UCSF Chimera Research Articles

IN SILICO STUDY OF MONOSACCHARIDE COMPOUNDS EFFECT ON B CELL RECEPTORS (BCR) FROM NONI FRUIT (MORINDA CITRIFOLIA)

Objective: Noni fruit has been widely used as a treatment. The content of saccharides in noni can affect the immune system, especially as independent antigens (TI) against B cell receptors (BCR). TI can produce antibodies without being influenced by T cells. Therefore, this study aims to look at the effect of IT on BCR with the in silico method approach.
 Methods: Ligands were obtained from Zink Web and macromolecules were obtained from Protein Data Bank with code 2H32. Ligand optimization using VegaZZ software and macromolecules is optimized using UCSF Chimera software. Ligands and macromolecules are docking using MOE software.
 Result: The results showed that monosaccharide compounds have an interaction with BCR, which is characterized by a decrease in free energy. The D-Galactose compound has the largest binding affinity of-4.80 kcal/mol.
 Conclusion: Monosaccharide compounds are independent antigens (TI) of noni (Morinda citrifolia) that can affect on B cell receptors (BCR), which have identical epitopes.

Novel Mutations within PRSS1 Gene that Could Potentially Cause Hereditary Pancreatitis: Using Bioinformatics Approach

Hereditary pancreatitis (HP) is a rare heterogeneous disease with partial penetrance identified by frequent episodes of severe abdominal pain, often showing in young aged children. It is complicating by chronic pancreatitis, and high rate of pancreatic cancer (up to 40-50%). The aim of this work was to classify the most deleterious mutation in PRSS1 gene and to predict their influence on the functional and structural level by a variety of bioinformatics analysis tools. The raw data of PRSS1 gene were recovered from SNP database, and further used to examine a deleterious effect using SIFT, PolyPhen-2, PROVEAN, SNAP2, SNPs&GO, PHD-SNP, PANTHER and P-Mut. The functional analysis predicted that two SNPs “rs1366278558 and rs767036052” have a deleterious effect at functional level. Additionally, we submitted them to I-mutant 3.0, and MUPro respectively to investigate their effect on structural level; the two tools revealed that; two mutations have a dramatic decrease of the protein stability, thus suggesting that the M1R and L4P mutations of PRSS1 gene could destabilize the amino acid interactions causing functional abnormalities of PRSS1 protein. The 3D structure of PRSS1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids. From the comparative analysis at the functional and structural level, these two SNPs “M1R and L4P” have a deleterious effect and thus could be used as diagnostic markers to predict HP. These findings can be used as a platform to develop large-scale studies in the future.

Evaluation of cancer related missense mutations in CENPH

Objective: CENPH, centromere protein H, is one of the constitutive kinetochore proteins. High expression of CENPH has been shown in various forms of cancers; however, studies searching the effect of CENPH mutations in cancers are limited. Therefore, the aim of this study is to investigate the potential effects of the missense mutations of CENPH that have been identified in different cancers.
 Materials and Methods: Missense CENPH mutations, which have been observed in cancers, were downloaded from the COSMIC v89. The effect of missense mutations was predicted by using PredictSNP1.0. The protein structure of the CENPH protein was generated with I-TASSER and missense mutations were visualized on CENPH protein with UCSF Chimera. Structural effects of selected mutations were assessed with HOPE.
 Results: 34 missense mutations were observed in human cancers. Of the 34 missense mutations 18 mutations were predicted as deleterious and 16 mutations were predicted as neutral with ranging expected accuracies. Predicted missense mutations showed a scattered pattern on 3D CENPH protein. Two of the predicted deleterious missense mutations with higher expected accuracy were further analyzed and assessed according to amino acid properties.
 Conclusion: This study provided a systematic analysis and evaluation of missense mutations on a CENPH protein that have been observed in different cancers.

Removal of Organic Pollutants Benzene and Phenol Using Nanofiltration: A Molecular Dynamics Study.

Population growth has resulted in an increased demand for clean water. It is known that chemical pollutants such as phenol and benzene often make water unfit for consumption, and can be responsible for the appearance of diseases such as cancer. In this sense, studies aimed at decontaminating water are still necessary. In this study, molecular dynamics simulations were performed to evaluate the abilities of activated charcoal structures to adsorb benzene and phenol; the results of which were evaluated on the basis of root mean square deviations for all systems. The data were collected from the molecular dynamics (MD) trajectories and edited with the grace plotting tool. Visual molecular dynamics software was used to visualize the MD paths, and images were created using the UCSF chimera software. The results show that activated charcoal are viable alternatives for water decontamination by nanofiltration.

Identification of Novel Key Biomarkers in Simpson-Golabi-Behmel Syndrome (SGBS): Evidence from Bioinformatics Analysis

The Simpson-Golabi-Behmel Syndrome (SGBS) or overgrowth Syndrome is an uncommon genetic X-linked disorder highlighted by macrosomia, renal defects, cardiac weaknesses and skeletal abnormalities. The purpose of the work was to classify the functional nsSNPs of GPC3 to serve as genetic biomarkers for overgrowth syndrome. The raw data of GPC3 gene were retrieved from dbSNP database and used to examine the most damaging effect using eight functional analysis tools, while we used I-mutant and MUPro to examine the effect of SNPs on GPC3 protein structure; The 3D structure of GPC3 protein is not found in the PDB, so RaptorX was used to create a 3D structural prototype to visualize the amino acids alterations by UCSF Chimera; For biophysical validation we used project HOPE; Lastly we run conservational analysis by BioEdit and Consurf web server respectively. Our results revealed three novel missense mutations (rs1460413167, rs1295603457 and rs757475450) that are that are more likely to be responsible for disturbance in the function and structure of GPC3. This work provides new insight into the molecular basis of overgrowth Syndrome by evidence from bioinformatics analysis. Three novel missense mutations (rs757475450, rs1295603457 and rs1460413167) are more likely to be responsible for disturbance in the function and structure of GPC3; therefore, they may be assisting as genetic biomarkers for overgrowth syndrome. As well as these SNPs can be used for the larger population-based studies of overgrowth syndrome.

Protein modeling to assess the pathogenicity of rare variants of SERPINA1 in patients suspected of having Alpha 1 Antitrypsin Deficiency

BackgroundAlpha 1 Antitrypsin (AAT) is a key serum proteinase inhibitor encoded by SERPINA1. Sequence variants of the gene can cause Alpha 1 Antitrypsin Deficiency (AATD), a condition associated with lung and liver disease. The majority of AATD cases are caused by the ‘Z’ and ‘S’ variants – single-nucleotide variations (SNVs) that result in amino acid substitutions of E342K and E264V. However, SERPINA1 is highly polymorphic, with numerous potentially clinically relevant variants reported. Novel variants continue to be discovered, and without reports of pathogenicity, it can be difficult for clinicians to determine the best course of treatment.MethodsWe assessed the utility of next-generation sequencing (NGS) and predictive computational analysis to guide the diagnosis of patients suspected of having AATD. Blood samples on serum separator cards were submitted to the DNA1 Advanced Screening Program (Biocerna LLC, Fulton, Maryland, USA) by physicians whose patients were suspected of having AATD. Laboratory analyses included quantification of serum AAT levels, qualitative analysis by isoelectric focusing, and targeted genotyping and NGS of the SERPINA1 gene. Molecular modeling software UCSF Chimera (University College of San Francisco, CA) was used to visualize the positions of amino acid changes as a result of rare/novel SNVs. Predictive software was used to assess the potential pathogenicity of these variants; methods included a support vector machine (SVM) program, PolyPhen-2 (Harvard University, Cambridge, MA), and FoldX (Centre for Genomic Regulation, Barcelona, Spain).ResultsSamples from 23 patients were analyzed; 21 rare/novel sequence variants were identified by NGS, including splice variants (n = 2), base pair deletions (n = 1), stop codon insertions (n = 2), and SNVs (n = 16). Computational modeling of protein structures caused by the novel SNVs showed that 8 were probably deleterious, and two were possibly deleterious. For the majority of probably/possibly deleterious SNVs (I50N, P289S, M385T, M221T, D341V, V210E, P369H, V333M and A142D), the mechanism is probably via disruption of the packed hydrophobic core of AAT. Several deleterious variants occurred in combination with more common deficiency alleles, resulting in very low AAT levels.ConclusionsNGS and computational modeling are useful tools that can facilitate earlier, more precise diagnosis, and consideration for AAT therapy in AATD.

Visualizing protein-ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site.

Kallikrein-8, a serine protease, is a target for structure-based drug design due to its therapeutic potential in treating Alzheimer's disease and is also useful as a biomarker in ovarian cancer. We present a binding assessment of ligands to kallikrein-8 using a residue-wise decomposition of the binding energy. Binding of four putative inhibitors of kallikrein-8 is investigated through molecular dynamics simulation and ligand binding energy evaluation with two methods (MM/PBSA and WaterSwap). For visualization of the residue-wise decomposition of binding energies, chemical energy-wise decomposition or CHEWD is introduced as a plugin to UCSF Chimera and Pymol. CHEWD allows easy comparison between ligands using individual residue contributions to the binding energy. Molecular dynamics simulations indicate one ligand binds stably to the kallikrein-8 S1 binding site. Comparison with other members of the kallikrein family shows that residues responsible for binding are specific to kallikrein-8. Thus, ZINC02927490 is a promising lead for development of novel kallikrein-8 inhibitors.

Improved De Novo Main-Chain Tracing Method Mainmast for Multi-Chain Modeling, Local Refinement, and Graphical User Interface

The significant progress of the cryo-EM poses a pressing need for software for structural interpretation of EM maps. Particularly, protein structure modeling tools are needed for maps determined around 4 Å resolution, where finding main-chain structure and assigning the amino acid sequence into EM map are still challenging problems. We have developed a de novo modeling tool named MAINMAST (MAINchain Model trAcing from Spanning Tree, http://kiharalab.org/mainmast/) for EM maps for this resolution range (Nature Communications, 2018). MAINMAST builds main-chain traces of a protein in an EM map from a tree structure constructed by connecting points with a high density in the map without referring to known protein structures or fragments.Here, we report substantial improvements of MAINMAST in three aspects. The largest improvement is that the method now can perform automatic map segmentation and structure modeling for symmetrical multi-chain complexes. The tree structure that connects dense points are traced for multiple chains simultaneously in a symmetric fashion. Moreover, the accuracy of a model is significantly improved by a new implementation of local sequence matching and structure refinement. The local matching protocol is also useful for identifying missing regions in a structure model, i.e. regions with a low density, in an EM map. Finally, we developed a software plugin of MAINMAST for the UCSF Chimera, so that users can monitor structures at each step of a modeling procedure. The major functionalities include to generate and to display tree structures from local dense points in the map, main-chain traces, and reconstructed all-atom models. Through the interface, users can easily control parameters of MAINMAST and save and restore sessions.

Structural Analysis of Piezo1 Ion Channel Reveals the Relationship between Amino Acid Sequence Mutations and Human Diseases

Since first identified in 2010, Piezo proteins have been found to perform as poreforming mechanosensitive ion channels across a wide range of animals. As a Piezo ortholog primarily expressed in mammalian systems, Piezo1 has been observed to distribute mainly in nonsensory tissues, regulating osmotic homeostasis, proprioception, and light touch. With previous studies on the putative structure of Piezo1, the gating system and several mechanotransduction mechanisms have been proposed. Besides, mutations of specific amino acid sequences in Piezo1 have been linked to several human diseases such as dehydrated hereditary xerocytosis (DHS) and congenital lymphatic dysplasia (CLD). However, most of these mutations have not been well characterized. To further elucidate the relations between these mutations and diseases, UCSF Chimera is used as the tool to visualize the structural importance of each of these mutated amino acids. With the aid from UCSF Chimera, this study has recorded and interpreted clashes and contacts originated from each of the mutations. Accordingly, specific mechanisms between mutations and human diseases are proposed, which pave the way for healing.

Docking with SwissDock.

Protein-ligand docking simulation is central in drug design and development. Therefore, the development of web servers intended to docking simulations is of pivotal importance. SwissDock is a web server dedicated to carrying out protein-ligand docking simulation intuitively and elegantly. SwissDock is based on the protein-ligand docking program EADock DSS and has a simple and integrated interface. The SwissDock allows the user to upload structure files for a protein and a ligand, and returns the results by e-mail. To facilitate the upload of the protein and ligand files, we can prepare these input files using the program UCSF Chimera. In this chapter, we describe how to use UCSF Chimera and SwissDock to perform protein-ligand docking simulations. To illustrate the process, we describe the molecular docking of the competitive inhibitor roscovitine against the structure of human cyclin-dependent kinase 2.

Functional expression and impact of testis-specific gene antigen 10 in breast cancer: a combined in vitro and in silico analysis.

Introduction: Testis-specific gene antigen 10 (TSGA10) is a less-known gene, which is involved in the vague biological paths of different cancers. Here, we investigated the TSGA10 expression using different concentrations of glucose under hypoxia and also its interaction with the hypoxia-inducible factor 1 (HIF-1). Methods: The breast cancer MDA-MB-231 and MCF-7 cells were cultured with different concentrations of glucose (5.5, 11.0 and 25.0 mM) under normoxia/hypoxia for 24, 48, and 72 hours and examined for the HIF-1α expression and cell migration by Western blotting and scratch assays. The qPCR was employed to analyze the expression of TSGA10. Three-dimensional (3D) structure and the energy minimization of the interacting domain of TSGA10 were performed by MODELLER v9.17 and Swiss-PDB viewer v4.1.0/UCSF Chimera v1.11. The UCSF Chimera v1.13.1 and Hex 6.0 were used for the molecular docking simulation. The Cytoscape v3.7.1 and STRING v11.0 were used for protein-protein interaction (PPI) network analysis. The HIF-1a related hypoxia pathways were obtained from BioModels database and reconstructed in CellDesigner v4.4.2. Results: The increased expression of TSGA10 was found to be significantly associated with the reduced metastasis in the MDA-MB-231 cells, while an inverse relationship was seen between the TSGA10 mRNA level and cellular migration but not in the MCF-7 cells. The C-terminal domain of TSGA10 interacted with HIF-1α with high affinity, resulting in PPI network with 10 key nodes (HIF-1α, VEGFA, HSP90AA1, AKT1, ARNT, TP53, TSGA10, VHL, JUN, and EGFR). Conclusions: Collectively, TSGA10 functional expression alters under the hyper-/hypo-glycemia and hypoxia, which indicates its importance as a candidate bio-target for the cancer therapy.

In Silico Genetics Revealing 5 Mutations in CEBPA Gene Associated With Acute Myeloid Leukemia

Background:Acute myeloid leukemia (AML) is an extremely heterogeneous malignant disorder; AML has been reported as one of the main causes of death in children. The objective of this work was to classify the most deleterious mutation in CCAAT/enhancer-binding protein-alpha (CEBPA) and to predict their influence on the functional, structural, and expression levels by various Bioinformatics analysis tools.Methods:The single nucleotide polymorphisms (SNPs) were claimed from the National Center for Biotechnology Information (NCBI) database and then submitted into various functional analysis tools, which were done to predict the influence of each SNP, followed by structural analysis of modeled protein followed by predicting the mutation effect on energy stability; the most damaging mutations were chosen for additional investigation by Mutation3D, Project hope, ConSurf, BioEdit, and UCSF Chimera tools.Results:A total of 5 mutations out of 248 were likely to be responsible for the structural and functional variations in CEBPA protein, whereas in the 3′-untranslated region (3′-UTR) the result showed that among 350 SNPs in the 3′-UTR of CEBPA gene, about 11 SNPs were predicted. Among these 11 SNPs, 65 alleles disrupted a conserved miRNA site and 22 derived alleles created a new site of miRNA.Conclusions:In this study, the impact of functional mutations in the CEBPA gene was investigated through different bioinformatics analysis techniques, which determined that R339W, R288P, N292S, N292T, and D63N are pathogenic mutations that have a possible functional and structural influence, therefore, could be used as genetic biomarkers and may assist in genetic studies with a special consideration of the large heterogeneity of AML.

MOLECULAR DYNAMICS SIMULATIONS OF SEVERAL SELECTED COMPOUNDS FROM THE HERBAL DATABASE OF INDONESIA RESULTS OF MOLECULAR DOCKING AGAINST DNA METHYLTRANSFERASE ENZYME

Objective: This study aimed to investigate the interactions of DNA methyltransferase (DNMT) enzymes and potential ligands as DNMT inhibitorsthrough molecular dynamics simulations.Methods: This study was conducted using tools in the form of hardware (primary and secondary computers) and software (OpenBabel, AutoDockTools, Amber MD, Amber Tools, VMD, PuTTY, LigandScout, and UCSF Chimera).Results: Results of molecular docking of cassiamin C, procyanidin B2, epicatechin-4alphaent-8-ent-epicatechin, epicatechin-4beta-8-epicatechin-3-O-gallate, neorhusflavanone, 3-O-galloylepigallocatechin -4beta-6-epicatechin-3-O-gallate, withanolide, 3-O-galloylepigallocatechin-4beta-6-epigallocatechin-3-O-gallate, cyanidin-3-6″-caffeylsophoroside-5-glucoside, epifriedelinol, gallocatechin-4alpha-8-epicatechin, scutellarein-7-glucosyl-1-4-rhamnoside, epigallocatechin-3-gallate (EGCG) (positive control), and sinefungin (co-crystal) compounds showed ΔG values −9.34,−10.95, −7.95, −11.01, −8.78, −8.87, −11.49, −7.98, −5.92, −8.92, −9.17, −8.76, −9.70, and −9.11 kcal/mol, respectively. Cassiamin C, procyanidin B2,epicatechin-4-beta-8-epicatechin-3-O-gallate, withanolide, and gallocatechin-4alpha-8-epicatechin compounds had lower ΔG than sinefungin (cocrystal)and EGCG (positive control) compounds. The results of molecular dynamic simulation of seven selected compounds showed the best overallactivities were procyanidin B2, epicatechin-4beta-8-epicatechin-3-O-gallate, and gallocatechin-4alpha-8-epi-catechin compounds.Conclusions: The best overall activities based on molecular docking and molecular dynamic simulation were procyanidin B2, epicatechin-4beta-8-epicatechin-3-O-gallate, and gallocatechin-4alpha-8-epi-catechin compounds. Amino acid residues that are important for the activity of DNMT1inhibitor are Phe1145, Glu1168, Met1169, Cys1191, Glu1266, Ala1579, and Val1580.

In silico structural and functional modelling of Antifreeze protein (AFP) sequences of Ocean pout (Zoarces americanus, Bloch & Schneider 1801).

Antifreeze proteins (AFPs) are known to polypeptide components formed by certain plants, animals, fungi and bacteria which support to survive in sub-zero temperature. Current study highlighted the seven different antifreeze proteins of fish Ocean pout (Zoarces americanus), in which protein (amino acids sequence) were collected from National Centre for Biotechnology Information and finely characterized using several in silico tools. Such biocomputational techniques applied to figure out the physicochemical, functional and conformational characteristics of targeted AFPs. Multiple physicochemical properties such as Isoelectric Point, Extinction Coefficient and Instability Index, Aliphatic Index, Grand Average Hydropathy were calculated and analysed by ExPASy-ProtParam prediction web server. EMBOSS: pepwheel online tool was used to represent the protein sequences in a helical form. The primary structure analysis shows that most of the AFPs are hydrophobic in nature due to the high content of non-polar residues. The secondary structure of these proteins was calculated using SOPMA tool. SOSUI server and CYS_REC program also run for ideal prediction of transmembrane helices and disulfide bridges of experimental proteins respectively. The modelling of 3D structures of seven desired AFPs were executed by the homology modelling programmes; SWISS MODEL and ProSA web server. UCSF Chimera, Antheprot 3D, PyMOL and RAMPAGE were used to visualize and analysis of the structural variation of the predicted protein model. MEGA7.0.9 software used to know the phylogenetic relationship among these AFPs. These models offered excellent and reliable baseline information for functional characterization of the experimentally derived protein domain composition by using the advanced tools and techniques of Computational Biology.

Inhibition of Enterococcus faecalis Growth and Biofilm Formation by Molecule Targeting Cyclic di-AMP Synthetase Activity

IntroductionEnterococcus faecalis is correlated with oral diseases including recurrent root canal treatment failure because of its biofilm formation ability and various virulence factors. Cyclic di-AMP (c-di-AMP) is an omnipresent second messenger involved in many crucial cellular physiological processes, including biofilm formation. ST056083 is a small molecule working as an inhibitor of the c-di-AMP synthetase DNA integrity scanning protein (DisA) in vitro. In this study, the impact of ST056083 on E. faecalis DisA activity, bacterial growth, and biofilm formation was tested. MethodsThe binding affinity between the protein and ligand was evaluated using the Amber score, and the binding mode was analyzed and visualized using UCSF Chimera (Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, San Francisco, CA). The effect of ST056083 on E. faecalis DisA was evaluated using the coralyne assay. The effect of ST056083 on E. faecalis biofilm formation was determined by the biofilm quantification assay, scanning electron microscopic examination, and 3-dimensional confocal laser scanning microscopic assay. The effect of ST056083 on E. faecalis exopolysaccharide synthesis was measured by the anthrone-sulfuric method. ResultsWe expressed and purified E. faecalis DisA in vitro and confirmed the inhibitory effect of ST056083 on its biological activity. In addition, we showed the inhibitory effect of ST056083 on E. faecalis growth, biofilm formation, and exopolysaccharide synthesis. ConclusionsOur findings enhance the understanding of the physiological role of c-di-AMP in E. faecalis and represent a preliminary study on the ST056083 inhibitory effect and mechanism.

Computational Studies of the NUDIX Hydrolase Superfamily

The Protein Structure Initiative (PSI) was an effort by consortiums to solve as many unique protein structures as possible; the Protein Data Bank contains a number of enzymes whose structures have been solved, but for which no enzymatic activity has been determined. The Enzyme Function Initiative (EFI) is an effort to determine as many unique enzyme functions as possible. There are a number of putative NUDIX Hydrolase superfamily members for which structures have been solved, but for which no enzymatic activity has been determined. We have catalogued the structurally‐determined enzymes within the NUDIX Hydrolase superfamily using the PDB, BLAST, Dali, and SCOP. We are now in the process of characterizing these enzymes in the biochemistry teaching laboratory.Computational programs, such as ProMOL and UCSF Chimera, aid in annotating uncharacterized enzymes. ProMOL works by aligning the relative spatial arrangement of the catalytic residues of a reference enzyme with query searches. Chimera is a molecular visualization program that provides various tools for the structural analysis of proteins, including comparative modeling and conformational analysis. We are using these programs to design catalytic motifs for the NUDIX hydrolase superfamily and subfamilies within, which then can be used to uncover family members whose structures have been solved. Likewise, we have used the docking program PyRx, which utilizes AutoDock Vina, to predict substrate specificity, and have discovered that due to its “static” nature, it does not satisfactorily predict substrate specificity. Thus, next we will use a “dynamic” docking program to reevaluate substrate specificity prediction. Through this process, we have discovered the strengths and limitations of these programs.Bioinformatics tools, including databases and computational programs, are good starting points for determining protein function; however, the only way to definitively determine protein function is through experimentally determining activity. Our ultimate goal is to discover and characterize new enzymes from human pathogens as potential novel antibiotic targets.Support or Funding InformationNSF IUSE grant (PAC, JLM, and SOH). RIT College of Science FEAD grant (SOH and JLM).This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics

Traditional informatics in comparative genomics work only with static representations of biomolecules (i.e., sequence and structure), thereby ignoring the molecular dynamics (MD) of proteins that define function in the cell. A comparative approach applied to MD would connect this very short timescale process, defined in femtoseconds, to one of the longest in the universe: molecular evolution measured in millions of years. Here, we leverage advances in graphics-processing-unit-accelerated MD simulation software to develop a comparative method of MD analysis and visualization that can be applied to any two homologous Protein Data Bank structures. Our open-source pipeline, DROIDS (Detecting Relative Outlier Impacts in Dynamic Simulations), works in conjunction with existing molecular modeling software to convert any Linux gaming personal computer into a “comparative computational microscope” for observing the biophysical effects of mutations and other chemical changes in proteins. DROIDS implements structural alignment and Benjamini-Hochberg-corrected Kolmogorov-Smirnov statistics to compare nanosecond-scale atom bond fluctuations on the protein backbone, color mapping the significant differences identified in protein MD with single-amino-acid resolution. DROIDS is simple to use, incorporating graphical user interface control for Amber16 MD simulations, cpptraj analysis, and the final statistical and visual representations in R graphics and UCSF Chimera. We demonstrate that DROIDS can be utilized to visually investigate molecular evolution and disease-related functional changes in MD due to genetic mutation and epigenetic modification. DROIDS can also be used to potentially investigate binding interactions of pharmaceuticals, toxins, or other biomolecules in a functional evolutionary context as well.

PyChimera: use UCSF Chimera modules in any Python 2.7 project.

UCSF Chimera is a powerful visualization tool remarkably present in the computational chemistry and structural biology communities. Built on a C++ core wrapped under a Python 2.7 environment, one could expect to easily import UCSF Chimera's arsenal of resources in custom scripts or software projects. Nonetheless, this is not readily possible if the script is not executed within UCSF Chimera due to the isolation of the platform. UCSF ChimeraX, successor to the original Chimera, partially solves the problem but yet major upgrades need to be undergone so that this updated version can offer all UCSF Chimera features. PyChimera has been developed to overcome these limitations and provide access to the UCSF Chimera codebase from any Python 2.7 interpreter, including interactive programming with tools like IPython and Jupyter Notebooks, making it easier to use with additional third-party software. PyChimera is LGPL-licensed and available at https://github.com/insilichem/pychimera. jaime.rodriguezguerra@uab.cat or jeandidier.marechal@uab.cat. Supplementary data are available at Bioinformatics online.

A Pattern Recognition Tool for Medium-resolution Cryo-EM Density Maps and Low-resolution Cryo-ET Density maps.

Cryo-electron microscopy (Cryo-EM) and cryo-electron tomography (cryo-ET) produce 3-D density maps of biological molecules at a range of resolution levels. Pattern recognition tools are important in distinguishing biological components from volumetric maps with the available resolutions. One of the most distinct characters in density maps at medium (5-10 Å) resolution is the visibility of protein secondary structures. Although computational methods have been developed, the accurate detection of helices and β-strands from cryo-EM density maps is still an active research area. We have developed a tool for protein secondary structure detection and evaluation of medium resolution 3-D cryo-EM density maps which combines three computational methods (SSETracer, StrandTwister, and AxisComparison). The program was integrated in UCSF Chimera, a popular visualization software in the cryo-EM community. In related work, we have developed BundleTrac, a computational method to trace filaments in a bundle from lower resolution cryo-ET density maps. It has been applied to actin filament tracing in stereocilia with good accuracy and can be potentially added as a tool in Chimera.

Functional and In Silico Assessment of GDF3 Gene Variants in a Chinese Congenital Scoliosis Population.

BackgroundThe present study aimed to evaluate the pathogenicity of 5 GDF3 gene variations using functional and in silico assessment approaches in a Chinese congenital scoliosis population.Material/MethodsWe selected 13 patients carrying 5 variants from a congenital scoliosis cohort. The PCR products of samples were verified by Sanger sequencing. The data and sequence alignment were analyzed using Chromas and ClustalW. SIFT and PolyPhen-2 were used to predict the functional effects of each missense and amino acid substitutions. SWISS-MODEL server and Swiss-PdbViewer were used to analyze conformational changes of GDF3 structure. DUET, UCSF Chimera, and Ligplot software were used to further explore the protein stability, side chains, and hydrophobic interaction changes, respectively. Luciferase reporter gene and Western blot assays were used to perform functional assessments for every variant from the molecular level.ResultsOf the 13 patients, the S212L variant reoccurred in 9 patients. The rest of the patients carried 1 missense mutation each. The variants of R84L and R84C were predicted as probably damaging loci. S212L, N215S, A251T were predicted as benign loci. In functional assays, R84L, S212L, and A251T display inhibitory effects on functional assays. N251S mutation showed a negative effect in protein expression assays but not in luciferase reporter gene assays. The variant of R84C displayed no negative effects on 2 functional assays.ConclusionsOur results suggest that the 4 of the 5 variants in GDF3 gene contribute different pathogenicity in congenital scoliosis, which may provide molecular evidence for clinical genetic testing.