Protein structure validation by generalized linear model root-mean-square deviation prediction

Exploring the inhibitory potential of novel bioactive compounds from mangrove actinomycetes against nsp10 the major activator of SARS-CoV-2 replication

The current study reveals the inhibitory potential of novel bioactive compounds of mangrove actinomycetes against nsp10 of SARS-CoV-2. A total of fifty (50) novel bioactive (antibacterial, antitumor, antiviral, antioxidant, and anti-inflammatory) compounds of mangrove actinomycetes from different chemical classes such as alkaloids, dilactones, sesquiterpenes, macrolides, and benzene derivatives are used for interaction analysis against nsp10 of SARS-CoV-2. The six antiviral agents sespenine, xiamycin c, xiamycin d, xiamycin e, xiamycin methyl ester, and xiamycin A (obeyed RO5 rule) are selected based on higher binding energy, low inhibition constant values, and better-docked positions. The effective hydrogen and hydrophobic (alkyl, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π–sigma, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π–\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π T shaped and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π-alkyl) interaction analysis reveals the four antivirals sespenine, xiamycin C, xiamycin methyl ester, and xiamycin A are supposed to be the most auspicious inhibitors against nsp10 of SARS-CoV-2. Quantum chemistry methods such as frontier molecular orbitals and molecular electrostatic potential are used to explain the thermal stability and chemical reactivity of ligands. The toxicity profile shows that selected ligands are safe by absorption, distribution, metabolism, excretion, and toxicity profiling and also effective for inhibition of nsp10 protein of SARS-CoV-2. The molecular dynamic simulation investigation of apo and halo forms of nsp10 done by RMSD of C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha$$\end{document}α atoms of nsp10, all amino acid residues RMSF, count total number of hydrogen bonds and radius of gyration (R_g). MD simulations reveal the complexes are stable and increase the structural compactness of nsp10 in the binding pocket. The lead antiviral compounds sespenine, xiamycin C, xiamycin methyl ester, and xiamycin A are recommended as the most promising inhibitors against nsp10 of SARS-CoV-2 pathogenicity.

Simulation studies, 3D QSAR and molecular docking on a point mutation of protein kinase B with flavonoids targeting ovarian Cancer

BACKGROUND

Ovarian cancer is the world's dreaded disease and its prevalence is expanding globally. The study of integrated molecular networks is crucial for the basic mechanism of cancer cells and their progression. During the present investigation, we have examined different flavonoids that target protein kinases B (AKT1) protein which exerts their anticancer efficiency intriguing the role in cross-talk cell signalling, by metabolic processes through in-silico approaches.

METHOD

Molecular dynamics simulation (MDS) was performed to analyze and evaluate the stability of the complexes under physiological conditions and the results were congruent with molecular docking. This investigation revealed the effect of a point mutation (W80R), considered based on their frequency of occurrence, with AKT1 protein.

RESULTS

The ligand with high docking scores and favourable behaviour on dynamic simulations are proposed as potential W80R inhibitors. A virtual screening analysis was performed with 12,000 flavonoids satisfying Lipinski's rule of five according to which drug-likeness is predicted based on its pharmacological and biological properties to be active and taken orally. The pharmacokinetic ADME (adsorption, digestion, metabolism, and excretion) studies featured drug-likeness. Subsequently, a statistically significant 3D-QSAR model of high correlation coefficient (R2) with 0.822 and cross-validation coefficient (Q2) with 0.6132 at 4 component PLS (partial least square) were used to verify the accuracy of the models. Taxifolin holds good interactions with the binding domain of W80R, highest Glide score of - 9.63 kcal/mol with OH of GLU234 and H bond ASP274 and LEU156 amino acid residues and one pi-cation interaction and one hydrophobic bond with LYS276.

CONCLUSION

Natural compounds have always been a richest source of active compounds with a wide variety of structures, therefore, these compounds showed a special inspiration for medical chemists. The present study has aimed molecular docking and molecular dynamics simulation studies on taxifolin targeting W80R mutant protein of protein kinase B/serine- threonine kinase/AKT1 (EC:2.7.11.1) protein of ovarian cancer for designing therapeutic intervention. The expected result supported the molecular cause in a mutant form which resulted in a gain of ovarian cancer. Here we discussed validations computationally and yet experimental evaluation or in vivo studies are endorsed for further study. Several of these compounds should become the next marvels for early detection of ovarian cancer.

NMR Spectroscopy in the Conformational Analysis of Peptides: An Overview

BACKGROUND

NMR spectroscopy is one of the most powerful tools to study the structure and interaction properties of peptides and proteins from a dynamic perspective. Knowing the bioactive conformations of peptides is crucial in the drug discovery field to design more efficient analogue ligands and inhibitors of protein-protein interactions targeting therapeutically relevant systems.

OBJECTIVE

This review provides a toolkit to investigate peptide conformational properties by NMR.

METHODS

Articles cited herein, related to NMR studies of peptides and proteins were mainly searched through PubMed and the web. More recent and old books on NMR spectroscopy written by eminent scientists in the field were consulted as well.

RESULTS

The review is mainly focused on NMR tools to gain the 3D structure of small unlabeled peptides. It is more application-oriented as it is beyond its goal to deliver a profound theoretical background. However, the basic principles of 2D homonuclear and heteronuclear experiments are briefly described. Protocols to obtain isotopically labeled peptides and principal triple resonance experiments needed to study them, are discussed as well.

CONCLUSION

NMR is a leading technique in the study of conformational preferences of small flexible peptides whose structure can be often only described by an ensemble of conformations. Although NMR studies of peptides can be easily and fast performed by canonical protocols established a few decades ago, more recently we have assisted to tremendous improvements of NMR spectroscopy to investigate instead large systems and overcome its molecular weight limit.

Computational Design and Preliminary Serological Analysis of a Novel Multi-Epitope Vaccine Candidate against Onchocerciasis and Related Filarial Diseases

: Onchocerciasis is a skin and eye disease that exerts a heavy socio-economic burden, particularly in sub-Saharan Africa, a region which harbours greater than 96% of either infected or at-risk populations. The elimination plan for the disease is currently challenged by many factors including amongst others; the potential emergence of resistance to the main chemotherapeutic agent, ivermectin (IVM). Novel tools, including preventative and therapeutic vaccines, could provide additional impetus to the disease elimination tool portfolio. Several observations in both humans and animals have provided evidence for the development of both natural and artificial acquired immunity. In this study, immuno-informatics tools were applied to design a filarial-conserved multi-epitope subunit vaccine candidate, (designated Ov-DKR-2) consisting of B-and T-lymphocyte epitopes of eight immunogenic antigens previously assessed in pre-clinical studies. The high-percentage conservation of the selected proteins and epitopes predicted in related nematode parasitic species hints that the generated chimera may be instrumental for cross-protection. Bioinformatics analyses were employed for the prediction, refinement, and validation of the 3D structure of the Ov-DKR-2 chimera. In-silico immune simulation projected significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ, and IL-2 responses. Preliminary immunological analyses revealed that the multi-epitope vaccine candidate reacted with antibodies in sera from both onchocerciasis-infected individuals, endemic normals as well as loiasis-infected persons but not with the control sera from European individuals. These results support the premise for further characterisation of the engineered protein as a vaccine candidate for onchocerciasis.

Molecular modeling and in vitro study on pyrocatechol as potential pharmacophore of CD151 inhibitor

CD151 has been recognized as a prognostic marker, the therapeutic target of breast cancers, but less explored for small molecule inhibitors due to lack of a validated model. The 3-D structure of CD151 large extracellular loop (LEL) was modeled using the LOMETS server and validated by the Ramachandran plot. The validated structure was employed for molecular docking and structure-based pharmacophore analysis. Druglikeness was evaluated by the ADMET description protocol. Antiproliferative activity was evaluated by MTT, BrdU incorporation, flow cytometry, and cell death ELISA^PLUS assay. This study predicted the best model for CD151-LEL with 94.1% residues in favored regions and Z score -2.79 kcal/mol using the threading method. The web-based receptor cavity method identified one functional target site, which was suitable for the binding of aromatic and heterocyclic compounds. Molecular docking study identified pyrocatechol (PCL) and 5-fluorouracil (FU) as potential leads of CD151-LEL. The pharmacophore model identified interaction points of modeled CD151-LEL with PCL and FU. Also, the analysis of ADMET properties revealed the drug-likeness of PCL and FU. The viability of MDA-MB 231 cells was significantly reduced with PCL and FU but less affected MCF-12A, normal healthy breast epithelial cell line. With 50% toxic concentration, both PCL and FU significantly inhibited 82.46 and 87.12% proliferation, respectively, of MDA-MB 231 cells by altering morphology and inducing G1 cell cycle arrest and apoptosis. In addition, PCL and FU inhibited the CD151 expression by 4.5-and 4.8-folds, respectively. This study suggests the further assessment of pyrocatechol as a potential lead of CD151 in breast cancer at the molecular level.

Molecular modelling and dynamics of CA2 missense mutations causative to carbonic anhydrase 2 deficiency syndrome

Carbonic anhydrase 2 (CA2) enzyme deficiency caused by CA2 gene mutations is an inherited disorder characterized by symptoms like osteopetrosis, renal tubular acidosis, and cerebral calcification. This study has collected the CA2 deficiency causal missense mutations and assessed their pathogenicity using diverse computational programs. The 3D protein models for all missense mutations were built, and analyzed for structural divergence, protein stability, and molecular dynamics properties. We found M-CAP as the most sensitive prediction method to measure the deleterious potential of CA2 missense mutations. Free energy dynamics of tertiary structure models of CA2 mutants with DUET, mCSM, and SDM based consensus methods predicted only 50% of the variants as destabilizing. Superimposition of native and mutant CA2 models revealed the minor structural fluctuations at the amino acid residue level but not at the whole protein structure level. Near native molecular dynamic simulation analysis indicated that CA2 causative missense variants result in residue level fluctuation pattern in the protein structure. This study expands the understanding of genotype-protein phenotype correlations underlying CA2 variant pathogenicity and presents a potential avenue for modifying the CA2 deficiency by targeting biophysical structural features of CA2 protein. Communicated by Ramaswamy H. Sarma.

Profiling of rotavirus 3'UTR-binding proteins reveals the ATP synthase subunit ATP5B as a host factor that supports late-stage virus replication

Genome replication and virion assembly of segmented RNA viruses are highly coordinated events, tightly regulated by sequence and structural elements in the UTRs of viral RNA. This process is poorly defined and likely requires the participation of host proteins in concert with viral proteins. In this study, we employed a proteomics-based approach, named RNA-protein interaction detection (RaPID), to comprehensively screen for host proteins that bind to a conserved motif within the rotavirus (RV) 3' terminus. Using this assay, we identified ATP5B, a core subunit of the mitochondrial ATP synthase, as having high affinity to the RV 3'UTR consensus sequences. During RV infection, ATP5B bound to the RV 3'UTR and co-localized with viral RNA and viroplasm. Functionally, siRNA-mediated genetic depletion of ATP5B or other ATP synthase subunits such as ATP5A1 and ATP5O reduced the production of infectious viral progeny without significant alteration of intracellular viral RNA levels or RNA translation. Chemical inhibition of ATP synthase diminished RV yield in both conventional cell culture and in human intestinal enteroids, indicating that ATP5B positively regulates late-stage RV maturation in primary intestinal epithelial cells. Collectively, our results shed light on the role of host proteins in RV genome assembly and particle formation and identify ATP5B as a novel pro-RV RNA-binding protein, contributing to our understanding of how host ATP synthases may galvanize virus growth and pathogenesis.

Protein phenotype diagnosis of autosomal dominant calmodulin mutations causing irregular heart rhythms

The life-threatening group of irregular cardiac rhythmic disorders also known as Cardiac Arrhythmias (CA) are caused by mutations in highly conserved Calmodulin (CALM/CaM) genes. Herein, we present a multidimensional approach to diagnose changes in phenotypic, stability, and Ca²⁺ ion binding properties of CA-causing mutations. Mutation pathogenicity was determined by diverse computational machine learning approaches. We further modeled the mutations in 3D protein structure and analyzed residue level phenotype plasticity. We have also examined the influence of torsion angles, number of H-bonds, and free energy dynamics on the stability, near-native simulation dynamic potential of residue fluctuations in protein structures, Ca²⁺ ion binding potentials, of CaM mutants. Our study recomends to use M-CAP method for measuring the pathogenicity of CA causing CaM variants. Interestingly, most CA-causing variants we analyzed, exists in either third (V/H-96, S/I-98, V-103) or fourth (G/V-130, V/E/H-132, H-134, P-136, G-141, and L-142) EF-hands located in carboxyl domains of the CaM molecule. We observed that the minor structural fluctuations caused by these variants are likely tolerable owing to the highly flexible nature of calmodulin's globular domains. However, our molecular docking results supports that these variants disturb the affinity of CaM toward Ca²⁺ ions and corroborate previous findings from functional studies. Taken together, these computational findings can explain the molecular reasons for subtle changes in structure, flexibility, and stability aspects of mutant CaM molecule. Our comprehensive molecular scanning approach demonstrates the utility of computational methods in quick preliminary screening of CA- CaM mutations before undertaking time consuming and complicated functional laboratory assays.

Robust and transferable quantification of NMR spectral quality using IROC analysis

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

Genome-wide identification and expression analysis of glutathione S-transferase gene family in tomato: Gaining an insight to their physiological and stress-specific roles

Glutathione S-transferase (GST) refers to one of the major detoxifying enzymes that plays an important role in different abiotic and biotic stress modulation pathways of plant. The present study aimed to a comprehensive genome-wide functional characterization of GST genes and proteins in tomato (Solanum lycopersicum L.). The whole genome sequence analysis revealed the presence of 90 GST genes in tomato, the largest GST gene family reported till date. Eight segmental duplicated gene pairs might contribute significantly to the expansion of SlGST gene family. Based on phylogenetic analysis of tomato, rice, and Arabidopsis GST proteins, GST family members could be further divided into ten classes. Members of each orthologous class showed high conservancy among themselves. Tau and lambda are the major classes of tomato; while tau and phi are the major classes for rice and Arabidopsis. Chromosomal localization revealed highly uneven distribution of SlGST genes in 13 different chromosomes, where chromosome 9 possessed the highest number of genes. Based on publicly available microarray data, expression analysis of 30 available SlGST genes exhibited a differential pattern in all the analyzed tissues and developmental stages. Moreover, most of the members showed highly induced expression in response to multiple biotic and abiotic stress inducers that could be harmonized with the increase in total GST enzyme activity under several stress conditions. Activity of tomato GST could be enhanced further by using some positive modulators (safeners) that have been predicted through molecular docking of SlGSTU5 and ligands. Moreover, tomato GST proteins are predicted to interact with a lot of other glutathione synthesizing and utilizing enzymes such as glutathione peroxidase, glutathione reductase, glutathione synthetase and γ-glutamyltransferase. This comprehensive genome-wide analysis and expression profiling would provide a rational platform and possibility to explore the versatile role of GST genes in crop engineering.

De novo design of a hyperstable non-natural protein-ligand complex with sub-Å accuracy

Protein catalysis requires the atomic-level orchestration of side chains, substrates and cofactors, and yet the ability to design a small-molecule-binding protein entirely from first principles with a precisely predetermined structure has not been demonstrated. Here we report the design of a novel protein, PS1, that binds a highly electron-deficient non-natural porphyrin at temperatures up to 100 °C. The high-resolution structure of holo-PS1 is in sub-Å agreement with the design. The structure of apo-PS1 retains the remote core packing of the holoprotein, with a flexible binding region that is predisposed to ligand binding with the desired geometry. Our results illustrate the unification of core packing and binding-site definition as a central principle of ligand-binding protein design.

Insights into unbound-bound states of GPR142 receptor in a membrane-aqueous system using molecular dynamics simulations

G protein coupled receptors (GPCRs) are source machinery in signal transduction pathways and being one of the major therapeutic targets play a significant in drug discovery. GPR142, an orphan GPCR, has been implicated in the regulation of insulin, thereby having a crucial role in Type II diabetes management. Deciphering of the structures of orphan, GPCRs (O-GPCRs) offer better prospects for advancements in research in ion translocation and transduction of extracellular signals. As the crystallographic structure of GPR142 is not available in PDB, therefore, threading and ab initio-based approaches were used for 3D modeling of GPR142. Molecular dynamic simulations (900 ns) were performed on the 3D model of GPR142 and complexes of GPR142 with top five hits, obtained through virtual screening, embedded in lipid bilayer with aqueous system using OPLS force field. Compound 1, 3, and 4 may act as scaffolds for designing potential lead agonists for GPR142. The finding of GPR142 MD simulation study provides more comprehensive representation of the functional properties. The concern for Type II diabetes is increasing worldwide and successful treatment of this disease demands novel drugs with better efficacy.

In Silico Identification of Mimicking Molecules as Defense Inducers Triggering Jasmonic Acid Mediated Immunity against Alternaria Blight Disease in Brassica Species

Alternaria brassicae and Alternaria brassicicola are two major phytopathogenic fungi which cause Alternaria blight, a recalcitrant disease on Brassica crops throughout the world, which is highly destructive and responsible for significant yield losses. Since no resistant source is available against Alternaria blight, therefore, efforts have been made in the present study to identify defense inducer molecules which can induce jasmonic acid (JA) mediated defense against the disease. It is believed that JA triggered defense response will prevent necrotrophic mode of colonization of Alternaria brassicae fungus. The JA receptor, COI1 is one of the potential targets for triggering JA mediated immunity through interaction with JA signal. In the present study, few mimicking compounds more efficient than naturally occurring JA in terms of interaction with COI1 were identified through virtual screening and molecular dynamics simulation studies. A high quality structural model of COI1 was developed using the protein sequence of Brassica rapa. This was followed by virtual screening of 767 analogs of JA from ZINC database for interaction with COI1. Two analogs viz. ZINC27640214 and ZINC43772052 showed more binding affinity with COI1 as compared to naturally occurring JA. Molecular dynamics simulation of COI1 and COI1-JA complex, as well as best screened interacting structural analogs of JA with COI1 was done for 50 ns to validate the stability of system. It was found that ZINC27640214 possesses efficient, stable, and good cell permeability properties. Based on the obtained results and its physicochemical properties, it is capable of mimicking JA signaling and may be used as defense inducers for triggering JA mediated resistance against Alternaria blight, only after further validation through field trials.

Genome-wide identification and expression analysis of glutathione S-transferase gene family in tomato: Gaining an insight to their physiological and stress-specific roles

Glutathione S-transferase (GST) refers to one of the major detoxifying enzymes that plays an important role in different abiotic and biotic stress modulation pathways of plant. The present study aimed to a comprehensive genome-wide functional characterization of GST genes and proteins in tomato (Solanum lycopersicum L.). The whole genome sequence analysis revealed the presence of 90 GST genes in tomato, the largest GST gene family reported till date. Eight segmental duplicated gene pairs might contribute significantly to the expansion of SlGST gene family. Based on phylogenetic analysis of tomato, rice, and Arabidopsis GST proteins, GST family members could be further divided into ten classes. Members of each orthologous class showed high conservancy among themselves. Tau and lambda are the major classes of tomato; while tau and phi are the major classes for rice and Arabidopsis. Chromosomal localization revealed highly uneven distribution of SlGST genes in 13 different chromosomes, where chromosome 9 possessed the highest number of genes. Based on publicly available microarray data, expression analysis of 30 available SlGST genes exhibited a differential pattern in all the analyzed tissues and developmental stages. Moreover, most of the members showed highly induced expression in response to multiple biotic and abiotic stress inducers that could be harmonized with the increase in total GST enzyme activity under several stress conditions. Activity of tomato GST could be enhanced further by using some positive modulators (safeners) that have been predicted through molecular docking of SlGSTU5 and ligands. Moreover, tomato GST proteins are predicted to interact with a lot of other glutathione synthesizing and utilizing enzymes such as glutathione peroxidase, glutathione reductase, glutathione synthetase and γ-glutamyltransferase. This comprehensive genome-wide analysis and expression profiling would provide a rational platform and possibility to explore the versatile role of GST genes in crop engineering.

Modeling of babesipain-1 and identification of natural and synthetic leads for bovine babesiosis drug development

Babesiosis is a tick-borne, zoonotic disease caused by species of the intraerythrocytic protozoan Babesia. It is distributed all around the world and affects various domestic and wild animals, mainly cattle. Recently, the cysteine protease enzyme, babesipain-1 from Babesia bigemina has been identified as a potential target for designing new anti-babesiosis drugs. In the present study, a three-dimensional structural model of babesipain-1 was developed. An active site with three pockets (S1, S2, and S3), which is congruent with its homolog, falcipain-3, was also identified. Moreover, the conservation of active site residues was consistent with the cysteine protease family. In order to identify potential inhibitors, a virtual screening workflow was employed with a chemical library containing natural and synthetic compounds. Potential inhibitors interacting with all the three subsites were identified. Further, molecular dynamic simulations were carried out to assess the interactions and stability of the inhibitors. The informatics approach, and the findings presented in this study will assist researchers in further development of potential anti-babesiosis molecules.

DockTope: a Web-based tool for automated pMHC-I modelling

The immune system is constantly challenged, being required to protect the organism against a wide variety of infectious pathogens and, at the same time, to avoid autoimmune disorders. One of the most important molecules involved in these events is the Major Histocompatibility Complex class I (MHC-I), responsible for binding and presenting small peptides from the intracellular environment to CD8⁺ T cells. The study of peptide:MHC-I (pMHC-I) molecules at a structural level is crucial to understand the molecular mechanisms underlying immunologic responses. Unfortunately, there are few pMHC-I structures in the Protein Data Bank (PDB) (especially considering the total number of complexes that could be formed combining different peptides), and pMHC-I modelling tools are scarce. Here, we present DockTope, a free and reliable web-based tool for pMHC-I modelling, based on crystal structures from the PDB. DockTope is fully automated and allows any researcher to construct a pMHC-I complex in an efficient way. We have reproduced a dataset of 135 non-redundant pMHC-I structures from the PDB (Cα RMSD below 1 Å). Modelling of pMHC-I complexes is remarkably important, contributing to the knowledge of important events such as cross-reactivity, autoimmunity, cancer therapy, transplantation and rational vaccine design.

The second round of Critical Assessment of Automated Structure Determination of Proteins by NMR: CASD-NMR-2013

The second round of the community-wide initiative Critical Assessment of automated Structure Determination of Proteins by NMR (CASD-NMR-2013) comprised ten blind target datasets, consisting of unprocessed spectral data, assigned chemical shift lists and unassigned NOESY peak and RDC lists, that were made available in both curated (i.e. manually refined) or un-curated (i.e. automatically generated) form. Ten structure calculation programs, using fully automated protocols only, generated a total of 164 three-dimensional structures (entries) for the ten targets, sometimes using both curated and un-curated lists to generate multiple entries for a single target. The accuracy of the entries could be established by comparing them to the corresponding manually solved structure of each target, which was not available at the time the data were provided. Across the entire data set, 71 % of all entries submitted achieved an accuracy relative to the reference NMR structure better than 1.5 Å. Methods based on NOESY peak lists achieved even better results with up to 100% of the entries within the 1.5 Å threshold for some programs. However, some methods did not converge for some targets using un-curated NOESY peak lists. Over 90% of the entries achieved an accuracy better than the more relaxed threshold of 2.5 Å that was used in the previous CASD-NMR-2010 round. Comparisons between entries generated with un-curated versus curated peaks show only marginal improvements for the latter in those cases where both calculations converged.

Solution NMR Structure Determination of Polytopic α-Helical Membrane Proteins: A Guide to Spin Label Paramagnetic Relaxation Enhancement Restraints

Solution nuclear magnetic resonance structures of polytopic α-helical membrane proteins require additional restraints beyond the traditional Nuclear Overhauser Effect (NOE) restraints. Several methods have been developed and this review focuses on paramagnetic relaxation enhancement (PRE). Important aspects of spin labeling, PRE measurements, structure calculations, and structural quality are discussed.

Structural determinants of the interaction between the TpsA and TpsB proteins in the Haemophilus influenzae HMW1 two-partner secretion system

The two-partner secretion (TPS) pathway in Gram-negative bacteria consists of a TpsA exoprotein and a cognate TpsB outer membrane pore-forming translocator protein. Previous work has demonstrated that the TpsA protein contains an N-terminal TPS domain that plays an important role in targeting the TpsB protein and is required for secretion. The nontypeable Haemophilus influenzae HMW1 and HMW2 adhesins are homologous proteins that are prototype TpsA proteins and are secreted by the HMW1B and HMW2B TpsB proteins. In the present study, we sought to define the structural determinants of HMW1 interaction with HMW1B during the transport process and while anchored to the bacterial surface. Modeling of HMW1B revealed an N-terminal periplasmic region that contains two polypeptide transport-associated (POTRA) domains and a C-terminal membrane-localized region that forms a pore. Biochemical studies demonstrated that HMW1 engages HMW1B via interaction between the HMW1 TPS domain and the HMW1B periplasmic region, specifically, the predicted POTRA1 and POTRA2 domains. Subsequently, HMW1 is shuttled to the HMW1B pore, facilitated by the N-terminal region, the middle region, and the NPNG motif in the HMW1 TPS domain. Additional analysis revealed that the interaction between HMW1 and HMW1B is highly specific and is dependent upon the POTRA domains and the pore-forming domain of HMW1B. Further studies established that tethering of HMW1 to the surface-exposed region of HMW1B is dependent upon the external loops of HMW1B formed by residues 267 to 283 and residues 324 to 330. These observations may have broad relevance to proteins secreted by the TPS pathway.

IMPORTANCE

Secretion of HMW1 involves a recognition event between the extended form of the HMW1 propiece and the HMW1B POTRA domains. Our results identify specific interactions between the HMW1 propiece and the periplasmic HMW1B POTRA domains. The results also suggest that the process of HMW1 translocation involves at least two discrete steps, including initial interaction between the HMW1 propiece and the HMW1B POTRA domains and then a separate translocation event. We have also discovered that the HMW1B pore itself appears to influence the translocation process. These observations extend our knowledge of the two-partner secretion system and may be broadly relevant to other proteins secreted by the TPS pathway.

Increased reliability of nuclear magnetic resonance protein structures by consensus structure bundles

Nuclear magnetic resonance (NMR) structures are represented by bundles of conformers calculated from different randomized initial structures using identical experimental input data. The spread among these conformers indicates the precision of the atomic coordinates. However, there is as yet no reliable measure of structural accuracy, i.e., how close NMR conformers are to the "true" structure. Instead, the precision of structure bundles is widely (mis)interpreted as a measure of structural quality. Attempts to increase precision often overestimate accuracy by tight bundles of high precision but much lower accuracy. To overcome this problem, we introduce a protocol for NMR structure determination with the software package CYANA, which produces, like the traditional method, bundles of conformers in agreement with a common set of conformational restraints but with a realistic precision that is, throughout a variety of proteins and NMR data sets, a much better estimate of structural accuracy than the precision of conventional structure bundles.

NMR structure validation in relation to dynamics and structure determination

NMR spectroscopy is a key technique for understanding the behaviour of proteins, especially highly dynamic proteins that adopt multiple conformations in solution. Overall, protein structures determined from NMR spectroscopy data constitute just over 10% of the Protein Data Bank archive. This review covers the validation of these NMR protein structures, but rather than describing currently available methodology, it focuses on concepts that are important for understanding where and how validation is most relevant. First, the inherent characteristics of the protein under study have an influence on quality and quantity of the distinct types of data that can be acquired from NMR experiments. Second, these NMR data are necessarily transformed into a model for use in a structure calculation protocol, and the protein structures that result from this reflect the types of NMR data used as well as the protein characteristics. The validation of NMR protein structures should therefore take account, wherever possible, of the inherent behavioural characteristics of the protein, the types of available NMR data, and the calculation protocol. These concepts are discussed in the context of 'knowledge based' and 'model versus data' validation, with suggestions for questions to ask and different validation categories to consider. The principal aim of this review is to stimulate discussion and to help the reader understand the relationships between the above elements in order to make informed decisions on which validation approaches are the most relevant in particular cases.

An overview of tools for the validation of protein NMR structures

Biomolecular structures at atomic resolution present a valuable resource for the understanding of biology. NMR spectroscopy accounts for 11% of all structures in the PDB repository. In response to serious problems with the accuracy of some of the NMR-derived structures and in order to facilitate proper analysis of the experimental models, a number of program suites are available. We discuss nine of these tools in this review: PROCHECK-NMR, PSVS, GLM-RMSD, CING, Molprobity, Vivaldi, ResProx, NMR constraints analyzer and QMEAN. We evaluate these programs for their ability to assess the structural quality, restraints and their violations, chemical shifts, peaks and the handling of multi-model NMR ensembles. We document both the input required by the programs and output they generate. To discuss their relative merits we have applied the tools to two representative examples from the PDB: a small, globular monomeric protein (Staphylococcal nuclease from S. aureus, PDB entry 2kq3) and a small, symmetric homodimeric protein (a region of human myosin-X, PDB entry 2lw9).

Recommendations of the wwPDB NMR Validation Task Force

As methods for analysis of biomolecular structure and dynamics using nuclear magnetic resonance spectroscopy (NMR) continue to advance, the resulting 3D structures, chemical shifts, and other NMR data are broadly impacting biology, chemistry, and medicine. Structure model assessment is a critical area of NMR methods development, and is an essential component of the process of making these structures accessible and useful to the wider scientific community. For these reasons, the Worldwide Protein Data Bank (wwPDB) has convened an NMR Validation Task Force (NMR-VTF) to work with wwPDB partners in developing metrics and policies for biomolecular NMR data harvesting, structure representation, and structure quality assessment. This paper summarizes the recommendations of the NMR-VTF, and lays the groundwork for future work in developing standards and metrics for biomolecular NMR structure quality assessment.

Implementation of the Hungarian algorithm to account for ligand symmetry and similarity in structure-based design

False negative docking outcomes for highly symmetric molecules are a barrier to the accurate evaluation of docking programs, scoring functions, and protocols. This work describes an implementation of a symmetry-corrected root-mean-square deviation (RMSD) method into the program DOCK based on the Hungarian algorithm for solving the minimum assignment problem, which dynamically assigns atom correspondence in molecules with symmetry. The algorithm adds only a trivial amount of computation time to the RMSD calculations and is shown to increase the reported overall docking success rate by approximately 5% when tested over 1043 receptor–ligand systems. For some families of protein systems the results are even more dramatic, with success rate increases up to 16.7%. Several additional applications of the method are also presented including as a pairwise similarity metric to compare molecules during de novo design, as a scoring function to rank-order virtual screening results, and for the analysis of trajectories from molecular dynamics simulation. The new method, including source code, is available to registered users of DOCK6 (http://dock.compbio.ucsf.edu).

Protein NMR structures refined with Rosetta have higher accuracy relative to corresponding X-ray crystal structures

We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5-22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10-25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function.

Protein structure quality assessment based on the distance profiles of consecutive backbone Cα atoms

Predicting the three dimensional native state structure of a protein from its primary sequence is an unsolved grand challenge in molecular biology. Two main computational approaches have evolved to obtain the structure from the protein sequence - ab initio/de novo methods and template-based modeling - both of which typically generate multiple possible native state structures. Model quality assessment programs (MQAP) validate these predicted structures in order to identify the correct native state structure. Here, we propose a MQAP for assessing the quality of protein structures based on the distances of consecutive Cα atoms. We hypothesize that the root-mean-square deviation of the distance of consecutive Cα (RDCC) atoms from the ideal value of 3.8 Å, derived from a statistical analysis of high quality protein structures (top100H database), is minimized in native structures. Based on tests with the top100H set, we propose a RDCC cutoff value of 0.012 Å, above which a structure can be filtered out as a non-native structure. We applied the RDCC discriminator on decoy sets from the Decoys 'R' Us database to show that the native structures in all decoy sets tested have RDCC below the 0.012 Å cutoff. While most decoy sets were either indistinguishable using this discriminator or had very few violations, all the decoy structures in the fisa decoy set were discriminated by applying the RDCC criterion. This highlights the physical non-viability of the fisa decoy set, and possible issues in benchmarking other methods using this set. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.

Quality assessment of protein NMR structures

Biomolecular NMR structures are now routinely used in biology, chemistry, and bioinformatics. Methods and metrics for assessing the accuracy and precision of protein NMR structures are beginning to be standardized across the biological NMR community. These include both knowledge-based assessment metrics, parameterized from the database of protein structures, and model versus data assessment metrics. On line servers are available that provide comprehensive protein structure quality assessment reports, and efforts are in progress by the world-wide Protein Data Bank (wwPDB) to develop a biomolecular NMR structure quality assessment pipeline as part of the structure deposition process. These quality assessment metrics and standards will aid NMR spectroscopists in determining more accurate structures, and increase the value and utility of these structures for the broad scientific community.

Estimating structure quality trends in the Protein Data Bank by equivalent resolution

The quality of protein structures obtained by different experimental and ab-initio calculation methods varies considerably. The methods have been evolving over time by improving both experimental designs and computational techniques, and since the primary aim of these developments is the procurement of reliable and high-quality data, better techniques resulted on average in an evolution toward higher quality structures in the Protein Data Bank (PDB). Each method leaves a specific quantitative and qualitative "trace" in the PDB entry. Certain information relevant to one method (e.g. dynamics for NMR) may be lacking for another method. Furthermore, some standard measures of quality for one method cannot be calculated for other experimental methods, e.g. crystal resolution or NMR bundle RMSD. Consequently, structures are classified in the PDB by the method used. Here we introduce a method to estimate a measure of equivalent X-ray resolution (e-resolution), expressed in units of Å, to assess the quality of any type of monomeric, single-chain protein structure, irrespective of the experimental structure determination method. We showed and compared the trends in the quality of structures in the Protein Data Bank over the last two decades for five different experimental techniques, excluding theoretical structure predictions. We observed that as new methods are introduced, they undergo a rapid method development evolution: within several years the e-resolution score becomes similar for structures obtained from the five methods and they improve from initially poor performance to acceptable quality, comparable with previously established methods, the performance of which is essentially stable.

Highly efficient NMR assignment of intrinsically disordered proteins: application to B- and T cell receptor domains

We present an integrated approach for efficient characterization of intrinsically disordered proteins. Batch cell-free expression, fast data acquisition, automated analysis, and statistical validation with data resampling have been combined for achieving cost-effective protein expression, and rapid automated backbone assignment. The new methodology is applied for characterization of five cytosolic domains from T- and B-cell receptors in solution.

CING: an integrated residue-based structure validation program suite

We present a suite of programs, named CING for Common Interface for NMR Structure Generation that provides for a residue-based, integrated validation of the structural NMR ensemble in conjunction with the experimental restraints and other input data. External validation programs and new internal validation routines compare the NMR-derived models with empirical data, measured chemical shifts, distance- and dihedral restraints and the results are visualized in a dynamic Web 2.0 report. A red-orange-green score is used for residues and restraints to direct the user to those critiques that warrant further investigation. Overall green scores below ~20 % accompanied by red scores over ~50 % are strongly indicative of poorly modelled structures. The publically accessible, secure iCing webserver ( https://nmr.le.ac.uk ) allows individual users to upload the NMR data and run a CING validation analysis.

RPF: a quality assessment tool for protein NMR structures

We describe the RPF web server, a quality assessment tool for protein NMR structures. The RPF server measures the ‘goodness-of-fit’ of the 3D structure with NMR chemical shift and unassigned NOESY data, and calculates a discrimination power (DP) score, which estimates the differences between the fits of the query structures and random coil structures to these experimental data. The DP-score is an accuracy predictor of the query structure. The RPF server also maps local structure quality measures onto the 3D structure using an online molecular viewer, and onto the NMR spectra, allowing refinement of the structure and/or NOESY peak list data. The RPF server is available at: http://nmr.cabm.rutgers.edu/rpf.