Recognition and cleavage of human tRNA methyltransferase TRMT1 by the SARS-CoV-2 main protease.

The SARS-CoV-2 main protease (M or Nsp5) is critical for production of viral proteins during infection and, like many viral proteases, also targets host proteins to subvert their cellular functions. Here, we show that the human tRNA methyltransferase TRMT1 is recognized and cleaved by SARS-CoV-2 M. TRMT1 installs the ,-dimethylguanosine (m2,2G) modification on mammalian tRNAs, which promotes cellular protein synthesis and redox homeostasis.

Investigating the differential therapeutic efficacy and mechanisms of human umbilical cord mesenchymal stem cells at various passages in osteoarthritis treatment.

This study aimed to assess the clinical efficacy of umbilical cord mesenchymal stem cells (hUC-MSCs) from different passages (P3, P8, and P13) in the treatment of knee osteoarthritis (OA) and explore the underlying mechanisms. The hUC-MSCs from each passage were characterized and evaluated for their stemness, migration, proliferation, and marker expression. Rats with OA were treated with hUC-MSCs from each passage, and the therapeutic effects were assessed based on knee swelling, discomfort, and pathological examination of the knee joint.

Chinese herbal formula, modified Guilu Erxian glue, alleviates apoptosis of hematopoietic stem cells by regulating SLAM-SAP signal pathway in aplastic anemia mice model.

Ethnopharmacological Relevance: Guilu Erxian Glue (GEG) and Danggui Buxue Tang (DBT) are traditional Chinese herbal formulas. According to the theory of traditional Chinese medicine, the combination of those two formulas (Modified Guilu Erxian Glue, MGEG) has the effects of tonifying the kidney and producing blood, was usually used to treat bone marrow failure diseases, including aplastic anemia (AA).

Aim Of The Study: T lymphocytes play a crucial role in the disease pathogenesis and progression of AA.

A Repurposed Drug Interferes with Nucleic Acid to Inhibit the Dual Activities of Coronavirus Nsp13.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlighted a critical need to discover more effective antivirals. While therapeutics for SARS-CoV-2 exist, its nonstructural protein 13 (Nsp13) remains a clinically untapped target. Nsp13 is a helicase responsible for unwinding double-stranded RNA during viral replication and is essential for propagation.

Accurate Prediction of NMR Chemical Shifts: Integrating DFT Calculations with Three-Dimensional Graph Neural Networks.

Computer prediction of NMR chemical shifts plays an increasingly important role in molecular structure assignment and elucidation for organic molecule studies. Density functional theory (DFT) and gauge-including atomic orbital (GIAO) have established a framework to predict NMR chemical shifts but often at a significant computational expense with a limited prediction accuracy. Recent advancements in deep learning methods, especially graph neural networks (GNNs), have shown promise in improving the accuracy of predicting experimental chemical shifts, either by using 2D molecular topological features or 3D conformational representation.

Dynamics underlie the drug recognition mechanism by the efflux transporter EmrE.

The multidrug efflux transporter EmrE from Escherichia coli requires anionic residues in the substrate binding pocket for coupling drug transport with the proton motive force. Here, we show how protonation of a single membrane embedded glutamate residue (Glu14) within the homodimer of EmrE modulates the structure and dynamics in an allosteric manner using NMR spectroscopy. The structure of EmrE in the Glu14 protonated state displays a partially occluded conformation that is inaccessible for drug binding by the presence of aromatic residues in the binding pocket.

FoxO3 Regulates Mouse Bone Mesenchymal Stem Cell Fate and Bone-Fat Balance During Skeletal Aging.

Age-related osteoporosis is characterized by an imbalance between osteogenic and adipogenic differentiation in bone mesenchymal stem cells (BMSCs). Forkhead box O 3 (FoxO3) transcription factor is involved in lifespan and cell differentiation. In this study, we explore whether FoxO3 regulates age-related bone loss and marrow fat accumulation.

A Bionic Thermosensitive Sustainable Delivery System for Reversing the Progression of Osteoarthritis by Remodeling the Joint Homeostasis.

Although the pathogenesis of osteoarthritis (OA) is unclear, inflammatory cytokines are related to its occurrence. However, few studies focused on the therapeutic strategies of regulating joint homeostasis by simultaneously remodeling the anti-inflammatory and immunomodulatory microenvironments. Fibroblast growth factor 18 (FGF18) is the only disease-modifying OA drug (DMOAD) with a potent ability and high efficiency in maintaining the phenotype of chondrocytes within cell culture models.

Integrated Molecular Modeling and Machine Learning for Drug Design.

Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping reduce the time and cost of the research and development of new drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling and machine learning to develop computational tools for modulator design, including a pocket-guided rational design approach based on AlphaSpace to target protein-protein interactions, delta machine learning scoring functions for protein-ligand docking as well as virtual screening, and state-of-the-art deep learning models to predict calculated and experimental molecular properties based on molecular mechanics optimized geometries.

Deciphering the Allosteric Activation Mechanism of SIRT6 Using Molecular Dynamics Simulations.

As a member of the histone deacetylase protein family, the NAD-dependent SIRT6 plays an important role in maintaining genomic stability and regulating cell metabolism. Interestingly, SIRT6 has been found to have a preference for hydrolyzing long-chain fatty acyls relative to deacetylation, and it can be activated by fatty acids. However, the mechanisms by which SIRT6 recognizes different substrates and can be activated by small molecular activators are still not well understood.

Angiogenesis coupled with osteogenesis in a bone tissue engineering scaffold enhances bone repair in osteoporotic bone defects.

Increased life expectancy has resulted in an increase in osteoporosis incidence worldwide. The coupling of angiogenesis and osteogenesis is indispensable for bone repair. Although traditional Chinese medicine (TCM) exerts therapeutic effects on osteoporosis, TCM-related scaffolds, which focus on the coupling of angiogenesis and osteogenesis, have not yet been used for the treatment of osteoporotic bone defects.

Recognition and Cleavage of Human tRNA Methyltransferase TRMT1 by the SARS-CoV-2 Main Protease.

Unlabelled: The SARS-CoV-2 main protease (M, or Nsp5) is critical for the production of functional viral proteins during infection and, like many viral proteases, can also target host proteins to subvert their cellular functions. Here, we show that the human tRNA methyltransferase TRMT1 can be recognized and cleaved by SARS-CoV-2 M. TRMT1 installs the , -dimethylguanosine (m2,2G) modification on mammalian tRNAs, which promotes global protein synthesis and cellular redox homeostasis.

Chinese herbal formula, modified Xianfang Huoming Yin, alleviates the inflammatory proliferation of rat synoviocytes induced by IL-1β through regulating the migration and differentiation of T lymphocytes.

Ethnopharmacological Relevance: Xianfang Huoming Yin (XFH) is a traditional Chinese herbal formula, which has the effect of clearing heat and detoxifying toxins, dispersing swellings, activating blood circulation, and relieving pain. It is usually applied to treat various autoimmune diseases, including Rheumatoid arthritis (RA).

Aim Of The Study: The migration of T lymphocytes plays an indispensable role in the pathogenesis of RA.

Gatekeeper mutations activate FGF receptor tyrosine kinases by destabilizing the autoinhibited state.

Many types of human cancers are being treated with small molecule ATP-competitive inhibitors targeting the kinase domain of receptor tyrosine kinases. Despite initial successful remission, long-term treatment almost inevitably leads to the emergence of drug resistance mutations at the gatekeeper residue hindering the access of the inhibitor to a hydrophobic pocket at the back of the ATP-binding cleft. In addition to reducing drug efficacy, gatekeeper mutations elevate the intrinsic activity of the tyrosine kinase domain leading to more aggressive types of cancer.

Multitask Deep Ensemble Prediction of Molecular Energetics in Solution: From Quantum Mechanics to Experimental Properties.

The past few years have witnessed significant advances in developing machine learning methods for molecular energetics predictions, including calculated electronic energies with high-level quantum mechanical methods and experimental properties, such as solvation free energy and logP. Typically, task-specific machine learning models are developed for distinct prediction tasks. In this work, we present a multitask deep ensemble model, sPhysNet-MT-ens5, which can simultaneously and accurately predict electronic energies of molecules in gas, water, and octanol phases, as well as transfer free energies at both calculated and experimental levels.

CovBinderInPDB: A Structure-Based Covalent Binder Database.

Covalent inhibition has emerged as a promising orthogonal approach for drug discovery, despite the significant challenge in achieving target specificity. To facilitate the structure-based rational design of target-specific covalent modulators, we developed an integrated computational protocol to curate covalent binders from the RCSB Protein Data Bank (PDB). Starting from the macromolecular crystallographic information files (mmCIF) in the PDB archive, covalent bond records, which indicate the side chain modification of amino acid residue by a covalent binder, were collected and cleaned.

Contralateral bridge fixation of freehand minimally invasive pedicle screws combined with unilateral MIS-TLIF vs. open TLIF in the treatment of multi-segmental lumbar degenerative diseases: A five years retrospective study and finite element analysis.

Objective: To evaluate the efficacy, safety, feasibility and biomechanical stability of contralateral bridge fixation of freehand minimally invasive pedicle screws (Freehand MIPS) combined with unilateral minimally invasive surgery-transforaminal lumbar interbody fusion (MIS-TLIF) (smile-face surgery) and open TLIF for the treatment of multi-segmental lumbar degenerative diseases (LDDs).

Methods: From January 2013 to January 2016, clinical data of multi-segmental (2- or 3-level) LDDs receiving smile-face surgery or open TLIF were retrospectively collected and analyzed. The back and leg pain VAS and ODI were used to assess clinical outcomes preoperatively and postoperatively.

Clinical Application of a Modified Local Transposition Flap (Parallelogram Flap) Surgery in Repairing Fingertip Defects.

Objective: Parallelogram flap was performed for transverse finger amputation with the loss of distal pulp, nails, and bone. This study aimed to compare the clinical effects of parallelogram flap, antegrade homodigital island flaps, and reverse digital artery island flaps in fingertip reconstruction.

Patients And Methods: From January 2017 to January 2021, clinical patient data with parallelogram flaps (78 cases), antegrade homodigital island flaps (78 cases), and reverse digital artery island flaps (78 cases) to repair fingertip defects were collected and analyzed.

Biomechanical research of medial femoral circumflex vascularized bone-grafting in the treatment of early-to-mid osteonecrosis of the femoral head: a finite element analysis.

Purpose: Hip preservation therapy of early ONFH (Osteonecrosis of the femoral head) has emerged as one of the hot areas of research. We have optimized the procedure of traditional MFCVBG (medial femoral circumflex vascularized bone grafting) by using specialized surgical tools and used the finite element analysis to guide the implantation position of the bone flap during surgery and validate the biological mechanical stability of the modified MFCVBG.

Methods: This study was based on the data of a male patient with left hip (ARCO stage IIB, JIC type C) hormonal ONFH.

The Herbal Combination of , , and Regulates the Functions of Type 2 Innate Lymphocytes and Macrophages Contributing to the Resolution of Collagen-Induced Arthritis.

Type 2 innate lymphocytes (ILC2s), promoting inflammation resolution, was a potential target for rheumatoid arthritis (RA) treatment. Our previous studies confirmed that . and .

Protein-Ligand Docking in the Machine-Learning Era.

Molecular docking plays a significant role in early-stage drug discovery, from structure-based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive power is critically dependent on the protein-ligand scoring function. In this review, we give a broad overview of recent scoring function development, as well as the docking-based applications in drug discovery. We outline the strategies and resources available for structure-based VS and discuss the assessment and development of classical and machine learning protein-ligand scoring functions.

Parallelogram flap versus homodigital island flap in the treatment of fingertip defects with bone exposure: a prospective controlled study.

Purpose: A modified local transposition flap (we call it "parallelogram flap") surgery was performed for fingertip injuries. This study aimed to compare the clinical effects of parallelogram flap and homodigital island flaps in fingertip reconstruction.

Methods: The study collected patients who underwent parallelogram transposition flaps and homodigital island flaps to repair fingertip defects from 2019 to 2021.

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions.

Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding the training set, developing physically meaningful features, employing our recently developed linear empirical scoring function Lin_F9 (Yang, C. 2021, 61, 4630-4644) as the baseline, and applying extreme gradient boosting (XGBoost) with Δ-machine learning, we have further improved the robustness and applicability of machine-learning scoring functions.

Accurate Prediction of Aqueous Free Solvation Energies Using 3D Atomic Feature-Based Graph Neural Network with Transfer Learning.

Graph neural network (GNN)-based deep learning (DL) models have been widely implemented to predict the experimental aqueous solvation free energy, while its prediction accuracy has reached a plateau partly due to the scarcity of available experimental data. In order to tackle this challenge, we first build a large and diverse calculated data set Frag20-Aqsol-100K of aqueous solvation free energy with reasonable computational cost and accuracy via electronic structure calculations with continuum solvent models. Then, we develop a novel 3D atomic feature-based GNN model with the principal neighborhood aggregation (PNAConv) and demonstrate that 3D atomic features obtained from molecular mechanics-optimized geometries can significantly improve the learning power of GNN models in predicting calculated solvation free energies.