CHARMM-GUI supports the Amber force fields

BamA-targeted antimicrobial peptide design for enhanced efficacy and reduced toxicity

The emergence of drug-resistant superbugs has necessitated a pressing need for innovative antibiotics. Antimicrobial peptides (AMPs) have demonstrated broad-spectrum antibacterial activity, reduced susceptibility to resistance, and immunomodulatory effects, rendering them promising for combating drug-resistant microorganisms. This study employed computational simulation methods to screen and design AMPs specifically targeting ESKAPE pathogens. Particularly, AMPs were rationally designed to target the BamA and obtain novel antimicrobial peptide sequences. The designed AMPs were assessed for their antibacterial activities, mechanisms, and stability. Molecular docking and dynamics simulations demonstrated the interaction of both designed AMPs, 11pep and D-11pep, with the β1, β9, β15, and β16 chains of BamA, resulting in misfolding of outer membrane proteins and antibacterial effects. Subsequent antibacterial investigations confirmed the broad-spectrum activity of both 11pep and D-11pep, with D-11pep demonstrating higher potency against resistant Gram-negative bacteria. D-11pep exhibited MICs of 16, 8, and 32 μg/mL against carbapenem-resistant Escherichia coli, carbapenem-resistant Pseudomonas aeruginosa, and multi-drug-resistant Acinetobacter baumannii, respectively, with a concomitant lower resistance induction. Mechanism of action studies confirmed that peptides could disrupt the bacterial outer membrane, aligning with the findings of molecular dynamics simulations. Additionally, D-11pep demonstrated superior stability and reduced toxicity in comparison to 11pep. The findings of this study underscore the efficacy of rational AMP design that targets BamA, along with the utilization of D-amino acid replacements as a strategy for developing AMPs against drug-resistant bacteria.

Virtual screening and biological activity evaluation of novel efflux pump inhibitors targeting AdeB

The AdeABC efflux pump is an important mechanism causing multidrug resistance in Acinetobacter baumannii, and its main component AdeB can recognize carbapenems, aminoglycosides, and other multi-class antibiotics and efflux them intracellularly, which is an ideal target for the development of anti-multidrug resistant bacteria drugs. Here, we combined multiple computer-aided drug design methods to target AdeB to identify promising novel structural inhibitors. Virtual screening was performed by molecular docking and molecular dynamics simulation (MD) and 12 potential compounds were identified from the databases. Meanwhile, their biological activities were validated by in vitro activity assays, and ChemDiv L676-2179 (γ-IFN), ChemDiv L676-1461, and Chembridge 53717615 were confirmed to suppress efflux effects and restore antibiotic susceptibility of resistant bacteria, which are expected to be developed as adjuvant drugs for the treatment of multi-drug resistant Acinetobacter baumannii clinical infections.

Drug candidates and potential targets of Curculigo spp. compounds for treating diabetes mellitus based on network pharmacology, molecular docking and molecular dynamics simulation

Curculigo spp. is a herb that is commonly used in Indonesia to treat diabetes mellitus (DM) . The main active components of Curculigo spp. were identified through our previous metabolomic study and online database platform. However, the biological mechanisms underlying Curculigo spp. activity in treating DM remain unclear. Therefore, in this study, a network pharmacology was used to explore the active compounds of Curculigo spp. and their potential molecular mechanisms for treating DM. Oral bioavailability and drug-likeness from the compounds of Curculigo spp. were screened using Lipinski's rule of five, BBB, HIA + and Caco-2 permeability criteria. A network of compound-target-disease-pathway was then constructed using Cytoscape. The highest degree compounds and targets were then confirmed by molecular docking and molecular dynamics (MD) simulations. The human body can absorb 33 compounds derived from Curculigo spp. In addition, 58 nodes and 62 edges generated a network analysis with the DM target. The highest degree of the compound-target-disease pathway was for orcinol glucoside, AKR1B1, autoimmune diabetes, bile acid and bile salt metabolism. Furthermore, the computational docking method on Curculigo spp. compounds with the highest degree revealed that orcinol glucoside interacted with PTPN1 through a hydrogen bond and resulted in a binding energy of -7.2 kcal mol-1. Through hydrogen bonds, orcinol glucoside in PTPN1 regulates multiple signaling pathways via the adherens junction pathway, which may play a therapeutic role in DM (type 2 diabetes: obesity). In addition, MD simulation confirmed that orcinol glucoside, is suitable for DM treatment by interacting with PTPN1.Communicated by Ramaswamy H. Sarma.

Quantitative Comparison against Experiments Reveals Imperfections in Force Fields' Descriptions of POPC-Cholesterol Interactions

Cholesterol is a central building block in biomembranes, where it induces orientational order, slows diffusion, renders the membrane stiffer, and drives domain formation. Molecular dynamics (MD) simulations have played a crucial role in resolving these effects at the molecular level; yet, it has recently become evident that different MD force fields predict quantitatively different behavior. Although easily neglected, identifying such limitations is increasingly important as the field rapidly progresses toward simulations of complex membranes mimicking the in vivo conditions: pertinent multicomponent simulations must capture accurately the interactions between their fundamental building blocks, such as phospholipids and cholesterol. Here, we define quantitative quality measures for simulations of binary lipid mixtures in membranes against the C-H bond order parameters and lateral diffusion coefficients from NMR spectroscopy as well as the form factors from X-ray scattering. Based on these measures, we perform a systematic evaluation of the ability of commonly used force fields to describe the structure and dynamics of binary mixtures of palmitoyloleoylphosphatidylcholine (POPC) and cholesterol. None of the tested force fields clearly outperforms the others across the tested properties and conditions. Still, the Slipids parameters provide the best overall performance in our tests, especially when dynamic properties are included in the evaluation. The quality evaluation metrics introduced in this work will, particularly, foster future force field development and refinement for multicomponent membranes using automated approaches.

Selection of a novel cell-internalizing RNA aptamer specific for CD22 antigen in B cell acute lymphoblastic leukemia

Despite improvements in B cell acute lymphoblastic leukemia (B-ALL) treatment, a significant number of patients experience relapse of the disease, resulting in poor prognosis and high mortality. One of the drawbacks of current B-ALL treatments is the high toxicity associated with the non-specificity of chemotherapeutic drugs. Targeted therapy is an appealing strategy to treat B-ALL to mitigate these toxic off-target effects. One such target is the B cell surface protein CD22. The restricted expression of CD22 on the B-cell lineage and its ligand-induced internalizing properties make it an attractive target in cases of B cell malignancies. To target B-ALL and the CD22 protein, we performed cell internalization SELEX (Systematic Evolution of Ligands by EXponential enrichment) followed by molecular docking to identify internalizing aptamers specific for B-ALL cells that bind the CD22 cell-surface receptor. We identified two RNA aptamers, B-ALL1 and B-ALL2, that target human malignant B cells, with B-ALL1 the first documented RNA aptamer interacting with the CD22 antigen. These B-ALL-specific aptamers represent an important first step toward developing novel targeted therapies for B cell malignancy treatments.

Computational biology and in vitro studies for anticipating cancer-related molecular targets of sweet wormwood (Artemisia annua)

BACKGROUND

Cancer is one of the leading causes of death worldwide. Recently, it was shown that many natural extracts have positive effects against cancer, compared with chemotherapy or recent hormonal treatments. A. annua is an annual medicinal herb used in the traditional Chinese medicine. It has also been shown to inhibit the proliferation of various cancer cell lines.

METHODS

Multi-level modes of action of A. annua constituents in cancer therapy were investigated using an integrated approach of network pharmacology, molecular docking, dynamic simulations and in-vitro cytotoxicity testing on both healthy and cancer cells.

RESULTS

Network pharmacology-based analysis showed that the hit Artemisia annua constituents related to cancer targets were 3-(2-methylpropanoyl)-4-cadinene-3,11-diol, artemisinin G, O-(2-propenal) coniferaldehyde, (2-glyceryl)-O-coniferaldehyde and arteamisinin III, whereas the main cancer allied targets were NFKB1, MAP2K1 and AR. Sixty-eight significant signaling KEGG pathways with p < 0.01 were recognized, the most enriched of which were prostate cancer, breast cancer, melanoma and pancreatic cancer. Thirty-five biological processes were mainly regulated by cancer, involving cellular response to mechanical stimulus, positive regulation of gene expression and transcription. Molecular docking analysis of the top hit compounds against the most enriched target proteins showed that 3-(2-methylpropanoyl)-4-cadinene-3,11-diol and O-(2-propenal) coniferaldehyde exhibited the most stabilized interactions. Molecular dynamics simulations were performed to explain the stability of these two compounds in their protein-ligand complexes. Finally, confirmation of the potential anticancer activity was attained by in-vitro cytotoxicity testing of the extract on human prostate (PC-3), breast (MDA-MB-231), pancreatic (PANC-1) and melanoma (A375) cancerous cell lines.

CONCLUSION

This study presents deeper insights into A. annua molecular mechanisms of action in cancer for the first time using an integrated approaches verifying the herb's value.

Lipid composition modulates interactions of p7 viroporin during membrane insertion

Viral proteins interact with lipid membranes during various stages in the viral life cycle to propagate infection. p7 is an ion channel forming protein of Hepatitis C virus (HCV) that participates in viral assembly. Studies show that it has close ties to lipid metabolism in the cell and anionic phosphatidylserine (PS) lipids are suggested to be key for its permeabilizing function, but the mechanism of its interaction with the lipid environment is largely unknown. To begin unraveling the molecular processes of the protein, we evaluated the impact of lipid environment on the binding and insertion mechanism of p7 prior to channel formation and viral assembly using molecular dynamics simulations. It is seen that p7 is sensitive to its lipid environment and results in different remodeling patterns in membranes. Helix 1 (H1) is especially important for peptide insertion, with deeper entry taking place when the membrane contains phosphatidylserine (PS). Helix 2 (H2) and the adjacent loop connecting to Helix 3 (H3) prompts recruitment of phosphatidylethanolamine (PE) lipids to the protein binding site in membrane models with lower surface charge. This work provides perspectives on the interplay between protein-lipid dynamics and membrane composition, and insights on membrane reorganization in mechanisms of disease.

Conformational response to ligand binding of TMPRSS2, a protease involved in SARS-CoV-2 infection: Insights through computational modeling

Thanks to the considerable research which has been undertaken in the last few years to improve our understanding of the biology and mechanism of action of SARS-CoV-2, we know how the virus uses its surface spike protein to infect host cells. The transmembrane prosthesis, serine 2 (TMPRSS2) protein, located on the surface of human cells, recognizes the cleavage site in the spike protein, leading to the release of the fusion peptide and entry of the virus into the host cells. Because of its role, TMPRSS2 has been proposed as a drug target to prevent infection by the virus. In this study, we aim to increase our understanding of TMPRSS2 using long scale microsecond atomistic molecular dynamics simulations, focusing on the conformational changes over time. The comparison between simulations conducted on the protein in the native (apo) and inhibited form (holo), has shown that in the holo form the inhibitor stabilizes the catalytic site and induces rearrangements in the extracellular domain of the protein. In turn, it leads to the formation of a new cavity in the vicinity of the ligand binding pocket that is stable in the microsecond time scale. Given the low specificity of known protease inhibitors, these findings suggest a new potential drug target site that can be used to improve TMPRSS2 specific recognition by newly designed inhibitors.

CHARMM-GUI Multicomponent Assembler for Modeling and Simulation of Complex Multicomponent Systems

Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. We demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to facilitate innovative studies of complex interactions between small (organic and inorganic) molecules, biomacromolecules, polymers, and nanomaterials.

Virtual screening indicates potential inhibitors of the P2X7 receptor

Anti-inflammatory agents can be synthetic or natural compounds and are often used to attenuate different levels of inflammation. Inflammatory diseases, due to the involvement of multiple systems, are becoming difficult to treat, involve long durations of therapy where applicable, have a high cost of management and have a deleterious impact on public health. The search for natural and synthetic compounds with anti-inflammatory activity is an important strategy in drug design. Bioactive synthetic drugs may be repurposed for other pharmacological applications, and natural product chemical structures offer unlimited opportunities for new drug discoveries due to the unparalleled availability of chemical diversity. Virtual screening of 2774 molecules on the mouse P2X7 protein showed that potential ligands are composed of five flavonoids (narirutin, diosmin, complanatuside, hesperidin, and oroxin B) and other drugs such as velpatasvir, itacitinib and lifitegrast. In vitro studies in mouse cells confirmed the inhibitory activity of the indicated ligands on the P2X7 receptor by applying virtual screening. The behavior of protein bonded to the ligands was verified by analysis of the molecular dynamic simulation trajectories for four of the most potent inhibitor compounds, indicating that the ligands velpatasvir, itacitinib, lithospermic acid and narirutin remained in the binding site indicated by molecular docking.

The depsidones from marine sponge-derived fungus Aspergillus unguis IB151 as an anti-MRSA agent: Molecular docking, pharmacokinetics analysis, and molecular dynamic simulation studies

Methicillin-resistant Staphylococcus aureus (MRSA) is an emerging nosocomial pathogen among hospitalized patients, with high morbidity and mortality rates. The discovery of a novel antibacterial is urgently needed to address this resistance problem. The present study aims to explore the antibacterial potential of three depsidone compounds: 2-clorounguinol (1), unguinol (2), and nidulin (3), isolated from the marine sponge-derived fungus Aspergillus unguis IB1, both in vitro and in silico. The antibacterial activity of all compounds was evaluated by calculating the Minimum inhibitory concentration (MIC) and Minimum bactericidal concentration (MBC) against MRSA using agar diffusion and total plate count methods, respectively. Bacterial cell morphology changes were  studied for the first time using scanning electron microscopy (SEM). Molecular docking, pharmacokinetics analysis, and molecular dynamics simulation were performed to determine possible protein-ligand interactions and the stability of the targeting penicillin-binding protein 2a (PBP2a) against 2-clorounguinol (1). The research findings indicated that compounds 1 to 3 exhibited MIC and MBC values of 2 µg/mL and 16 µg/mL against MRSA, respectively. MRSA cells displayed a distinct shape after the addition of the depsidone compound, as observed in SEM. According to the in silico study, 2-chlorounguinol exhibited the highest binding-free energy (BFE) with PBP2a (-6.7 kcal/mol). For comparison, (E)-3-(2-(4-cyanostyryl)-4-oxoquinazolin-3(4H)-yl) benzoic acid inhibits PBP2a with a BFE less than -6.6 kcal/mol. Based on the Lipinski's rule of 5, depsidone compounds constitute a class of compounds with good pharmacokinetic properties, being easily absorbed and permeable. These findings suggest that 2-chlorounguinol possesses potential antibacterial activity and could be developed as an antibiotic adjuvant to reduce antimicrobial resistance.

Structural basis for the ligand recognition and signaling of free fatty acid receptors

Free fatty acid receptors 1-4 (FFA1-4) are class A G protein-coupled receptors (GPCRs). FFA1-3 share substantial sequence similarity whereas FFA4 is unrelated. Despite this FFA1 and FFA4 are activated by the same range of long chain fatty acids (LCFAs) whilst FFA2 and FFA3 are instead activated by short chain fatty acids (SCFAs) generated by the intestinal microbiota. Each of FFA1, 2 and 4 are promising targets for novel drug development in metabolic and inflammatory conditions. To gain insights into the basis of ligand interactions with, and molecular mechanisms underlying activation of, FFAs by LCFAs and SCFAs, we determined the active structures of FFA1 and FFA4 bound to the polyunsaturated LCFA docosahexaenoic acid (DHA), FFA4 bound to the synthetic agonist TUG-891, as well as SCFA butyrate-bound FFA2, each complexed with an engineered heterotrimeric Gq protein (miniGq), by cryo-electron microscopy. Together with computational simulations and mutagenesis studies, we elucidated the similarities and differences in the binding modes of fatty acid ligands with varying chain lengths to their respective GPCRs. Our findings unveil distinct mechanisms of receptor activation and G protein coupling. We anticipate that these outcomes will facilitate structure-based drug development and underpin future research to understand allosteric modulation and biased signaling of this group of GPCRs.

CHARMM-GUI-Based Induced Fit Docking Workflow to Generate Reliable Protein-Ligand Binding Modes

Molecular docking is a preferred method to predict ligand binding modes and their binding energy to target protein receptors, which is critical in early phase structure-based drug discovery. However, there is a persistent challenge in docking that can be attributed to the induced fit effect, as receptor binding sites undergo induced fit conformational changes upon ligand binding to achieve better binding modes. In this work, based on CHARMM-GUI LBS Finder& Refiner and High-Throughput Simulator, we present a straightforward CHARMM-GUI induced fit docking (CGUI-IFD) workflow to generate reliable protein-ligand binding modes. The CGUI-IFD workflow generates an ensemble of receptor binding site conformations through ligand-binding site (LBS) refinement, runs rigid receptor docking, and performs high-throughput molecular dynamics (MD) simulations of protein-ligand complex structures in explicit solvents. The results are evaluated based on the ligand root-mean-square deviation (RMSD)-based binding stability and the molecular mechanics generalized Born surface area binding energy. For a benchmark test, we used 258 cross-docking protein-ligand pairs across 41 target proteins from the Schrodinger IFD-MD data set. The application of CGUI-IFD on this data set shows 80% success rate (within 2.5 Å RMSD from the experimental structures). We expect that the CGUI-IFD workflow can be useful to generate reliable ligand binding modes for cross-docking cases.

A centronuclear myopathy-causing mutation in dynamin-2 disrupts neuronal morphology and excitatory synaptic transmission in a murine model of the disease

AIMS

Dynamin-2 is a large GTPase, a member of the dynamin superfamily that regulates membrane remodelling and cytoskeleton dynamics. Mutations in the dynamin-2 gene (DNM2) cause autosomal dominant centronuclear myopathy (CNM), a congenital neuromuscular disorder characterised by progressive weakness and atrophy of the skeletal muscles. Cognitive defects have been reported in some DNM2-linked CNM patients suggesting that these mutations can also affect the central nervous system (CNS). Here we studied how a dynamin-2 CNM-causing mutation influences the CNS function.

METHODS

Heterozygous mice harbouring the p.R465W mutation in the dynamin-2 gene (HTZ), the most common causing autosomal dominant CNM, were used as disease model. We evaluated dendritic arborisation and spine density in hippocampal cultured neurons, analysed excitatory synaptic transmission by electrophysiological field recordings in hippocampal slices, and evaluated cognitive function by performing behavioural tests.

RESULTS

HTZ hippocampal neurons exhibited reduced dendritic arborisation and lower spine density than WT neurons, which was reversed by transfecting an interference RNA against the dynamin-2 mutant allele. Additionally, HTZ mice showed defective hippocampal excitatory synaptic transmission and reduced recognition memory compared to the WT condition.

CONCLUSION

Our findings suggest that the dynamin-2 p.R465W mutation perturbs the synaptic and cognitive function in a CNM mouse model and support the idea that this GTPase plays a key role in regulating neuronal morphology and excitatory synaptic transmission in the hippocampus.

Computational biology-based study of the molecular mechanism of spermidine amelioration of acute pancreatitis

Acute pancreatitis (AP) is an acute inflammatory gastrointestinal disease, the mortality and morbility of which has been on the increase in the past years. Spermidine, a natural polyamine, has a wide range of pharmacological effects including anti-inflammation, antioxidation, anti-aging, and anti-tumorigenic. This study aimed to investigate the reliable targets and molecular mechanisms of spermidine in treating AP. By employing computational biology methods including network pharmacology, molecular docking, and molecular dynamics (MD) simulations, we explored the potential targets of spermidine in improving AP with dietary supplementation. The computational biology results revealed that spermidine had high degrees (degree: 18, betweenness: 38.91; degree: 18, betweenness: 206.41) and stable binding free energy (ΔG_bind: - 12.81 ± 0.55 kcal/mol, - 15.00 ± 1.00 kcal/mol) with acetylcholinesterase (AchE) and serotonin transporter (5-HTT). Experimental validation demonstrates that spermidine treatment could reduce the necrosis and AchE activity in pancreatic acinar cells. Cellular thermal shift assay (CETSA) results revealed that spermidine could bind to and stabilize the 5-HTT protein in acinar cells. Moreover, spermidine treatment impeded the rise of the expression of 5-HTT in pancreatic tissues of caerulein induced acute pancreatitis mice. In conclusion, serotonin transporter might be a reliable target of spermidine in treating AP. This study provides new idea for the exploration of potential targets of natural compounds.

GC-MS chemical profiling, antioxidant, anti-diabetic, and anti-inflammatory activities of ethyl acetate fraction of Spilanthes filicaulis (Schumach. and Thonn.) C.D. Adams leaves: experimental and computational studies

Introduction: This study aimed to investigate the chemical profile of GC-MS, antioxidant, anti-diabetic, and anti-inflammatory activities of the ethyl acetate fraction of Spilanthes filicaulis leaves (EFSFL) via experimental and computational studies. Methods: After inducing oxidative damage with FeSO4, we treated the tissues with different concentrations of EFSFL. An in-vitro analysis of EFSFL was carried out to determine its potential for antioxidant, anti-diabetic, and anti-inflammatory activities. We also measured the levels of CAT, SOD, GSH, and MDA. Results and discussion: EFSFL exhibited anti-inflammatory properties through membrane stabilizing properties (IC50 = 572.79 μg/ml), proteinase inhibition (IC50 = 319.90 μg/ml), and inhibition of protein denaturation (IC50 = 409.88 μg/ml). Furthermore, EFSFL inhibited α-amylase (IC50 = 169.77 μg/ml), α-glucosidase (IC50 = 293.12 μg/ml) and DPP-IV (IC50 = 380.94 μg/ml) activities, respectively. Our results indicated that induction of tissue damage reduced the levels of GSH, SOD, and CAT activities, and increased MDA levels. However, EFSFL treatment restores these levels to near normal. GC-MS profiling shows that EFSFL contains 13 compounds, with piperine being the most abundant. In silico interaction of the phytoconstituents using molecular and ensembled-based docking revealed strong binding tendencies of two hit compounds to DPP IV (alpha-caryophyllene and piperine with a binding affinity of -7.8 and -7.8 Kcal/mol), α-glucosidase (alpha-caryophyllene and piperine with a binding affinity of -9.6 and -8.9 Kcal/mol), and to α-amylase (piperine and Benzocycloheptano[2,3,4-I,j]isoquinoline, 4,5,6,6a-tetrahydro-1,9-dihydroxy-2,10-dimethoxy-5-methyl with a binding affinity of -7.8 and -7.9 Kcal/mol), respectively. These compounds also presented druggable properties with favorable ADMET. Conclusively, the antioxidant, antidiabetic, and anti-inflammatory activities of EFSFL could be due to the presence of secondary metabolites.

pyCHARMM: Embedding CHARMM Functionality in a Python Framework

CHARMM is rich in methodology and functionality as one of the first programs addressing problems of molecular dynamics and modeling of biological macromolecules and their partners, e.g., small molecule ligands. When combined with the highly developed CHARMM parameters for proteins, nucleic acids, small molecules, lipids, sugars, and other biologically relevant building blocks, and the versatile CHARMM scripting language, CHARMM has been a trendsetting platform for modeling studies of biological macromolecules. To further enhance the utility of accessing and using CHARMM functionality in increasingly complex workflows associated with modeling biological systems, we introduce pyCHARMM, Python bindings, functions, and modules to complement and extend the extensive set of modeling tools and methods already available in CHARMM. These include access to CHARMM function-generated variables associated with the system (psf), coordinates, velocities and forces, atom selection variables, and force field related parameters. The ability to augment CHARMM forces and energies with energy terms or methods derived from machine learning or other sources, written in Python, CUDA, or OpenCL and expressed as Python callable routines is introduced together with analogous functions callable during dynamics calculations. Integration of Python-based graphical engines for visualization of simulation models and results is also accessible. Loosely coupled parallelism is available for workflows such as free energy calculations, using MBAR/TI approaches or high-throughput multisite λ-dynamics (MSλD) free energy methods, string path optimization calculations, replica exchange, and molecular docking with a new Python-based CDOCKER module. CHARMM accelerated platform kernels through the CHARMM/OpenMM API, CHARMM/DOMDEC, and CHARMM/BLaDE API are also readily integrated into this Python framework. We anticipate that pyCHARMM will be a robust platform for the development of comprehensive and complex workflows utilizing Python and its extensive functionality as well as an optimal platform for users to learn molecular modeling methods and practices within a Python-friendly environment such as Jupyter Notebooks.

Phytochemical Composition, In Vitro Antimicrobial, Antioxidant, and Enzyme Inhibition Activities, and In Silico Molecular Docking and Dynamics Simulations of Centaurea lycaonica: A Computational and Experimental Approach

Centaurea lycaonica is a local endemic species from the Centaurea L. genus. The Centaurea species has a wide range of usage in treating diseases in folk medicine. There are limited biological activity studies on this species in the literature. This study investigated enzyme inhibition and antimicrobial activity, antioxidant effect, and chemical content of extract and fractions of C. lycaonica. Enzyme inhibition activity was tested by α-amylase, α-glucosidase, and tyrosinase enzyme inhibition methods and antimicrobial activity by the microdilution method. The antioxidant activity was investigated using DPPH^•, ABTS^•+, and FRAP tests. The chemical content was determined by LC-MS/MS. The methanol extract showed the highest activity for α-glucosidase and α-amylase, even surpassing the positive control acarbose, with IC₅₀ values of 56.333 ± 0.986 and 172.800 ± 0.816 μg/mL, respectively. Additionally, the ethyl acetate fraction also exhibited high activity for α-amylase with an IC₅₀ value of 204.067 ± 1.739 μg/mL and tyrosinase with an IC₅₀ value of 213.900 ± 1.553 μg/mL. Moreover, this extract and fraction were found to have the highest total phenolic and flavonoid contents and antioxidant activity. Additionally, LC-MS/MS analyses of active extract and fraction revealed mainly the presence of phenolic compounds and flavonoids. In silico molecular docking and molecular dynamics simulation studies of determining compounds apigenin and myristoleic acid, common in CLM and CLE extracts and active against α-glucosidase and α-amylase, were performed. In conclusion, methanol extract and ethyl acetate fraction showed potential enzyme inhibition and antioxidant activity as a natural agent. Molecular modeling studies corroborate the findings of in vitro activity analyses.

Targeting RNA Structure to Inhibit Editing in Trypanosomes

Mitochondrial RNA editing in trypanosomes represents an attractive target for developing safer and more efficient drugs for treating infections with trypanosomes because this RNA editing pathway is not found in humans. Other workers have targeted several enzymes in this editing system, but not the RNA. Here, we target a universal domain of the RNA editing substrate, which is the U-helix formed between the oligo-U tail of the guide RNA and the target mRNA. We selected a part of the U-helix that is rich in G-U wobble base pairs as the target site for the virtual screening of 262,000 compounds. After chemoinformatic filtering of the top 5000 leads, we subjected 50 representative complexes to 50 nanoseconds of molecular dynamics simulations. We identified 15 compounds that retained stable interactions in the deep groove of the U-helix. The microscale thermophoresis binding experiments on these five compounds show low-micromolar to nanomolar binding affinities. The UV melting studies show an increase in the melting temperatures of the U-helix upon binding by each compound. These five compounds can serve as leads for drug development and as research tools to probe the role of the RNA structure in trypanosomal RNA editing.

Molecular recognition of two endogenous hormones by the human parathyroid hormone receptor-1

Parathyroid hormone (PTH) and PTH-related peptide (PTHrP) are two endogenous hormones recognized by PTH receptor-1 (PTH1R), a member of class B G protein- coupled receptors (GPCRs). Both PTH and PTHrP analogs including teriparatide and abaloparatide are approved drugs for osteoporosis, but they exhibit distinct pharmacology. Here we report two cryo-EM structures of human PTH1R bound to PTH and PTHrP in the G protein-bound state at resolutions of 2.62 Å and 3.25 Å, respectively. Detailed analysis of these structures uncovers both common and unique features for the agonism of PTH and PTHrP. Molecular dynamics (MD) simulation together with site-directed mutagenesis studies reveal the molecular basis of endogenous hormones recognition specificity and selectivity to PTH1R. These results provide a rational template for the clinical use of PTH and PTHrP analogs as an anabolic therapy for osteoporosis and other disorders.

Structural basis of metabolite transport by the chloroplast outer envelope channel OEP21

Triose phosphates (TPs) are the primary products of photosynthetic CO₂ fixation in chloroplasts, which need to be exported into the cytosol across the chloroplast inner envelope (IE) and outer envelope (OE) membranes to sustain plant growth. While transport across the IE is well understood, the mode of action of the transporters in the OE remains unclear. Here we present the high-resolution nuclear magnetic resonance (NMR) structure of the outer envelope protein 21 (OEP21) from garden pea, the main exit pore for TPs in C₃ plants. OEP21 is a cone-shaped β-barrel pore with a highly positively charged interior that enables binding and translocation of negatively charged metabolites in a competitive manner, up to a size of ~1 kDa. ATP stabilizes the channel and keeps it in an open state. Despite the broad substrate selectivity of OEP21, these results suggest that control of metabolite transport across the OE might be possible.

Simulations of Amyloid-Forming Peptides in the Crystal State

There still is little treatment available for amyloid diseases, despite their significant impact on individuals and the social and economic implications for society. One reason for this is that the physical nature of amyloid formation is not understood sufficiently well. Therefore, fundamental research at the molecular level remains necessary to support the development of therapeutics. A few structures of short peptides from amyloid-forming proteins have been determined. These can in principle be used as scaffolds for designing aggregation inhibitors. Attempts to this end have often used the tools of computational chemistry, in particular molecular simulation. However, few simulation studies of these peptides in the crystal state have been presented so far. Hence, to validate the capability of common force fields (AMBER19SB, CHARMM36m, and OPLS-AA/M) to yield insight into the dynamics and structural stability of amyloid peptide aggregates, we have performed molecular dynamics simulations of twelve different peptide crystals at two different temperatures. From the simulations, we evaluate the hydrogen bonding patterns, the isotropic B-factors, the change in energy, the Ramachandran plots, and the unit cell parameters and compare the results with the crystal structures. Most crystals are stable in the simulations but for all force fields there is at least one that deviates from the experimental crystal, suggesting more work is needed on these models.

Computational insights into ligand-induced G protein and β-arrestin signaling of the dopamine D1 receptor

The dopamine D1 receptor (D1R), is a class A G protein coupled-receptor (GPCR) which has been a promising drug target for psychiatric and neurological disorders such as Parkinson's disease (PD). Previous studies have suggested that therapeutic effects can be realized by targeting the β-arrestin signaling pathway of dopamine receptors, while overactivation of the G protein-dependent pathways leads to side effects, such as dyskinesias. Therefore, it is highly desirable to develop a D1R ligand that selectively regulates the β-arrestin pathway. Currently, most D1R agonists are signaling-balanced and stimulate both G protein and β-arrestin pathways, with a few reports of G protein biased ligands. However, identification and characterization of β-arrestin biased D1R agonists has been a challenge thus far. In this study, we implemented Gaussian accelerated molecular dynamics (GaMD) simulations to provide valuable computational insights into the possible underlying molecular mechanism of the different signaling properties of two catechol and two non-catechol D1R agonists that are either G protein biased or signaling-balanced. Dynamic network analysis further identified critical residues in the allosteric signaling network of D1R for each ligand at different conformational or binding states. Some of these residues are crucial for G protein or arrestin signals of GPCRs based on previous studies. Finally, we provided a molecular design strategy which can be utilized by medicinal chemists to develop potential β-arrestin biased D1R ligands. The proposed hypotheses are experimentally testable and can guide the development of safer and more effective medications for a variety of CNS disorders.

CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications

Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.

Prediction of dynamic allostery for the transmembrane domain of the sweet taste receptor subunit, TAS1R3

The sweet taste receptor plays an essential role as an energy sensor by detecting carbohydrates. However, the dynamic mechanisms of receptor activation remain unclear. Here, we describe the interactions between the transmembrane domain of the G protein-coupled sweet receptor subunit, TAS1R3, and allosteric modulators. Molecular dynamics simulations reproduced species-specific sensitivity to ligands. We found that a human-specific sweetener, cyclamate, interacted with the mouse receptor as a negative allosteric modulator. Agonist-induced allostery during receptor activation was found to destabilize the intracellular part of the receptor, which potentially interfaces with the Gα subunit, through ionic lock opening. A common human variant (R757C) of the TAS1R3 exhibited a reduced response to sweet taste, in support of our predictions. Furthermore, histidine residues in the binding site acted as pH-sensitive microswitches to modulate the sensitivity to saccharin. This study provides important insights that may facilitate the prediction of dynamic activation mechanisms for other G protein-coupled receptors.

Restriction of access to the central cavity is a major contributor to substrate selectivity in plant ABCG transporters

ABCG46 of the legume Medicago truncatula is an ABC-type transporter responsible for highly selective translocation of the phenylpropanoids, 4-coumarate, and liquiritigenin, over the plasma membrane. To investigate molecular determinants of the observed substrate selectivity, we applied a combination of phylogenetic and biochemical analyses, AlphaFold2 structure prediction, molecular dynamics simulations, and mutagenesis. We discovered an unusually narrow transient access path to the central cavity of MtABCG46 that constitutes an initial filter responsible for the selective translocation of phenylpropanoids through a lipid bilayer. Furthermore, we identified remote residue F562 as pivotal for maintaining the stability of this filter. The determination of individual amino acids that impact the selective transport of specialized metabolites may provide new opportunities associated with ABCGs being of interest, in many biological scenarios.

Lipidation Alters the Structure and Hydration of Myristoylated Intrinsically Disordered Proteins

Lipidated proteins are an emerging class of hybrid biomaterials that can integrate the functional capabilities of proteins into precisely engineered nano-biomaterials with potential applications in biotechnology, nanoscience, and biomedical engineering. For instance, fatty-acid-modified elastin-like polypeptides (FAMEs) combine the hierarchical assembly of lipids with the thermoresponsive character of elastin-like polypeptides (ELPs) to form nanocarriers with emergent temperature-dependent structural (shape or size) characteristics. Here, we report the biophysical underpinnings of thermoresponsive behavior of FAMEs using computational nanoscopy, spectroscopy, scattering, and microscopy. This integrated approach revealed that temperature and molecular syntax alter the structure, contact, and hydration of lipid, lipidation site, and protein, aligning with the changes in the nanomorphology of FAMEs. These findings enable a better understanding of the biophysical consequence of lipidation in biology and the rational design of the biomaterials and therapeutics that rival the exquisite hierarchy and capabilities of biological systems.

MoSDeF-GOMC: Python Software for the Creation of Scientific Workflows for the Monte Carlo Simulation Engine GOMC

MoSDeF-GOMC is a python interface for the Monte Carlo software GOMC to the Molecular Simulation Design Framework (MoSDeF) ecosystem. MoSDeF-GOMC automates the process of generating initial coordinates, assigning force field parameters, and writing coordinate (PDB), connectivity (PSF), force field parameter, and simulation control files. The software lowers entry barriers for novice users while allowing advanced users to create complex workflows that encapsulate simulation setup, execution, and data analysis in a single script. All relevant simulation parameters are encoded within the workflow, ensuring reproducible simulations. MoSDeF-GOMC's capabilities are illustrated through a number of examples, including prediction of the adsorption isotherm for CO₂ in IRMOF-1, free energies of hydration for neon and radon over a broad temperature range, and the vapor-liquid coexistence curve of a four-component surrogate for the jet fuel S-8. The MoSDeF-GOMC software is available on GitHub at https://github.com/GOMC-WSU/MoSDeF-GOMC.

Unveiling mutation effects on the structural dynamics of the main protease from SARS-CoV-2 with hybrid simulation methods

The main protease of SARS-CoV-2 (called M^pro or 3CL^pro) is essential for processing polyproteins encoded by viral RNA. Several M^pro mutations were found in SARS-CoV-2 variants, which are related to higher transmissibility, pathogenicity, and resistance to neutralization antibodies. Macromolecules adopt several favored conformations in solution depending on their structure and shape, determining their dynamics and function. In this study, we used a hybrid simulation method to generate intermediate structures along the six lowest frequency normal modes and sample the conformational space and characterize the structural dynamics and global motions of WT SARS-CoV-2 M^pro and 48 mutations, including mutations found in P.1, B.1.1.7, B.1.351, B.1.525 and B.1.429+B.1.427 variants. We tried to contribute to the elucidation of the effects of mutation in the structural dynamics of SARS-CoV-2 M^pro. A machine learning analysis was performed following the investigation regarding the influence of the K90R, P99L, P108S, and N151D mutations on the dimeric interface assembling of the SARS-CoV-2 M^pro. The parameters allowed the selection of potential structurally stable dimers, which demonstrated that some single surface aa substitutions not located at the dimeric interface (K90R, P99L, P108S, and N151D) are able to induce significant quaternary changes. Furthermore, our results demonstrated, by a Quantum Mechanics method, the influence of SARS-CoV-2 M^pro mutations on the catalytic mechanism, confirming that only one of the chains of the WT and mutant SARS-CoV-2 M^pros are prone to cleave substrates. Finally, it was also possible to identify the aa residue F140 as an important factor related to the increasing enzymatic reactivity of a significant number of SARS-CoV-2 M^pro conformations generated by the normal modes-based simulations.

Vanillin-Based Indolin-2-one Derivative Bearing a Pyridyl Moiety as a Promising Anti-Breast Cancer Agent via Anti-Estrogenic Activity

The structure-based design introduced indoles as an essential motif in designing new selective estrogen receptor modulators employed for treating breast cancer. Therefore, here, a series of synthesized vanillin-substituted indolin-2-ones were screened against the NCI-60 cancer cell panel followed by in vivo, in vitro, and in silico studies. Physicochemical parameters were evaluated with HPLC and SwissADME tools. The compounds demonstrated promising anti-cancer activity for the MCF-7 breast cancer cell line (GI = 6-63%). The compound with the highest activity (6j) was selective for the MCF-7 breast cancer cell line (IC₅₀ = 17.01 μM) with no effect on the MCF-12A normal breast cell line supported by real-time cell analysis. A morphological examination of the used cell lines confirmed a cytostatic effect of compound 6j. It inhibited both in vivo and in vitro estrogenic activity, triggering a 38% reduction in uterine weight induced by estrogen in an immature rat model and hindering 62% of ER-α receptors in in vitro settings. In silico molecular docking and molecular dynamics simulation studies supported the stability of the ER-α and compound 6j protein-ligand complex. Herein, we report that indolin-2-one derivative 6j is a promising lead compound for further pharmaceutical formulations as a potential anti-breast cancer drug.

Mechanism of activation and biased signaling in complement receptor C5aR1

The complement system plays an important role in the innate immune response to invading pathogens. The complement fragment C5a is one of its important effector components and exerts diverse physiological functions through activation of the C5a receptor 1 (C5aR1) and associated downstream G protein and β-arrestin signaling pathways. Dysfunction of the C5a-C5aR1 axis is linked to numerous inflammatory and immune-mediated diseases, but the structural basis for activation and biased signaling of C5aR1 remains elusive. Here, we present cryo-electron microscopy structures of the activated wild-type C5aR1-G_i protein complex bound to each of the following: C5a, the hexapeptidic agonist C5a^pep, and the G protein-biased agonist BM213. The structures reveal the landscape of the C5a-C5aR1 interaction as well as a common motif for the recognition of diverse orthosteric ligands. Moreover, combined with mutagenesis studies and cell-based pharmacological assays, we deciphered a framework for biased signaling using different peptide analogs and provided insight into the activation mechanism of C5aR1 by solving the structure of C5aR1^I116A mutant-G_i signaling activation complex induced by C089, which exerts antagonism on wild-type C5aR1. In addition, unusual conformational changes in the intracellular end of transmembrane domain 7 and helix 8 upon agonist binding suggest a differential signal transduction process. Collectively, our study provides mechanistic understanding into the ligand recognition, biased signaling modulation, activation, and G_i protein coupling of C5aR1, which may facilitate the future design of therapeutic agents.

Effects of presenilin-1 familial Alzheimer's disease mutations on γ-secretase activation for cleavage of amyloid precursor protein

Presenilin-1 (PS1) is the catalytic subunit of γ-secretase which cleaves within the transmembrane domain of over 150 peptide substrates. Dominant missense mutations in PS1 cause early-onset familial Alzheimer's disease (FAD); however, the exact pathogenic mechanism remains unknown. Here we combined Gaussian accelerated molecular dynamics (GaMD) simulations and biochemical experiments to determine the effects of six representative PS1 FAD mutations (P117L, I143T, L166P, G384A, L435F, and L286V) on the enzyme-substrate interactions between γ-secretase and amyloid precursor protein (APP). Biochemical experiments showed that all six PS1 FAD mutations rendered γ-secretase less active for the endoproteolytic (ε) cleavage of APP. Distinct low-energy conformational states were identified from the free energy profiles of wildtype and PS1 FAD-mutant γ-secretase. The P117L and L286V FAD mutants could still sample the "Active" state for substrate cleavage, but with noticeably reduced conformational space compared with the wildtype. The other mutants hardly visited the "Active" state. The PS1 FAD mutants were found to reduce γ-secretase proteolytic activity by hindering APP residue L49 from proper orientation in the active site and/or disrupting the distance between the catalytic aspartates. Therefore, our findings provide mechanistic insights into how PS1 FAD mutations affect structural dynamics and enzyme-substrate interactions of γ-secretase and APP.

Mechanism of hormone and allosteric agonist mediated activation of follicle stimulating hormone receptor

Follicle stimulating hormone (FSH) is an essential glycoprotein hormone for human reproduction, which functions are mediated by a G protein-coupled receptor, FSHR. Aberrant FSH-FSHR signaling causes infertility and ovarian hyperstimulation syndrome. Here we report cryo-EM structures of FSHR in both inactive and active states, with the active structure bound to FSH and an allosteric agonist compound 21 f. The structures of FSHR are similar to other glycoprotein hormone receptors, highlighting a conserved activation mechanism of hormone-induced receptor activation. Compound 21 f formed extensive interactions with the TMD to directly activate FSHR. Importantly, the unique residue H615^7.42 in FSHR plays an essential role in determining FSHR selectivity for various allosteric agonists. Together, our structures provide a molecular basis of FSH and small allosteric agonist-mediated FSHR activation, which could inspire the design of FSHR-targeted drugs for the treatment of infertility and controlled ovarian stimulation for in vitro fertilization.

Genomic landscape of the emerging XDR Salmonella Typhi for mining druggable targets clpP, hisH, folP and gpmI and screening of novel TCM inhibitors, molecular docking and simulation analyses

Typhoid fever is transmitted by ingestion of polluted water, contaminated food, and stool of typhoid-infected individuals, mostly in developing countries with poor hygienic environments. To find novel therapeutic targets and inhibitors, We employed a subtractive genomics strategy towards Salmonella Typhi and the complete genomes of eight strains were primarily subjected to the EDGAR tool to predict the core genome (n = 3207). Human non-homology (n = 2450) was followed by essential genes identification (n = 37). The STRING database predicted maximum protein-protein interactions, followed by cellular localization. The virulent/immunogenic ability of predicted genes were checked to differentiate drug and vaccine targets. Furthermore, the 3D models of the identified putative proteins encoded by the respective genes were constructed and subjected to druggability analyses where only "highly druggable" proteins were selected for molecular docking and simulation analyses. The putative targets ATP-dependent CLP protease proteolytic subunit, Imidazole glycerol phosphate synthase hisH, 7,8-dihydropteroate synthase folP and 2,3-bisphosphoglycerate-independent phosphoglycerate mutase gpmI were screened against a drug-like library (n = 12,000) and top hits were selected based on H-bonds, RMSD and energy scores. Finally, the ADMET properties for novel inhibitors ZINC19340748, ZINC09319798, ZINC00494142, ZINC32918650 were optimized followed by binding free energy (MM/PBSA) calculation for ligand-receptor complexes. The findings of this work are expected to aid in expediting the identification of novel protein targets and inhibitors in combating typhoid Salmonellosis, in addition to the already existing therapies.

Colchicine as potential inhibitor targeting MMP-9, NOX2 and TGF-β1 in myocardial infarction: a combination of docking and molecular dynamic simulation study

The global data revealed that myocardial infarction (MI) in coronary heart disease has been the leading cause of mortality worldwide in both developing and developed countries. The remodeling process after MI is essential to be the leading cause of heart failure due to cardiac remodeling. The evidence showed the increment of MMP-9, NOX2 and TGF-β1 expressions are biomarkers that influence cardiac remodeling. Lately, colchicine is widely used in the treatment of cardiovascular diseases. The effects of colchicine on NOX2, MMP-9 and TGF-β1 in the molecular models are still not yet discussed. We proposed a molecular docking and molecular dynamics simulation study to show the interaction between colchicine, NOX2, MMP-9 and TGF-β1. Colchicine has a good binding affinity with MMP-9, NOX2 and TGF-β1 based on the value, which are -8.3 Kcal/mol, -6.7 Kcal/mol and -6.5 Kcal/mol, respectively. Colchicine also binds to some catalytic residues in MMP-9, NOX2 and TGF-β1 that are responsible for inhibitor effects. The RMSD values between colchicine and MMP-9, NOX2 and TGF-β1 are 2.4 Å, 2 Å and 2.1 Å, respectively. The RMSF values of ligand and receptors complex showed relatively similar fluctuations. The SASA analysis showed that colchicine could create a more stable interaction with MMP-9. PCA analysis revealed that colchicine is capable of creating a solid and stable interaction with MMP-9 mainly, also NOX2 and TGF-β1. In conclusion, docking and molecular dynamics analysis showed evidence of colchicine roles in the inhibition of MMP-9, NOX2 and TGF-β1 in order to inhibit the remodeling process after MI.Communicated by Ramaswamy H. Sarma.

Modeling the molecular fingerprint of protein-lipid interactions of MLKL on complex bilayers

Lipids, the structural part of membranes, play important roles in biological functions. However, our understanding of their implication in key cellular processes such as cell division and protein-lipid interaction is just emerging. This is the case for molecular interactions in mechanisms of cell death, where the role of lipids for protein localization and subsequent membrane permeabilization is key. For example, during the last stage of necroptosis, the mixed lineage kinase domain-like (MLKL) protein translocates and, eventually, permeabilizes the plasma membrane (PM). This process results in the leakage of cellular content, inducing an inflammatory response in the microenvironment that is conducive to oncogenesis and metastasis, among other pathologies that exhibit inflammatory activity. This work presents insights from long all-atom molecular dynamics (MD) simulations of complex membrane models for the PM of mammalian cells with an MLKL protein monomer. Our results show that the binding of the protein is initially driven by the electrostatic interactions of positively charged residues. The protein bound conformation modulates lipid recruitment to the binding site, which changes the local lipid environment recruiting PIP lipids and cholesterol, generating a unique fingerprint. These results increase our knowledge of protein-lipid interactions at the membrane interface in the context of molecular mechanisms of the necroptotic pathway, currently under investigation as a potential treatment target in cancer and inflamatory diseases.

An ensemble docking-based virtual screening according to different TRPV1 pore states toward identifying phytochemical activators

Identifying phytochemical activators for TRPV1 using ensemble-based virtual screening, machine learning, and MD simulation.

Effect of phosphorylation on the structural dynamics, thermal stability of human dopamine transporter: A simulation study using normal modes, molecular dynamics and Markov State Model

The Human Dopamine Transporter (hDAT) plays an essential role in modulating the Influx/Efflux of dopamine, and it is involved in the mechanism of certain neurodegenerative diseases such as Parkinson's disease. Several studies have reported important states for Dopamine transport: outward-facing open state (OFo), the outward-facing closed state (OFc), the holo-occluded state closed (holo), and the inward-facing open state (IFo). Furthermore, experimental assays have shown that different phosphorylation conditions in hDAT can affect the rate of dopamine absorption. We present a protocol using hybrid simulation methods to study the conformational dynamics and stability of states of hDAT under different phosphorylation sites. With this protocol, we explored the conformational space of hDAT, identified the states, and evaluated the free energy differences and the transition probabilities between them in each of the phosphorylation cases. We also presented the conformational changes and correlated them with those described in the literature. There is a thesis/hypothesis that the phosphorylation condition corresponding to NP-333 system (where all sites Ser/Thr from residue 2 to 62 and 254 to 613 are phosphorylated, except residue 333) would decrease the rate of dopamine transport from the extracellular medium to the intracellular medium by hDAT as previously described in the literature by Lin et al., 2003. Our results corroborated this thesis/hypothesis and the data reported. It is probably due to the affectation/changes/alteration of the conformational dynamics of this system that makes the intermediate states more likely and makes it difficult to initial states associated with the uptake of dopamine in the extracellular medium, corroborating the experimental results. Furthermore, our results showed that just single phosphorylation/dephosphorylation could alter intrinsic protein motions affecting the sampling of one or more states necessary for dopamine transport. In this sense, the modification of phosphorylation influences protein movements and conformational preferences, affecting the stability of states and the transition between them and, therefore, the transport.

Influence of DPPE surface undulations on melting temperature determination: UV/Vis spectroscopic and MD study

One of the most distinguished quantities that describes lipid main phase transition, i.e. the transition from the gel (L_β(')) to the fluid (L_α) phase, is its melting temperature (T_m). Because melting is accompanied by a large change in enthalpy the, L_β(') → L_α transition can be monitored by various calorimetric, structural and spectroscopic techniques and T_m should be the same regardless of the metric monitored or the technique employed. However, in the case of DPPE multilamellar aggregates there is a small but systematic deviation of T_m values determined by DSC and FTIR spectroscopy. The aim of this paper is to explain this discrepancy by combined UV/Vis spectroscopic and MD computational approach. Multivariate analysis performed on temperature-dependent UV/Vis spectra of DPPE suspensions demonstrated that at 55 ± 1 °C certain phenomenon causes a small but detectable change in suspension turbidity, whereas a dominant change in the latter is registered at 63.2 ± 0.4 °C that coincides with T_m value determined from DSC curve. If this effect should be ignored, the overall data give T_m value the same as FTIR spectra data (61.0 ± 0.4 °C). As the classical MD simulations suggest that about 10° below T_m certain undulations appear at the surface of DPPE bilayers, we concluded that certain discontinuities in curvature fluctuations arise at reported temperature which are to some extent coupled with lipid melting. Ultimately, such events and the associated changes in curvature affect T_m value measured by different techniques.

Molecular docking and simulation studies of synthetic protease inhibitors against COVID-19: a computational study

COVID-19 is the most recent threat to global health. Many people preferred treatment in case of infection instead of vaccination. The inhibition of viral replication is a good strategy for the treatment of COVID-19 infection. 3CLpro and PLpro are two important viral proteases responsible for proteolysis, infection, and replication of the virus. Therefore, targeting of these two enzymes is an attractive way to deal with COVID-19. The aim of this study was to screen some synthetic protease inhibitors to determine an appropriate hit molecule against COVID-19 using molecular docking and molecular dynamic simulations. The strategy depends on docking existing synthetic compounds mostly HIV protease inhibitors against two COVID-19 proteases to identify promising drugs for the treatment of COVID-19. We used protein data bank to obtain the X-ray crystal structure of the most important COVID-19 proteases 3CL pro (PDB ID: 6M2N) and PL pro (PDB ID: 6WX4). In this conceptual context, an attempt has been made to suggest an in silico computational relationship between 50 synthetic protease inhibitors and COVID-19 proteases. Out of 50 screened compounds, the best docking scores were found for these five protease inhibitors BDBM7021, BDBM698, BDBM694, BDBM93239, BDBM700. A 100-ns MD simulation was carried out to assess the stability of COVID-19 proteases and inhibitors, revealing an average RMSD value of 0.7 and favorable binding free energy (MM-GBSA) for all complexes confirming their potency as powerful binders in the COVID-19 proteases' binding pocket. Furthermore, the current results must be confirmed using in-vitro and in-vivo antiviral methods.Communicated by Ramaswamy H. Sarma.

Deaza-modification of MR1 ligands modulates recognition by MR1-restricted T cells

MR1-restricted T (MR1T) cells recognize microbial small molecule metabolites presented on the MHC Class I-like molecule MR1 and have been implicated in early effector responses to microbial infection. As a result, there is considerable interest in identifying chemical properties of metabolite ligands that permit recognition by MR1T cells, for consideration in therapeutic or vaccine applications. Here, we made chemical modifications to known MR1 ligands to evaluate the effect on MR1T cell activation. Specifically, we modified 6,7-dimethyl-8-D-ribityllumazine (DMRL) to generate 6,7-dimethyl-8-D-ribityldeazalumazine (DZ), and then further derivatized DZ to determine the requirements for retaining MR1 surface stabilization and agonistic properties. Interestingly, the IFN-γ response toward DZ varied widely across a panel of T cell receptor (TCR)-diverse MR1T cell clones; while one clone was agnostic toward the modification, most displayed either an enhancement or depletion of IFN-γ production when compared with its response to DMRL. To gain insight into a putative mechanism behind this phenomenon, we used in silico molecular docking techniques for DMRL and its derivatives and performed molecular dynamics simulations of the complexes. In assessing the dynamics of each ligand in the MR1 pocket, we found that DMRL and DZ exhibit differential dynamics of both the ribityl moiety and the aromatic backbone, which may contribute to ligand recognition. Together, our results support an emerging hypothesis for flexibility in MR1:ligand-MR1T TCR interactions and enable further exploration of the relationship between MR1:ligand structures and MR1T cell recognition for downstream applications targeting MR1T cells.

Practical Guidance for Consensus Scoring and Force Field Selection in Protein-Ligand Binding Free Energy Simulations

The advances in ligand binding affinity prediction have been fostered by system generation tools and improved force fields (FFs). CHARMM-GUI Free Energy Calculator provides input and postprocessing scripts for AMBER-TI free energy calculations with various FFs. In this study, we used 12 different FF combinations (ff14SB and ff19SB for protein, GAFF2.2 and OpenFF for ligand, and TIP3P, TIP4PEW, and OPC for water) to calculate relative binding free energies (ΔΔG_bind) for 80 alchemical transformations (among the JACS benchmark set) with different numbers of λ windows (12 or 21) and simulation times (1, 5, or 10 ns). Our results show that 12 λ windows and 5 ns simulation time for each window are sufficient to obtain reliable ΔΔG_bind with 4 independent runs for the current benchmark set. While there is no statistically noticeable performance difference among 12 different FF combinations compared to the experimental values, a combination of ff14SB + GAFF2.2 + TIP3P FFs appears to be best with a mean unsigned error of 0.87 [0.69, 1.07] kcal/mol, a root-mean-square error of 1.22 [0.94, 1.50] kcal/mol, a Pearson's correlation of 0.64 [0.52, 0.76], a Spearman's correlation of 0.73 [0.58, 0.83], and a Kendell's correlation of 0.54 [0.42, 0.64]. This large-scale ΔΔG_bind calculation study provides useful information about ΔΔG_bind prediction with different AMBER FF combinations and presents valuable suggestions for FF selection in AMBER-TI ΔΔG_bind calculations.

The human signal peptidase complex acts as a quality control enzyme for membrane proteins

Cells need to detect and degrade faulty membrane proteins to maintain homeostasis. In this study, we identify a previously unknown function of the human signal peptidase complex (SPC)—the enzyme that removes endoplasmic reticulum (ER) signal peptides—as a membrane protein quality control factor. We show that the SPC cleaves membrane proteins that fail to correctly fold or assemble into their native complexes at otherwise hidden cleavage sites, which our study reveals to be abundant in the human membrane proteome. This posttranslocational cleavage synergizes with ER-associated degradation to sustain membrane protein homeostasis and contributes to cellular fitness. Cryptic SPC cleavage sites thus serve as predetermined breaking points that, when exposed, help to target misfolded or surplus proteins for degradation, thereby maintaining a healthy membrane proteome.

Identification of Small Molecular Chaperones Binding P23H Mutant Opsin through an In Silico Structure-Based Approach

N-terminal P23H opsin mutation accounts for most of retinitis pigmentosa (RP) cases. P23H functions and folding can be rescued by small chaperone ligands, which contributes to validate mutant opsin as a suitable target for pharmacological treatment of RP. However, the lack of structural details on P23H mutant opsin strongly impairs drug design, and new chemotypes of effective chaperones of P23H opsin are in high demand. Here, a computational-boosted workflow combining homology modeling with molecular dynamics (MD) simulations and virtual screening was used to select putative P23H opsin chaperones among different libraries through a structure-based approach. In vitro studies corroborated the reliability of the structural model generated in this work and identified a number of novel chemotypes of safe and effective chaperones able to promote P23H opsin trafficking to the outer cell membrane.

Molecular docking and molecular dynamics study Lianhua Qingwen granules (LHQW) treats COVID-19 by inhibiting inflammatory response and regulating cell survival

Purpose

2019 Coronavirus disease (COVID-19) is endangering health of populations worldwide. Latest research has proved that Lianhua Qingwen granules (LHQW) can reduce tissue damage caused by inflammatory reactions and relieve patients' clinical symptoms. However, the mechanism of LHQW treats COVID-19 is currently lacking. Therefore, we employed computer simulations to investigate the mechanism of LHQW treats COVID-19 by modulating inflammatory response.

Methods

We employed bioinformatics to screen active ingredients in LHQW and intersection gene targets. PPI, GO and KEGG was used to analyze relationship of intersection gene targets. Molecular dynamics simulations validated the binding stability of active ingredients and target proteins. Binding free energy, radius of gyration and the solvent accessible surface area were analyzed by supercomputer platform.

Results

COVID-19 had 4628 gene targets, LHQW had 1409 gene targets, intersection gene targets were 415. Bioinformatics analysis showed that intersection targets were closely related to inflammation and immunomodulatory. Molecular docking suggested that active ingredients (including: licopyranocoumarin, Glycyrol and 3-3-Oxopropanoic acid) in LHQW played a role in treating COVID-19 by acting on CSF2, CXCL8, CCR5, NLRP3, IFNG and TNF. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets.

Conclusion

The mechanism of active ingredients in LHQW treats COVID-19 was investigated by computer simulations. We found that active ingredients in LHQW not only reduce cell damage and tissue destruction by inhibiting the inflammatory response through CSF2, CXCL8, CCR5 and IFNG, but also regulate cell survival and growth through NLRP3 and TNF thereby reducing apoptosis.

Structural insights into adhesion GPCR ADGRL3 activation and Gq, Gs, Gi, and G12 coupling

Adhesion G-protein-coupled receptors (aGPCRs) play key roles in a diversity of physiologies. A hallmark of aGPCR activation is the removal of the inhibitory GAIN domain and the dipping of the cleaved stalk peptide into the ligand-binding pocket of receptors; however, the detailed mechanism remains obscure. Here, we present cryoelectron microscopy (cryo-EM) structures of ADGRL3 in complex with G_q, G_s, G_i, and G₁₂. The structures reveal unique ligand-engaging mode, distinctive activation conformation, and key mechanisms of aGPCR activation. The structures also reveal the uncharted structural information of GPCR/G₁₂ coupling. A comparison of G_q, G_s, G_i, and G₁₂ engagements with ADGRL3 reveals the key determinant of G-protein coupling on the far end of αH5 of Gα. A detailed analysis of the engagements allows us to design mutations that specifically enhance one pathway over others. Taken together, our study lays the groundwork for understanding aGPCR activation and G-protein-coupling selectivity.

Molecular recognition of morphine and fentanyl by the human μ-opioid receptor

Morphine and fentanyl are among the most used opioid drugs that confer analgesia and unwanted side effects through both G protein and arrestin signaling pathways of μ-opioid receptor (μOR). Here, we report structures of the human μOR-G protein complexes bound to morphine and fentanyl, which uncover key differences in how they bind the receptor. We also report structures of μOR bound to TRV130, PZM21, and SR17018, which reveal preferential interactions of these agonists with TM3 side of the ligand-binding pocket rather than TM6/7 side. In contrast, morphine and fentanyl form dual interactions with both TM3 and TM6/7 regions. Mutations at the TM6/7 interface abolish arrestin recruitment of μOR promoted by morphine and fentanyl. Ligands designed to reduce TM6/7 interactions display preferential G protein signaling. Our results provide crucial insights into fentanyl recognition and signaling of μOR, which may facilitate rational design of next-generation analgesics.

CHARMM-GUI Enhanced Sampler for various collective variables and enhanced sampling methods

Enhanced sampling methodologies modifying underlying Hamiltonians can be used for the systems with a rugged potential energy surface that makes it hard to observe convergence using conventional unbiased molecular dynamics (MD) simulations. We present CHARMM-GUI Enhanced Sampler, a web-based tool to prepare various enhanced sampling simulations inputs with user-selected collective variables (CVs). Enhanced Sampler provides inputs for the following nine methods: accelerated MD, Gaussian accelerated MD, conformational flooding, metadynamics, adaptive biasing force, steered MD, temperature replica exchange MD, replica exchange solute tempering 2, and replica exchange umbrella sampling for the method-implemented MD packages including AMBER, CHARMM, GENESIS, GROMACS, NAMD, and OpenMM. Users only need to select a group of atoms via intuitive web-implementation in order to define commonly used nine CVs of interest: center of mass based distance, angle, dihedral, root-mean-square-distance, radius of gyration, distance projected on axis, two types of angles projected on axis, and coordination numbers. The enhanced sampling methods are tested with several biological systems to illustrate their efficiency over conventional MD. Enhanced Sampler with carefully optimized system-dependent parameters will help users to get meaningful results from their enhanced sampling simulations.

Globin X: A highly stable intrinsically hexacoordinate globin

Several novel members of the vertebrate globin family were recently discovered with unique structural features that are not found in traditional penta-coordinate globins. Here we combine structural tools to better understand and recognize molecular determinants that contribute to the stability of hexacoordinate globin X (GbX) from Danio rerio (zebrafish). pH-induced unfolding data indicates increased stability of GbX with pH_mid of 1.9 ± 0.1 for met GbXWT, 2.4 ± 0.1 for met GbXC65A, and 3.4 ± 0.1 for GbXH90V. These results are in good agreement with GbX unfolding experiments using GuHCl, where a ΔG_unf 13.8 ± 2.5 kcal mol^-1 and 16.3 ± 2.6 kcal mol^-1 are observed for metGbXWT, and metGbXC65A constructs, respectively, and diminished stability is measured for GbXH90V, ΔG_unf = 9.5 ± 3.6 kcal mol^-1. The metGbXWT and metGbXC65A also exhibit high thermal stability (melting points of 118 °C and 107 °C, respectively). Native ion mobility - mass spectrometry (IM-MS) experiments showed a narrow charge state distribution (9-12+) characteristics of a native, structured protein; a single mobility band was observed for the native states. Collision induced unfolding IM-MS experiments showed a two-state transition, in good agreement with the solution studies. GbXWT retains the heme over a wide range of charge states, suggesting strong interactions between the prosthetic group and the apoprotein. The above results indicate that in addition to the disulfide bond and the heme iron hexa-coordination, other structural determinants enhance stability of this protein.