Exploring microproteins from various model organisms using the mip-mining database.

Microproteins, prevalent across all kingdoms of life, play a crucial role in cell physiology and human health. Although global gene transcription is widely explored and abundantly available, our understanding of microprotein functions using transcriptome data is still limited. To mitigate this problem, we present a database, Mip-mining ( https://weilab.sjtu.edu.cn/mipmining/ ), underpinned by high-quality RNA-sequencing data exclusively aimed at analyzing microprotein functions. The Mip-mining hosts 336 sets of high-quality transcriptome data from 8626 samples and nine representative living organisms, including microorganisms, plants, animals, and humans, in our Mip-mining database. Our database specifically provides a focus on a range of diseases and environmental stress conditions, taking into account chemical, physical, biological, and diseases-related stresses. Comparatively, our platform enables customized analysis by inputting desired data sets with self-determined cutoff values. The practicality of Mip-mining is demonstrated by identifying essential microproteins in different species and revealing the importance of ATP15 in the acetic acid stress tolerance of budding yeast. We believe that Mip-mining will facilitate a greater understanding and application of microproteins in biotechnology. Moreover, it will be beneficial for designing therapeutic strategies under various biological conditions.

NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods.

Neuropeptides acting as signaling molecules in the nervous system of various animals play crucial roles in a wide range of physiological functions and hormone regulation behaviors. Neuropeptides offer many opportunities for the discovery of new drugs and targets for the treatment of neurological diseases. In recent years, there have been several data-driven computational predictors of various types of bioactive peptides, but the relevant work about neuropeptides is little at present. In this work, we developed an interpretable stacking model, named NeuroPpred-Fuse, for the prediction of neuropeptides through fusing a variety of sequence-derived features and feature selection methods. Specifically, we used six types of sequence-derived features to encode the peptide sequences and then combined them. In the first layer, we ensembled three base classifiers and four feature selection algorithms, which select non-redundant important features complementarily. In the second layer, the output of the first layer was merged and fed into logistic regression (LR) classifier to train the model. Moreover, we analyzed the selected features and explained the feasibility of the selected features. Experimental results show that our model achieved 90.6% accuracy and 95.8% AUC on the independent test set, outperforming the state-of-the-art models. In addition, we exhibited the distribution of selected features by these tree models and compared the results on the training set to that on the test set. These results fully showed that our model has a certain generalization ability. Therefore, we expect that our model would provide important advances in the discovery of neuropeptides as new drugs for the treatment of neurological diseases.

Understanding base and backbone contributions of phosphorothioate DNA for molecular recognition with SBD proteins.

Bacterial DNA phosphorothioate (PT) modification provides a specific anchoring site for sulfur-binding proteins (SBDs). Besides, their recognition patterns include phosphate links and bases neighboring the PT-modified site, thereby bringing about genome sequence-dependent properties in PT-related epigenetics. Here, we analyze the contributions of the DNA backbone (phosphates and deoxyribose) and bases bound with two SBD proteins in Streptomyces pristinaespiralis and coelicolor (SBDSco and SBDSpr). The chalcogen-hydrophobic interactions remained constantly at the anchoring site while the adjacent bases formed conditional and distinctive non-covalent interactions. More importantly, SBD/PT-DNA interactions were not limited within the traditional "4-bp core" range from 5'-I to 3'-III but extended to upstream 5'-II and 5'-III bases and even 5''-I to 5''-III at the non-PT-modified complementary strand. From the epigenetic viewpoint, bases 3'-II, 5''-I, and 5''-III of SBDSpr and 3'-II, 5''-II, and 5''-III of SBDSco present remarkable differentiations in the molecular recognitions. From the protein viewpoint, H102 in SBDSpr and R191 in SBDSco contribute significantly while proline residues at the PT-bound site are strictly conserved for the PT-chalcogen bond. The mutual and make-up mutations are proposed to alter the SBD/PT-DNA recognition pattern, besides additional chiral phosphorothioate modifications on phosphates 5'-II, 5'-II, 3'-I, and 3'-II.

Gain-of-Function SHP2 E76Q Mutant Rescuing Autoinhibition Mechanism Associated with Juvenile Myelomonocytic Leukemia.

Juvenile myelomonocytic leukemia (JMML) is an invasive myeloproliferative neoplasm and is a childhood disease with very high clinical lethality. The SHP2 is encoded by the PTPN11 gene, which is a nonreceptor (pY)-phosphatase and mutation causes JMML. The structural hierarchy of SHP2 includes protein tyrosine phosphatase domain (PTP) and Src-homology 2 domain (N-SH2 and C-SH2). Somatic mutation (E76Q) in the interface of SH2-PTP domain is the most commonly identified mutation found in up to 35% of patients with JMML. The mechanism of this mutant associated with JMML is poorly understood. Here, molecular dynamics simulation was performed on wild-type and mutant (E76Q) of SHP2 to explore the precise impact of gain-of-function on PTP's activity. Consequently, such impact rescues the SHP2 protein from autoinhibition state through losing the interface interactions of Q256/F7 and S502/Q76 or weakening interactions of Q256/R4, Q510/G60, and Q506/A72 between N-SH2 and PTP domains. The consequences of these interactions further relieve the D'E loop away from the PTP catalytic site. The following study would provide a mechanistic insight for better understanding of how individual SHP2 mutations alter the PTP's activity at the atomic level.

Examining asymmetric pairwise pre-reaction and transition states in enzymatic catalysis by molecular dynamics simulation and quantum mechanics/molecular mechanics calculation.

Here, we present a protocol to examine asymmetric pairwise pre-reaction and transition states in enzymatic catalysis. We describe steps to set up the calculated systems, run umbrella sampling molecular dynamics simulation, and conduct quantum mechanics/molecular mechanics calculations. We also provide analytical scripts to yield potential of mean force of pre-reaction states and reaction barriers. This protocol can generate quantum-mechanistic data for constructing pre-reaction state/transition state machine learning models. For complete details on the use and execution of this protocol, please refer to Luo et al. (2022).1.

Sensitivity of family GH11 Bacillus amyloliquefaciens xylanase A (BaxA) and the T33I mutant to Oryza sativa xylanase inhibitor protein (OsXIP): An experimental and computational study.

Glycoside hydrolase (GH) family 10 and 11 xylanases are inhibited by many xylanase inhibitor proteins (XIPs). We recombinantly expressed the Oryza sativa xylanase inhibitor protein (OsXIP) in Pichia pastoris GS115, with a molecular mass of 47.0 kDa. Family GH11 Bacillus amyloliquefaciens xylanase A (BaxA) and the mutant T33I (DS199) were inhibited by the recombinant OsXIP (rePOsXIP) through competive inhibition, with corresponding inhibition constants (Ki) of 54.09 and 12.16 nM. After incubation with rePOsXIP (70 nM) at 40 °C for 40 min, inhibitory rates of reBaxA and DS199 (0.2 U) were 23.7% and 76.7%, respectively. Xylooligosaccharides with low concentration were released from beechwood xylan by reBaxA and DS199 in the presence of reOsXIP. Intrinsic fluorescences of reBaxA and DS199 were statically quenched by rePOsXIP in a concentration-dependent manner. Molecular dynamics (MD) simulations and conformational analysis of OsXIP-BaxA and OsXIP-DS199 revealed that the long loop (Lα4ß5) of OsXIP inserted into the catalytic grooves of BaxA and DS199. The DS199 enhanced the binding affinity to OsXIP, causing conformational alterations on protein-protein interface residues, thereby forming more hydrogen bonds and van der Waals forces. MM/GBSA analysis revealed that the binding free energy (∆Gbind) of OsXIP-DS199 was enhanced by 2.08 kcal/mol compared to that of OsXIP-BaxA. The OsXIP binding induced a conformational changes among residues in the cord and thumb regions of BaxA and DS199. In particular, the T111RYNAP116 residues in the thumb region of DS199 was maintained close to OsXIP by specific bonds. Additional MD simulations revealed that Y113A or T93A mutation of BaxA suppressed the binding affinity by diminishing interface associations of OsXIP-BaxA. This study partially elucidats the molecular basis of inhibitory mechanism and structure-function relationships of GH11 xylanases. Our findings inform rational designs of mutant xylanases with higher resistance to inhibitor proteins.

Design of 2,5-furandicarboxylic based polyesters degraded in different environmental conditions: Comprehensive experimental and theoretical study.

Nowadays, the promotion and application of aliphatic-aromatic copolyesters, such as poly (butylene adipate-co-terephthalate) (PBAT), are growing into a general trend. Although the structures of diacids exerted substantial impacts on degradation behavior, the underlying mechanisms have rarely been studied. In this work, 2,5-Furandicarboxylic acid was combined with succinic acid (PBSF), adipic acid (PBAF) and diglycolic acid (PBDF) to prepare three kinds of copolyesters. They showed unique degradation behaviors in buffer, enzyme environment and artificial seawater. These characteristics are closely related to the structural compositions of diacids. PBAFs displayed impressive biodegradability when catalyzed by Candida antarctica lipase B (CALB), while the more hydrophilic PBDFs exhibited faster hydrolysis in both buffer and artificial seawater. PBSFs, with hydrophobic and short segments, obtained a relatively slower rate of hydrolysis and enzymatic degradation. The reactivity sites and hydrolytic pathway were revealed by the combination of DFT calculation and Fukui function analysis. MD simulations, QM/MM optimizations and theozyme calculations showed that PBAF-CALB was prone to form a pre-reaction state, leading to the reduced energy barrier in the acylation process. This work revealed the effects of different structural features of diacids on polymer degradation and paved a way to design target biodegradable polymers in different degradation conditions.