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Abstract Background The HIV viral genome mutates at a high rate and poses a significant long term health risk even in the presence of combination antiretroviral therapy. Current methods for predicting a patient's response to therapy rely on site-directed mutagenesis experiments and in vitro resistance assays. In this bioinformatics study we treat response to antiretroviral therapy as a two-body problem: response to therapy is considered to be a function of both the host and pathogen proteomes. We set out to identify potential responders based on the presence or absence of host protein and DNA motifs on the HIV proteome. Results An alignment of thousands of HIV-1 sequences attested to extensive variation in nucleotide sequence but also showed conservation of eukaryotic short linear motifs on the protein coding regions. The reduction in viral load of patients in the Stanford HIV Drug Resistance Database exhibited a bimodal distribution after 24 weeks of antiretroviral therapy, with 2,000 copies/ml cutoff. Similarly, patients allocated into responder/non-responder categories based on consistent viral load reduction during a 24 week period showed clear separation. In both cases of phenotype identification, a set of features composed of short linear motifs in the reverse transcriptase region of HIV sequence accurately predicted a patient's response to therapy. Motifs that overlap resistance sites were highly predictive of responder identification in single drug regimens but these features lost importance in defining responders in multi-drug therapies. Conclusion HIV sequence mutates in a way that preferentially preserves peptide sequence motifs that are also found in the human proteome. The presence and absence of such motifs at specific regions of the HIV sequence is highly predictive of response to therapy. Some of these predictive motifs overlap with known HIV-1 resistance sites. These motifs are well established in bioinformatics databases and hence do not require identification via in vitro mutation experiments.

Abstract Background Host protein-protein interaction networks are altered by invading virus proteins, which create new interactions, and modify or destroy others. The resulting network topology favors excessive amounts of virus production in a stressed host cell network. Short linear peptide motifs common to both virus and host provide the basis for host network modification. Methods We focused our host-pathogen study on the binding and competing interactions of HIV-1 and human proteins. We showed that peptide motifs conserved across 70% of HIV-1 subtype B and C samples occurred in similar positions on HIV-1 proteins, and we documented protein domains that interact with these conserved motifs. We predicted which human proteins may be targeted by HIV-1 by taking pairs of human proteins that may interact via a motif conserved in HIV-1 and the corresponding interacting protein domain. Results Our predictions were enriched with host proteins known to interact with HIV-1 proteins ENV, NEF, and TAT (p-value < 4.26E-21). Cellular pathways statistically enriched for our predictions include the T cell receptor signaling, natural killer cell mediated cytotoxicity, cell cycle, and apoptosis pathways. Gene Ontology molecular function level 5 categories enriched with both predicted and confirmed HIV-1 targeted proteins included categories associated with phosphorylation events and adenyl ribonucleotide binding. Conclusion A list of host proteins highly enriched with those targeted by HIV-1 proteins can be obtained by searching for host protein motifs along virus protein sequences. The resulting set of host proteins predicted to be targeted by virus proteins will become more accurate with better annotations of motifs and domains. Nevertheless, our study validates the role of linear binding motifs shared by virus and host proteins as an important part of the crosstalk between virus and host.

Beneficial mutations that arise in an evolving asexual population may compete or interact in ways that alter the overall rate of adaptation through mechanisms such as clonal or functional interference. The application of multiple selective pressures simultaneously may allow for a greater number of adaptive mutations, increasing the opportunities for competition between selectively advantageous alterations, and thereby reducing the rate of adaptation. We evolved a strain of Saccharomyces cerevisiae that could not produce its own histidine or uracil for ~500 generations under one or three selective pressures: limitation of the concentration of glucose, histidine, and/or uracil in the media. The rate of adaptation was obtained by measuring evolved relative fitness using competition assays. Populations evolved under a single selective pressure showed a statistically significant increase in fitness on those pressures relative to the ancestral strain, but the populations evolved on all three pressures did not show a statistically significant increase in fitness over the ancestral strain on any single pressure. Simultaneously limiting three essential nutrients for a population of S. cerevisiae effectively slows the rate of evolution on any one of the three selective pressures applied, relative to the single selective pressure cases. We identify possible mechanisms for fitness changes seen between populations evolved on one or three limiting nutrient pressures by high‐throughput sequencing. Adding multiple selective pressures to evolving disease like cancer and infectious diseases could reduce the rate of adaptation and thereby may slow disease progression, prolong drug efficacy and prevent deaths. [ABSTRACT FROM AUTHOR]

Single-nucleotide variants that underlie phenotypic variation can affect chromatin occupancy of transcription factors (TFs). To delineate determinants of in vivo TF binding and chromatin accessibility, we introduce an approach that compares ChIP-seq and DNase-seq data sets from genetically divergent murine erythroid cell lines. The impact of discriminatory singlenucleotide variants on TF ChIP signal enables definition at single base resolution of in vivo binding characteristics of nuclear factors GATA1, TAL1, and CTCF. We further develop a facile complementary approach to more deeply test the requirements of critical nucleotide positions for TF binding by combining CRISPR-Cas9-mediated mutagenesis with ChIP and targeted deep sequencing. Finally, we extend our analytical pipeline to identify nearby contextual DNA elements that modulate chromatin binding by these three TFs, and to define sequences that impact kb-scale chromatin accessibility. Combined, our approaches reveal insights into the genetic basis of TF occupancy and their interplay with chromatin features. [ABSTRACT FROM AUTHOR]

MYCN amplification and 11q deletion are two inversely correlated prognostic factors of poor outcome in neuroblastoma. Here we identify common variants at 11q22.2 within MMP20 that associate with neuroblastoma cases harboring 11q deletion (rs10895322), using GWAS in 113 European-American cases and 5109 ancestry-matched controls. The association is replicated in 44 independent cases and 1902 controls. Our study yields novel insights into the genetic underpinnings of neuroblastoma, demonstrating that the inherited common variants reported contribute to the origin of intra-tumor genetic heterogeneity in neuroblastoma. [ABSTRACT FROM AUTHOR]

Background: Red blood cell (RBC) alloimmunization is a concern for patients who receive multiple or chronic transfusions. Alloimmunization prevalence in transfused patients with bone marrow failure syndrome (BMFS) is unknown. This study aimed to determine physician practice for RBC antigen matching, immunization rates, and antibody specificities in patients with BMFS.Study Design and Methods: The clinical records of all patients with BMFS seen at the Children's Hospital of Philadelphia between 2001 and 2015 were reviewed. Immunization rate was determined per 100 units transfused.Results: ABO/D, C, E, and K (CEK) RBC matching was requested for 21.8% of patients. A total of 3782 RBC units were transfused to 87 patients, of which 2551 (67.5%) were CEK matched and 1231 (32.5%) were ABO/D only matched. The majority of units transfused to patients on a chronic transfusion regimen were CEK matched (89.6% of 2728 units). No anti-C, -E, or -K antibodies formed in any patient during the 14-year study period. Two alloantibodies and two autoantibodies formed, resulting in a rate of 0.05 alloantibodies and 0.05 autoantibodies per 100 units transfused. The prevalence of alloimmunization was 2.3%.Conclusion: The rate and prevalence of RBC alloimmunization were low in patients with BMFS. CEK matching avoided alloimmunization to these antigens in chronically transfused patients. [ABSTRACT FROM AUTHOR]

We report on whole-exome sequencing (WES) of 213 melanomas. Our analysis established NF1, encoding a negative regulator of RAS, as the third most frequently mutated gene in melanoma, after BRAF and NRAS. Inactivating NF1 mutations were present in 46% of melanomas expressing wild-type BRAF and RAS, occurred in older patients and showed a distinct pattern of co-mutation with other RASopathy genes, particularly RASA2. Functional studies showed that NF1 suppression led to increased RAS activation in most, but not all, melanoma cases. In addition, loss of NF1 did not predict sensitivity to MEK or ERK inhibitors. The rebound pathway, as seen by the induction of phosphorylated MEK, occurred in cells both sensitive and resistant to the studied drugs. We conclude that NF1 is a key tumor suppressor lost in melanomas, and that concurrent RASopathy gene mutations may enhance its role in melanomagenesis. [ABSTRACT FROM AUTHOR]

A common goal of tumor sequencing projects is finding genes whose mutations are selected for during tumor development. This is accomplished by choosing genes that have more non-synonymous mutations than expected from an estimated background mutation frequency. While this background frequency is unknown, it can be estimated using both the observed synonymous mutation frequency and the non-synonymous to synonymous mutation ratio. The synonymous mutation frequency can be determined across all genes or in a gene-specific manner. This choice introduces an interesting trade-off. A gene-specific frequency adjusts for an underlying mutation bias, but is difficult to estimate given missing synonymous mutation counts. Using a genome-wide synonymous frequency is more robust, but is less suited for adjusting biases. Studying four evaluation criteria for identifying genes with high non-synonymous mutation burden (reflecting preferential selection of expressed genes, genes with mutations in conserved bases, genes with many protein interactions, and genes that show loss of heterozygosity), we find that the gene-specific synonymous frequency is superior in the gene expression and protein interaction tests. In conclusion, the use of the gene-specific synonymous mutation frequency is well suited for assessing a gene's non-synonymous mutation burden. [ABSTRACT FROM PUBLISHER]

Transcriptional regulation critically depends on proper interactions between transcription factors (TF) and their cognate DNA binding sites. The widely used model of TF-DNA binding – the Positional Weight Matrix (PWM) – presumes independence between positions within the binding site. However, there is evidence to show that the independence assumption may not always hold, and the extent of interposition dependence is not completely known. We hypothesize that the interposition dependence should partly be manifested as correlated evolution at the positions. We report a Maximum-Likelihood (ML) approach to infer correlated evolution at any two positions within a PWM, based on a multiple alignment of 5 mammalian genomes. Application to a genome-wide set of putative cis elements in human promoters reveals a prevalence of correlated evolution within cis elements. We found that the interdependence between two positions decreases with increasing distance between the positions. The interdependent positions tend to be evolutionarily more constrained and moreover, the dependence patterns are relatively similar across structurally related transcription factors. Although some of the detected mutational dependencies may be due to context-dependent genomic hyper-mutation, notably CG to TG, the majority is likely due to context-dependent preferences for specific nucleotide combinations within the cis elements. Patterns of evolution at individual nucleotide positions within mammalian TF binding sites are often significantly correlated, suggesting interposition dependence. The proposed methodology is also applicable to other classes of non-coding functional elements. A detailed investigation of mutational dependencies within specific motifs could reveal preferred nucleotide combinations that may help refine the DNA binding models. [ABSTRACT FROM AUTHOR]

Purpose |!|#8211; The purpose of this paper is to outline what it takes to be a successful interim manager in today|!|#39;s pharmaceutical industry, based on the experiences of two people currently in the role.Design/methodology/approach |!|#8211; The paper explains when it is and is not appropriate to employ an interim manager, and details the main advantages and disadvantages from the points of view of both the company and interim manager involved.Findings |!|#8211; The paper describes the main challenges as: working across a range of time zones; traveling between countries; juggling different and demanding clients; recognizing that one has been brought in to solve a specific problem, not to become a permanent employee; guiding without interfering; managing client expectations; and coping with down-time when the contract finishes.Practical implications |!|#8211; The paper demonstrates how interns may help companies to solve a particular problem quickly and easily.Social implications |!|#8211; The paper explains that, when companies are feeling the pinch and may have frozen their recruitment of permanent employees, interims offer immediate support and expertise but are dispensable.Originality/value |!|#8211; The paper contains much to interest companies thinking of taking on an interim and individuals considering interim management as a career. [ABSTRACT FROM AUTHOR]

Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs). MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using smallmolecule drugs. [ABSTRACT FROM AUTHOR]

Background: Host protein-protein interaction networks are altered by invading virus proteins, which create new interactions, and modify or destroy others. The resulting network topology favors excessive amounts of virus production in a stressed host cell network. Short linear peptide motifs common to both virus and host provide the basis for host network modification. Methods: We focused our host-pathogen study on the binding and competing interactions of HIV- 1 and human proteins. We showed that peptide motifs conserved across 70% of HIV-1 subtype B and C samples occurred in similar positions on HIV-1 proteins, and we documented protein domains that interact with these conserved motifs. We predicted which human proteins may be targeted by HIV-1 by taking pairs of human proteins that may interact via a motif conserved in HIV- 1 and the corresponding interacting protein domain. Results: Our predictions were enriched with host proteins known to interact with HIV-1 proteins ENV, NEF, and TAT (p-value < 4.26E-21). Cellular pathways statistically enriched for our predictions include the T cell receptor signaling, natural killer cell mediated cytotoxicity, cell cycle, and apoptosis pathways. Gene Ontology molecular function level 5 categories enriched with both predicted and confirmed HIV-1 targeted proteins included categories associated with phosphorylation events and adenyl ribonucleotide binding. Conclusion: A list of host proteins highly enriched with those targeted by HIV-1 proteins can be obtained by searching for host protein motifs along virus protein sequences. The resulting set of host proteins predicted to be targeted by virus proteins will become more accurate with better annotations of motifs and domains. Nevertheless, our study validates the role of linear binding motifs shared by virus and host proteins as an important part of the crosstalk between virus and host. [ABSTRACT FROM AUTHOR]

During mitosis, RNA polymerase II (Pol II) and many transcription factors dissociate from chromatin, and transcription ceases globally. Transcription is known to restart in bulk by telophase, but whether de novo transcription at the mitosis–G1 transition is in any way distinct from later in interphase remains unknown. We tracked Pol II occupancy genome-wide in mammalian cells progressing from mitosis through late G1. Unexpectedly, during the earliest rounds of transcription at the mitosis–G1 transition, ∼50% of active genes and distal enhancers exhibit a spike in transcription, exceeding levels observed later in G1 phase. Enhancer–promoter chromatin contacts are depleted during mitosis and restored rapidly upon G1 entry but do not spike. Of the chromatin-associated features examined, histone H3 Lys27 acetylation levels at individual loci in mitosis best predict the mitosis–G1 transcriptional spike. Single-molecule RNA imaging supports that the mitosis–G1 transcriptional spike can constitute the maximum transcriptional activity per DNA copy throughout the cell division cycle. The transcriptional spike occurs heterogeneously and propagates to cell-to-cell differences in mature mRNA expression. Our results raise the possibility that passage through the mitosis–G1 transition might predispose cells to diverge in gene expression states. [ABSTRACT FROM AUTHOR]

Summary Bromodomain and extraterminal motif (BET) proteins are pharmacologic targets for the treatment of diverse diseases, yet the roles of individual BET family members remain unclear. We find that BRD2, but not BRD4, co-localizes with the architectural/insulator protein CCCTC-binding factor (CTCF) genome-wide. CTCF recruits BRD2 to co-bound sites whereas BRD2 is dispensable for CTCF occupancy. Disruption of a CTCF/BRD2-occupied element positioned between two unrelated genes enables regulatory influence to spread from one gene to another, suggesting that CTCF and BRD2 form a transcriptional boundary. Accordingly, single-molecule mRNA fluorescence in situ hybridization (FISH) reveals that, upon site-specific CTCF disruption or BRD2 depletion, expression of the two genes becomes increasingly correlated. HiC shows that BRD2 depletion weakens boundaries co-occupied by CTCF and BRD2, but not those that lack BRD2. These findings indicate that BRD2 supports boundary activity, and they raise the possibility that pharmacologic BET inhibitors can influence gene expression in part by perturbing domain boundary function. [ABSTRACT FROM AUTHOR]

Recent advances in DNA sequencing have expanded our understanding of the molecular basis of genetic disorders and increased the utilization of clinical genomic tests. Given the paucity of evidence to accurately classify each variant and the difficulty of experimentally evaluating its clinical significance, a large number of variants generated by clinical tests are reported as variants of unknown clinical significance. Population-scale variant databases can improve clinical interpretation. Specifically, pathogenicity prediction for novel missense variants can use features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant data set. Here, we introduce one variant data set derived from clinical sequencing panels and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This data set is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further use this data set to demonstrate the necessity of disease-specific classifiers and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant-level features. PathoPredictor achieves an average precision >90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. The accumulation of larger clinical variant training data sets can significantly enhance their performance in a disease- and gene-specific manner., (© 2019 Evans et al.; Published by Cold Spring Harbor Laboratory Press.)

Exome-based panels are becoming the preferred diagnostic strategy in clinical laboratories. This approach enables dynamic gene content update and, if needed, cost-effective reflex to whole-exome sequencing. Currently, no guidelines or appropriate resources are available to support the clinical implementation of exome-based panels. Here, we highlight principles and important considerations for the clinical development and validation of exome-based panels. In addition, we developed ExomeSlicer, a novel, web-based resource, which uses empirical exon-level next-generation sequencing quality metrics to predict and visualize technically challenging exome-wide regions in any gene or genes of interest. Exome sequencing data from 100 clinical epilepsy cases were used to illustrate the clinical utility of ExomeSlicer in predicting poor-quality regions and its impact on streamlining the ad hoc Sanger sequencing fill in burden. With the use of ExomeSlicer, >2100 low complexity and/or high-homology regions affecting >1615 genes across the exome were also characterized. These regions can be a source of false-positive or false-negative variant calls, which can lead to misdiagnoses in tested patients and/or inaccurate functional annotations. We provide important considerations and a novel resource for the clinical development of exome-based panels., (Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Alterations in the synthesis and bioavailability of NO are central to the pathogenesis of cardiovascular and metabolic disorders. Although endothelial NO synthase-derived (eNOS-derived) NO affects mitochondrial long-chain fatty acid β-oxidation, the pathophysiological significance of this regulation remains unclear. Accordingly, we determined the contributions of eNOS/NO signaling in the adaptive metabolic responses to fasting and in age-induced metabolic dysfunction. Four-month-old eNOS-/- mice are glucose intolerant and exhibit serum dyslipidemia and decreased capacity to oxidize fatty acids. However, during fasting, eNOS-/- mice redirect acetyl-CoA to ketogenesis to elevate circulating levels of β-hydroxybutyrate similar to wild-type mice. Treatment of 4-month-old eNOS-/- mice with nitrite for 10 days corrected the hypertension and serum hyperlipidemia and normalized the rate of fatty acid oxidation. Fourteen-month-old eNOS-/- mice exhibited metabolic derangements, resulting in reduced utilization of fat to generate energy, lower resting metabolic activity, and diminished physical activity. Seven-month administration of nitrite to eNOS-/- mice reversed the age-dependent metabolic derangements and restored physical activity. While the eNOS/NO signaling is not essential for the metabolic adaptation to fasting, it is critical for regulating systemic metabolic homeostasis in aging. The development of age-dependent metabolic disorder is prevented by low-dose replenishment of bioactive NO.

Accumulation of aggregated α-synuclein into Lewy bodies is thought to contribute to the onset and progression of dopaminergic neuron degeneration in Parkinson's disease (PD) and related disorders. Although protein aggregation is associated with perturbation of proteostasis, how α-synuclein aggregation affects the brain proteome and signaling remains uncertain. In a mouse model of α-synuclein aggregation, 6% of 6215 proteins and 1.6% of 8183 phosphopeptides changed in abundance, indicating conservation of proteostasis and phosphorylation signaling. The proteomic analysis confirmed changes in abundance of proteins that regulate dopamine synthesis and transport, synaptic activity and integrity, and unearthed changes in mRNA binding, processing and protein translation. Phosphorylation signaling changes centered on axonal and synaptic cytoskeletal organization and structural integrity. Proteostatic responses included a significant increase in the levels of Lmp7, a component of the immunoproteasome. Increased Lmp7 levels and activity were also quantified in postmortem human brains with PD and dementia with Lewy bodies. Functionally, the immunoproteasome degrades α-synuclein aggregates and generates potentially antigenic peptides. Expression and activity of the immunoproteasome may represent testable targets to induce adaptive responses that maintain proteome integrity and modulate immune responses in protein aggregation disorders., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

MYCN amplification and 11q deletion are two inversely correlated prognostic factors of poor outcome in neuroblastoma. Here we identify common variants at 11q22.2 within MMP20 that associate with neuroblastoma cases harboring 11q deletion (rs10895322), using GWAS in 113 European-American cases and 5109 ancestry-matched controls. The association is replicated in 44 independent cases and 1902 controls. Our study yields novel insights into the genetic underpinnings of neuroblastoma, demonstrating that the inherited common variants reported contribute to the origin of intra-tumor genetic heterogeneity in neuroblastoma.Chromosomal abnormalities such as 11q deletion are associated with poor prognosis in neuroblastoma. Here, the authors perform a genome-wide association study and identify an association between a variant within a Matrix metalloproteinase (MMP) gene member, MMP20, and 11q-deletion subtype neuroblastoma.

Exome sequencing in cancer is a powerful tool for identifying mutational events across the coding region of human genes. Here, we describe computational methods that use exome sequencing reads from cancer samples to identify somatic single nucleotide variants (SNVs), copy number alterations, and short insertions and deletions (InDels). We further describe analytical methods to generate lists of driver genes with more mutational events than expected by chance.

Science blogs, Twitter commentary, and comments on journal websites represent an immediate response to journal articles, and may help in identifying relevant publications. However, the use of these media for establishing paper impact is not well studied. Using Wikipedia as a proxy for other social media, we explore the correlation between inclusion of a journal article in Wikipedia, and article impact as measured by citation count. We start by cataloging features of PubMed articles cited in Wikipedia. We find that Wikipedia pages referencing the most journal articles are about disorders and diseases, while the most referenced articles in Wikipedia are about genomics. We note that journal articles in Wikipedia have significantly higher citation counts than an equivalent random article subset. We also observe that articles are included in Wikipedia soon after publication. Our data suggest that social media may represent a largely untapped post-publication review resource for assessing paper impact.

Background: The HIV viral genome mutates at a high rate and poses a significant long term health risk even in the presence of combination antiretroviral therapy. Current methods for predicting a patient's response to therapy rely on site-directed mutagenesis experiments and in vitro resistance assays. In this bioinformatics study we treat response to antiretroviral therapy as a two-body problem: response to therapy is considered to be a function of both the host and pathogen proteomes. We set out to identify potential responders based on the presence or absence of host protein and DNA motifs on the HIV proteome., Results: An alignment of thousands of HIV-1 sequences attested to extensive variation in nucleotide sequence but also showed conservation of eukaryotic short linear motifs on the protein coding regions. The reduction in viral load of patients in the Stanford HIV Drug Resistance Database exhibited a bimodal distribution after 24 weeks of antiretroviral therapy, with 2,000 copies/ml cutoff. Similarly, patients allocated into responder/non-responder categories based on consistent viral load reduction during a 24 week period showed clear separation. In both cases of phenotype identification, a set of features composed of short linear motifs in the reverse transcriptase region of HIV sequence accurately predicted a patient's response to therapy. Motifs that overlap resistance sites were highly predictive of responder identification in single drug regimens but these features lost importance in defining responders in multi-drug therapies., Conclusion: HIV sequence mutates in a way that preferentially preserves peptide sequence motifs that are also found in the human proteome. The presence and absence of such motifs at specific regions of the HIV sequence is highly predictive of response to therapy. Some of these predictive motifs overlap with known HIV-1 resistance sites. These motifs are well established in bioinformatics databases and hence do not require identification via in vitro mutation experiments.