Graphormer supervised de novo protein design method and function validation.

Protein design is central to nearly all protein engineering problems, as it can enable the creation of proteins with new biological functions, such as improving the catalytic efficiency of enzymes. One key facet of protein design, fixed-backbone protein sequence design, seeks to design new sequences that will conform to a prescribed protein backbone structure. Nonetheless, existing sequence design methods present limitations, such as low sequence diversity and shortcomings in experimental validation of the designed functional proteins. These inadequacies obstruct the goal of functional protein design. To improve these limitations, we initially developed the Graphormer-based Protein Design (GPD) model. This model utilizes the Transformer on a graph-based representation of three-dimensional protein structures and incorporates Gaussian noise and a sequence random masks to node features, thereby enhancing sequence recovery and diversity. The performance of the GPD model was significantly better than that of the state-of-the-art ProteinMPNN model on multiple independent tests, especially for sequence diversity. We employed GPD to design CalB hydrolase and generated nine artificially designed CalB proteins. The results show a 1.7-fold increase in catalytic activity compared to that of the wild-type CalB and strong substrate selectivity on p-nitrophenyl acetate with different carbon chain lengths (C2-C16). Thus, the GPD method could be used for the de novo design of industrial enzymes and protein drugs. The code was released at https://github.com/decodermu/GPD.

Phanto-IDP: compact model for precise intrinsically disordered protein backbone generation and enhanced sampling.

The biological function of proteins is determined not only by their static structures but also by the dynamic properties of their conformational ensembles. Numerous high-accuracy static structure prediction tools have been recently developed based on deep learning; however, there remains a lack of efficient and accurate methods for exploring protein dynamic conformations. Traditionally, studies concerning protein dynamics have relied on molecular dynamics (MD) simulations, which incur significant computational costs for all-atom precision and struggle to adequately sample conformational spaces with high energy barriers. To overcome these limitations, various enhanced sampling techniques have been developed to accelerate sampling in MD. Traditional enhanced sampling approaches like replica exchange molecular dynamics (REMD) and frontier expansion sampling (FEXS) often follow the MD simulation approach and still cost a lot of computational resources and time. Variational autoencoders (VAEs), as a classic deep generative model, are not restricted by potential energy landscapes and can explore conformational spaces more efficiently than traditional methods. However, VAEs often face challenges in generating reasonable conformations for complex proteins, especially intrinsically disordered proteins (IDPs), which limits their application as an enhanced sampling method. In this study, we presented a novel deep learning model (named Phanto-IDP) that utilizes a graph-based encoder to extract protein features and a transformer-based decoder combined with variational sampling to generate highly accurate protein backbones. Ten IDPs and four structured proteins were used to evaluate the sampling ability of Phanto-IDP. The results demonstrate that Phanto-IDP has high fidelity and diversity in the generated conformation ensembles, making it a suitable tool for enhancing the efficiency of MD simulation, generating broader protein conformational space and a continuous protein transition path.

Multi-indicator comparative evaluation for deep learning-based protein sequence design methods.

MOTIVATION: Proteins found in nature represent only a fraction of the vast space of possible proteins. Protein design presents an opportunity to explore and expand this protein landscape. Within protein design, protein sequence design plays a crucial role, and numerous successful methods have been developed. Notably, deep learning-based protein sequence design methods have experienced significant advancements in recent years. However, a comprehensive and systematic comparison and evaluation of these methods have been lacking, with indicators provided by different methods often inconsistent or lacking effectiveness. RESULTS: To address this gap, we have designed a diverse set of indicators that cover several important aspects, including sequence recovery, diversity, root-mean-square deviation of protein structure, secondary structure, and the distribution of polar and nonpolar amino acids. In our evaluation, we have employed an improved weighted inferiority-superiority distance method to comprehensively assess the performance of eight widely used deep learning-based protein sequence design methods. Our evaluation not only provides rankings of these methods but also offers optimization suggestions by analyzing the strengths and weaknesses of each method. Furthermore, we have developed a method to select the best temperature parameter and proposed solutions for the common issue of designing sequences with consecutive repetitive amino acids, which is often encountered in protein design methods. These findings can greatly assist users in selecting suitable protein sequence design methods. Overall, our work contributes to the field of protein sequence design by providing a comprehensive evaluation system and optimization suggestions for different methods.

Transcriptome-wide subtyping of pediatric and adult T cell acute lymphoblastic leukemia in an international study of 707 cases.

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy of T cell progenitors, known to be a heterogeneous disease in pediatric and adult patients. Here we attempted to better understand the disease at the molecular level based on the transcriptomic landscape of 707 T-ALL patients (510 pediatric, 190 adult patients, and 7 with unknown age; 599 from published cohorts and 108 newly investigated). Leveraging the information of gene expression enabled us to identify 10 subtypes (G1­G10), including the previously undescribed one characterized by GATA3 mutations, with GATA3R276Q capable of affecting lymphocyte development in zebrafish. Through associating with T cell differentiation stages, we found that high expression of LYL1/LMO2/SPI1/HOXA (G1­G6) might represent the early T cell progenitor, pro/precortical/cortical stage with a relatively high age of disease onset, and lymphoblasts with TLX3/TLX1 high expression (G7­G8) could be blocked at the cortical/postcortical stage, while those with high expression of NKX2-1/TAL1/LMO1 (G9­G10) might correspond to cortical/postcortical/mature stages of T cell development. Notably, adult patients harbored more cooperative mutations among epigenetic regulators, and genes involved in JAK-STAT and RAS signaling pathways, with 44% of patients aged 40 y or above in G1 bearing DNMT3A/IDH2 mutations usually seen in acute myeloid leukemia, suggesting the nature of mixed phenotype acute leukemia.

Map conformational landscapes of intrinsically disordered proteins with polymer physics quantities.

Disordered proteins are conformationally flexible proteins that are biologically important and have been implicated in devastating diseases such as Alzheimer's disease and cancer. Unlike stably folded structured proteins, disordered proteins sample a range of different conformations that needs to be accounted for. Here, we treat disordered proteins as polymer chains, and compute a dimensionless quantity called instantaneous shape ratio (Rs), as Rs = Ree2/Rg2, where Ree is end-to-end distance and Rg is radius of gyration. Extended protein conformations tend to have high Ree compared with Rg, and thus have high Rs values, whereas compact conformations have smaller Rs values. We use a scatter plot of Rs (representing shape) against Rg (representing size) as a simple map of conformational landscapes. We first examine the conformational landscape of simple polymer models such as Random Walk, Self-Avoiding Walk, and Gaussian Walk (GW), and we notice that all protein/polymer maps lie within the boundaries of the GW map. We thus use the GW map as a reference and, to assess conformational diversity, we compute the fraction of the GW conformations (fC) covered by each protein/polymer. Disordered proteins all have high fC scores, consistent with their disordered nature. Each disordered protein accesses a different region of the reference map, revealing differences in their conformational ensembles. We additionally examine the conformational maps of the nonviral gene delivery vector polyethyleneimine at various protonation states, and find that they resemble disordered proteins, with coverage of the reference map decreasing with increasing protonation state, indicating decreasing conformational diversity. We propose that our method of combining Rs and Rg in a scatter plot generates a simple, meaningful map of the conformational landscape of a disordered protein, which in turn can be used to assess conformational diversity of disordered proteins.

PTMint database of experimentally verified PTM regulation on protein-protein interaction.

MOTIVATION: Post-translational modification (PTM) is an important biochemical process. which includes six most well-studied types: phosphorylation, acetylation, methylation, sumoylation, ubiquitylation and glycosylation. PTM is involved in various cell signaling pathways and biological processes. Abnormal PTM status is closely associated with severe diseases (such as cancer and neurologic diseases) by regulating protein functions, such as protein-protein interactions (PPIs). A set of databases was constructed separately for PTM sites and PPI; however, the resource of regulation for PTM on PPI is still unsolved. RESULTS: Here, we firstly constructed a public accessible database of PTMint (PTMs that are associated with PPIs) (https://ptmint.sjtu.edu.cn/) that contains manually curated complete experimental evidence of the PTM regulation on PPIs in multiple organisms, including Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae and Schizosaccharomyces pombe. Currently, the first version of PTMint encompassed 2477 non-redundant PTM sites in 1169 proteins affecting 2371 protein-protein pairs involving 357 diseases. Various annotations were systematically integrated, such as protein sequence, structure properties and protein complex analysis. PTMint database can help to insight into disease mechanism, disease diagnosis and drug discovery associated with PTM and PPI. AVAILABILITY AND IMPLEMENTATION: PTMint is freely available at: https://ptmint.sjtu.edu.cn/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Early Aggregation Mechanism of SOD128-38 Based on Force Field Parameter of 5-Cyano-Tryptophan.

The aggregation of superoxide dismutase 1 (SOD1) results in amyloid deposition and is involved in familial amyotrophic lateral sclerosis, a fatal motor neuron disease. There have been extensive studies of its aggregation mechanism. Noncanonical amino acid 5-cyano-tryptophan (5-CN-Trp), which has been incorporated into the amyloid segments of SOD1 as infrared probes to increase the structural sensitivity of IR spectroscopy, is found to accelerate the overall aggregation rate and potentially modulate the aggregation process. Despite these observations, the underlying mechanism remains elusive. Here, we optimized the force field parameters of 5-CN-Trp and then used molecular dynamics simulation along with the Markov state model on the SOD128-38 dimer to explore the kinetics of key intermediates in the presence and absence of 5-CN-Trp. Our findings indicate a significantly increased probability of protein aggregate formation in 5CN-Trp-modified ensembles compared to wildtype. Dimeric ß-sheets of different natures were observed exclusively in the 5CN-Trp-modified peptides, contrasting with wildtype simulations. Free-energy calculations and detailed analyses of the dimer structure revealed augmented interstrand interactions attributed to 5-CN-Trp, which contributed more to peptide affinity than any other residues. These results explored the key events critical for the early nucleation of amyloid-prone proteins and also shed light on the practice of using noncanonical derivatives to study the aggregation mechanism.

Four undescribed coumarin derivatives, with ten amides from the roots of Ficus hirta and their cytotoxic activities.

Four undescribed coumarin derivatives, ficusalt A (1) and ficusalt B (2), a pair of racemic coumarins, (±) ficudimer A (3a/3b), along with ten known amides, were isolated from the roots of Ficus hirta. Their structures were elucidated by several spectroscopic data analyses, including HRESIMS, NMR, and X-ray single-crystal diffraction. The cytotoxic activities of all compounds against HeLa, HepG2, MCF-7, and H460 cell lines were detected using the MTT assay. Among these, 5 showed the highest activity against HeLa cells. Subsequently, the apoptotic, anti-invasive, and anti-migration effects of 5 on HeLa cells were determined by flow cytometer, transwell invasion assay, and wound-healing assay, respectively. The result suggested that 5 distinctly induced the apoptosis in HeLa cells and inhibited their invasion and migration. Further studies on anticancer mechanisms were conducted using Western blotting. As a result, 5 increased the cleavage of PARP and the expression of pro-apoptotic protein Bax. Moreover, 5 notably upregulated the phosphorylation of p38 and JNK, whereas inhibited the expression of p-ERK and p-AKT. Our results demonstrated that 5 could be a potential leading compound for further application in the treatment of cervical cancer.

Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning.

Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associated with Parkinson's disease, Alzheimer's disease, cancer, cardiovascular disease, amyloidosis, diabetes, and other diseases. Experimental methods can hardly capture the ensemble of diverse conformations for IDPs. Molecular dynamics (MD) simulations can sample continuous conformations that might provide a valuable complement to experimental data. However, the accuracy of MD simulations depends on the quality of force field. In particular, the evolutionary conservation and coevolution of IDPs introduce that current force fields could not precisely reproduce the conformation of IDPs. In order to improve the performance of force field, deep learning and reweighting methods were used to automatically generate personal force field parameters for intrinsically disordered and ordered proteins. At first, the deep learning method predicted more accuracy φ/ψ dihedral of residue than the previous method. Then, reweighting optimized the personal force field parameters for each residue. Finally, typical representative systems such as IDPs, structure protein, and fast-folding protein were used to evaluate this force field. The results indicate that two personal force field parameters (named PPFF1 and PPFF1_af2) could better reproduce the experimental observables than ff03CMAP force field. In summary, this strategy will provide feasibility for the development of precise personal force fields.

Phosphorylation Modification Force Field FB18CMAP Improving Conformation Sampling of Phosphoproteins.

Phosphorylation of proteins plays an important regulatory role at almost all levels of cellular organization. Molecular dynamics (MD) simulation is a promising tool to reveal the mechanism of how phosphorylation regulates many key biological processes at the atomistic level. MD simulation accuracy depends on force field precision, while the current force fields for phospho-amino acids have resulted in notable inconsistency with experimental data. Here, a new force field parameter (named FB18CMAP) is generated by fitting against quantum mechanics (QM) energy in aqueous solution with φ/ψ dihedral potential-energy surfaces optimized using CMAP parameters. MD simulations of phosphorylated dipeptides, intrinsically disordered proteins (IDPs), and ordered (folded) proteins show that FB18CMAP can mimic NMR observables and structural characteristics of phosphorylated dipeptides and proteins more accurately than the FB18 force field. These findings suggest that FB18CMAP performs well in both the simulation of ordered and disordered states of phosphorylated proteins.

Phosphorylation Regulation Mechanism of ß2 Integrin for the Binding of Filamin Revealed by Markov State Model.

Leukocyte adhesion deficiency-1 (LAD-1) disorder is a severe immunodeficiency syndrome caused by deficiency or mutation of ß2 integrin. The phosphorylation on threonine 758 of ß2 integrin acts as a molecular switch inhibiting the binding of filamin. However, the switch mechanism of site-specific phosphorylation at the atom level is still poorly understood. To resolve the regulation mechanism, all-atom molecular dynamics simulation and Markov state model were used to study the dynamic regulation pathway of phosphorylation. Wild type system possessed lower binding free energy and fewer number of states than the phosphorylated system. Both systems underwent local disorder-to-order conformation conversion when achieving steady states. To reach steady states, wild type adopted less number of transition paths/shortest path according to the transition path theory than the phosphorylated system. The underlying phosphorylated regulation pathway was from P1 to P0 and then P4 state, and the main driving force should be hydrogen bond and hydrophobic interaction disturbing the secondary structure of phosphorylated states. These studies will shed light on the pathogenesis of LAD-1 disease and lay a foundation for drug development.

Research and Evaluation of the Allosteric Protein-Specific Force Field Based on a Pre-Training Deep Learning Model.

Allosteric modulators are important regulation elements that bind the allosteric site beyond the active site, leading to the changes in dynamic and/or thermodynamic properties of the protein. Allosteric modulators have been a considerable interest as potential drugs with high selectivity and safety. However, current experimental methods have limitations to identify allosteric sites. Therefore, molecular dynamics simulation based on empirical force field becomes an important complement of experimental methods. Moreover, the precision and efficiency of current force fields need improvement. Deep learning and reweighting methods were used to train allosteric protein-specific precise force field (named APSF). Multiple allosteric proteins were used to evaluate the performance of APSF. The results indicate that APSF can capture different types of allosteric pockets and sample multiple energy-minimum reference conformations of allosteric proteins. At the same time, the efficiency of conformation sampling for APSF is higher than that for ff14SB. These findings confirm that the newly developed force field APSF can be effectively used to identify the allosteric pocket that can be further used to screen potential allosteric drugs based on these pockets.

Severe wound infection by MRCNS following bilateral inguinal herniorrhaphy.

BACKGROUND: Wound infection after inguinal hernia surgery is not uncommon in the clinical setting. The common microbial aetiology of postoperative inguinal hernia wound infection is Gram-positive bacteria. Staphylococcus aureus is a common pathogen causing wound infection while Staphylococcus epidermidis and Pseudomonas are rare. Staphylococcus epidermidis as a cause of severe wound infection is rarely described in literature. We herein present a case of a 79-year-old man with a rare wound infection after bilateral inguinal herniorrhaphy caused by MRCNS (Methicillin Resistant Coagulase Negative Staphylococcus). CASE PRESENTATION: We present a case of wound infection accompanied by fever with a temperature of 38.8 °C after bilateral inguinal herniorrhaphy in a 79-year-old man. Bilateral inguinal wounds were marked by redness and swelling, with skin necrosis. In addition, an abscess of approximately 1.5 cm × 1.5 cm was seen on the left wrist. A small amount of gas under the skin in the wound area was observed after pelvic computed tomography (CT) scans. No bacteria were cultured from the inguinal wound discharge, while blood culture detected MRCNS, and Acinetobacter lwoffi was cultured from the pus in the left wrist. We chose appropriate antibiotics based on the results of the bacterial culture and the drug susceptibility results. Vacuum assisted closure (VAC) therapy was used after debridement. The patient was discharged after the wounds improved. He was followed up for ten months and showed no signs of complications. We are sharing our experience along with literature review. CONCLUSIONS: We are presenting a rare case of MRCNS wound infection following open inguinal hernia surgery. Although a rarity, clinicians performing inguinal hernia surgery must consider this entity in an infected wound and follow up the patient for complications of MRCNS.

Enhancing Conformational Sampling for Intrinsically Disordered and Ordered Proteins by Variational Autoencoder.

Intrinsically disordered proteins (IDPs) account for more than 50% of the human proteome and are closely associated with tumors, cardiovascular diseases, and neurodegeneration, which have no fixed three-dimensional structure under physiological conditions. Due to the characteristic of conformational diversity, conventional experimental methods of structural biology, such as NMR, X-ray diffraction, and CryoEM, are unable to capture conformational ensembles. Molecular dynamics (MD) simulation can sample the dynamic conformations at the atomic level, which has become an effective method for studying the structure and function of IDPs. However, the high computational cost prevents MD simulations from being widely used for IDPs conformational sampling. In recent years, significant progress has been made in artificial intelligence, which makes it possible to solve the conformational reconstruction problem of IDP with fewer computational resources. Here, based on short MD simulations of different IDPs systems, we use variational autoencoders (VAEs) to achieve the generative reconstruction of IDPs structures and include a wider range of sampled conformations from longer simulations. Compared with the generative autoencoder (AEs), VAEs add an inference layer between the encoder and decoder in the latent space, which can cover the conformational landscape of IDPs more comprehensively and achieve the effect of enhanced sampling. Through experimental verification, the Cα RMSD between VAE-generated and MD simulation sampling conformations in the 5 IDPs test systems was significantly lower than that of AE. The Spearman correlation coefficient on the structure was higher than that of AE. VAE can also achieve excellent performance regarding structured proteins. In summary, VAEs can be used to effectively sample protein structures.

Polarizable Force Field of Intrinsically Disordered Proteins with CMAP and Reweighting Optimization.

Intrinsically disordered proteins (IDPs) are highly structurally heterogeneous without a specific tertiary structure under physiology conditions and play key roles in the development of human diseases. Due to the characteristics of diverse conformations, as one of the important methods, molecular dynamics simulation can complement information for experimental methods. Because of the enrichment for charged amino acids for IDPs, polarizable force fields should be a good choice for the simulation of IDPs. However, current polarizable force fields are limited in sampling conformer features of IDPs. Therefore, a polarizable force field was released and named Drude2019IDP based on Drude2019 with reweighting and grid-based potential energy correction map optimization. In order to evaluate the performance of Drude2019IDP, 16 dipeptides, 18 short peptides, 3 representative IDPs, and 5 structural proteins were simulated. The results show that the NMR observables driven by Drude2019IDP are in better agreement with the experiment data than those by Drude2019 on short peptides and IDPs. Drude2019IDP can sample more diverse conformations than Drude2019. Furthermore, the performances of the two force fields are similar to the sample ordered proteins. These results confirm that the developed Drude2019IDP can improve the reproduction of conformers for intrinsically disordered proteins and can be used to gain insight into the paradigm of sequence-disorder for IDPs.

RNA-Specific Force Field Optimization with CMAP and Reweighting.

RNA plays a key role in a variety of cell activities. However, it is difficult to capture its structure dynamics by the traditional experimental methods because of the inherent limitations. Molecular dynamics simulation has become a valuable complement to the experimental methods. Previous studies have indicated that the current force fields cannot accurately reproduce the conformations and structural dynamics of RNA. Therefore, an RNA-specific force field was developed to improve the conformation sampling of RNA. The distribution of ζ/α dihedrals of tetranucleotides was optimized by a reweighting method, and the grid-based energy correction map (CMAP) term was first introduced into the Amber RNA force field of ff99bsc0χOL3, named ff99OL3_CMAP1. Extensive validations of tetranucleotides and tetraloops show that ff99OL3_CMAP1 can significantly decrease the population of an incorrect structure, increase the consistency between the simulation results and experimental values for tetranucleotides, and improve the stability of tetraloops. ff99OL3_CMAP1 can also precisely reproduce the conformation of a duplex and riboswitches. These findings confirm that the newly developed force field ff99OL3_CMAP1 can improve the conformer sampling of RNA.

Performance evaluation of the balanced force field ff03CMAP for intrinsically disordered and ordered proteins.

Intrinsically disordered proteins (IDPs) have been found to be closely associated with various human diseases. Because IDPs have no fixed tertiary structure under physiological conditions, current experimental methods, such as X-ray spectroscopy, NMR, and CryoEM, cannot capture all the dynamic conformations. Molecular dynamics simulation is an useful tool that is widely used to study the conformer distributions of IDPs and has become an important complementary tool for experimental methods. However, the accuracy of MD simulations directly depends on utilizing a precise force field. Recently a CMAP optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of IDPs and folded proteins. In order to further evaluate the performance, more types of disordered and ordered proteins were used to test the ability for conformer sampling. The results showed that simulated chemical shifts, J-coupling, and Rg distribution with the ff03CMAP force field were in better agreement with NMR measurements and were more accurate than those with the ff03 force field. The sampling conformations by ff03CMAP were more diverse than those of ff03. At the same time, ff03CMAP could stabilize the conformers of the ordered proteins. These findings indicate that ff03CMAP can be widely used to sample diverse conformers for proteins, including the intrinsically disordered regions.

Induction mechanism of cigarette smoke components (CSCs) on dyslipidemia and hepatic steatosis in rats.

OBJECTIVE: The purpose of this study was to explore the effect of cigarette smoke component (CSC) exposure on serum lipid levels in rats and the underlying molecular mechanism. METHODS: Male SPF-grade SD rats were randomly divided into a control group and a CSC exposure group, with the CSC group being exposed to CSC for 6 weeks. RT-PCR and Western blotting methods were used to detect lipid metabolism gene expression in rats, and 16S RNA gene sequencing was used to detect the gut microbiota in the rat cecum. Rat serum exosomes were prepared and identified, and the interaction of exosomal miR-291a-3p and miR-126a-5p with AMPK and CYP7A1 was detected by a dual luciferase reporter gene assay (DLRG). RESULTS: Serum indicators, including cholesterol levels and trimethylamine oxide (TMAO) content, were significantly affected in the CSC exposure group compared with the control group (P < 0.05), and the expression levels of adenylate-activated protein kinase (AMPK), acetyl-coenzyme A carboxylase (ACC) and HMG-CoA reductase (HMG-CoAR) genes were significantly increased (P < 0.05) in the liver, while the expression level of cholesterol 7α-hydroxylase (CYP7A1) was markedly decreased (P < 0.01). 16S rRNA gene sequencing of the gut microbiota in the rat cecum showed that the abundance of Firmicutes in the CSC group increased significantly at the phylum level, while the abundances of Bacteroidota and Spirochaetota were reduced significantly (P < 0.01). The relative abundance of Romboutsia, Turicibacter, and Clostridium sensu stricto increased significantly (P < 0.01), and the relative abundance of Prevotella, Muribaculaceae_norank, Lachnospiraceae NK4A136 group, Roseburia, Treponema, and Ruminococcus significantly decreased (P < 0.01) at the genus level. In addition, the exosome miR-291a-3p and miR-126a-5p levels were markedly regulated by CSC exposure (P < 0.01). The interactions of miR-291a-3p and miR-126a-5p with AMPK and CYP7A1 mRNA were also validated by the DLRG method. CONCLUSIONS: In summary, the rat dyslipidemia induced by CSC exposure may be related to the interference of gut microbiota structure and interaction of miRNAs from serum exosomes with target mRNAs, which further regulated AMPK-ACC/CYP7A1 signaling in rats.

Balanced Force Field ff03CMAP Improving the Dynamics Conformation Sampling of Phosphorylation Site.

Phosphorylation plays a key role in plant biology, such as the accumulation of plant cells to form the observed proteome. Statistical analysis found that many phosphorylation sites are located in disordered regions. However, current force fields are mainly trained for structural proteins, which might not have the capacity to perfectly capture the dynamic conformation of the phosphorylated proteins. Therefore, we evaluated the performance of ff03CMAP, a balanced force field between structural and disordered proteins, for the sampling of the phosphorylated proteins. The test results of 11 different phosphorylated systems, including dipeptides, disordered proteins, folded proteins, and their complex, indicate that the ff03CMAP force field can better sample the conformations of phosphorylation sites for disordered proteins and disordered regions than ff03. For the solvent model, the results strongly suggest that the ff03CMAP force field with the TIP4PD water model is the best combination for the conformer sampling. Additional tests of CHARMM36m and FB18 force fields on two phosphorylated systems suggest that the overall performance of ff03CMAP is similar to that of FB18 and better than that of CHARMM36m. These results can help other researchers to choose suitable force field and solvent models to investigate the dynamic properties of phosphorylation proteins.

Mechanism Underlying the Bypass of Apurinic/Pyrimidinic Site Analogs by Sulfolobus acidocaldarius DNA Polymerase IV.

The spontaneous depurination of genomic DNA occurs frequently and generates apurinic/pyrimidinic (AP) site damage that is mutagenic or lethal to cells. Error-prone DNA polymerases are specifically responsible for the translesion synthesis (TLS) of specific DNA damage, such as AP site damage, generally with relatively low fidelity. The Y-family DNA polymerases are the main error-prone DNA polymerases, and they employ three mechanisms to perform TLS, including template-skipping, dNTP-stabilized misalignment, and misincorporation-misalignment. The bypass mechanism of the dinB homolog (Dbh), an archaeal Y-family DNA polymerase from Sulfolobus acidocaldarius, is unclear and needs to be confirmed. In this study, we show that the Dbh primarily uses template skipping accompanied by dNTP-stabilized misalignment to bypass AP site analogs, and the incorporation of the first nucleotide across the AP site is the most difficult. Furthermore, based on the reported crystal structures, we confirmed that three conserved residues (Y249, R333, and I295) in the little finger (LF) domain and residue K78 in the palm subdomain of the catalytic core domain are very important for TLS. These results deepen our understanding of how archaeal Y-family DNA polymerases deal with intracellular AP site damage and provide a biochemical basis for elucidating the intracellular function of these polymerases.