UCSF Chimera Research Articles

Molecular Docking Assessment of Limonoids from Cameroonian Entandrophragma Species as Potential Inhibitors of Anopheles gambiae Acetylcholinesterase (AChE)

Malaria remains one of the great killers in tropical regions of the world due to the transmission of the Plasmodium parasite by the bites of the female mosquito Anopheles. The resistance of this species to synthetic insecticides contributes to an increase in the incidence of malaria and therefore necessitates the development of new potent and eco-friendly insecticides. In this study, twelve previously reported limonoids from four Entandrophragma species collected in Cameroon have been computationally evaluated for their Anopheles gambiae AChE inhibitory activity. The docking procedure was carried out through Molecular Operating Environment 2019.01 (MOE), while the UCSF Chimera program was used to model the docking results based on interactions between proteins and ligands, and molecular dynamics trajectories were analyzed using the GROMACS 2021.1 tool. Entandrophragmin and encandollens B and C with docking scores ranging from −6.45 to −7.28 kcal/mol were the most promising hits compared to the reference azadirachtin (−6.22 kcal/mol) and were further evaluated for their mechanism of action. Subsequent evaluation classified encandollen C as the best candidate for the development of new potent eco-friendly insecticides based on its lower average RMSD and RMSF and its compactness over a 150 ns duration with acetylcholinesterase.

Anti-inflammatory effects of resveratrol in treating interstitial cystitis/bladder pain syndrome: a multi-faceted approach integrating network pharmacology, molecular docking, and experimental validation.

This study aims to investigate the anti-inflammatory effects of Resveratrol (RES) in the treatment of Interstitial Cystitis/Bladder Pain Syndrome (IC/BPS) by integrating network pharmacology, molecular docking, and experimental validation. Potential targets of RES were identified using DrugBank and SwissTargetPrediction, while IC/BPS-related targets were obtained from DisGeNET and Genecards. Molecular docking was performed using UCSF Chimera and SwissDock to validate the binding affinity of RES to key targets. Experimental validation involved treating TNF-α induced urothelial cells with RES, followed by assessments using RT-qPCR, ELISA, and Western blotting. A total of 86 drug targets and 211 disease targets were analyzed, leading to the identification of 8 key therapeutic targets for RES in IC/BPS treatment. Molecular docking revealed a strong affinity of RES for ESR2, with notable interactions also observed with SHBG, PTGS2, PPARG, KIT, PI3KCA, and AKT1. In vitro experiments confirmed that RES significantly alleviated the inflammatory response in TNF-α-induced urothelial cells, normalizing the expression levels of ESR2, SHBG, PPARG, and AKT1. RES can modulate critical pathways involving ESR2, SHBG, PPARG, and AKT1, highlighting its potential as a therapeutic agent for IC/BPS. This study provides a theoretical foundation for the clinical application of RES in treating IC/BPS.

Anti-methanogenic effect of pyrogallol in Spirulina platensis – molecular docking and dynamics simulation on methyl-coenzyme M reductase

Methane, along with carbon dioxide and nitrogen oxides, is a key greenhouse gas contributing significantly to the global concern over climate change. This study investigated the anti-methanogenic properties of pyrogallol in Spirulina platensis using molecular docking and dynamics simulation on methyl-coenzyme M reductase (MCR). The Swiss ADME web server was used to identify pyrogallol's absorption, distribution, metabolism, and excretion (ADME) properties. Molecular docking studies were conducted using UCSF Chimera with the Vina script as the executor. The docking results were further analyzed through molecular dynamics simulation using Gromacs-2024. ADME analysis indicated that pyrogallol meets Lipinski’s Rule of Five. Docking studies revealed that pyrogallol has a binding affinity of 4.6 kJ/mol with 2 hydrogen bonds and 1 hydrophobic interaction. Additionally, the MCR-pyrogallol simulation results showed fluctuating root mean square deviation (RMSD) values that stabilized at t = 26,200 until the end of the simulation with an average value of 2.50 nm. Moreover, the hydrogen bonds formed during the simulation fluctuated, with no bonds observed for more than 75% of the simulation time. The energy released during the simulation reached –300.24 kJ/mol with an average of –5.19 kJ/mol. In conclusion, the pyrogallol compound in Spirulina plantensis can potentially inhibit the MCR enzyme, thereby reducing methane production and mitigating the impact of climate change.

CHIMERA_NA: A Customizable Mutagenesis Tool for Structural Manipulations in Nucleic Acids and Their Complexes.

Studying the structure and dynamics of nucleic acids and their complexes is crucial for understanding fundamental biological processes and developing therapeutic interventions. However, the limited availability of experimentally characterized nucleic acid structures poses a challenge for exploring their properties comprehensively. To address this, we developed a customizable mutagenesis tool, CHIMERA_NA, to manipulate nucleic acid structures and their complexes. Utilizing the user-friendly CHIMERA_NA, researchers can perform mutations in nucleic acid structures, enabling the exploration of diverse structural configurations and dynamic behaviors. The tool offers the flexibility to generate all possible combinations of mutations or specific user-defined mutations based on research requirements. CHIMERA_NA leverages the capabilities of UCSF Chimera software, a widely used platform for molecular structure analysis, to facilitate the generation of mutations in nucleic acids. Our tool modifies the reference structure of nucleic acids or their complexes to generate initial coordinates of mutated structures/complexes within seconds for further computational exploration. This capability allows users to extend their investigations beyond structural repositories, enabling the study of DNA/RNA drug recognition, nucleic acid-protein interactions, and the intrinsic structural and dynamic properties of nucleic acids. By providing a user-friendly and customizable approach to nucleic acid mutagenesis, CHIMERA_NA contributes to advancing our understanding of nucleic acid biology and facilitating drug discovery efforts targeting nucleic acid-based mechanisms. CHIMERA_NA is freely available in the Supporting Information of this article.

In-silico binding affinity of a phage display library screened novel peptide against various FABPs.

In accordance to the American Heart Association (AHA), cardiovascular diseases (CVDs) are the leading cause of death around the globe, causing more than 19.1million deaths in 2020. Heart-type fatty acid binding protein (H-FABP) is required for the metabolism of fatty acids (FA) inside cardiomyocytes is reported as a biomarker for myocardial damage. As early as one hour after an Acute myocardial infarction (AMI), H-FABP can be used to detect myocardial ischemia. Thus, H-FABP based detection can reduce the burden on the emergency department. A peptide-based detection system can provide point-of-care diagnostics for CVDs. There is a lot of research being done on peptide-based detection, and it has a lot of potential to help with unmet medical diagnostic needs. A twelve (12) amino acid peptide has been discovered using Phage Display Library Screening. The affinity of peptide with H-FABP and other FABPs has been done using molecular docking and ADMET profile has been done. Molecular docking of small peptides against the target protein can play a crucial role in recognizing peptide binding sites and poses. The docking study was done using the HDOCK server and the visualization of the docked complex was done using Pymol and UCSF chimera. The molecular simulation study of three protein-peptide complexes were done which also validated the binding affinity of peptide with the proteins. The RMSD, RMSF and radius of gyration are also analyzed. The results indicate that H-FABP shows higher level of binding interaction with the peptide having bond length ranging from 2.3 to 3.4 Å. The screened peptide is suitable for H-FABP binding and can be used for prognosis purposes in the heart ischemic conditions.

Network Pharmacology-Based Virtual Screening of Chemical Constituents from Vitexnegundo Linn's Discovered Novel Molecular Targets for Breast Cancer Treatment.

The Chinese chaste tree Vitexnegundo (VN) is a popular herb in South and Southeast Asia that has several health benefits, including the ability to inhibit tumor growth and induce apoptosis in multiple tumors. Literature revealed scanty research on breast cancer, with little focus on the molecular mechanism of the disease and an emphasis on targets, biological networks, and active components. Exploring natural compounds as possible therapeutic options is an old but still promising approach for drug discovery and development. This study used a thorough computational and statistical method to screen potential drug candidates. The active ingredients and targets of VN were identified using SwissADME, SwissTargetPrediction, STITCH, IMPPAT database, KNapSAcK database, and literature. The OMIM and GeneCards databases were searched for possible targets related to breast cancer. The PASS online server was used to check the probability of active metabolite (Pa) against breast cancer. To build protein-protein interactions (PPI) networking, the intersection of disease and drug targets was uploaded to the STITCH database. Cytoscape software was used to analyze the topology parameters of networking to identify hub targets. Gene Ontology (GO) was analyzed using Metascape and ShinyGO, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed using the David database and SR plot, and the site of expression and protein domain were studied using FunRich. We employed AutoDockvina, Discovery Studio, and UCSF ChimeraX software and auxiliary tools for molecular docking and analysis. Zincpharmer was used for pharmacophore mapping. ADMET analysis was conducted using ADMETsar, Swiss ADME, ADMETLab servers, and mypresto using GROMACS for molecular dynamics simulation (MDS). A total of 65 targets and 21 active ingredients were identified. Further investigation was conducted on 20 hub targets selected through PPI networking construction. The enrichment analysis results indicated that the key factors were P, amyloid-beta response, cellular response to amyloid- beta, Pos. reg. of G2/M transition of the mitotic cell cycle, and response to a toxic substance. The molecular docking, pharmacophore mapping, and MD simulation results indicated that apigenin, kaempferol, and luteolin positively interacted with CDK1 and CDK6 proteins. This study is the first to use network pharmacology, molecular docking, pharmacophore mapping, and MD simulation to identify the active ingredients, molecular targets, and critical biological pathways responsible for VN anti-breast cancer. The study provides a theoretical basis for further research in this area.

Comparative analysis of the RVA VP7 and VP4 antigenic epitopes circulating in Iran and the Rotarix and RotaTeq vaccines

Analyzing the lineages and detecting antigenic variation in immunogenic motifs of Group A Rotavirus (RVA) variants is crucial because it can impact vaccine efficacy. This study investigated the circulating lineages of VP4 and VP7 proteins of human RVA isolates and their phylogeny in ≤24-month-old symptomatic, rotavirus-positive children with transudative diarrhea within 48 h of admission to Mofid Children's Hospital between December 2020 and March 2022 in Tehran, Iran. Antigen detection was performed by ELISA, RNA extraction, and semi-nested multiplex PCR for G/P genotypes, followed by sequencing and bioinformatic analysis using multiple sequence alignments in MEGA and phylogenetic analysis by Geneious Prime. The similarity of VP7 and VP4 amino acids with the RotaTeq and Rotarix vaccine strains for cytotoxic T cell and antigenic epitopes was evaluated using the UCSF Chimera Molecular Modeling System. Overall, 27.3 % of the samples were RVA positive, showing untypeable (2.5 %), single (76.9 %), and mixed (20.5 %) genotypic characteristics. The strains clustered in the G1/II, G2/IV, G3/I, G4/I, G9/III, P[8]/III, P[4]/V, and P[6]/I lineages. Comparative analysis of VP7 antigenic epitopes showed that the G1/II strains were completely conserved, while the G2/IV, G3/I, G4/I, G6, G9/III strains contained 2, 3–5, 2, 4 and 9 amino acid substitutions, respectively. The P[8]/III genotypes differed by 3 amino acids, while the P[6]/I genotype had the most substitutions. CTL epitopes were completely conserved in G3/I strains, but other genotypes differed by 1–4 amino acids compared to the vaccine strains. Given the diversity of circulating RVA genotypes and the observed mutations in neutralizing and CTL epitopes, immune escape by some of the strains is likely in Iran. This finding underscores the importance of evaluating the effect of rotavirus vaccines on local genotypes and related lineages before implementing a vaccination program.

Computational Screening for the Dipeptidyl Peptidase-IV Inhibitory Peptides from Putative Hemp Seed Hydrolyzed Peptidome as a Potential Antidiabetic Agent.

Dipeptidyl peptidase-IV (DPPIV) inhibitory peptides are a class of antihyperglycemic drugs used in the treatment of type 2 diabetes mellitus, a metabolic disorder resulting from reduced levels of the incretin hormone GLP-1. Given that DPPIV degrades incretin, a key regulator of blood sugar levels, various antidiabetic medications that inhibit DPPIV, such as vildagliptin, sitagliptin, and linagliptin, are employed. However, the potential side effects of these drugs remain a matter of debate. Therefore, we aimed to investigate food-derived peptides from Cannabis sativa (hemp) seeds. Our developed bioinformatics pipeline was used to identify the putative hydrolyzed peptidome of three highly abundant proteins: albumin, edestin, and vicilin. These proteins were subjected to in silico digestion by different proteases (trypsin, chymotrypsin, and pepsin) and then screened for DPPIV inhibitory peptides using IDPPIV-SCM. To assess potential adverse effects, several prediction tools, namely, TOXINpred, AllerCatPro, and HemoPred, were employed to evaluate toxicity, allergenicity, and hemolytic effects, respectively. COPID was used to determine the amino acid composition. Molecular docking was performed using GalaxyPepDock and HPEPDOCK, 3D visualizations were conducted using the UCSF Chimera program, and MD simulations were carried out with AMBER20 MD software. Based on the predictive outcomes, FNVDTE from edestin and EAQPST from vicilin emerged as promising candidates for DPPIV inhibitors. We anticipate that our findings may pave the way for the development of alternative DPPIV inhibitors.

RNA-Seq data analysis reveals novel nonsense mutations in the NPR3 gene leading to the progression of intellectual disability disorder

Intellectual disability (ID) is a progressive disorder that affects around 1–3% of the world's population. The heterogeneity of intellectual disability makes it difficult to diagnose as a complete disease. Genetic factors and major mutations play a noticeable role in the development and progression of ID. There is a high need to explore novel variants that may lead to new insights into the progressive aspects of ID. In the current course of study, 31 samples of ID from different studies available on GEO (GSE77742, GSE74263, GSE90682, GSE98476, GSE108887, GSE145710, and PRJEB21964) datasets were taken for the study. These datasets were analyzed for differential gene expression and single nucleotide polymorphism (SNPs). The SNPs of high impact were compared with the differentially expressed genes. Comparison leads to the identification of the priority gene ie NPR3 gene. The identified priority gene further was evaluated for the effect of the mutation using a Mutation Taster. Structure comparison analysis of the wild and mutated proteins of the NPR3 gene was further carried out by UCSF Chimera. Structural analysis reveals the anomalies in protein expression affecting the regulations of the NPR3 gene. These findings identified a novel nonsense mutation (E222*) in the downregulated NPR3 gene that leads to anomalies in the regulation of its protein expression. This missense mutation reveals a major role in causing ID. Our study concludes that the decrease in the expression of the NPR3 gene causes delayed sensory, motor, and physiological functions of the human brain leading to neurodevelopmental delay that causes ID.

How do physicochemical properties contribute to inhibitory activity of promising peptides against Zika Virus NS3 protease?

Flavivirus diseases' cycles, especially Dengue and Yellow Fever, can be observed all over Brazilian territory, representing a great health concern. Additionally, there are no drugs available in therapy. In this scenario, in silico methodologies were applied to obtain physicochemical properties, as well as to better understand the ligand-biological target interaction mode of 20 previously reported NS2B/NS3 protease inhibitors of Dengue virus. Since catalytic site of flavivirus hold similarities, such as the same catalytic triad (His51, Asp75 e Ser135), the ability of this series of molecules to fit in Zika NS3 domains can be achieved. We performed an exploratory data analysis, using statistical methodologies, such as PCA (Principal Component Analysis) and HCA (Hierarchical Component Analysis), to assist the comprehension of how physicochemical properties impact the interaction observed by the docking studies, as well as to build a correlation between the respective ranked characteristics. Based on these previous studies, peptides were selected for the dynamics simulations, which were useful to better understand the ligand-protein interactions. Information relating to, for instance, energy, ΔG, average number of hydrogen bonds and distance from Ser135 (one of the main amino acids in the catalytic pocket) were discussed. In this sense, peptides 15 (considering ΔG value and Hbond number), 7 (ΔG and energy) and 1, 6, 7 and 15 (the proximity to Ser135 throughout the dynamics simulation) were highlighted as promising. Those interesting results could contribute to future studies regarding Zika virus drug design, since this infection represents a great concern in neglected populations. The models were constructed in the ChemDraw software. The ligand parametrization was performed in the CHEM3D 17.0, UCSF Chimera. Docking simulations were carried out in the GOLD software, after the redocking validation. We used ASP as the function score. Additionally, for dynamics simulations we applied GROMACS software, exploring, mainly, free binding energy calculations. Exploratory analysis was carried out in Minitab 17.3.1 statistical software. Prior to the exploratory analysis, data of quantum chemical properties of the peptides were collected in Microsoft Excel spreadsheet and organized to obtain Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA).

In silico simulation of hyperoside, isoquercetin, quercetin, and quercitrin as potential antivirals against the pNP868R protein of African swine fever virus.

African swine fever (ASF) causes disease in pigs with up to 100% mortality rates. There is no effective vaccine to protect against it. This study aimed to perform in silico docking of ASF virus (ASFV) pNP868R protein with potential flavonoid ligands to identify ligands that interfere with mRNA cap formation. The ASFV pNP868R protein was tested with hyperoside, isoquercetin, quercetin, and quercitrin in this in silico simulation. ASFV pNP868R protein was extracted from the Research Collaboration for Structural Bioinformatics Protein Data Bank (RCSB PDB) database with PDB ID 7D8U (https://www.rcsb.org/structure/7D8U). Standard ligands were separated from proteins using UCSF Chimera 1.13. The standard ligand was redocked to protein using AutoDockTools 1.5.6 with the AutoDock4 method for validation. In the docking process, the grid box size was 40 × 40 × 40 Å3 with x, y, and z coordinates of 16.433, -43.826, and -9.496, respectively. The molecular docking process of the proposed ligand-protein complex can proceed if the standard ligand position is not significantly different from its original position in the viral protein's pocket. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (RoG) of the hyperoside with the lowest energy binding need to be analyzed with molecular dynamics using Groningen machine for chemical simulation 5.1.1. Molecular docking and dynamic simulation revealed that hyperoside had the most stable and compact binding to the pNP868R protein. Hyperoside binds to the protein at the minimum energy of -9.07 KJ/mol. The RMSD, RMSF, and RoG values of 0.281 nm, 0.2 nm, and 2.175 nm, respectively, indicate the stability and compactness of this binding. Hyperoside is the most likely antiviral candidate to bind to the pNP868R protein in silico. Therefore, it is necessary to test whether this flavonoid can inhibit mRNA capping in vitro and elicit the host immune response against uncapped viral mRNA.

The design of Benzimidazole derivatives to bind to GDP-bound K-RAS for targeted cancer therapy

KRAS is a proto-oncogene that plays an important role in cell proliferation and division. It is found to be mutated in approximately 25% of cancer tumors. Several studies have tried to find ways to inhibit the KRAS protein, with modest success. This research aims to design molecules to bind to GDP-bound KRAS to predict how different molecules might bind to an inactivated version of the protein. We observed the binding affinity of various small molecules using UCSF Chimera and Autodock Vina and modified them to enhance their affinity to GDP-bound KRAS. We hypothesized that oxygen additions to the compound would increase hydrogen bonds, which in turn would increase the thermodynamic favorability of binding. We observed that molecules with favorable free-energy binding affinities tended to have more hydrogen bonds between the ligand and the protein, and they were mostly between oxygens in the ligand and various residues on the protein. Certain benzimidazole derivatives, such as Methiazole and Fenbendazole, have been found to inhibit growth of KRAS-mutant cells, so we tested several benzimidazole derivatives on GDP-bound KRAS in silico. Irbesartan had the most favorable binding affinity after modifications as compared to the other compounds docked on GDP-bound KRAS. The modified versions of Irbesartan can bind to GDP-bound KRAS better than the original Irbesartan.

In silico prediction and in vitro assessment of novel heterocyclics with antimalarial activity

The development of new antimalarials is paramount to keep the goals on reduction of malaria cases in endemic regions. The search for quality hits has been challenging as many inhibitory molecules may not progress to the next development stage. The aim of this work was to screen an in-house library of heterocyclic compounds (HCUV) for antimalarial activity combining computational predictions and phenotypic techniques to find quality hits. The physicochemical determinants, pharmacokinetic properties (ADME), and drug-likeness of HCUV were evaluated in silico, and compounds were selected for structure-based virtual screening and in vitro analysis. Seven Plasmodium target proteins were selected from the DrugBank Database, and ligands and receptors were processed using UCSF Chimera and Open Babel before being subjected to docking using Autodock Vina and Autodock 4. Growth inhibition of P. falciparum (3D7) cultures was tested by SYBR Green assays, and toxicity was assessed using hemolytic activity tests and the Galleria mellonella in vivo model. From a total of 792 compounds, 341 with good ADME properties, drug-likeness, and no interference structures were subjected to in vitro analysis. Eight compounds showed IC50 ranging from 0.175 to 0.990 µM, and active compounds included pyridyl-diaminopyrimido-diazepines, pyridyl-N-acetyl- and pyridyl-N-phenyl-pyrazoline derivatives. The most potent compound (UV802, IC50 0.178 µM) showed no toxicophoric and was predicted to interact with P. falciparum 1-cysperoxidredoxin (PfPrx1). For the remaining 7 hits (IC50 < 1 μM), 3 showed in silico binding to PfPrx1, one was predicted to bind the haloacid dehalogenase-like hydrolase and plasmepsin II, and one interacted with the plasmodial heat shock protein 90.

Structural Modeling of Biological Entities, Such as Viruses, At Atomic Resolution

The structural modeling of biological entities, particularly viruses, at the atomic level is a noteworthy pursuit in the field of molecular biology. This endeavor necessitates the application of advanced computational techniques to elucidate the three-dimensional structures of these entities at the molecular level, thereby providing insights into their functioning and interactions with other biological components. The results of such studies hold immense potential for enhancing our understanding of the fundamental mechanisms governing biological processes and informing the development of novel therapeutic strategies. The achievements in question were realized through the utilization of UCSF Chimera, a software program for molecular visualization. These accomplishments include the investigation of T bacteriophages and other bacterial infection models. To attain this level of detail, X-ray structures and cryo-EM maps sourced from the RCSB (Research Collaboratory for Structural Bioinformatics) and EMDB (Electron Microscopy Data Bank) databanks were employed in conjunction with a high-performance computer to construct structures comprising millions of atoms.

In silico Characterization of Esophageal Cancer Predominant Genes

Cancer is an important health problem nowadays. One of these problems is esophageal cancer (EC). The 7th most common cancer is EC worldwide. Rhomboid-related biomarkers play an important role in EC. Analysis of such biomarkers can yield important insights into the role of rhomboid 5 Homolog 2 (RHBDF2) in cancer pathology. The characterization of genes was made in silico tools such as STRING, SWISS-MODEL, UCSF Chimera ver 1.15, ProtParam, and GeneCards. The protein interactions string of the rhomboid 5 homologs 2 (RHBDF2) gene was obtained from STRING. Epidermal growth factor (EGF), and ADAM Metallopeptidase Domain 17 (ADAM17) genes were detected as related genes. Amino acid sequences of these genes were obtained from NCBI. Homology models, and Ramachandran graphic of RHBDF2, ADAM17, and EGF genes were created by the SWISS-MODEL database and UCSF Chimera ver 1.15 program. Physicochemical properties of RHBDF2, ADAM17, and EGF genes were calculated by the ProtParam database. Subcellular localizations were detected by the GeneCards server. As a result of this study, genomic and subcellular localization of RHBDF2, ADAM17, and EGF genes were obtained. Amino acid sequences, 3D-protein structures, and physicochemical properties were detected.

Investigation of the mutated antimicrobial peptides to inhibit ACE2, TMPRSS2 and GRP78 receptors of SARS-CoV-2 and angiotensin II type 1 receptor (AT1R) as well as controlling COVID-19 disease

SARS-CoV-2 is a global problem nowadays. Based on studies, some human receptors are involved in binding to SARS-CoV-2. Thus, the inhibition of these receptors can be effective in the treatment of Covid-19. Because of the proven benefits of antimicrobial peptides (AMPs) and the side effects of chemical drugs, they can be known as an alternative to recent medicines. RCSB PDB to obtain PDB id, StraPep and PhytAMP to acquire Bio-AMPs information and 3-D structure, and AlgPred, Toxinpred, TargetAntiAngio, IL-4pred, IL-6pred, ACPred and Hemopred databases were used to find the best score peptide features. HADDOCK 2.2 was used for molecular docking analysis, and UCSF Chimera software version 1.15, SWISS-MODEL and BIOVIA Discovery Studio Visualizer4.5 were used for mutation and structure modeling. Furthermore, MD simulation results were achieved from GROMACS 4.6.5. Based on the obtained results, the Moricin peptide was found to have the best affinity for ACE2. Moreover, Bacteriocin leucocin-A had the highest affinity for GRP78, Cathelicidin-6 had the best affinity for AT1R, and Bacteriocin PlnK had the best binding affinity for TMPRSS2. Additionally, Bacteriocin glycocin F, Bacteriocin lactococcin-G subunit beta and Cathelicidin-6 peptides were the most common compounds among the four receptors. However, these peptides also have some side effects. Consequently, the mutation eliminated the side effects, and MD simulation results indicated that the mutation proved the result of the docking analysis. The effect of AMPs on ACE2, GRP78, TMPRSS2 and AT1R receptors can be a novel treatment for Covid-19. Communicated by Ramaswamy H. Sarma

In-silico assessment of the potential impact of missense SNPs in SYNE4 and SUN1 on the LINC complex and their association with hearing loss

The LINC complex plays a significant role in the auditory system, as it participates in maintaining proper positioning and survival of the nucleus within the outer hair cells. To investigate the potential effect of mutations on the LINC complex structure and its association with hearing loss, we used a computational approach to analyze missense SNPs in SYNE4 and SUN1 genes, which encode Nesprin4 and SUN1 proteins, respectively. SNPs were collected from the Ensembl database and subsequently subjected to various prediction tools, such as SIFT, Polyphen2, MetaRNN, Mutation Taster, Provean, BayesDel_addAF, M-CAP, and MetaRL. Then, the UCSF chimera was used for the introduction of a corresponding amino acid substitution in each protein. HADDOCK 2.4 executed a molecular docking, the protein–protein interaction was driven by PRODIGY, and the conservation state was determined using ConSurf. Finally, a molecular dynamics simulation using Gromacs (2019.3) software was executed for the LINC complexes that correspond to the most deleterious variants for both genes. Our findings show that specific variants in SYNE4 (C381F) and SUN1 (D735Y, D735G, R761W, and C773R) significantly affect the structural integrity of the LINC complex, leading to observable destabilization. These variants are predicted to have a damaging effect on hearing ability. The bioinformatics tools employed in this study consistently predicted these variants as highly structurally affected. However, further investigations are necessary to establish a more comprehensive understanding of the precise implications of these alterations on human auditory function.

Tetrasiklin Antibiyotikleri ve Bromelain Enzimi Arasındaki Etkileşimlerin Kenetleme Araçları Kullanılarak İncelenmesi

Bromelain, extracted from the stem of the pineapple, is a complex enzyme used for different purposes. Bromelain supplements are often used to facilitate digestion, improve the circulatory system and relieve arthritis symptoms due to its pain relief. However, in some cases where there is a risk of antibiotic use or bleeding, the use of bromelain or direct consumption of pineapple should be limited. For this purpose, this study was carried out to show the mechanism by which the antibiotic bromelain interaction occurs. Firstly, the bromelain molecule and demeclocycline, minocycline, and tetracycline antibiotics were prepared in the UCSF Chimera visualizing program. The interactions were monitored in the Auto Dock Molecular Modelling Toolkit molecular modeling program. The free binding energies of these interactions were also calculated in Auto Dock. According the molecular modelling results, bromelain and demeclocycline, minocycline, tetracycline antibiotics were interact with hydrogen bonds and hydrophobic interactions. These interactions between bromelain and antibiotics were energetically favorable based on free binding energy calculations.

Structural Effect of Gγ and Aγ Globin Chains in Fetal Hemoglobin Tetramer

Introduction. Hemoglobin (Hb) is a tetrameric oxigen and carbon dioxide transportation protein; it is composed of four polypeptide chains, two of alpha type, which can be ζ, α 2 or α 1; and two beta chains, which include ε, Gγ, Aγ, δ or β (Antonini and Brunori, 1970).The synthesis of these globin chains depends on the stage of human development; in embryonic stages the hemoglobins Gower I (ζ 2ε 2), Gower II (α 2ε 2) and Portland (ζ 2γ 2) are synthesized; subsequently, from the third week of gestation begins the synthesis of fetal hemoglobin (HbF) formed by two alpha chains and two gamma chains (α 2γ 2); finally during the last trimester the second hemoglobin switching takes place consisting on decreased synthesis of gamma globin chains and the beginning of beta and delta globin chain synthesis that will be forming adult hemoglobin (α 2β 2) and hemoglobin A 2 (α 2δ 2), which will remain constant throughout extrauterine life (Wilber, 2011). One of the molecular mechanisms that has allowed the evolutionary success of humans has been gene duplication, although it results from a random process it favors DNA variation that increases the adaptive capacity of a population (Magadum, 2013). The high homology between duplicated genes is clear, however, it allows differences to arise because of genetic conversion, globin genes HBG2, HBG1, for instance ,which can be observed in their functional products; Gγ and Aγ globin chains (Chen, 2007), both formed by 146 residues, with their distinct difference a position 136 where there is a change of glycine in Gγ by alanine in Aγ and maintain a ratio of 3:1 ( Gγ: Aγ) during fetal stages; while in extra uterine life this ratio is reversed to 2:3 ( Gγ: Aγ), the heterogeneity of γ globins available for HbF synthesis allows the formation of three variants of the same molecule α 2Gγ 2; 2α A/Gγ and 2α Aγ 2; these γ globin chainsdifferences potential implication on HbF interaction with oxygen has not been elucidated as well as whether the presence of a specific type occurs to a greater or lesser extent in different pathologies(Alter 1979). Objective . To evaluate the structural effect of the type of γ globin chain in three models of Fetal Hemoglobin. Methodology . Modeling of the three HbF possible structures: α 2Gγ 2; 2α A/Gγ and 2α Aγ 2 was performed on UCSF Chimera using the crystallography structures of a HbA (1a3n) and Hb Bart (1i3d) hemoglobins as atomic position templates of α and Aγglobin chains. HbF models as well as HbA and Bart hemoglobin (as reference) where then uploaded to CHARMM-GUIplatform to establish system conditions for molecular dynamic simulation such as force field (c36m), water box size (90 Å) and temperature (310 K), molecular dynamics simulation was run for 100 ns on GROMCS (by triplicate), results were analyzed by Root Mean Square Deviation (RMDS) and Root Mean Square Fluctuation (RMSF) of γ globin chains. Results.Three different HbF tetrameric structures where created based on γ globin chains available α 2Gγ 2; 2α A/Gγ and 2α Aγ 2, RMSD shows fluctuation in atomic positions through time among the three HbF models (figure 1: a, b, c), it is shown that the HbF behavior most similar to HbA (figure 1d) is the 2α A/Gγ (figure 1b)which could indicate that this particular type of HbF would be the more abundant during healthy extrauterine life since HbA responds to a normoxic environment that can become hypoxic at medular level when some disease are present, leukemia for instance. By comparing Bart hemoglobin to HbF models is clear that Aγreduces residues movement, limiting tetramer flexibility thus restraining allosteric changes needed for gases exchange, which can be seen when analyzing HbF γ globin chains at 100-146 residues region where there is no fluctuation in the Aγ 2chains opposite to what is shown by Gγ 2 (Figure 2a, b and c). To evaluate these RMSD results, cluster analysis was performed for each replica in the three HbF structures, resulting in values of α 2Gγ 2: 0.13, 2α A/Gγ and 2α Aγ 2: 0.12 with differences below 0.20 among replicates showing the validity of the results. Conclusion and perspectives . There are structural changes in HbF depending on the presence of Gγ or Aγ globin chains. Further studies are required to identify the type of tetramer present in healthy individuals as in patients with different blood malignancies where HbF has been reported as a therapeutic target or risk factor to understand its effect and association with opposite outcomes.

UCSF ChimeraX: Tools for structure building and analysis.

Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3-4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine-learning structure predictions, provide likelihood-based fitting in maps, and compute per-residue scores to identify modeling errors. Additional model-building tools assist analysis of mutations, post-translational modifications, and interactions with ligands. We present the latest ChimeraX model-building capabilities, including several community-developed extensions. ChimeraX is available free of charge for noncommercial use at https://www.rbvi.ucsf.edu/chimerax.