Knowledge-based real-space explorations for low-resolution structure determination

Antiviral effects of probiotic metabolites on COVID-19

SARS coronavirus (COVID-19) is a real health challenge of the 21st century for scientists, health workers, politicians, and all humans that has severe cause epidemic worldwide. The virus exerts its pathogenic activity through by mechanism and gains the entry via spike proteins (S) and Angiotensin-Converting Enzyme 2 (ACE2) receptor proteins on host cells. The present work is an effort for a computational target to block the residual binding protein (RBP) on spike proteins (S), Angiotensin-Converting Enzyme 2 (ACE2) receptor proteins by probiotics namely Plantaricin BN, Plantaricin JLA-9, Plantaricin W, Plantaricin D along with RNA-dependent RNA polymerase (RdRp). Docking studies were designed in order to obtain the binding energies for Plantaricin metabolites. The binding energies for Plantaricin W were -14.64, -11.1 and -12.68 for polymerase, RBD and ACE2 respectively comparatively very high with other compounds. Plantaricin W, D, and JLA-9 were able to block the residues (THR556, ALA558) surrounding the deep grove catalytic site (VAL557) of RdRp making them more therapeutically active for COVID-19. Molecular dynamics studies further strengthen stability of the complexes of plantaricin w and SARS-CoV-2 RdRp enzyme, RBD of spike protein, and human ACE2 receptor. The present study present multi-way options either by blocking RBD on S proteins or interaction of S protein with ACE2 receptor proteins or inhibiting RdRp to counter any effect of COVID-19 by Plantaricin molecules paving a way that can be useful in the treatment of COVID-19 until some better option will be available.Communicated by Ramaswamy H. Sarma.

Escherichia coli expression and characterization of α-amylase from Geobacillus thermodenitrificans DSM-465

Alpha amylase, catalyzing the hydrolysis of starch is a ubiquitous enzyme with tremendous industrial applications. A 1698 bp gene coding for 565 amino acid amylase was PCR amplified from Geobacillus thermodenitrificans DSM-465, cloned in pET21a (+) plasmid, expressed in BL21 (DE3) strain of E. coli and characterized. The recombinant enzyme exhibited molecular weight of 63 kDa, optimum pH 8, optimum temperature 70°C, and KM value of 157.7µM. On pilot scale, the purified enzyme efficiently removed up to 95% starch from the cotton fabric indicating its desizing ability at high temperature. 3D model of enzyme built by Raptor-X and validated by Ramachandran plot appeared as a monomer having 31% α-helices, 15% β-sheets, and 52% loops. Docking studies have shown the best binding affinity of enzyme with amylopectin (∆G -10.59). According to our results, Asp 232, Glu274, Arg448, Glu385, Asp34, Asn276, and Arg175 constitute the potential active site of enzyme.

The Computational Intervention of Macrolide Antibiotics in the Treatment of COVID-19

BACKGROUND

The spike (S) glycoprotein of SARS corona virus (SARS-CoV-2) and human Angiotensin- converting enzyme 2 (ACE2), are both considered the key factors for the initiation of virus infection. The present work is an effort for computational target to block the spike proteins (S) and ACE2 receptor proteins with Macrolide antibiotics like Azithromycin, (AZM), Clarithromycin (CLAM) and Erythromycin (ERY) along with RNA-dependent RNA polymerase (RdRp).

METHODS

Three-dimensional structure of the SARS-CoV-2RdRp was built by the SWISS-MODEL server, the generated structure showed 96.35% identity to the available structure of SARS-Coronavirus NSP12 (6NUR), for model validity, we utilized the SWISS-model server quality parameters and Ramachandran plots.

RESULTS

These compounds were able to block the residues (Arg553, Arg555, and Ala558) surrounding the deep grove catalytic site (Val557) of RdRp and thus plays an important role in tight blocking of enzyme active site. Reference drug Remdesivir was used to compare the docking score of antibiotics with RdRp. Docking value exhibited good binding energy (-7.7 up to -8.2 kcal/mol) with RdRp, indicating their potential as a potent RdRp inhibitor. Interaction of CLAM and ERY presented low binding energy (-6.8 and -6.6) with the ACE2 receptor. At the same time, CLAM exhibited a good binding affinity of -6.4 kcal/mol, making it an excellent tool to block the attachment of spike protein to ACE2 receptors. Macrolides not only affected the attachment to ACE2 but also blocked the spike proteins further, consequently inhibiting the internalization in the host cell. Three Alkyl bonds between Arg555, Ala558, and Met542 by CLAM and two Alkyl bonds of Arg624 and Lys621 by ERY plays an important role for RdRp inactivation, that can prevent the rise of newly budded progeny virus. These macrolides interacted with the main protease protein in the pocket responsible for the dimerization and catalytic function of this protein. The interaction occurred with residue Glu166, along with the catalytic residues (Tyr343, and His235) of Endoribonuclease (NSP15) protein.

CONCLUSION

The present study gives three-way options either by blocking S proteins or ACE2 receptor proteins or inhibiting RdRp to counter any effect of COVID-19 by macrolide and could be useful in the treatment of COVID-19 till some better option available.

Combinatorial screening algorithm to engineer multiepitope subunit vaccine targeting human T-lymphotropic virus-1 infection

Human T-lymphotropic virus (HTLV), the first human retrovirus has been discovered which is known to cause the age-old assassinating disease HTLV-1 associated myelopathy. Cancer caused by this virus is adult T cell leukemia/lymphoma which targets 10-20 million throughout the world. The effect of this virus extends to the fact that it causes chronic disease to the spinal cord resulting in loss of sensation and further causes blood cancer. So, to overcome the complications, we designed a subunit vaccine by the assimilation of B-cell, cytotoxic T-lymphocyte , and helper T-lymphocyte epitopes. The epitopes were joined together along with adjuvant and linkers and a vaccine was fabricated which was further subjected to 3D modeling. The physiochemical properties, allergenicity, and antigenicity were evaluated. Molecular docking and dynamics were performed with the obtained 3D model against toll like receptor (TLR-3) immune receptor. Lastly, in silico cloning was performed to ensure the expression of the designed vaccine in pET28a(+) expression vector. The future prospects of the study entailed the in vitro and in vivo experimental analysis for evaluating the immune response of the designed vaccine construct.

Restraining Pathogenicity in Candida albicans by Taxifolin as an Inhibitor of Ras1-pka Pathway

Candida albicans is one of the most virulent and opportunistic fungal strains. In the present scenario, majority metabolic imbalances and unsuccessful treatments of some severe diseases including cancer, diabetes, HIV, psoriasis are because of invasive Candida emergence. Being a beneficial integral part of human biome, its elimination is not possible. The major pathogenicity characteristics in Candida involve hyphal growth, biofilm formation, HSP90 down regulation and genetic modifications. Ras1-pka pathway initiated by HSP90 down regulation is important for hyphal growth and has been focused in the present study. The principle transcriptional factors that induce hyphal growth causing invasiveness and virulence through this pathway have been identified as Tec1 and Rfg1. In the present study, taxifolin, a naturally occurring polyphenol, has been identified as inhibitor for both the transcriptional factors in parallel.

Databases, Repositories, and Other Data Resources in Structural Biology

Structural biology, like many other areas of modern science, produces an enormous amount of primary, derived, and "meta" data with a high demand on data storage and manipulations. Primary data come from various steps of sample preparation, diffraction experiments, and functional studies. These data are not only used to obtain tangible results, like macromolecular structural models, but also to enrich and guide our analysis and interpretation of various biomedical problems. Herein we define several categories of data resources, (a) Archives, (b) Repositories, (c) Databases, and (d) Advanced Information Systems, that can accommodate primary, derived, or reference data. Data resources may be used either as web portals or internally by structural biology software. To be useful, each resource must be maintained, curated, as well as integrated with other resources. Ideally, the system of interconnected resources should evolve toward comprehensive "hubs", or Advanced Information Systems. Such systems, encompassing the PDB and UniProt, are indispensable not only for structural biology, but for many related fields of science. The categories of data resources described herein are applicable well beyond our usual scientific endeavors.

Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations

Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/.

Structure and function of a spectrin-like regulator of bacterial cytokinesis

Bacterial cell division is facilitated by a molecular machine--the divisome--that assembles at mid-cell in dividing cells. The formation of the cytokinetic Z-ring by the tubulin homologue FtsZ is regulated by several factors, including the divisome component EzrA. Here we describe the structure of the 60-kDa cytoplasmic domain of EzrA, which comprises five linear repeats of an unusual triple helical bundle. The EzrA structure is bent into a semicircle, providing the protein with the potential to interact at both N- and C-termini with adjacent membrane-bound divisome components. We also identify at least two binding sites for FtsZ on EzrA and map regions of EzrA that are responsible for regulating FtsZ assembly. The individual repeats, and their linear organization, are homologous to the spectrin proteins that connect actin filaments to the membrane in eukaryotes, and we thus propose that EzrA is the founding member of the bacterial spectrin family.

Reaction trajectory revealed by a joint analysis of protein data bank

Structural motions along a reaction pathway hold the secret about how a biological macromolecule functions. If each static structure were considered as a snapshot of the protein molecule in action, a large collection of structures would constitute a multidimensional conformational space of an enormous size. Here I present a joint analysis of hundreds of known structures of human hemoglobin in the Protein Data Bank. By applying singular value decomposition to distance matrices of these structures, I demonstrate that this large collection of structural snapshots, derived under a wide range of experimental conditions, arrange orderly along a reaction pathway. The structural motions along this extensive trajectory, including several helical transformations, arrive at a reverse engineered mechanism of the cooperative machinery (Ren, companion article), and shed light on pathological properties of the abnormal homotetrameric hemoglobins from α-thalassemia. This method of meta-analysis provides a general approach to structural dynamics based on static protein structures in this post genomics era.

Improved crystallographic structures using extensive combinatorial refinement

Identifying errors and alternate conformers and modeling multiple main-chain conformers in poorly ordered regions are overarching problems in crystallographic structure determination that have limited automation efforts and structure quality. Here, we show that implementation of a full factorial designed set of standard refinement approaches, termed ExCoR (Extensive Combinatorial Refinement), significantly improves structural models compared to the traditional linear tree approach, in which individual algorithms are tested linearly and are only incorporated if the model improves. ExCoR markedly improved maps and models and reveals building errors and alternate conformations that were masked by traditional refinement approaches. Surprisingly, an individual algorithm that renders a model worse in isolation could still be necessary to produce the best overall model, suggesting that model distortion allows escape from local minima of optimization target function, here shown to be a hallmark limitation of the traditional approach. ExCoR thus provides a simple approach to improving structure determination.

Further characterization of functional domains of PerA, role of amino and carboxy terminal domains in DNA binding

PerA is a key regulator of virulence genes in enteropathogenic E. coli. PerA is a member of the AraC/XylS family of transcriptional regulators that directly regulates the expression of the bfp and per operons in response to different environmental cues. Here, we characterized mutants in both the amino (NTD) and carboxy (CTD) terminal domains of PerA that affect its ability to activate the expression of the bfp and per promoters. Mutants at residues predicted to be important for DNA binding within the CTD had a significant defect in their ability to bind to the regulatory regions of the bfp and per operons and, consequently, in transcriptional activation. Notably, mutants in specific NTD residues were also impaired to bind to DNA suggesting that this domain is involved in structuring the protein for correct DNA recognition. Mutations in residues E116 and D168, located in the vicinity of the putative linker region, significantly affected the activation of the perA promoter, without affecting PerA binding to the per or bfp regulatory sequences. Overall these results provide additional evidence of the importance of the N-terminal domain in PerA activity and suggest that the activation of these promoters involves differential interactions with the transcriptional machinery. This study further contributes to the characterization of the functional domains of PerA by identifying critical residues involved in DNA binding, differential promoter activation and, potentially, in the possible response to environmental cues.

Structure of the proton-gated urea channel from the gastric pathogen Helicobacter pylori

Half the world's population is chronically infected with Helicobacter pylori¹, causing gastritis, ulcers and increased incidence of gastric adenocarcinoma². Its proton-gated inner-membrane urea channel, HpUreI, is essential for survival in the acidic environment of the stomach³. The channel is closed at neutral pH and opens at acidic pH to allow rapid urea access to cytoplasmic urease⁴. Urease produces NH₃ and CO₂ that neutralize entering protons and thus buffer the periplasm to pH ∼6.1 even in gastric juice at pH <2.0. Here we report the structure of HpUreI, revealing six protomers assembled in a hexameric ring surrounding a central bilayer plug of ordered lipids. Each protomer encloses a channel formed by a twisted bundle of six transmembrane helices. The bundle defines a novel fold comprising a two-helix hairpin motif repeated three times around the central axis of the channel, without the inverted repeat of mammalian urea transporters. Both the channel and the protomer interface contain residues conserved in the AmiS/UreI superfamily, suggesting preservation of channel architecture and oligomeric state in this superfamily. Predominantly aromatic or aliphatic side chains line the entire channel and define two consecutive constriction sites in the middle of the channel. Mutation of Trp153 in the cytoplasmic constriction site to Ala or Phe reduces the selectivity for urea compared to thiourea, suggesting that solute interaction with Trp153 contributes specificity. The novel hexameric channel structure described here provides a new paradigm for permeation of urea and other small amide solutes in prokaryotes and archaea.

Role of salt bridge dynamics in inter domain recognition of human IMPDH isoforms: an insight to inhibitor topology for isoform-II

Inosine monophosphate dehydrogenase (IMPDH) enzyme involves in the biosynthesis pathway of guanosine nucleotide. Type II isoform of the enzyme is selectively upregulated in neoplastic fast replicating lymphocytes and CML cancer cells. The hIMPDH-II is an excellent target for antileukemic agent. The detailed investigation during MD-Simulation (15 ns) of three different unliganded structures (1B3O, 1JCN and 1JR1) have clearly explored the salt bridge mediated stabilization of inter or intra domain (catalytic domains I(N), I(C) with res. Id. 28-111 and 233-504, whereas two CBS domains C₁, C₂ are 112-171 and 172-232) in IMPDH enzyme which are mostly inaccessible in their X-rays structures. The salt bridge interaction in I(N)---C₁ inter-domain of hIMPDH-I, I(N)---C₂ of IMPDH-II and C₁---I(C) of nhIMPDH-II are discriminative features among the isoforms. The I(N)---C₂ recognition in hIMPDH-II (1B3O) is missing in type-I isoform (1JCN). The salt bridge interaction D232---K238 at the surface of protein and the involvement of three conserved water molecules or the hydrophilic centers (WA²³²(OD1), WB ²³²(OD2) and W²³⁸(NZ)) to those acidic and basic residues seem to be unique in hIMPDH-II. The hydrophilic susceptibility, geometrical and electronic consequences of this salt bridge interaction could be useful to design the topology of specific inhibitor for hIMPDH-II which may not be effective for hIMPDH-I. Possibly, the aliphatic ligand containing carboxyl, amide or hydrophilic groups with flexible structure may be implicated for hIMPDH-II inhibitor design using the conserved water mimic drug design protocol.

Overview of the CCP4 suite and current developments

The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package.

FILTREST3D: discrimination of structural models using restraints from experimental data

SUMMARY

Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directed mutagenesis, deuterium exchange coupled with mass spectrometry, etc.). We present a simple server for scoring and ranking of models according to their agreement with user-defined restraints.

AVAILABILITY

FILTREST3D is freely available for users as a web server and standalone software at: http://filtrest3d.genesilico.pl/

CONTACT

iamb@genesilico.pl

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Building and refining protein models within cryo-electron microscopy density maps based on homology modeling and multiscale structure refinement

Automatic modeling methods using cryoelectron microscopy (cryoEM) density maps as constraints are promising approaches to building atomic models of individual proteins or protein domains. However, their application to large macromolecular assemblies has not been possible largely due to computational limitations inherent to such unsupervised methods. Here we describe a new method, EM-IMO (electron microscopy-iterative modular optimization), for building, modifying and refining local structures of protein models using cryoEM maps as a constraint. As a supervised refinement method, EM-IMO allows users to specify parameters derived from inspections so as to guide, and as a consequence, significantly speed up the refinement. An EM-IMO-based refinement protocol is first benchmarked on a data set of 50 homology models using simulated density maps. A multiscale refinement strategy that combines EM-IMO-based and molecular dynamics-based refinement is then applied to build backbone models for the seven conformers of the five capsid proteins in our near-atomic-resolution cryoEM map of the grass carp reovirus virion, a member of the Aquareovirus genus of the Reoviridae family. The refined models allow us to reconstruct a backbone model of the entire grass carp reovirus capsid and provide valuable functional insights that are described in the accompanying publication [Cheng, L., Zhu, J., Hui, W. H., Zhang, X., Honig, B., Fang, Q. & Zhou, Z. H. (2010). Backbone model of an aquareovirus virion by cryo-electron microscopy and bioinformatics. J. Mol. Biol. (this issue). doi:10.1016/j.jmb.2009.12.027.]. Our study demonstrates that the integrated use of homology modeling and a multiscale refinement protocol that combines supervised and automated structure refinement offers a practical strategy for building atomic models based on medium- to high-resolution cryoEM density maps.

Model-building strategies for low-resolution X-ray crystallographic data

Interpretation of low-resolution X-ray crystallographic data can prove to be a difficult task. The challenges faced in electron-density interpretation, the strategies that have been employed to overcome them and developments to automate the process are reviewed.

The interpretation of low-resolution X-ray crystallographic data proves to be challenging even for the most experienced crystallographer. Ambiguity in the electron-density map makes main-chain tracing and side-chain assignment difficult. However, the number of structures solved at resolutions poorer than 3.5 Å is growing rapidly and the structures are often of high biological interest and importance. Here, the challenges faced in electron-density interpretation, the strategies that have been employed to overcome them and developments to automate the process are reviewed. The methods employed in model generation from electron microscopy, which share many of the same challenges in providing high-confidence models of macromolecular structures and assemblies, are also considered.

Structural basis for inhibition of homologous recombination by the RecX protein

The RecA/RAD51 nucleoprotein filament is central to the reaction of homologous recombination (HR). Filament activity must be tightly regulated in vivo as unrestrained HR can cause genomic instability. Our mechanistic understanding of HR is restricted by lack of structural information about the regulatory proteins that control filament activity. Here, we describe a structural and functional analysis of the HR inhibitor protein RecX and its mode of interaction with the RecA filament. RecX is a modular protein assembled of repeated three-helix motifs. The relative arrangement of the repeats generates an elongated and curved shape that is well suited for binding within the helical groove of the RecA filament. Structure-based mutagenesis confirms that conserved basic residues on the concave side of RecX are important for repression of RecA activity. Analysis of RecA filament dynamics in the presence of RecX shows that RecX actively promotes filament disassembly. Collectively, our data support a model in which RecX binding to the helical groove of the filament causes local dissociation of RecA protomers, leading to filament destabilisation and HR inhibition.

Flexible ligand docking to multiple receptor conformations: a practical alternative

State of the art docking algorithms predict an incorrect binding pose for about 50-70% of all ligands when only a single fixed receptor conformation is considered. In many more cases, lack of receptor flexibility results in meaningless ligand binding scores, even when the correct pose is obtained. Incorporating conformational rearrangements of the receptor binding pocket into predictions of both ligand binding pose and binding score is crucial for improving structure-based drug design and virtual ligand screening methodologies. However, direct modeling of protein binding site flexibility remains challenging because of the large conformational space that must be sampled, and difficulties remain in constructing a suitably accurate energy function. Here we show that using multiple fixed receptor conformations, either experimentally determined by crystallography or NMR, or computationally generated, is a practical shortcut that may improve docking calculations. In several cases, such an approach has led to experimentally validated predictions.

Comparative modelling by restraint-based conformational sampling

BACKGROUND

Although comparative modelling is routinely used to produce three-dimensional models of proteins, very few automated approaches are formulated in a way that allows inclusion of restraints derived from experimental data as well as those from the structures of homologues. Furthermore, proteins are usually described as a single conformer, rather than an ensemble that represents the heterogeneity and inaccuracy of experimentally determined protein structures. Here we address these issues by exploring the application of the restraint-based conformational space search engine, RAPPER, which has previously been developed for rebuilding experimentally defined protein structures and for fitting models to electron density derived from X-ray diffraction analyses.

RESULTS

A new application of RAPPER for comparative modelling uses positional restraints and knowledge-based sampling to generate models with accuracies comparable to other leading modelling tools. Knowledge-based predictions are based on geometrical features of the homologous templates and rules concerning main-chain and side-chain conformations. By directly changing the restraints derived from available templates we estimate the accuracy limits of the method in comparative modelling.

CONCLUSION

The application of RAPPER to comparative modelling provides an effective means of exploring the conformational space available to a target sequence. Enhanced methods for generating positional restraints can greatly improve structure prediction. Generation of an ensemble of solutions that are consistent with both target sequence and knowledge derived from the template structures provides a more appropriate representation of a structural prediction than a single model. By formulating homologous structural information as sets of restraints we can begin to consider how comparative models might be used to inform conformer generation from sparse experimental data.

Dealing with structural variability in molecular replacement and crystallographic refinement through normal-mode analysis

Normal-mode analysis (NMA) can be used to generate multiple structural variants of a given template model, thereby increasing the chance of finding the molecular-replacement solution. Here, it is shown that it is also possible to directly refine the amplitudes of the normal modes against experimental data (X-ray or cryo-EM), generalizing rigid-body refinement methods by adding just a few additional degrees of freedom that sample collective and large-amplitude movements. It is also argued that the situation where several (conformations of) models are present simultaneously in the crystal can be studied with adjustable occupancies using techniques derived from statistical thermodynamics and already used in molecular modelling.

Rappertk: a versatile engine for discrete restraint-based conformational sampling of macromolecules

Background

Macromolecular structures are modeled by conformational optimization within experimental and knowledge-based restraints. Discrete restraint-based sampling generates high-quality structures within these restraints and facilitates further refinement in a continuous all-atom energy landscape. This approach has been used successfully for protein loop modeling, comparative modeling and electron density fitting in X-ray crystallography.

Results

Here we present a software toolkit (Rappertk) which generalizes discrete restraint-based sampling for use in structural biology. Modular design and multi-layered architecture enables Rappertk to sample conformations of any macromolecule at many levels of detail and within a variety of experimental restraints. Performance against a C_α-tracing benchmark shows that the efficiency has not suffered despite the overhead required by this flexibility. We demonstrate the toolkit's capabilities by building high-quality β-sheets and by introducing restraint-driven sampling. RNA sampling is demonstrated by rebuilding a protein-RNA interface. Ability to construct arbitrary ligands is used in sampling protein-ligand interfaces within electron density. Finally, secondary structure and shape information derived from EM are combined to generate multiple conformations of a protein consistent with the observed density.

Conclusion

Through its modular design and ease of use, Rappertk enables exploration of a wide variety of interesting avenues in structural biology. This toolkit, with illustrative examples, is freely available to academic users from .