In-silico approaches to assessing multiple high-level drug-drug and drug-disease adverse drug effects

INTRODUCTION

Pharmacovigilance plays a pivotal role in monitoring adverse events (AEs) related to chemical substances in human/animal populations. With increasing spontaneous-reporting systems, researchers turned to in-silico approaches to efficiently analyze drug safety profiles. Here, we review in-silico methods employed for assessing multiple drug-drug/drug-disease AEs covered by comparative analyses and visualization strategies.

AREAS COVERED

Disproportionality, involving multi-stage statistical methodologies and data processing, identifies safety signals among drug-AE pairs. By stratifying data based on disease indications/demographics, researchers address confounders and assess drug safety. Comparative analyses, including clustering techniques and visualization techniques, assess drug similarities, patterns, and trends, calculate correlations, and identify distinct toxicities. Furthermore, we conducted a thorough Scopus search on 'pharmacovigilance,' yielding 5,836 publications spanning 2003 to 2023.

EXPERT OPINION

Pharmacovigilance relies on diverse data sources, presenting challenges in the integration of in-silico approaches and requiring compliance with regulations and AI adoption. Systematic use of statistical analyses enables identifications of potential risks with drugs. Frequentist and Bayesian methods are used in disproportionalities, each with its strengths and weaknesses. Integration of pharmacogenomics with pharmacovigilance enables personalized medicine, with AI further enhancing patient engagement. This multidisciplinary approach holds promise, improving drug efficacy and safety, and should be a core mission of One-Health studies.

The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials

Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.

A retrospective study of adverse drug events in anticoagulant administration with relevance to COVID-19

Initial studies in COVID-19 patients reported lower mortality rates associated with the use of the drug heparin, a widely used anticoagulant. The objective of this analysis was to determine whether there are adverse events associated with the administration of anticoagulants, and specifically how this might apply in patients known to have COVID-19. Data for this study were obtained from the Food and Drug Administration's Adverse Event Reporting System (FAERS) public database and from the NIH's clinical trials website. Proportional Reporting Ratios (PRR) with lower 95% confidence intervals (lower CI) and empirical Bayes geometric mean (EBGM) scores with lower 95% confidence limits were calculated for data from the FAERS database where the adverse events studied mimicked COVID-19 symptoms.

Computational Target-Based Screening of Anti-MRSA Natural Products Reveals Potential Multitarget Mechanisms of Action through Peptidoglycan Synthesis Proteins

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the leading causes of bacterial infections in both healthcare and community settings. MRSA can acquire resistance to any current antibiotic, which has major implications for its current and future treatment options. As such, it is globally a major focus for infection control efforts. The mechanical rigidity provided by peptidoglycans in the bacteria cell walls makes it a promising target for broad-spectrum antibacterial drug discovery. The development of drugs that can target different stages of the synthesis of peptidoglycan in MRSA may compromise the integrity of its cell wall and consequently result in the rapid decline of diseases associated with this drug-resistant bacteria. The present study is aimed at screening natural products with known in vitro activities against MRSA to identify their potential to inhibit the proteins involved in the biosynthesis of the peptidoglycan cell wall. A total of 262 compounds were obtained when a literature survey was conducted on anti-MRSA natural products (AMNPs). Virtual screening of the AMNPs was performed against various proteins (targets) that are involved in the biosynthesis of the peptidoglycan (PPC) cell wall using Schrödinger software (release 2020-3) to determine their binding affinities. Nine AMNPs were identified as potential multitarget inhibitors against peptidoglycan biosynthesis proteins. Among these compounds, DB211 showed the strongest binding affinity and interactions with six protein targets, representing three stages of peptidoglycan biosynthesis, and thus was selected as the most promising compound. The MD simulation results for DB211 and its proteins indicated that the protein-ligand complexes were relatively stable over the simulation period of 100 ns. In conclusion, DB211 showed the potential to inhibit six proteins involved in the biosynthesis of the peptidoglycan cell wall in MRSA, thus reducing the chance of MRSA developing resistance to this compound. Therefore, DB211 provided a starting point for the design of new compounds that can inhibit multiple targets in the biosynthesis of the peptidoglycan layer in MRSA.

Data-driven methodology for discovery and response to pulmonary symptomology in hypertension through statistical learning and data mining: Application to COVID-19 related pharmacovigilance

Background: Potential therapy and confounding factors including typical co-administered medications, patient's disease states, disease prevalence, patient demographics, medical histories, and reasons for prescribing a drug often are incomplete, conflicting, missing, or uncharacterized in spontaneous adverse drug event (ADE) reporting systems. These missing or incomplete features can affect and limit the application of quantitative methods in pharmacovigilance for meta-analyses of data during randomized clinical trials.

Methods: Data from patients with hypertension were retrieved and integrated from the FDA Adverse Event Reporting System. 134 antihypertensive drugs out of 1151 drugs were filtered and then evaluated using the Empirical Bayes Geometric Mean (EBGM) of the posterior distribution to build ADE-drug profiles with an emphasis on the pulmonary ADEs (pADE). Afterward, the Graphical Least Absolute Shrinkage and Selection Operator (GLASSO) captured drug associations based on pADEs by correcting hidden factors and confounder misclassification. Selected drugs were then compared using the Friedman test in drug classes and clusters obtained from GLASSO.

Results: Following multiple filtering stages to exclude insignificant and noise-driven reports, we found that drugs from antihypertensives agents, urologicals, and antithrombotic agents (macitentan, bosentan, epoprostenol, selexipag, sildenafil, tadalafil, and beraprost) form a similar class with a significantly higher incidence of pADEs. Macitentan and bosentan were associates with 64% and 56% of pADEs, respectively. Because these two medications are prescribed in diseases affecting pulmonary function and may be likely to emerge among the highest reported pADEs, in fact, they serve to validate the methods utilized here. Conversely, doxazosin and rilmenidine were found to have the least pADEs in selected drugs from hypertension patients. Nifedipine and candesartan were also found by signal detection methods to form a drug cluster, shown by several studies an effective combination of these drugs on lowering blood pressure and appeared an improved side effect profile in comparison with single-agent monotherapy.

Conclusions: We consider pADE profiles in multiple long-standing groups of therapeutics including antihypertensive agents, antithrombotic agents, beta-blocking agents, calcium channel blockers, or agents acting on the renin-angiotensin system, in patients with hypertension associated with high-risk for COVID-19. We found that several individual drugs have significant differences between their drug classes and compared to other drug classes. For instance, macitentan and bosentan from endothelin receptor antagonists show major concern while doxazosin and rilmenidine exhibited the least pADEs compared to the outcomes of other drugs. Using techniques in this study, we assessed and confirmed the hypothesis that drugs from the same drug class could have very different pADE profiles affecting outcomes in acute respiratory illness.

Funding: GJW and MJD accepted funding from BioNexus KC for funding on this project, but BioNexus KC had no direct role in this article.

Pulmonary adverse drug event data in hypertension with implications on COVID-19 morbidity

Hypertension is a recognized comorbidity for COVID-19. The association of antihypertensive medications with outcomes in patients with hypertension is not fully described. However, angiotensin-converting enzyme 2 (ACE2), responsible for host entry of the novel coronavirus (SARS-CoV-2) leading to COVID-19, is postulated to be upregulated in patients taking angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs). Here, we evaluated the occurrence of pulmonary adverse drug events (ADEs) in patients with hypertension receiving ACEIs/ARBs to determine if disparities exist between individual drugs within the respective classes using data from the FDA Spontaneous Reporting Systems. For this purpose, we proposed the proportional reporting ratio to provide a statistical summary for the commonality of an ADE for a specific drug as compared to the entire database for drugs in the same or other classes. In addition, a statistical procedure, multiple logistic regression analysis, was employed to correct hidden confounders when causative covariates are underreported or untrusted to correct analyses of drug-ADE combinations. To date, analyses have been focused on drug classes rather than individual drugs which may have different ADE profiles depending on the underlying diseases present. A retrospective analysis of thirteen pulmonary ADEs showed significant differences associated with quinapril and trandolapril, compared to other ACEIs and ARBs. Specifically, quinapril and trandolapril were found to have a statistically significantly higher incidence of pulmonary ADEs compared with other ACEIs as well as ARBs (P < 0.0001) for group comparison (i.e., ACEIs vs. ARBs vs. quinapril vs. trandolapril) and (P ≤ 0.0007) for pairwise comparison (i.e., ACEIs vs. quinapril, ACEIs vs. trandolapril, ARBs vs. quinapril, or ARBs vs. trandolapril). This study suggests that specific members of the ACEI antihypertensive class (quinapril and trandolapril) have a significantly higher cluster of pulmonary ADEs.

Extinction of chromosomes due to specialization is a universal occurrence

The human X and Y chromosomes evolved from a pair of autosomes approximately 180 million years ago. Despite their shared evolutionary origin, extensive genetic decay has resulted in the human Y chromosome losing 97% of its ancestral genes while gene content and order remain highly conserved on the X chromosome. Five 'stratification' events, most likely inversions, reduced the Y chromosome's ability to recombine with the X chromosome across the majority of its length and subjected its genes to the erosive forces associated with reduced recombination. The remaining functional genes are ubiquitously expressed, functionally coherent, dosage-sensitive genes, or have evolved male-specific functionality. It is unknown, however, whether functional specialization is a degenerative phenomenon unique to sex chromosomes, or if it conveys a potential selective advantage aside from sexual antagonism. We examined the evolution of mammalian orthologs to determine if the selective forces that led to the degeneration of the Y chromosome are unique in the genome. The results of our study suggest these forces are not exclusive to the Y chromosome, and chromosomal degeneration may have occurred throughout our evolutionary history. The reduction of recombination could additionally result in rapid fixation through isolation of specialized functions resulting in a cost-benefit relationship during times of intense selective pressure.

Novel Data Sharing Agreement to Accelerate Big Data Translational Research Projects in the One Health Sphere

When conducting translational research, the ability to share data generated by researchers and clinicians working with for-profit companies is essential, particularly in cases that involve "one health" data (i.e., data that could come from human, animal, or environmental sources). The 1DATA Project, a collaboration between Kansas State University and the University of Missouri, has examined and overcome some of the barriers to sharing this information for "big data" projects. This article discusses some of the obstacles we encountered, and the ways those obstacles can be surmounted via a novel form of Master Sharing Agreement. Developed in collaboration with industry partners, it is presented here as a template for expediting future one health work.

Identification of Novel Regulatory Genes in APAP Induced Hepatocyte Toxicity by a Genome-Wide CRISPR-Cas9 Screen

Acetaminophen (APAP) is a commonly used analgesic responsible for more than half of acute liver failure cases. Identification of previously unknown genetic risk factors would provide mechanistic insights and novel therapeutic targets for APAP-induced liver injury. This study used a genome-wide CRISPR-Cas9 screen to evaluate genes that are protective against, or cause susceptibility to, APAP-induced liver injury. HuH7 human hepatocellular carcinoma cells containing CRISPR-Cas9 gene knockouts were treated with 15 mM APAP for 30 minutes to 4 days. A gene expression profile was developed based on the 1) top screening hits, 2) overlap of expression data from APAP overdose studies, and 3) predicted affected biological pathways. We further demonstrated the implementation of intermediate time points for the identification of early and late response genes. This study illustrated the power of a genome-wide CRISPR-Cas9 screen to systematically identify novel genes involved in APAP-induced hepatotoxicity and to provide potential targets to develop novel therapeutic modalities.

Co-option of bacteriophage lysozyme genes by bivalve genomes

Eukaryotes have occasionally acquired genetic material through horizontal gene transfer (HGT). However, little is known about the evolutionary and functional significance of such acquisitions. Lysozymes are ubiquitous enzymes that degrade bacterial cell walls. Here, we provide evidence that two subclasses of bivalves (Heterodonta and Palaeoheterodonta) acquired a lysozyme gene via HGT, building on earlier findings. Phylogenetic analyses place the bivalve lysozyme genes within the clade of bacteriophage lysozyme genes, indicating that the bivalves acquired the phage-type lysozyme genes from bacteriophages, either directly or through intermediate hosts. These bivalve lysozyme genes underwent dramatic structural changes after their co-option, including intron gain and fusion with other genes. Moreover, evidence suggests that recurrent gene duplication occurred in the bivalve lysozyme genes. Finally, we show the co-opted lysozymes exhibit a capacity for antibacterial action, potentially augmenting the immune function of related bivalves. This represents an intriguing evolutionary strategy in the eukaryote–microbe arms race, in which the genetic materials of bacteriophages are co-opted by eukaryotes, and then used by eukaryotes to combat bacteria, using a shared weapon against a common enemy.

Genome-Wide Convergence during Evolution of Mangroves from Woody Plants

When living organisms independently invade a new environment, the evolution of similar phenotypic traits is often observed. An interesting but contentious issue is whether the underlying molecular biology also converges in the new habitat. Independent invasions of tropical intertidal zones by woody plants, collectively referred to as mangrove trees, represent some dramatic examples. The high salinity, hypoxia, and other stressors in the new habitat might have affected both genomic features and protein structures. Here, we developed a new method for detecting convergence at conservative Sites (CCS) and applied it to the genomic sequences of mangroves. In simulations, the CCS method drastically reduces random convergence at rapidly evolving sites as well as falsely inferred convergence caused by the misinferences of the ancestral character. In mangrove genomes, we estimated ∼400 genes that have experienced convergence over the background level of convergence in the nonmangrove relatives. The convergent genes are enriched in pathways related to stress response and embryo development, which could be important for mangroves' adaptation to the new habitat.

Identification of C3b-Binding Small-Molecule Complement Inhibitors Using Cheminformatics

The complement system is an elegantly regulated biochemical cascade formed by the collective molecular recognition properties and proteolytic activities of more than two dozen membrane-bound or serum proteins. Complement plays diverse roles in human physiology, such as acting as a sentry against invading microorganisms, priming of the adaptive immune response, and removal of immune complexes. However, dysregulation of complement can serve as a trigger for a wide range of human diseases, which include autoimmune, inflammatory, and degenerative conditions. Despite several potential advantages of modulating complement with small-molecule inhibitors, small-molecule drugs are highly underrepresented in the current complement-directed therapeutics pipeline. In this study, we have employed a cheminformatics drug discovery approach based on the extensive structural and functional knowledge available for the central proteolytic fragment of the cascade, C3b. Using parallel in silico screening methodologies, we identified 45 small molecules that putatively bind C3b near ligand-guided functional hot spots. Surface plasmon resonance experiments resulted in the validation of seven dose-dependent C3b-binding compounds. Competition-based biochemical assays demonstrated the ability of several C3b-binding compounds to interfere with binding of the original C3b ligand that guided their discovery. In vitro assays of complement function identified a single complement inhibitory compound, termed cmp-5, and mechanistic studies of the cmp-5 inhibitory mode revealed it acts at the level of C5 activation. This study has led to the identification of a promising new class of C3b-binding small-molecule complement inhibitors and, to our knowledge, provides the first demonstration of cheminformatics-based, complement-directed drug discovery.

A One Health overview, facilitating advances in comparative medicine and translational research

A1 One health advances and successes in comparative medicine and translational research

Cheryl Stroud

A2 Dendritic cell-targeted gorilla adenoviral vector for cancer vaccination for canine melanoma

Igor Dmitriev, Elena Kashentseva, Jeffrey N. Bryan, David T. Curiel

A3 Viroimmunotherapy for malignant melanoma in the companion dog model

Jeffrey N. Bryan, David Curiel, Igor Dmitriev, Elena Kashentseva, Hans Rindt, Carol Reinero, Carolyn J. Henry

A4 Of mice and men (and dogs!): development of a commercially licensed xenogeneic DNA vaccine for companion animals with malignant melanoma

Philip J. Bergman

A5 Successful immunotherapy with a recombinant HER2-expressing Listeria monocytogenes in dogs with spontaneous osteosarcoma paves the way for advances in pediatric osteosarcoma

Nicola J. Mason, Josephine S. Gnanandarajah, Julie B. Engiles, Falon Gray, Danielle Laughlin, Anita Gaurnier-Hausser, Anu Wallecha, Margie Huebner, Yvonne Paterson

A6 Human clinical development of ADXS-HER2

Daniel O’Connor

A7 Leveraging use of data for both human and veterinary benefit

Laura S. Treml

A8 Biologic replacement of the knee: innovations and early clinical results

James P. Stannard

A9 Mizzou BioJoint Center: a translational success story

James L. Cook

A10 University and industry translational partnership: from the lab to commercialization

Marc Jacobs

A11 Beyond docking: an evolutionarily guided OneHealth approach to drug discovery

Gerald J. Wyckoff, Lee Likins, Ubadah Sabbagh, Andrew Skaff

A12 Challenges and opportunities for data applications in animal health: from precision medicine to precision husbandry

Amado S. Guloy

A13 A cloud-based programmable platform for health

Harlen D. Hays

A14 Comparative oncology: One Health in action

Amy K. LeBlanc

A15 Companion animal diseases bridge the translational gap for human neurodegenerative disease

Joan R. Coates, Martin L. Katz, Leslie A. Lyons, Gayle C. Johnson, Gary S. Johnson, Dennis P. O’Brien

A16 Duchenne muscular dystrophy gene therapy

Dongsheng Duan

A17 Polycystic kidney disease: cellular mechanisms to emerging therapies

James P. Calvet

A18 The domestic cat as a large animal model for polycystic kidney disease

Leslie A. Lyons, Barbara Gandolfi

A19 The support of basic and clinical research by the Polycystic Kidney Disease Foundation

David A. Baron

A20 Using naturally occurring large animal models of human disease to enable clinical translation: treatment of arthritis using autologous stromal vascular fraction in dogs

Mark L. Weiss

A21 Regulatory requirements regarding clinical use of human cells, tissues, and tissue-based products

Debra A. Webster

A22 Regenerative medicine approaches to Type 1 diabetes treatment

Francis N. Karanu

A23 The zoobiquity of canine diabetes mellitus, man’s best friend is a friend indeed-islet transplantation

Edward J. Robb

A24 One Medicine: a development model for cellular therapy of diabetes

Robert J. Harman

Inhibition of bacterial mevalonate diphosphate decarboxylase by eriochrome compounds

Mevalonate diphosphate decarboxylase (MDD; EC 4.1.1.33) catalyzes the irreversible decarboxylation of mevalonate diphosphate in the mevalonate pathway to form isopentenyl diphosphate, which is a precursor in the biosynthesis of many essential polyisoprenoid natural products, including sterols. In low G/C Gram-positive bacteria, which utilize the mevalonate pathway, MDD is required for cell viability and thus is a potential target for development of antibiotic drugs. To identify potential inhibitors of the enzyme, the National Cancer Institute's Mechanistic Diversity Set library of compounds was screened for inhibitors of Staphylococcus epidermidis MDD. From this screen, the compound Eriochrome Black A (EBA), an azo dye, was found to inhibit the enzyme with an IC50 value<5μM. Molecular docking of EBA into a crystal structure of S. epidermidis MDD suggested binding at the active site. EBA, along with the related Eriochrome B and T compounds, was evaluated for its ability to not only inhibit enzymatic activity but to inhibit bacterial growth as well. These compounds exhibited competitive inhibition towards the substrate mevalonate diphosphate, with Ki values ranging from 0.6 to 2.7μM. Non-competitive inhibition was observed versus ATP indicating binding of the inhibitor in the mevalonate diphosphate binding site, consistent with molecular docking predictions. Fluorescence quenching analyses also supported active site binding of EBA. These eriochrome compounds are effective at inhibiting S. epidermidis cell growth on both solid media and in liquid culture (MIC50 from 31 to 350μM) raising the possibility that they could be developed into antibiotic leads targeting pathogenic low-G/C Gram-positive cocci.

ChemVassa: A New Method for Identifying Small Molecule Hits in Drug Discovery

ChemVassa, a new chemical structure search technology, was developed to allow rapid in silico screening of compounds for hit and hit-to-lead identification in drug development. It functions by using a novel type of molecular descriptor that examines, in part, the structure of the small molecule undergoing analysis, yielding its “information signature.” This descriptor takes into account the atoms, bonds, and their positions in 3-dimensional space.

For the present study, a database of ChemVassa molecular descriptors was generated for nearly 16 million compounds (from the ZINC database and other compound sources), then an algorithm was developed that allows rapid similarity searching of the database using a query molecular descriptor (e.g., the signature of atorvastatin, below). A scoring metric then allowed ranking of the search results.

We used these tools to search a subset of drug-like molecules using the signature of a commercially successful statin, atorvastatin (Lipitor™). The search identified ten novel compounds, two of which have been demonstrated to interact with HMG-CoA reductase, the macromolecular target of atorvastatin. In particular, one compound discussed in the results section tested successfully with an IC50 of less than 100uM and a completely novel structure relative to known inhibitors. Interactions were validated using computational molecular docking and an Hmg-CoA reductase activity assay. The rapidity and low cost of the methodology, and the novel structure of the interactors, suggests this is a highly favorable new method for hit generation.

Evolutionary history and genome organization of DUF1220 protein domains

DUF1220 protein domains exhibit the most extreme human lineage-specific (HLS) copy number increase of any protein coding region in the human genome and have recently been linked to evolutionary and pathological changes in brain size (e.g., 1q21-associated microcephaly). These findings lend support to the view that DUF1220 domain dosage is a key factor in the determination of primate (and human) brain size. Here we analyze 41 animal genomes and present the most complete account to date of the evolutionary history and genome organization of DUF1220 domains and the gene family that encodes them (NBPF). Included among the novel features identified by this analysis is a DUF1220 domain precursor in nonmammalian vertebrates, a unique predicted promoter common to all mammalian NBPF genes, six distinct clades into which DUF1220 sequences can be subdivided, and a previously unknown member of the NBPF gene family (NBPF25). Most importantly, we show that the exceptional HLS increase in DUF1220 copy number (from 102 in our last common ancestor with chimp to 272 in human; an average HLS increase of ~28 copies every million years since the Homo/Pan split) was driven by intragenic domain hyperamplification. This increase primarily involved a 4.7 kb, tandemly repeated three DUF1220 domain unit we have named the HLS DUF1220 triplet, a motif that is a likely candidate to underlie key properties unique to the Homo sapiens brain. Interestingly, all copies of the HLS DUF1220 triplet lie within a human-specific pericentric inversion that also includes the 1q12 C-band, a polymorphic heterochromatin expansion that is unique to the human genome. Both cytogenetic features likely played key roles in the rapid HLS DUF1220 triplet hyperamplification, which is among the most striking genomic changes specific to the human lineage.

The structures of coiled-coil domains from type III secretion system translocators reveal homology to pore-forming toxins

Many pathogenic Gram-negative bacteria utilize type III secretion systems (T3SSs) to alter the normal functions of target cells. Shigella flexneri uses its T3SS to invade human intestinal cells to cause bacillary dysentery (shigellosis) that is responsible for over one million deaths per year. The Shigella type III secretion apparatus is composed of a basal body spanning both bacterial membranes and an exposed oligomeric needle. Host altering effectors are secreted through this energized unidirectional conduit to promote bacterial invasion. The active needle tip complex of S. flexneri is composed of a tip protein, IpaD, and two pore-forming translocators, IpaB and IpaC. While the atomic structure of IpaD has been elucidated and studied, structural data on the hydrophobic translocators from the T3SS family remain elusive. We present here the crystal structures of a protease-stable fragment identified within the N-terminal regions of IpaB from S. flexneri and SipB from Salmonella enterica serovar Typhimurium determined at 2.1 Å and 2.8 Å limiting resolution, respectively. These newly identified domains are composed of extended-length (114 Å in IpaB and 71 Å in SipB) coiled-coil motifs that display a high degree of structural homology to one another despite the fact that they share only 21% sequence identity. Further structural comparisons also reveal substantial similarity to the coiled-coil regions of pore-forming proteins from other Gram-negative pathogens, notably, colicin Ia. This suggests that these mechanistically separate and functionally distinct membrane-targeting proteins may have diverged from a common ancestor during the course of pathogen-specific evolutionary events.

Phosphatidylinositol transfer proteins: sequence motifs in structural and evolutionary analyses

Phosphatidylinositol transfer proteins (PITP) are a family of monomeric proteins that bind and transfer phosphatidylinositol and phosphatidylcholine between membrane compartments. They are required for production of inositol and diacylglycerol second messengers, and are found in most metazoan organisms. While PITPs are known to carry out crucial cell-signaling roles in many organisms, the structure, function and evolution of the majority of family members remains unexplored; primarily because the ubiquity and diversity of the family thwarts traditional methods of global alignment. To surmount this obstacle, we instead took a novel approach, using MEME and a parsimony-based analysis to create a cladogram of conserved sequence motifs in 56 PITP family proteins from 26 species. In keeping with previous functional annotations, three clades were supported within our evolutionary analysis; two classes of soluble proteins and a class of membrane-associated proteins. By, focusing on conserved regions, the analysis allowed for in depth queries regarding possible functional roles of PITP proteins in both intra- and extra- cellular signaling.

CrossSearch, a user-friendly search engine for detecting chemically cross-linked peptides in conjugated proteins

Chemical cross-linking and high resolution MS have been integrated successfully to capture protein interactions and provide low resolution structural data for proteins that are refractive to analyses by NMR or crystallography. Despite the versatility of these combined techniques, the array of products that is generated from the cross-linking and proteolytic digestion of proteins is immense and generally requires the use of labeling strategies and/or data base search algorithms to distinguish actual cross-linked peptides from the many side products of cross-linking. Most strategies reported to date have focused on the analysis of small cross-linked protein complexes (<60 kDa) because the number of potential forms of covalently modified peptides increases dramatically with the number of peptides generated from the digestion of such complexes. We report herein the development of a user-friendly search engine, CrossSearch, that provides the foundation for an overarching strategy to detect cross-linked peptides from the digests of large (>or=170-kDa) cross-linked proteins, i.e. conjugates. Our strategy combines the use of a low excess of cross-linker, data base searching, and Fourier transform ion cyclotron resonance MS to experimentally minimize and theoretically cull the side products of cross-linking. Using this strategy, the (alpha beta gamma delta)(4) phosphorylase kinase model complex was cross-linked to form with high specificity a 170-kDa betagamma conjugate in which we identified residues involved in the intramolecular cross-linking of the 125-kDa beta subunit between its regulatory N terminus and its C terminus. This finding provides an explanation for previously published homodimeric two-hybrid interactions of the beta subunit and suggests a dynamic structural role for the regulatory N terminus of that subunit. The results offer proof of concept for the CrossSearch strategy for analyzing conjugates and are the first to reveal a tertiary structural element of either homologous alpha or beta regulatory subunit of phosphorylase kinase.

Virtual polymorphism: finding divergent peptide matches in mass spectrometry data

The prevailing method of analyzing tandem-MS data for protein identification involves the comparison of peptide molecular weight and fragmentation data to theoretically predicted values, based on known protein sequences in databases. This is generally effective since proteins from most species under study are in the database or have sufficient homology to allow significant matching. We have encountered difficulties identifying proteins from fungal species Alternaria alternata due to significant interspecies protein sequence differences (divergence) and its absence from the database. This common household mold causes asthma and allergy problems, but the genome has not been sequenced. De novo sequencing and error-tolerant methods can facilitate protein identifications in divergent, unsequenced species. But these standard methods can be laborious and only allow single amino acid substitution, respectively. We have developed an alternative approach focusing on database engineering, predicting biologically rational polymorphism using statistically weighted amino acid substitution information held in BLOSUM62. Like other second pass methods, it is based on the initially identified protein. However, this approach allows more control over sequences to be considered, including multiple changes per peptide. The results show considerable improvement for routine protein identification and the potential for rescuing otherwise unconvincing identifications in unusually divergent species.

Evidence for the location of the allosteric activation switch in the multisubunit phosphorylase kinase complex from mass spectrometric identification of chemically crosslinked peptides

Phosphorylase kinase (PhK), an (alphabetagammadelta)(4) complex, regulates glycogenolysis. Its activity, catalyzed by the gamma subunit, is tightly controlled by phosphorylation and activators acting through allosteric sites on its regulatory alpha, beta and delta subunits. Activation by phosphorylation is predominantly mediated by the regulatory beta subunit, which undergoes a conformational change that is structurally linked with the gamma subunit and that is characterized by the ability of a short chemical crosslinker to form beta-beta dimers. To determine potential regions of interaction of the beta and gamma subunits, we have used chemical crosslinking and two-hybrid screening. The beta and gamma subunits were crosslinked to each other in phosphorylated PhK, and crosslinked peptides from digests were identified by Fourier transform mass spectrometry, beginning with a search engine developed "in house" that generates a hypothetical list of crosslinked peptides. A conjugate between beta and gamma that was verified by MS/MS corresponded to crosslinking between K303 in the C-terminal regulatory domain of gamma (gammaCRD) and R18 in the N-terminal regulatory region of beta (beta1-31), which contains the phosphorylatable serines 11 and 26. A synthetic peptide corresponding to residues 1-22 of beta inhibited the crosslinking between beta and gamma, and was itself crosslinked to K303 of gamma. In two-hybrid screening, the beta1-31 region controlled beta subunit self-interactions, in that they were favored by truncation of this region or by mutation of the phosphorylatable serines 11 and 26, thus providing structural evidence for a phosphorylation-dependent subunit communication network in the PhK complex involving at least these two regulatory regions of the beta and gamma subunits. The sum of our results considered together with previous findings implicates the gammaCRD as being an allosteric activation switch in PhK that interacts with all three of the enzyme's regulatory subunits and is proximal to the active site cleft.

Human lineage-specific amplification, selection, and neuronal expression of DUF1220 domains

Extreme gene duplication is a major source of evolutionary novelty. A genome-wide survey of gene copy number variation among human and great ape lineages revealed that the most striking human lineage-specific amplification was due to an unknown gene, MGC8902, which is predicted to encode multiple copies of a protein domain of unknown function (DUF1220). Sequences encoding these domains are virtually all primate-specific, show signs of positive selection, and are increasingly amplified generally as a function of a species' evolutionary proximity to humans, where the greatest number of copies (212) is found. DUF1220 domains are highly expressed in brain regions associated with higher cognitive function, and in brain show neuron-specific expression preferentially in cell bodies and dendrites.

SPEED: a molecular-evolution-based database of mammalian orthologous groups

MOTIVATION

The abundance of nucleotide sequence information available has expanded horizons of inquiry for molecular evolution; however, the full potential of whole-genome analysis has not been realized because of inadequate tools. Here, we present one of the first toolkits to aid multidisciplinary high-throughput analysis.

SUMMARY

SPEED was created to integrate molecular evolutionary data with existing genetic resources and provide a straightforward user interface to 17,352 orthologous gene groups, containing representatives from eight mammalian species and an avian outgroup.

AVAILABILITY

See http://bioinfobase.umkc.edu/speed/ for access.

A highly unexpected strong correlation between fixation probability of nonsynonymous mutations and mutation rate

Under prevailing theories, the nonsynonymous-to-synonymous substitution ratio (i.e. K(a)/K(s)), which measures the fixation probability of nonsynonymous mutations, is correlated with the strength of selection. In this article, we report that K(a)/K(s) is also strongly correlated with the mutation rate as measured by K(s), and that this correlation appears to have a similar magnitude as the correlation between K(a)/K(s) and selective strength. This finding cannot be reconciled with current theories. It suggests that we should re-evaluate the current paradigms of coding-sequence evolution, and that the wide use of K(a)/K(s) as a measure of selective strength needs reassessment.

FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression

BACKGROUND

While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes.

RESULTS

We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P < 0.001) enrichment in genes associated with amine metabolism.

CONCLUSION

The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.

Accelerated Evolution of Nervous System Genes in the Origin of Homo sapiens

Human evolution is characterized by a dramatic increase in brain size and complexity. To probe its genetic basis, we examined the evolution of genes involved in diverse aspects of nervous system biology. We found that these genes display significantly higher rates of protein evolution in primates than in rodents. Importantly, this trend is most pronounced for the subset of genes implicated in nervous system development. Moreover, within primates, the acceleration of protein evolution is most prominent in the lineage leading from ancestral primates to humans. Thus, the remarkable phenotypic evolution of the human nervous system has a salient molecular correlate, i.e., accelerated evolution of the underlying genes, particularly those linked to nervous system development. In addition to uncovering broad evolutionary trends, our study also identified many candidate genes--most of which are implicated in regulating brain size and behavior--that might have played important roles in the evolution of the human brain.

Rate of molecular evolution of the seminal protein gene SEMG2 correlates with levels of female promiscuity

Postcopulatory sperm competition is a key aspect of sexual selection and is believed to drive the rapid evolution of both reproductive physiology and reproduction-related genes. It is well-established that mating behavior determines the intensity of sperm competition, with polyandry (i.e., female promiscuity) leading to fiercer sperm competition than monandry. Studies in mammals, particularly primates, showed that, owing to greater sperm competition, polyandrous taxa generally have physiological traits that make them better adapted for fertilization than monandrous species, including bigger testes, larger seminal vesicles, higher sperm counts, richer mitochondrial loading in sperm and more prominent semen coagulation. Here, we show that the degree of polyandry can also impact the dynamics of molecular evolution. Specifically, we show that the evolution of SEMG2, the gene encoding semenogelin II, a main structural component of semen coagulum, is accelerated in polyandrous primates relative to monandrous primates. Our study showcases the intimate relationship between sexual selection and the molecular evolution of reproductive genes.

A Universal Evolutionary Index for Amino Acid Changes

Different nonsynonymous changes may be under different selective pressure during evolution. Of the 190 possible interchanges among the 20 amino acids, only 75 can be attained by a single-base substitution. An evolutionary index (EI) can be empirically computed for each of the 75 elementary changes as the likelihood of substitutions, relative to that of synonymous changes. We used 280, 1,306, 2,488, and 309 orthologous genes from primates (human versus Old World monkey), rodents (mouse versus rat), yeast (S. cerevisiae versus S. paradoxus), and Drosophila (D. melanogaster versus D. simulans), respectively, to estimate the EIs. In each data set, EI varies more than 10-fold, and the correlation coefficients of EIs from the pairwise comparisons are high (e.g., r = 0.91 between rodent and yeast). The high correlations suggest that the amino acid properties are strong determinants of protein evolution, irrespective of the identities of the proteins or the taxa of interest. However, these properties are not well captured in conventional measures of amino acid exchangeability. We, therefore, propose a universal index of exchange (U): for any large data set, its EI can be expressed as U*R, where R is the average Ka/Ks for that data set. The codon-based, empirically determined EI (i.e., U*R) makes much better predictions on protein evolution than do previous methods.

Genic mutation rates in mammals: local similarity, chromosomal heterogeneity, and X-versus-autosome disparity

The reduction of mutation rates on the mammalian X chromosome relative to autosomes is most often explained in the literature as evidence of male-driven evolution. This hypothesis attributes lowered mutation rates on the X chromosome to the fact that this chromosome spends less time in the germline of males than in the germline of females. In contrast to this majority view, two articles argued that the patterns of mutation rates across chromosomes are inconsistent with male-driven evolution. One article reported a 40% reduction in synonymous substitution rates (Ks) for X-linked genes relative to autosomes in the mouse-rat lineage. The authors argued that this reduction is too dramatic to be explained by male-driven evolution and concluded that selection has systematically reduced mutation rate on the X chromosome to a level optimal for this male-hemizygous chromosome. More recently, a second article found that chromosomal mutation rates in both the human-mouse and mouse-rat lineages were so heterogeneous that the X chromosome was not an outlier. Here again, the authors argued that this is at odds with male-driven evolution and suggested that selection has modulated chromosomal mutation rates to locally optimal levels, thus extending the argument of the first mentioned article to include autosomes. Here, we reexamine these conclusions using mouse-rat and human-mouse coding-region data. We find a more modest reduction of Ks on the X chromosome, but our results contradict the finding that the X chromosome is not distinct from autosomes. Multiple statistical tests show that Ks rates on the X chromosome differ systematically from the autosomes in both lineages. We conclude that the moderate reduction of mutation rate on the X chromosome of both lineages is consistent with male-driven evolution; however, the large variance in mutation rates across chromosomes suggests that mutation rates are affected by additional factors besides male-driven evolution. Investigation of mutation rates by synteny reveals that synteny blocks, rather than entire chromosomes, might represent the unit of mutation rate variation.

Testing the neutral theory of molecular evolution with genomic data from Drosophila

Although positive selection has been detected in many genes, its overall contribution to protein evolution is debatable. If the bulk of molecular evolution is neutral, then the ratio of amino-acid (A) to synonymous (S) polymorphism should, on average, equal that of divergence. A comparison of the A/S ratio of polymorphism in Drosophila melanogaster with that of divergence from Drosophila simulans shows that the A/S ratio of divergence is twice as high---a difference that is often attributed to positive selection. But an increase in selective constraint owing to an increase in effective population size could also explain this observation, and, if so, all genes should be affected similarly. Here we show that the difference between polymorphism and divergence is limited to only a fraction of the genes, which are also evolving more rapidly, and this implies that positive selection is responsible. A higher A/S ratio of divergence than of polymorphism is also observed in other species, which suggests a rate of adaptive evolution that is far higher than permitted by the neutral theory of molecular evolution.

Positive and negative selection on the human genome

The distinction between deleterious, neutral, and adaptive mutations is a fundamental problem in the study of molecular evolution. Two significant quantities are the fraction of DNA variation in natural populations that is deleterious and destined to be eliminated and the fraction of fixed differences between species driven by positive Darwinian selection. We estimate these quantities using the large number of human genes for which there are polymorphism and divergence data. The fraction of amino acid mutations that is neutral is estimated to be 0.20 from the ratio of common amino acid (A) to synonymous (S) single nucleotide polymorphisms (SNPs) at frequencies of > or =15%. Among the 80% of amino acid mutations that are deleterious at least 20% of them are only slightly deleterious and often attain frequencies of 1-10%. We estimate that these slightly deleterious mutations comprise at least 3% of amino acid SNPs in the average individual or at least 300 per diploid genome. This estimate is not sensitive to human population history. The A/S ratio of fixed differences is greater than that of common SNPs and suggests that a large fraction of protein divergence is adaptive and driven by positive Darwinian selection.

Rapid evolution of male reproductive genes in the descent of man

A diverse body of morphological and genetic evidence has suggested that traits pertaining to male reproduction may have evolved much more rapidly than other types of character. Recently, DNA sequence comparisons have also shown a very high level of divergence in male reproductive proteins between closely related Drosophila species, among marine invertebrates and between mouse and rat. Here we show that rapid evolution of male reproductive genes is observable in primates and is quite notable in the lineages to human and chimpanzee. Nevertheless, rapid evolution by itself is not necessarily an indication of positive darwinian selection; relaxation of negative selection is often equally compatible with the DNA sequence data. By taking three statistical approaches, we show that positive darwinian selection is often the driving force behind this rapid evolution. These results open up opportunities to test the hypothesis that sexual selection plays some role in the molecular evolution of higher primates.