Proteins and nucleic acids participate in essentially every biochemical process in living organisms, and the elucidation of their structure and motions is essential for our understanding how these molecular machines perform their function. Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful versatile technique that provides critical information on the molecular structure and dynamics. Spin-relaxation data are used to determine the overall rotational diffusion and local motions of biological macromolecules, while residual dipolar couplings (RDCs) reveal local and long-range structural architecture of these molecules and their complexes. This information allows researchers to refine structures of proteins and nucleic acids and provides restraints for molecular docking. Several software packages have been developed by NMR researchers in order to tackle the complicated experimental data analysis and structure modeling. However, many of them are offline packages or command-line applications that require users to set up the run time environment and also to possess certain programming skills, which inevitably limits accessibility of this software to a broad scientific community. Here we present new science gateways designed for NMR/structural biology community that address these current limitations in NMR data analysis. Using the GenApp technology for scientific gateways (https://genapp.rocks), we successfully transformed ROTDIF and ALTENS, two offline packages for bio-NMR data analysis, into science gateways that provide advanced computational functionalities, cloud-based data management, and interactive 2D and 3D plotting and visualizations. Furthermore, these gateways are integrated with molecular structure visualization tools (Jmol) and with gateways/engines (SASSIE-web) capable of generating huge computer-simulated structural ensembles of proteins and nucleic acids. This enables researchers to seamlessly incorporate conformational ensembles into the analysis in order to adequately take into account structural heterogeneity and dynamic nature of biological macromolecules. ROTDIF-web offers a versatile set of integrated modules/tools for determining and predicting molecular rotational diffusion tensors and model-free characterization of bond dynamics in biomacromolecules and for docking of molecular complexes driven by the information extracted from NMR relaxation data. ALTENS allows characterization of the molecular alignment under anisotropic conditions, which enables researchers to obtain accurate local and long-range bond-vector restraints for refining 3-D structures of macromolecules and their complexes. We will describe our experience bringing our programs into GenApp and illustrate the use of these gateways for specific examples of protein systems of high biological significance. We expect these gateways to be useful to structural biologists and biophysicists as well as NMR community and to stimulate other researchers to share their scientific software in a similar way.
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Modeling protein–nucleic acid complexes with extremely large conformational changes using Flex‐LZerD
Proteins and nucleic acids are key components in many processes in living cells, and interactions between proteins and nucleic acids are often crucial pathway components. In many cases, large flexibility of proteins as they interact with nucleic acids is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D atomic structures of such protein–nucleic acid complexes. When such structures are not yet experimentally determined, protein docking can be used to computationally generate useful structure models. However, such docking has long had the limitation that the consideration of flexibility is usually limited to small movements or to small structures. We previously developed a method of flexible protein docking which could model ordered proteins which undergo large‐scale conformational changes, which we also showed was compatible with nucleic acids. Here, we elaborate on the ability of that pipeline, Flex‐LZerD, to model specifically interactions between proteins and nucleic acids, and demonstrate that Flex‐LZerD can model more interactions and types of conformational change than previously shown.
more » « less- Award ID(s):
- 2146026
- NSF-PAR ID:
- 10418664
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- PROTEOMICS
- Volume:
- 23
- Issue:
- 17
- ISSN:
- 1615-9853
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The parasitoid wasp Venturia canescens is an important biological control agent of stored products moth pests and serves as a model to study the function and evolution of domesticated endogenous viruses (DEVs). The DEVs discovered in V. canescens are known as virus-like particles (VcVLPs), which are produced using nudivirus-derived components and incorporate wasp-derived virulence proteins instead of packaged nucleic acids. Previous studies of virus-derived components in the V. canescens genome identified 53 nudivirus-like genes organized in six gene clusters and several viral pseudogenes, but how VcVLP genes are organized among wasp chromosomes following their integration in the ancestral wasp genome is largely unknown. Here, we present a chromosomal scale genome of V. canescens consisting of 11 chromosomes and 56 unplaced small scaffolds. The genome size is 290.8 Mbp with a N50 scaffold size of 24.99 Mbp. A high-quality gene set including 11,831 protein-coding genes were produced using RNA-Seq data as well as publicly available peptide sequences from related Hymenoptera. A manual annotation of genes of viral origin produced 61 intact and 19 pseudogenized nudivirus-derived genes. The genome assembly revealed that two previously identified clusters were joined into a single cluster and a total of 5 gene clusters comprising of 60 intact nudivirus-derived genes were located in three chromosomes. In contrast, pseudogenes are dispersed among 8 chromosomes with only 4 pseudogenes associated with nudivirus gene clusters. The architecture of genes encoding VcVLP components suggests it originates from a recent virus acquisition and there is a link between the processes of dispersal and pseudogenization. This high-quality genome assembly and annotation represents the first chromosome-scale assembly for parasitoid wasps associated with VLPs, and is publicly available in the National Center for Biotechnology Information Genome and RefSeq databases, providing a valuable resource for future studies of DEVs in parasitoid wasps.
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Abstract Motivation Binding-induced conformational changes challenge current computational docking algorithms by exponentially increasing the conformational space to be explored. To restrict this search to relevant space, some computational docking algorithms exploit the inherent flexibility of the protein monomers to simulate conformational selection from pre-generated ensembles. As the ensemble size expands with increased flexibility, these methods struggle with efficiency and high false positive rates.
Results Here, we develop and benchmark RosettaDock 4.0, which efficiently samples large conformational ensembles of flexible proteins and docks them using a novel, six-dimensional, coarse-grained score function. A strong discriminative ability allows an eight-fold higher enrichment of near-native candidate structures in the coarse-grained phase compared to RosettaDock 3.2. It adaptively samples 100 conformations each of the ligand and the receptor backbone while increasing computational time by only 20–80%. In local docking of a benchmark set of 88 proteins of varying degrees of flexibility, the expected success rate (defined as cases with ≥50% chance of achieving 3 near-native structures in the 5 top-ranked ones) for blind predictions after resampling is 77% for rigid complexes, 49% for moderately flexible complexes and 31% for highly flexible complexes. These success rates on flexible complexes are a substantial step forward from all existing methods. Additionally, for highly flexible proteins, we demonstrate that when a suitable conformer generation method exists, the method successfully docks the complex.
Availability and implementation As a part of the Rosetta software suite, RosettaDock 4.0 is available at https://www.rosettacommons.org to all non-commercial users for free and to commercial users for a fee.
Supplementary information Supplementary data are available at Bioinformatics online.
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Abstract Structure-based drug design targeting the SARS-CoV-2 virus has been greatly facilitated by available virus-related protein structures. However, there is an urgent need for effective, safe small-molecule drugs to control the spread of the virus and variants. While many efforts are devoted to searching for compounds that selectively target individual proteins, we investigated the potential interactions between eight proteins related to SARS-CoV-2 and more than 600 compounds from a traditional Chinese medicine which has proven effective at treating the viral infection. Our original ensemble docking and cooperative docking approaches, followed by a total of over 16-micorsecond molecular simulations, have identified at least 9 compounds that may generally bind to key SARS-CoV-2 proteins. Further, we found evidence that some of these compounds can simultaneously bind to the same target, potentially leading to cooperative inhibition to SARS-CoV-2 proteins like the Spike protein and the RNA-dependent RNA polymerase. These results not only present a useful computational methodology to systematically assess the anti-viral potential of small molecules, but also point out a new avenue to seek cooperative compounds toward cocktail therapeutics to target more SARS-CoV-2-related proteins.
