΔΔG values in the thermal flexibility region were screened out. Notably, the S72Ya mutant not only displayed 17.96 % further increase in specific activity but also exhibited improved stability compared to T91S, manifesting as a remarkable 30.97 % increase in relative activity following a 1-hour incubation at 42 °C. Furthermore, enhanced kinetic stability was observed. To gain deeper insights into the mechanism underlying the enhanced thermostability of the S72Ya mutant, we conducted molecular dynamics simulations, principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. The results unveiled a reduction in the flexibility of the surface loop, a stronger correlation dynamic and a narrower motion subspace in S72Ya system, along with the formation of more stable hydrogen bonds. Collectively, our findings suggest amino acids substitutions resulting in smaller side chains proximate to the active site can positively impact enzyme activity, while reducing the flexibility of surface loops emerges as a pivotal factor in conferring thermal stability. These insights offer valuable guidance and a framework for the engineering of other enzyme types.

Abstract 4890: In silico study of enzymes involved in heparan sulfate catabolic process in cancer resistant mammals

Abstract Some mammals such as elephants, bats, whales, and blind mole rats (Spalax) are resistant to cancer. One of the cancer protective mechanisms present in such species includes a reduced degradation of heparan sulfate (HS), an important component of the extracellular matrix (ECM), present in Spalax. Such effect occurs due to a splicing variant of heparanase, called variant 36, that lacks enzymatic activity. Consequently, both HS and ECM are very stable in Spalax’s tissues. If HS is stabilized, in cancer resistant mammals, due to the decrease of heparanase or other enzymes involved in HS catabolic process is unknown. We studied total of 9 enzymes (HPSE2, GusB, IDUA, IDS, NAGLU, SGSH, GNS, Sulf-2, HGSNAT) that regulate HS catabolism and homologs in 9 mammals. Multiple sequence alignments were done by MEGA to identify substitutions present in cancer resistant species in comparison with cancer susceptible animals. Such amino acid variants were further analyzed and both their energy stability and their functional effects were predicted by using online in silico tools including MAESTROweb, Condel, PANTHER, REVEL, and CADD. Finally, homologs with deleterious predicted variants were modelled with SWISSMODEL and their 3D structures were analyzed with Pymol and ChimeraX to identify structural features likely related to its loss of function. We found two loss of function missense variants, K264Q and W626L, in Alpha-L-iduronidase (IDUA) of Spalax. In addition, most of Brandt's bat enzymes and the N-sulphoglucosamine sulphohydrolase (SGSH) of the bowhead whale were very energy destabilizing enzymes with positive and higher ΔΔG values compared to human homologs. In the other hand, although some catalytic residues in the study enzymes are conserved in cancer resistant animals, their spatial arrangement and conformation in the 3D structure are different compared to human homologs, including E182 of IDUA which is one of the catalytic residues. In general, the secondary structure is conserved across the 9 enzymes studied but some differences were observed in cancer resistant animals including one of the beta strands near the catalytic domain in human and mice IDUA that appears as a loop in Spalax. In summary, HS stabilization could raise in cancer resistant mammals through the existence of lack of enzymatic activity not only in heparanase but also in other enzymes that participate in HS catabolic process, via a set of loss of function variants and changes in secondary and tertiary structure as well as a reduction of energy stabilization. More interestingly, such mechanism could be present in other cancer resistant mammals such as bats and bowhead whales. This study demonstrates that computational approaches are useful to study biological mechanisms of cancer resistance present in some mammals. This knowledge could be translated to humans and HS catabolic process could offer a new source of therapeutic anticancer targets. Citation Format: Fabrizio Oliveri Payet, Claudia Machicado Rivero. In silico study of enzymes involved in heparan sulfate catabolic process in cancer resistant mammals [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 4890.

Computational Mutagenesis of Antibody Fragments: Disentangling Side Chains from ΔΔG Predictions.

The development of highly potent antibodies and antibody fragments as binding agents holds significant implications in fields such as biosensing and biotherapeutics. Their binding strength is intricately linked to the arrangement and composition of residues at the binding interface. Computational techniques offer a robust means to predict the three-dimensional structure of these complexes and to assess the affinity changes resulting from mutations. Given the interdependence of structure and affinity prediction, our objective here is to disentangle their roles. We aim to evaluate independently six side-chain reconstruction methods and ten binding affinity estimation techniques. This evaluation was pivotal in predicting affinity alterations due to single mutations, a key step in computational affinity maturation protocols. Our analysis focuses on a data set comprising 27 distinct antibody/hen egg white lysozyme complexes, each with crystal structures and experimentally determined binding affinities. Using six different side-chain reconstruction methods, we transformed each structure into its corresponding mutant via in silico single-point mutations. Subsequently, these structures undergo minimization and molecular dynamics simulation. We therefore estimate ΔΔG values based on the original crystal structure, its energy-minimized form, and the ensuing molecular dynamics trajectories. Our research underscores the critical importance of selecting reliable side-chain reconstruction methods and conducting thorough molecular dynamics simulations to accurately predict the impact of mutations. In summary, our study demonstrates that the integration of conformational sampling and scoring is a potent approach to precisely characterizing mutation processes in single-point mutagenesis protocols and crucial for computational antibody design.

Computer-Aided Rational Design Strategy to Improve the Thermal Stability of Alginate Lyase AlyMc.

Alginate lyase degrades alginate by the β-elimination mechanism to produce unsaturated alginate oligosaccharides (UAOS), which have better bioactivities than saturated AOS. Enhancing the thermal stability of alginate lyases is crucial for their industrial applications. In this study, a feasible and efficient rational design strategy was proposed by combining the computer-aided ΔΔG value calculation with the B-factor analysis. Two thermal stability-enhanced mutants, Q246V and K249V, were obtained by site-directed mutagenesis. Particularly, the t1/2,50°C for mutants Q246V and K249V was increased from 2.36 to 3.85 and 3.65 h, respectively. Remarkably, the specific activities of Q246V and K249V were enhanced to 2.41- and 2.96-fold that of alginate lyase AlyMc, respectively. Structural analysis and molecular dynamics simulations suggested that mutations enhanced the hydrogen bond networks and the overall rigidity of the molecular structure. Notably, mutant Q246V exhibited excellent thermal stability among the PL-7 alginate lyase family, especially considering the heightened enzymatic activity. Moreover, the rational design strategy used in this study can effectively improve the thermal stability of enzymes and has important significance in advancing applications of alginate lyase.

Identification of a Novel Variant c.163delG in HBB Gene Resulting in a Beta Null Phenotype in a Proband with Thalassemia Intermedia

A 21-year-old patient presented with a previous medical history of pallor, mild icterus, increased fatigue, low hemoglobin, and abnormal hemoglobin variant analysis with more than 70 transfusions. He was referred for genetic analysis to identify the pathogenic variations in the β-globin gene. Sanger’s sequencing of the proband and his family revealed the presence of a novel frame shift variant HBB:c.163delG in a compound heterozygous state with hemoglobin E (HbE) (HBB:c.79G > A) variant. The father and the sibling of the patient were found to be normal for the HBB gene. Mother was found to be heterozygous for HbE (HBB:c.79G > A) variant. In silico analysis by Mutalyzer predicted that c.163delG variant generated a premature stop codon after seven codons, leading to a truncated protein. FoldX protein stability analysis showed a positive ΔΔG value of 45.27 kcal/mol suggesting a decrease in protein stability. HBB:c.79G > A is a known variant coding for HbE variant, which results in the reduced synthesis of β-globin chain and shows mild thalassemia. Combined effect of HBB:c.163delG and HBB:c.79G > A variants in the proband might have led to the reduced synthesis of β-globin chains resulting in a thalassemia intermedia type of clinical manifestation.

In silico analysis of deleterious SNPs of human DCDC2 gene and their impacts on subsequent protein-protein interactions

DCDC2 is a clinically significant protein causing a number of neurological disorders and, hence, is an important protein for analysis. In this study, multiple tools were employed to identify missense SNPs that are harmful to the protein itself and destabilize the interaction of this protein with tubulin subunits. After analyzing all 378 missense SNPs retrieved from the dbSNP database, thirteen were found to have harmful effects on the protein, which are L20P, R23L, G25W, G25R, D26E, I36N, G60E, P68S, G83R, T174I, L179R, R186G, V208E. Among these, four SNPs- T174I, L179R, R186G, and V208E were suggested to be significantly destabilizing for the interaction of the C-DC domain with microtubule, and three SNPs- L20P, D26E, and G83R for the interaction of N-DC domain with microtubule. Based on the total ΔΔG value, SNP R186G and L20P seem most destabilizing for the interaction of the C-DC and N-DC domains. These SNPs are found to affect the protein negatively by analysis using several computational tools. Genetic association and protein-protein interaction studies focused on these SNPs can reveal new findings about dyslexia or other neurodevelopmental disorders. J. Bangladesh Acad. Sci. 47(2); 181-193: December 2023

Quantum Chemical Insight into 1,2-Shift Rearrangement in Bromination of Allylaryls.

In this work, we have provided mechanistic insight into the addition of bromine to an allylic double bond of allylaryl derivatives using experimental and DFT-based electronic structure methods. The experimental yields indicate the influence of the functional group on the aryl ring on the ratio of 1,2-dibromo and 1,3-dibromo adducts formed in the reaction. The optimized geometry and the electron density maps of the allylaryls and their cationic intermediates from DFT simulations revealed that electron-rich aryl rings promoted formation of cationic spiro[2.5] intermediate II, whereas electron-poor aryl rings resulted in formation of bromonium intermediate I. It was observed that electron-rich allylaryls promoted the 1,2-shift of the aryl ring that resulted in bond formation between the carbon atom (C1) on the aryl ring and the central carbon atom (C3) in the allylic double bond and formed spiro[2.5] intermediate II, a trend which was confirmed by harmonic oscillator model of aromaticity index. Also, Wiberg bond order analysis is in good agreement with the experimental work. Thermochemical analysis indicates that smaller C1···C3 distance resulted in favorable values for the difference in free energy change (ΔΔG). The favorable ΔΔG values are a result of higher electron density on the aryl ring, making it more nucleophilic toward C3 carbon and promoting 1,2-shift that led to formation of the spiro[2.5] intermediate. Thus, the underlying mechanism indicates that the electron-rich allylaryls promote the formation of 1,3-dibromo compounds through formation and stabilization of the spiro[2.5] intermediate II.

Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States.

The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.

In silico screening of non-synonymous SNPs in human TUFT1 gene

BackgroundTuftelin 1 (TUFT1) gene is important in the development and mineralization of dental enamel. The study aimed to identify potential functionally deleterious non-synonymous SNPs (nsSNPs) in the TUFT1 gene by using different in silico tools. The deleterious missense SNPs were identified from SIFT, PolyPhen-2, PROVEAN, SNPs & GO, PANTHER, and SNAP2. The stabilization, conservation, and three-dimensional modeling of mutant proteins were analyzed by I-Mutant 3.0, Consurf, and Project HOPE, respectively. The protein–protein interaction using STRING, GeneMANIA for gene–gene interaction, and DynaMut for evaluating the impact of the mutation on protein stability, conformation, and flexibility. ResultsEight deleterious nsSNPs (E242A, R303W, K182N, K123N, R117W, H289Q, R203W, and Q107R) out of 304 were found to have high-risk damaging effects using six in silico tools. Among them, K182N and K123N alone had increased stability, whereas E242A, R303W, R117W, H289Q, Q107R, and R203W exhibited a decrease in protein stability, based on DDG values. Meanwhile, all the eight deleterious nsSNPs altered the size, charge, hydrophobicity, and spatial organization of the amino acids and predominantly had alpha helix domains. These deleterious variants were located in highly conserved regions except R203W. Protein–protein interaction predicted that TUFT1 interacted with ten proteins that are involved in enamel mineralization and odontogenesis. Gene–gene interaction network showed that TUFT1 is involved in physical interactions, gene co-localization, and pathway interactions. DynaMut ΔΔG values predicted that five nsSNPs were destabilizing the protein, ΔΔG ENCoM values showed a destabilizing effect for all mutants, and seven nsSNPs increased the molecular flexibility of TUFT1. ConclusionOur study predicted eight functional SNPs that had detrimental effects on the structure and function of the TUFT1 gene. This will aid in the development of candidate deleterious markers as a potential target for disease diagnosis and therapeutic interventions.

Identification of a novel variant c.761C>T on ABO*B.01 gene in ABO glycosyltransferases associated with Bweak phenotype.

ABO antigens are produced from H antigen by the activity of glycosyltransferase enzyme encoded by the ABO gene. Variants in the ABO gene can produce a weak ABO phenotype. In this study, we identify a novel ABO*BW allele and investigate the underlying mechanism leading to the Bweak phenotype. The ABO phenotype and genotype of the sample were determined using serological and direct DNA sequencing methods. We assessed the impact of the novel variant by three-dimensional modelling to predict protein stability changes (ΔΔG), and carried out an in vitro expression assay. The total glycosyltransferase transfer capacity in the supernatant of transfected cells was also examined. Serological analysis confirmed the Bweak phenotype in the subject, and gene sequencing identified a novel variant c.761C>T (p.A254V) on the ABO*B.01 allele, resulting in a BW-var/O.01.02 genotype. In silico analysis suggested that the p.A254V variant on the B allele may reduce the stability of glycosyltransferase B (GTB), as indicated by the ΔΔG values. In vitro expression studies showed that the variant p.A254V impaired H to B antigen conversion, although it did not affect the expression of GTB. We identified a novel BW allele and demonstrated that the variant c.761C>T (p.A254V) can cause the Bweak phenotype by reducing the stability of GTB.

Seasonal and water restriction-related changes in Eucalyptus grandis leaf proteins: Shedding light on the dark proteome

Climate change is escalating the frequency and intensity of warming and drought periods around the globe, currently representing a threat to many plant species. Understanding how plants cope with such abiotic stresses is crucial.We investigate how Eucalyptus grandis, a plant species with several industry applications, copes with seasonal variation and water restriction imposition at the proteomic level under field conditions. Therefore, we attempted to identify known proteins and novel peptides associated with the effect of seasonality and water restriction impositions, as well as to provide insights into how novel peptides behave under such conditions. The leaf proteome of E. grandis plants was studied under both a conventional proteomic workflow and a dedicated proteogenomics approach. The highest proteomic variability was identified in the summer season and the most abundant known proteins associated with seasonal variation were related to photosynthesis. Post-translational modifications, protein turnover, and chaperones were the main functional classifications identified among biological treatments. Furthermore, 144 novel peptides not predicted by current proteomics pipelines, were identified by both spectral correlations against modified databases (43) and a de novo peptide sequencing approach (101). It is predicted that most single amino acid substituted (SAS) peptides, mainly associated with the photosynthesis process, decrease protein stability by altering the quantitative change upon ΔΔG values and non-covalent interactions. Multiple reaction monitoring validation assays were performed for selected novel peptide identifications demonstrating that it is a very robust mass spectrometry-based method of validation. Data are available via ProteomeXchange with identifier PXD031100.

Conformational dynamics of A30G α-synuclein that causes familial Parkinson disease

The first gene shown to be responsible for autosomal-dominant Parkinson’s disease (PD) is the SNCA gene, which encodes for alpha synuclein (α-Syn). Recently, a novel heterozygous A30G mutation of the SNCA gene associated with familial PD has been reported. However, little research has been done on how the A30G mutation affects the structure of α-Syn. So, using atomistic molecular dynamics (MD) simulation, we demonstrate here the key structural characteristics of A30G α-Syn in the free monomer form and membrane associated state. From the MD trajectory analysis, the structure of A30G α-Syn was noticed to exhibit rapid conformational change, increase in backbone flexibility near the site of mutation and decrease in α-helical propensity. The typical torsion angles in residues (Val26 and Glu28) near the mutation site were observed to deviate significantly in A30G α-Syn. In the case of membrane bound A30G α-Syn, the regions that were submerged in the lipid bilayer (N-helix (3-37) and turn region (38-44)) found to contain higher helical content than the elevated region above the lipid surface. The bending angle in the helix-N and helix-C regions were noticed to be relatively higher in the free form of A30G α-Syn (38.50) than in the membrane bound form (370). The A30G mutation in α-Syn was predicted to have an impact on the stability and function of the protein based on ΔΔG values obtained from the online servers. Our results demonstrate that the A30G mutation in α-Syn altered the protein’s α-helical structure and slightly altered the membrane binding. Communicated by Ramaswamy H. Sarma

Using AlphaFold to predict the impact of single mutations on protein stability and function.

AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted the pLDDT and <pLDDT> metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the same AlphaFold pLDDT metrics with the impact of a single mutation on structure using a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold may not be immediately applied to other problems or applications in protein folding.

Regeneration and Degradation in a Biomimetic Polyoxometalate Water Oxidation Catalyst.

Complete understanding of catalytic cycles is required to advance the design of water oxidation catalysts, but it is difficult to attain, due to the complex factors governing their reactivity and stability. In this study, we investigate the regeneration and degradation pathways of the highly active biomimetic water oxidation catalyst [Mn3+ 2Mn4+ 2V4O17(OAc)3]3-, thereby completing its catalytic cycle. Beginning with the deactivated species [Mn3+ 4V4O17(OAc)2]4- left over after O2 evolution, we scrutinize a network of reaction intermediates belonging to two alternative water oxidation cycles. We find that catalyst regeneration to the activated species [Mn4+ 4V4O17(OAc)2(OH)(H2O)]- proceeds via oxidation of each Mn center, with one water ligand being bound during the first oxidation step and a second water ligand being bound and deprotonated during the final oxidation step. ΔΔG values for this last oxidation are consistent with previous experimental results, while regeneration within an alternative catalytic cycle was found to be thermodynamically unfavorable. Extensive in silico sampling of catalyst structures also revealed two degradation processes: cubane opening and ligand dissociation, both of which have low barriers at highly reduced states of the catalyst due to the presence of Jahn-Teller effects. These mechanistic insights are expected to spur the development of more efficient and stable Mn cubane water oxidation catalysts.

Biochemical and Bioinformatic Studies of Mutations of Residues at the Monomer-Monomer Interface of Human Ornithine Aminotransferase Leading to Gyrate Atrophy of Choroid and Retina.

Deficit of human ornithine aminotransferase (hOAT), a mitochondrial tetrameric pyridoxal-5'-phosphate (PLP) enzyme, leads to gyrate atrophy of the choroid and retina (GA). Although 70 pathogenic mutations have been identified, only few enzymatic phenotypes are known. Here, we report biochemical and bioinformatic analyses of the G51D, G121D, R154L, Y158S, T181M, and P199Q pathogenic variants involving residues located at the monomer-monomer interface. All mutations cause a shift toward a dimeric structure, and changes in tertiary structure, thermal stability, and PLP microenvironment. The impact on these features is less pronounced for the mutations of Gly51 and Gly121 mapping to the N-terminal segment of the enzyme than those of Arg154, Tyr158, Thr181, and Pro199 belonging to the large domain. These data, together with the predicted ΔΔG values of monomer-monomer binding for the variants, suggest that the proper monomer-monomer interactions seem to be correlated with the thermal stability, the PLP binding site and the tetrameric structure of hOAT. The different impact of these mutations on the catalytic activity was also reported and discussed on the basis of the computational information. Together, these results allow the identification of the molecular defects of these variants, thus extending the knowledge of enzymatic phenotypes of GA patients.