An exact algorithm to find a maximum weight clique in a weighted undirected graph.

We introduce a new algorithm MaxCliqueWeight for identifying a maximum weight clique in a weighted graph, and its variant MaxCliqueDynWeight with dynamically varying bounds. This algorithm uses an efficient branch-and-bound approach with a new weighted graph coloring algorithm that efficiently determines upper weight bounds for a maximum weighted clique in a graph. We evaluate our algorithm on random weighted graphs with node counts up to 10,000 and on standard DIMACS benchmark graphs used in a variety of research areas. Our findings reveal a remarkable improvement in computational speed when compared to existing algorithms, particularly evident in the case of high-density random graphs and DIMACS graphs, where our newly developed algorithm outperforms existing alternatives by several orders of magnitude. The newly developed algorithm and its variant are freely available to the broader research community at http://insilab.org/maxcliqueweight , paving the way for transformative applications in various research areas, including drug discovery.

Whole genome sequencing of mouse lines divergently selected for fatness (FLI) and leanness (FHI) revealed several genetic variants as candidates for novel obesity genes.

BACKGROUND: Analysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts. OBJECTIVE: To analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations. METHODS: Genetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database. RESULTS: WGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536. CONCLUSION: WGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.

Ultra-high resolution X-ray structure of orthorhombic bovine pancreatic Ribonuclease A at 100K.

The crystal structure of orthorhombic Bovine Pancreatic Ribonuclease A has been determined to 0.85 Å resolution using low temperature, 100 K, synchrotron X-ray data collected at 16000 keV (λ = 0.77 Å). This is the first ultra-high-resolution structure of a native form of Ribonuclease A to be reported. Refinement carried out with anisotropic displacement parameters, stereochemical restraints, inclusion of H atoms in calculated positions, five [Formula: see text] moieties, eleven ethanol molecules and 293 water molecules, converged with final R values of R1(Free) = 0.129 (4279 reflections) and R1 = 0.112 (85,346 reflections). The refined structure was deposited in the Protein Data Bank as structure 7p4r. Conserved waters, using four high resolution structures, have been investigated. Cluster analysis identified clusters of water molecules that are associated with the active site of Bovine Ribonuclease A. Particular attention has been paid to making detailed comparisons between the present structure and other high quality Bovine Pancreatic Ribonuclease A X-ray crystal structures with special reference to the deposited classic monoclinic structure 3RN3 Howlin et al. (Acta Crystallogr A 45:851-861, 1989). Detailed studies of various aspects of hydrogen bonding and conformation have been carried out with particular reference to active site residues Lys-1, Lys-7, Gln-11, His-12, Lys-41, Asn-44, Thr-45, Lys-66, His-119 and Ser-123. For the two histidine residues in the active site the initial electron density map gives a clear confirmation that the position of His-12 is very similar in the orthorhombic structure to that in 3RN3. In 3RN3 His-119 exhibited poor electron density which was modelled and refined as two distinct sites, A (65%) and B (35%) but with respect to His-119 in the present ultra-high resolution orthorhombic structure there is clear electron density which was modelled and refined as a single conformation distinct from either conformation A or B in 3RN3. Other points of interest include Serine-32 which is disordered at the end of the sidechain in the present orthorhombic form but has been modelled as a single form in 3RN3. Lysine-66: there is density indicating a possible conformation for this residue. However, the density is relatively weak, and the conformation is unclear. Three types of amino acid representation in the ultra-high resolution electron density are examined: (i) sharp with very clearly resolved features, for example Lys-37; (ii) well resolved but clearly divided into two conformations which are well behaved in the refinement, both having high quality geometry, for example Tyr-76; (iii) poor density and difficult or impossible to model, an example is Lys-31 for which density is missing except for Cß. The side chains of Gln-11, His-12, Lys-41, Thr-45 and His-119 are generally recognised as being closely involved in the enzyme activity. It has also been suggested that Lys-7, Asp-44, Lys-66, Phe-120, Asp-121 and Ser-123 may also have possible roles in this mechanism. A molecular dynamics study on both structures has investigated the conformations of His-119 which was modelled as two conformations in 3RN3 but is observed to have a single clearly defined conformation in the present orthorhombic structure. MD has also been used to investigate Lys-31, Lys-41 and Ser32. The form of the Ribonuclease A enzyme used in both the present study and in 3RN3 (Howlin et al. in Acta Crystallogr A 45:851-861, 1989) includes a sulphate anion which occupies approximately the same location as the [Formula: see text] phosphate group in protein nucleotide complexes (Borkakoti et al. in J Mol Biol 169:743-755, 1983). The present structure contains 5 [Formula: see text] groups SO41151-SO41155 two of which, SO41152 and SO41153 are disordered, SO41152 being in the active site, and 11 EtOH molecules, EOH A 201-EOH A 211 all of which have good geometry. H atoms were built into the EtOH molecules geometrically. Illustrations of these features in the present structure are included here. The sulphates are presumably present in the material purchased for use in the present study. 293 water molecules are included in the present structure compared to 134 in 3RN3 (Howlin et al. in Acta Crystallogr A 45:851-861, 1989).

Genome-wide screening for genetic variants in polyadenylation signal (PAS) sites in mouse selection lines for fatness and leanness.

Alternative polyadenylation (APA) determines mRNA stability, localisation, translation and protein function. Several diseases, including obesity, have been linked to APA. Studies have shown that single nucleotide polymorphisms in polyadenylation signals (PAS-SNPs) can influence APA and affect phenotype and disease susceptibility. However, these studies focussed on associations between single PAS-SNP alleles with very large effects and phenotype. Therefore, we performed a genome-wide screening for PAS-SNPs in the polygenic mouse selection lines for fatness and leanness by whole-genome sequencing. The genetic variants identified in the two lines were overlapped with locations of PAS sites obtained from the PolyASite 2.0 database. Expression data for selected genes were extracted from the microarray expression experiment performed on multiple tissue samples. In total, 682 PAS-SNPs were identified within 583 genes involved in various biological processes, including transport, protein modifications and degradation, cell adhesion and immune response. Moreover, 63 of the 583 orthologous genes in human have been previously associated with human diseases, such as nervous system and physical disorders, and immune, endocrine, and metabolic diseases. In both lines, PAS-SNPs have also been identified in genes broadly involved in APA, such as Polr2c, Eif3e and Ints11. Five PAS-SNPs within 5 genes (Car, Col4a1, Itga7, Lat, Nmnat1) were prioritised as potential functional variants and could contribute to the phenotypic disparity between the two selection lines. The developed PAS-SNPs catalogue presents a key resource for planning functional studies to uncover the role of PAS-SNPs in APA, disease susceptibility and fat deposition.

Protein binding sites for drug design.

Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules-ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov.

A small bacteriophage protein determines the hierarchy over co-residential jumbo phage in Bacillus thuringiensis serovar israelensis.

Bacillus thuringiensis serovar israelensis is the most widely used biopesticide against insects, including vectors of animal and human diseases. Among several extrachromosomal elements, this endospore-forming entomopathogen harbors two bacteriophages: a linear DNA replicon named GIL01 that does not integrate into the chromosome during lysogeny and a circular-jumbo prophage known as pBtic235. Here, we show that GIL01 hinders the induction of cohabiting prophage pBtic235. The GIL01-encoded small protein, gp7, which interacts with the host LexA repressor, is a global transcription regulator and represses the induction of pBtic235 after DNA damage to presumably allow GIL01 to multiply first. In a complex with host LexA in stressed cells, gp7 down-regulates the expression of more than 250 host and pBtic235 genes, many of which are involved in the cellular functions of genome maintenance, cell-wall transport, and membrane and protein stability. We show that gp7 homologs that are found exclusively in bacteriophages act in a similar fashion to enhance LexA's binding to DNA, while likely also affecting host gene expression. Our results provide evidence that GIL01 influences both its host and its co-resident bacteriophage.

ProBiS-Fold Approach for Annotation of Human Structures from the AlphaFold Database with No Corresponding Structure in the PDB to Discover New Druggable Binding Sites.

ProBiS (Protein Binding Sites), a local structure-based comparison algorithm, is used in the new ProBiS-Fold web server to annotate human structures from the AlphaFold database without a corresponding structure in the Protein Data Bank (PDB) to discover new druggable binding sites. The ProBiS algorithm is used to compare each query protein structure predicted by the AlphaFold approach with the protein structures from the PDB to identify similarities between known binding sites found in the PDB and yet unknown binding sites in the AlphaFold database. Ligands bound in these identified similar PDB sites are then transferred to each query protein from the AlphaFold database, and binding sites are identified as ligand clusters on an AlphaFold protein. Small molecule binding sites are assigned druggability scores based on the similarity of their ligands to known drugs, allowing them to be ranked according to their perceived and actual potential for drug development. ProBiS-Fold provides interactive and downloadable binding sites for the entire human structural proteome, including more than 3000 new druggable binding sites that have no corresponding structure in the PDB, taking into account AlphaFold's model quality, to enable protein structure-function relationship studies and pharmaceutical drug discovery research. The web server is freely accessible to academic users at http://probis-fold.insilab.org.

A Set of Experimentally Validated Decoys for the Human CC Chemokine Receptor 7 (CCR7) Obtained by Virtual Screening.

We present a state-of-the-art virtual screening workflow aiming at the identification of novel CC chemokine receptor 7 (CCR7) antagonists. Although CCR7 is associated with a variety of human diseases, such as immunological disorders, inflammatory diseases, and cancer, this target is underexplored in drug discovery and there are no potent and selective CCR7 small molecule antagonists available today. Therefore, computer-aided ligand-based, structure-based, and joint virtual screening campaigns were performed. Hits from these virtual screenings were tested in a CCL19-induced calcium signaling assay. After careful evaluation, none of the in silico hits were confirmed to have an antagonistic effect on CCR7. Hence, we report here a valuable set of 287 inactive compounds that can be used as experimentally validated decoys.

Genetic variants of the hypoxia-inducible factor 3 alpha subunit (Hif3a) gene in the Fat and Lean mouse selection lines.

BACKGROUND: Adipose tissue hypoxia and members of the hypoxia-inducible factor alpha (HIFA) are involved in development of obesity. However, the mechanism and functions of HIF3A, one of three HIFA paralogs, in fat deposition have not been sufficiently studied. METHODS AND RESULTS: In the present study, we investigated whether Hif3a sequence variants are associated with divergent fat deposition in mouse selection lines for fatness and leanness. Sequencing and RFLP were used to analyse sequence variants within Hif3a. To identify candidate regulatory variants, we performed literature screening and used databases and bioinformatics tools like Ensembl, MethPrimer, TargetScanMouse, miRDB, PolyAsite, RISE, LncRRIsearch, RNAfold, PredictProtein, CAIcal, and switches.ELM Resource. There are 90 sequence variants in Hif3a between the two mouse lines. While most Fat line variants locate within intronic regions, Lean line variants are mainly in 3' UTR. We constructed a map of Hif3a potential regulatory regions and identified 39 regulatory variants by integrating data on constrained and regulatory elements, CpGs, and miRNAs and lncRNAs binding sites. Moreover, 3' UTR and two exonic variants may influence mRNA stability, translation rate and protein functionality. We propose as priority candidates for further functional studies a missense (rs37398126) and synonymous (rs37739792) variants, and intronic (rs47471302) variant that overlap conserved element in promoter region and predicted lncRNAs binding site. CONCLUSION: The results indicate a potential involvement of Hif3a in fat deposition. Additionally, approach used in the present study may serve as a general guideline for constructing an integrative gene map for prioritizing candidate gene variants with phenotypic effects.

ProBiS-Dock: A Hybrid Multitemplate Homology Flexible Docking Algorithm Enabled by Protein Binding Site Comparison.

The protein data bank (PDB) is a rich source of protein ligand structures, but ligands are not explicitly used in current docking algorithms. We have developed ProBiS-Dock, a docking algorithm complementary to the ProBiS-Dock Database (J. Chem. Inf. Model. 2021, 61, 4097-4107) that treats small molecules and proteins as fully flexible entities and allows conformational changes in both after ligand binding. A new scoring function is described that consists of a binding site-specific scoring function (ProBiS-Score) and a general statistical scoring function. ProBiS-Dock enables rapid docking of small molecules to proteins and has been successfully validated in silico against standard benchmarks. It enables rapid search for new active ligands by leveraging existing knowledge in the PDB. The potential of the software for drug development has been confirmed in vitro by the discovery of new inhibitors of human indoleamine 2,3-dioxygenase 1, an enzyme that is an attractive target for cancer therapy and catalyzes the first rate-determining step of l-tryptophan metabolism via the kynurenine pathway. The software is freely available to academic users at http://insilab.org/probisdock.

Molecular Dynamics Simulations Reveal Interactions of an IgG1 Antibody With Selected Fc Receptors.

In a survey of novel interactions between an IgG1 antibody and different Fcγ receptors (FcγR), molecular dynamics simulations were performed of interactions of monoclonal antibody involved complexes with FcγRs. Free energy simulations were also performed of isolated wild-type and substituted Fc regions bound to FcγRs with the aim of assessing their relative binding affinities. Two different free energy calculation methods, Molecular Mechanical/Generalized Born Molecular Volume (MM/GBMV) and Bennett Acceptance Ratio (BAR), were used to evaluate the known effector substitution G236A that is known to selectively increase antibody dependent cellular phagocytosis. The obtained results for the MM/GBMV binding affinity between different FcγRs are in good agreement with previous experiments, and those obtained using the BAR method for the complete antibody and the Fc-FcγR simulations show increased affinity across all FcγRs when binding to the substituted antibody. The FcγRIIa, a key determinant of antibody agonistic efficacy, shows a 10-fold increase in binding affinity, which is also consistent with the published experimental results. Novel interactions between the Fab region of the antibody and the FcγRs were discovered with this in silico approach, and provide insights into the antibody-FcγR binding mechanism and show promise for future improvements of therapeutic antibodies for preclinical studies of biological drugs.

ProBiS-Dock Database: A Web Server and Interactive Web Repository of Small Ligand-Protein Binding Sites for Drug Design.

We have developed a new system, ProBiS-Dock, which can be used to determine the different types of protein binding sites for small ligands. The binding sites identified this way are then used to construct a new binding site database, the ProBiS-Dock Database, that allows for the ranking of binding sites according to their utility for drug development. The newly constructed database currently has more than 1.4 million binding sites and offers the possibility to investigate potential drug targets originating from different biological species. The interactive ProBiS-Dock Database, a web server and repository that consists of all small-molecule ligand binding sites in all of the protein structures in the Protein Data Bank, is freely available at http://probis-dock-database.insilab.org. The ProBiS-Dock Database will be regularly updated to keep pace with the growth of the Protein Data Bank, and our anticipation is that it will be useful in drug discovery.

Mechanistic Insights into Side Effects of Troglitazone and Rosiglitazone Using a Novel Inverse Molecular Docking Protocol.

Thiazolidinediones form drugs that treat insulin resistance in type 2 diabetes mellitus. Troglitazone represents the first drug from this family, which was removed from use by the FDA due to its hepatotoxicity. As an alternative, rosiglitazone was developed, but it was under the careful watch of FDA for a long time due to suspicion, that it causes cardiovascular diseases, such as heart failure and stroke. We applied a novel inverse molecular docking protocol to discern the potential protein targets of both drugs. Troglitazone and rosiglitazone were docked into predicted binding sites of >67,000 protein structures from the Protein Data Bank and examined. Several new potential protein targets with successfully docked troglitazone and rosiglitazone were identified. The focus was devoted to human proteins so that existing or new potential side effects could be explained or proposed. Certain targets of troglitazone such as 3-oxo-5-beta-steroid 4-dehydrogenase, neutrophil collagenase, stromelysin-1, and VLCAD were pinpointed, which could explain its hepatoxicity, with additional ones indicating that its application could lead to the treatment/development of cancer. Results for rosiglitazone discerned its interaction with members of the matrix metalloproteinase family, which could lead to cancer and neurodegenerative disorders. The concerning cardiovascular side effects of rosiglitazone could also be explained. We firmly believe that our results deepen the mechanistic understanding of the side effects of both drugs, and potentially with further development and research maybe even help to minimize them. On the other hand, the novel inverse molecular docking protocol on the other hand carries the potential to develop into a standard tool to predict possible cross-interactions of drug candidates potentially leading to adverse side effects.

CaNDis: a web server for investigation of causal relationships between diseases, drugs and drug targets.

MOTIVATION: Causal biological interaction networks represent cellular regulatory pathways. Their fusion with other biological data enables insights into disease mechanisms and novel opportunities for drug discovery. RESULTS: We developed Causal Network of Diseases (CaNDis), a web server for the exploration of a human causal interaction network, which we expanded with data on diseases and FDA-approved drugs, on the basis of which we constructed a disease-disease network in which the links represent the similarity between diseases. We show how CaNDis can be used to identify candidate genes with known and novel roles in disease co-occurrence and drug-drug interactions. AVAILABILITYAND IMPLEMENTATION: CaNDis is freely available to academic users at http://candis.ijs.si and http://candis.insilab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Loop Grafting between Similar Local Environments for Fc-Silent Antibodies.

Reduction of the affinity of the fragment crystallizable (Fc) region with immune receptors by substitution of one or a few amino acids, known as Fc-silencing, is an established approach to reduce the immune effector functions of monoclonal antibody therapeutics. This approach to Fc-silencing, however, is problematic as it can lead to instability and immunogenicity of the developed antibodies. We evaluated loop grafting as a novel approach to Fc-silencing in which the Fc loops responsible for immune receptor binding were replaced by loops of up to 20 amino acids from similar local environments in other human and mouse antibodies. Molecular dynamics simulations of the designed variants of an Fc region in a complex with the immune receptor FcγIIIa confirmed that loop grafting potentially leads to a significant reduction in the binding of the antibody variants to the receptor, while retaining their stability. In comparison, standard variants with less than eight substituted amino acids showed possible instability and a lower degree of Fc-silencing due to the occurrence of compensatory interactions. The presented approach to Fc-silencing is general and could be used to modulate undesirable side effects of other antibody therapeutics without affecting their stability or increasing their immunogenicity.

ProBiS H2O MD Approach for Identification of Conserved Water Sites in Protein Structures for Drug Design.

The ProBiS H2O MD approach for identification of conserved waters and water sites of interest in macromolecular systems, which is becoming a typical step in a structure-based drug design or macromolecular study in general, is described. This work explores an extension of the ProBiS H2O approach introduced by Jukic et al. Indeed, water molecules are key players in the interaction mechanisms of macromolecules and small molecules and play structural roles. Our earlier developed approach, ProBiS H2O, is a simple and transparent workflow for conserved water detection. Here we have considered generalizing the idea by supplementing the experimental data with data derived from molecular dynamics to facilitate work on less known systems. Newly developed ProBiS H2O MD workflow uses trajectory data, extracts and identifies interesting water sites, and visualizes the results. ProBiS H2O MD can thus robustly process molecular dynamic trajectory snapshots, perform local superpositions, collect water location data, and perform density-based clustering to identify discrete sites with high conservation of water molecules. This is a new approach that uses experimental data in silico to identify interesting water sites. Methodology is fast and water-model or molecular dynamics software independent. Trends in the conservation of water molecules can be followed over a variety of trajectories, and our approach has been successfully validated using reported protein systems with experimentally observed conserved water molecules. ProBiS H2O MD is freely available as PyMOL plugin at http://insilab.org.

CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials.

Small-molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations such as improper treatment of the interactions of essential components in the chemical environment of the binding pocket (e.g., cofactors, metal ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and the inability to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm, that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample biologically relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions, and cofactor interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind, Astex, and PINC proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions such that the statistical score of the best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best-docked pose with biological activity. CANDOCK along with all structures and scripts used for benchmarking is available at https://github.com/chopralab/candock_benchmark.

Stereoselective Activity of 1-Propargyl-4-styrylpiperidine-like Analogues That Can Discriminate between Monoamine Oxidase Isoforms A and B.

The resurgence of interest in monoamine oxidases (MAOs) has been fueled by recent correlations of this enzymatic activity with cardiovascular, neurological, and oncological disorders. This has promoted increased research into selective MAO-A and MAO-B inhibitors. Here, we shed light on how selective inhibition of MAO-A and MAO-B can be achieved by geometric isomers of cis- and trans-1-propargyl-4-styrylpiperidines. While the cis isomers are potent human MAO-A inhibitors, the trans analogues selectively target only the MAO-B isoform. The inhibition was studied by kinetic analysis, UV-vis spectrum measurements, and X-ray crystallography. The selective inhibition of the MAO-A and MAO-B isoforms was confirmed ex vivo in mouse brain homogenates, and additional in vivo studies in mice show the therapeutic potential of 1-propargyl-4-styrylpiperidines for central nervous system disorders. This study represents a unique case of stereoselective activity of cis/trans isomers that can discriminate between structurally related enzyme isoforms.

In Silico Laboratory: Tools for Similarity-Based Drug Discovery.

Computational methods that predict and evaluate binding of ligands to receptors implicated in different pathologies have become crucial in modern drug design and discovery. Here, we describe protocols for using the recently developed package of computational tools for similarity-based drug discovery. The ProBiS stand-alone program and web server allow superimposition of protein structures against large protein databases and predict ligands based on detected binding site similarities. GenProBiS allows mapping of human somatic missense mutations related to cancer and non-synonymous single nucleotide polymorphisms and subsequent visual exploration of specific interactions in connection to these mutations. We describe protocols for using LiSiCA, a fast ligand-based virtual screening software that enables easy screening of large databases containing billions of small molecules. Finally, we show the use of BoBER, a web interface that enables user-friendly access to a large database of bioisosteric and scaffold hopping replacements.

Genetic Variations of Ultraconserved Elements in the Human Genome.

Ultraconserved elements (UCEs) are among the most popular DNA markers for phylogenomic analysis. In at least three of five placental mammalian genomes (human, dog, cow, mouse, and rat), 2189 UCEs of at least 200 bp in length that are identical have been identified. Most of these regions have not yet been functionally annotated, and their associations with diseases remain largely unknown. This is an important knowledge gap in human genomics with regard to UCE roles in physiologically critical functions, and by extension, their relevance for shared susceptibilities to common complex diseases across several mammalian organisms in the event of their polymorphic variations. In the present study, we remapped the genomic locations of these UCEs to the latest human genome assembly, and examined them for documented polymorphisms in sequenced human genomes. We identified 29,983 polymorphisms within analyzed UCEs, but revealed that a vast majority exhibits very low minor allele frequencies. Notably, only 112 of the identified polymorphisms are associated with a phenotype in the Ensembl genome browser. Through literature analyses, we confirmed associations of 37 (i.e., out of the 112) polymorphisms within 23 UCEs with 25 diseases and phenotypic traits, including, muscular dystrophies, eye diseases, and cancers (e.g., familial adenomatous polyposis). Most reports of UCE polymorphism-disease associations appeared to be not cognizant that their candidate polymorphisms were actually within UCEs. The present study offers strategic directions and knowledge gaps for future computational and experimental work so as to better understand the thus far intriguing and puzzling role(s) of UCEs in mammalian genomes.