Y-chromosomal diversity in Lebanon is structured by recent historical events.

Lebanon is an eastern Mediterranean country inhabited by approximately four million people with a wide variety of ethnicities and religions, including Muslim, Christian, and Druze. In the present study, 926 Lebanese men were typed with Y-chromosomal SNP and STR markers, and unusually, male genetic variation within Lebanon was found to be more strongly structured by religious affiliation than by geography. We therefore tested the hypothesis that migrations within historical times could have contributed to this situation. Y-haplogroup J*(xJ2) was more frequent in the putative Muslim source region (the Arabian Peninsula) than in Lebanon, and it was also more frequent in Lebanese Muslims than in Lebanese non-Muslims. Conversely, haplogroup R1b was more frequent in the putative Christian source region (western Europe) than in Lebanon and was also more frequent in Lebanese Christians than in Lebanese non-Christians. The most common R1b STR-haplotype in Lebanese Christians was otherwise highly specific for western Europe and was unlikely to have reached its current frequency in Lebanese Christians without admixture. We therefore suggest that the Islamic expansion from the Arabian Peninsula beginning in the seventh century CE introduced lineages typical of this area into those who subsequently became Lebanese Muslims, whereas the Crusader activity in the 11(th)-13(th) centuries CE introduced western European lineages into Lebanese Christians.

Free energy simulations reveal a double mutant avian H5N1 virus hemagglutinin with altered receptor binding specificity.

Historically, influenza pandemics have been triggered when an avian influenza virus or a human/avian reassorted virus acquires the ability to replicate efficiently and become transmissible in the human population. Most critically, the major surface glycoprotein hemagglutinin (HA) must adapt to the usage of human-like (alpha-2,6-linked) sialylated glycan receptors. Therefore, identification of mutations that can switch the currently circulating H5N1 HA receptor binding specificity from avian to human might provide leads to the emergence of pandemic H5N1 viruses. To define such mutations in the H5 subtype, here we provide a computational framework that combines molecular modeling with extensive free energy simulations. Our results show that the simulated binding affinities are in good agreement with currently available experimental data. Moreover, we predict that one double mutation (V135S and A138S) in HA significantly enhances alpha-2,6-linked receptor recognition by the H5 subtype. Our simulations indicate that this double mutation in H5N1 HA increases the binding affinity to alpha-2,6-linked sialic acid receptors by 2.6 +/- 0.7 kcal/mol per HA monomer that primarily arises from the electrostatic interactions. Further analyses reveal that introduction of this double mutation results in a conformational change in the receptor binding pocket of H5N1 HA. As a result, a major rearrangement occurs in the hydrogen-bonding network of HA with the human receptor, making the human receptor binding pattern of double mutant H5N1 HA surprisingly similar to that observed in human H1N1 HA. These large scale molecular simulations on single and double mutants thus provide new insights into our understanding toward human adaptation of the avian H5N1 virus.

Maximum-likelihood estimation of site-specific mutation rates in human mitochondrial DNA from partial phylogenetic classification.

The mitochondrial DNA hypervariable segment I (HVS-I) is widely used in studies of human evolutionary genetics, and therefore accurate estimates of mutation rates among nucleotide sites in this region are essential. We have developed a novel maximum-likelihood methodology for estimating site-specific mutation rates from partial phylogenetic information, such as haplogroup association. The resulting estimation problem is a generalized linear model, with a nonstandard link function. We develop inference and bias correction tools for our estimates and a hypothesis-testing approach for site independence. We demonstrate our methodology using 16,609 HVS-I samples from the Genographic Project. Our results suggest that mutation rates among nucleotide sites in HVS-I are highly variable. The 16,400-16,500 region exhibits significantly lower rates compared to other regions, suggesting potential functional constraints. Several loci identified in the literature as possible termination-associated sequences (TAS) do not yield statistically slower rates than the rest of HVS-I, casting doubt on their functional importance. Our tests do not reject the null hypothesis of independent mutation rates among nucleotide sites, supporting the use of site-independence assumption for analyzing HVS-I. Potential extensions of our methodology include its application to estimation of mutation rates in other genetic regions, like Y chromosome short tandem repeats.

Correction to: Sequencing and curation strategies for identifying candidate glioblastoma treatments.

Following publication of the original article [1], it was reported that the given name of the fourteenth author was incorrectly published. The incorrect and the correct names are given below.

Sequencing and curation strategies for identifying candidate glioblastoma treatments.

BACKGROUND: Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. METHODS: A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. RESULTS: WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. CONCLUSION: These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.

Single mutation induced H3N2 hemagglutinin antibody neutralization: a free energy perturbation study.

The single mutation effect on the binding affinity of H3N2 viral protein hemagglutinin (HA) with the monoclonical antibody fragment (Fab) is studied in this paper using the free energy perturbation (FEP) simulations. An all-atom protein model with explicit solvents is used to perform an aggregate of several microsecond FEP molecular dynamics simulations. A recent experiment shows that a single mutation in H3N2 HA, T131I, increases the antibody-antigen dissociation constant Kd by a factor of approximately 4000 (equivalent to a binding affinity decrease of approximately 5 kcal/mol), thus introducing an escape of the antibody (Ab) neutralization. Our FEP result confirms this experimental finding by estimating the HA-Ab binding affinity decrease of 5.2 +/- 0.9 kcal/mol but with a somewhat different molecular mechanism from the experimental findings. Detailed analysis reveals that this large binding affinity decrease in the T131I mutant is mainly due to the displacement of two bridge water molecules otherwise present in the wild-type HA/Ab interface. The decomposition of the binding free energy supports this observation, as the major contribution to the binding affinity is from the electrostatic interactions. In addition, we find that the loss of the binding affinity is also related to the large conformational distortion of one loop (loop 155-161) in the unbound state of the mutant. We then simulate all other possible mutations for this specific mutation site T131, and predict a few more mutations with even larger decreases in the binding affinity (i.e., better candidates for antibody neutralization), such as T131W, T131Y, and T131F. As for further validation, we have also modeled another mutation, S157L, with experimental binding affinity available (Kd increasing approximately 500 times), and found a binding affinity decrease of 4.1 +/- 1.0 kcal/mol, which is again in excellent agreement with experiment. These large scale simulations might provide new insights into the detailed physical interaction, possible future escape mutation, and antibody-antigen coevolution relationship between influenza virus and human antibodies.

Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma.

OBJECTIVE: To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. METHODS: Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. RESULTS: More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. CONCLUSIONS: The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. CLINICALTRIALSGOV IDENTIFIER: NCT02725684.

Spatial profiling of protein hydrophobicity: native vs. decoy structures.

A recent study of 30 soluble globular protein structures revealed a quasi-invariant called the hydrophobic ratio. This invariant, which is the ratio of the distance at which the second order hydrophobic moment vanished to the distance at which the zero order moment vanished, was found to be 0.75 +/- 0.05 for 30 protein structures. This report first describes the results of the hydrophobic profiling of 5,387 non-redundant globular protein domains of the Protein Data Bank, which yields a hydrophobic ratio of 0.71 +/- 0.08. Then, a new hydrophobic score is defined based on the hydrophobic profiling to discriminate native-like proteins from decoy structures. This is tested on three widely used decoy sets, namely the Holm and Sander decoys, Park and Levitt decoys, and Baker decoys. Since the hydrophobic moment profiling characterizes a global feature and requires reasonably good statistics, this imposes a constraint upon the size of the protein structures in order to yield relatively smooth moment profiles. We show that even subject to the limitations of protein size (both Park & Levitt and Baker sets are small protein decoys), the hydrophobic moment profiling and hydrophobic score can provide useful information that should be complementary to the information provided by force field calculations.

Molecular recognition of metabotropic glutamate receptor type 1 (mGluR1): synergistic understanding with free energy perturbation and linear response modeling.

Metabotropic glutamate receptors (mGluRs) constitute an important family of the G-protein coupled receptors. Due to their widespread distribution in the central nervous system (CNS), these receptors are attractive candidates for understanding the molecular basis of various cognitive processes as well as for designing inhibitors for relevant psychiatric and neurological disorders. Despite many studies on drugs targeting the mGluR receptors to date, the molecular level details on the ligand binding dynamics still remain unclear. In this study, we performed in silico experiments for mGluR1 with 29 different ligands including known synthetic agonists and antagonists as well as natural amino acids. The ligand-receptor binding affinities were estimated by the use of atomistic simulations combined with the mathematically rigorous, Free Energy Perturbation (FEP) method, which successfully recognized the native agonist l-glutamate among the highly favorable binders, and also accurately distinguished antagonists from agonists. Comparative contact analysis also revealed the binding mode differences between natural and non-natural amino acid-based ligands. Several factors potentially affecting the ligand binding affinity and specificity were identified including net charges, dipole moments, and the presence of aromatic rings. On the basis of these findings, linear response models (LRMs) were built for different sets of ligands that showed high correlations (R(2) > 0.95) to the corresponding FEP binding affinities. These results identify some key factors that determine ligand-mGluR1 binding and could be used for future inhibitor designs and support a role for in silico modeling for understanding receptor ligand interactions.

Population differentiation of southern Indian male lineages correlates with agricultural expansions predating the caste system.

Previous studies that pooled Indian populations from a wide variety of geographical locations, have obtained contradictory conclusions about the processes of the establishment of the Varna caste system and its genetic impact on the origins and demographic histories of Indian populations. To further investigate these questions we took advantage that both Y chromosome and caste designation are paternally inherited, and genotyped 1,680 Y chromosomes representing 12 tribal and 19 non-tribal (caste) endogamous populations from the predominantly Dravidian-speaking Tamil Nadu state in the southernmost part of India. Tribes and castes were both characterized by an overwhelming proportion of putatively Indian autochthonous Y-chromosomal haplogroups (H-M69, F-M89, R1a1-M17, L1-M27, R2-M124, and C5-M356; 81% combined) with a shared genetic heritage dating back to the late Pleistocene (10-30 Kya), suggesting that more recent Holocene migrations from western Eurasia contributed <20% of the male lineages. We found strong evidence for genetic structure, associated primarily with the current mode of subsistence. Coalescence analysis suggested that the social stratification was established 4-6 Kya and there was little admixture during the last 3 Kya, implying a minimal genetic impact of the Varna (caste) system from the historically-documented Brahmin migrations into the area. In contrast, the overall Y-chromosomal patterns, the time depth of population diversifications and the period of differentiation were best explained by the emergence of agricultural technology in South Asia. These results highlight the utility of detailed local genetic studies within India, without prior assumptions about the importance of Varna rank status for population grouping, to obtain new insights into the relative influences of past demographic events for the population structure of the whole of modern India.

Destruction of long-range interactions by a single mutation in lysozyme.

We propose a mechanism, based on a > or =10-micros molecular dynamics simulation, for the surprising misfolding of hen egg-white lysozyme caused by a single mutation (W62G). Our simulations of the wild-type and mutant lysozymes in 8 M urea solution at biological temperature (with both pH 2 and 7) reveal that the mutant structure is much less stable than that of the wild type, with the mutant showing larger fluctuations and less native-like contacts. Analysis of local contacts reveals that the Trp-62 residue is the key to a cooperative long-range interaction within the wild type, where it acts like a bridge between two neighboring basic residues. Thus, a native-like cluster or nucleation site can form near these residues in the wild type but not in the mutant. The time evolution of the secondary structure also exhibits a quicker loss of the beta-sheets in the mutant than in the wild type, whereas some of the alpha-helices persist during the entire simulation in both the wild type and the mutant in 8 M urea (even though the tertiary structures are basically all gone). These findings, while supporting the general conclusions of a recent experimental study by Dobson and coworkers [Klein-Seetharam J, Oikama M, Grimshaw SB, Wirmer J, Duchardt E, Ueda T, Imoto T, Smith LJ, Dobson CM, Schwalbe H (2002) Science 295:1719-1722], provide a detailed but different molecular picture of the misfolding mechanism.

Thermal denaturing of mutant lysozyme with both the OPLSAA and the CHARMM force fields.

Biomolecular simulations enabled by massively parallel supercomputers such as BlueGene/L promise to bridge the gap between the currently accessible simulation time scale and the experimental time scale for many important protein folding processes. In this study, molecular dynamics simulations were carried out for both the wild-type and the mutant hen lysozyme (TRP62GLY) to study the single mutation effect on lysozyme stability and misfolding. Our thermal denaturing simulations at 400-500 K with both the OPLSAA and the CHARMM force fields show that the mutant structure is indeed much less stable than the wild-type, which is consistent with the recent urea denaturing experiment (Dobson et al. Science 2002, 295, 1719-1722; Nature 2003, 424, 783-788). Detailed results also reveal that the single mutation TRP62GLY first induces the loss of native contacts in the beta-domain region of the lysozyme protein at high temperatures, and then the unfolding process spreads into the alpha-domain region through Helix C. Even though the OPLSAA force field in general shows a more stable protein structure than does the CHARMM force field at high temperatures, the two force fields examined here display qualitatively similar results for the misfolding process, indicating that the thermal denaturing of the single mutation is robust and reproducible with various modern force fields.

Principles of mucin architecture: structural studies on synthetic glycopeptides bearing clustered mono-, di-, tri-, and hexasaccharide glycodomains.

The structural characteristics of a mucin glycopeptide motif derived from the N-terminal fragment STTAV of the cell surface glycoprotein CD43 have been investigated by NMR. In this study, a series of molecules prepared by total synthesis were examined, consisting of the peptide itself, three glycopeptides having clustered sites of alpha-O-glycosylation on the serine and threonine side chains with the Tn, TF, and STF carbohydrate antigens, respectively, and one with the beta-O-linked TF antigen. Additionally, a glycopeptide having the sequence SSSAVAV, triglycosylated with the Le(y) epitope, was investigated. NMR data for the tri-STF-STTAV glycopeptide were used to solve the structure of this construct through restrained molecular dynamics calculations. The calculations revealed a defined conformation for the glycopeptide core rooted in the interaction of the peptide and the first N-acetylgalactosamine residue. The similarity of the NMR data for each of the alpha-O-linked glycopeptides demonstrates that this structure persists for each construct and that the mode of attachment of the first sugar and the peptide is paramount in establishing the organization of the core. The core provides a common framework on which a variety of glycans may be displayed. Remarkably, while there is a profound organizational effect on the peptide backbone with the alpha-linked glycans, attachment via a beta-linkage has little apparent consequence.