Challenges and other linked features in promoting open access to bioinformation literature over about 2 decades.

Open access to known literature is critical for creating a harmonious society across continents on planet earth. However, this objective is not simple. Therefore, it is of interest to document the challenges and linked features in promoting open access to bioinformation literature over about 2 decades.

From Anna University to America and to Agriculture.

Anna University (AU) is an awesome alma mater for attracting the attention of the invincible through awareness from education. It is a place with a plan for preparing a palace in a person's life. It is an avenue for America through adequate cGPA and Advanced GRE (AGRE) with good TOEFL score. The views,visions, modes and models of several faculty members shaped many technocrats, teachers, entrepreneurs, journalists, editors and even farmers. Technology is engineering with science. The foundation and facilities at AU is priceless. AU created the framework for Industrial Biotechnology, a truly inter disciplinary curriculum with an optimal blend of Engineering and Science (Biology especially Agriculture and Healthcare through Organic chemistry) in 1992 almost 28 years back. The place was positioned just perfect in the world for wonders to come true. The Raman auditorium (in reverence to the Nobel Laureate Sir CV Raman) reassured rational research with reasonable respect in many minds at the ACTECH (Alagappa College of Technology) under the administration of AU. The admiration, acknowledgement and accountability for the alma mater, the AU will always remain precious.

Biotechnology, Bioinformatics and Bioinformation in an Autobiography.

Science is observation. Application of Science is engineering. A 0% error is desired in Science, while a 25% error is usually allowed in Engineering. Technology is engineering with Science where the error rate is considerably reduced to improve precision. Biotechnology is truly interdisciplinary with an optimal mix of physics, chemistry and biology linked by Mathematics. Chemistry evolved into Chemical Engineering and thus Biochemistry into Biochemical Engineering. Biochemical engineering with genetics and molecular biology created Biotechnology. Biotechnology with computer science developed Bioinformatics. Bioinformatics used biological data to glean BIOINFORMATION for Biological Knowledge Discovery (BKD). This helped to accelerate drug discovery and develop other biologics (biomarkers, vaccines, seed developments, bio-fertilizers and bio-pesticides) towards improved service in healthcare, agriculture, food production, food processing and food distribution across international borders as per demand supply in the supply chain. It is joyful to realize the personal experience with the multifaceted features of Biotechnology, Bioinformatics and Bioinformation in a comprehensive manner over a period of three decades. This educational path is truly exciting, engaging and enterprising. This journey provided an opportunity to debate on cry toxins, lipase, ibuprofen, HLA alleles, antigens, peptide vaccines, protein-protein interactions, genomes and biological knowledge discovery models.

Pointless pondering on predatory publications.

It is a pointless pondering (thinking) on predatory (meaning greedy) publications (meaning journals) while practicing publishing through freedom of expression and or the Press where applicable. It should be noted that a weak publication will vanish (disappear) itself in an open access publishing model where contents are made available for free on the WWW. The fundamental question in this context is the definition of host (congregation) and predator (intruder). The second question is the type (data and or commercial) and subsequent measure of effect of the predator on the host. Detailed discussion on this issue or any other related issue is welcomed under the freedom of the Press yet conclusion on it will be often biased and is clearly unwarranted. The parties aware of such concerns should write to the publisher (with address for communication) to take such action within such time to stand corrected. Please be informed that ISSN is unique for each publication and portals for ISSN is distributed throughout the world in each country. This is well monitored and clearly streamlined. Therefore, NO two publication titles will be identical. Awareness from authors on misleading or misinformed or misrepresented ISSN is important and such information should be petitioned to ISSN and portals for ISSN that is distributed throughout the world with state mechanisms to monitor such activities. Academia should be self-aware on these issues and have discussions on the quality and quantity of data taken to the context. Caveat Emptor is applicable to a considerable extend among the literate community as in this case. The only problem could arise because of compromised (unregistered or mirrored) ISSN number published on the WWW which is already well regulated through DNS lookup. Therefore, parties concerned about ethical issues on scientific publishing should write to concerned publishers with known address to stand corrected or to ISSN and portals for ISSN or to DNS lookup where address is not available to correct such issues through available state mechanisms. Hence, biased advisory notes from government representations, society sponsored mass campaign through news/TV media and academic miss representation based on data collected by an individual without physical address for communication is clearly unwarranted in this regard.

Science for service in a society is the success story of scientists with serenity.

Available data on science is constantly gleaned for gathering valuable information to create concise yet precise knowledge on specific subjects (especially, the biology oriented agriculture and biomedicine) for service in the society. These sacrifices surmounts as success stories for scientists worldwide. Data in the form of known literature plays a radical role in serving the society with improved infrastructure and facilities making associated resources available, accessible and affordable. This is possible by making known literature available and accessible for application in a modern economy dominant with features of democratic socialism. The public investment from tax payers coupled with the privately propelled commercial factions involved in the gathering, archiving and distribution of known literature data is complex in its current status quo in the context of creating a harmonious society with optimal social benefits. It should be noted that the role played by indirect, unorganized, unskilled and unaccounted farmers, farm laborers and service men in different layers of the supply chain in accordance with demand and supply is highly imperative. Therefore, it is of interest for a comprehensive discussion on issues in making known literature available and accessible for application towards the benefit of the society through open access publishing models within the acceptable ethical frameworks of Creative Commons (CC) and Committee on Publication Ethics (COPE).

Small protein-protein interfaces rich in electrostatic are often linked to regulatory function.

Protein-protein interaction (PPI) is critical for several biological functions in living cells through the formation of an interface. Therefore, it is of interest to characterize protein-protein interfaces using an updated non-redundant structural dataset of 2557 homo (identical subunits) and 393 hetero (different subunits) dimer protein complexes determined by X-ray crystallography. We analyzed the interfaces using van der Waals (vdW), hydrogen bonding and electrostatic energies. Results show that on average homo and hetero interfaces are similar. Hence, we further grouped the 2950 interfaces based on percentage vdW to total energies into dominant (≥60%) and sub-dominant (<60%) vdW interfaces. Majority (92%) of interfaces have dominant vdW energy with large interface size (146 ± 87 (homo) and 137 ± 76 (hetero) residues) and interface area (1622 ± 1135 Å2 (homo) and 1579 ± 1060 Å2 (hetero)). However, a proportion (8%) of interfaces have sub-dominant vdW energy with small interface size (85 ± 46 (homo) and 88 ± 36 (hetero) residues) and interface area (823 ± 538 Å2 (homo) and 881 ± 377 Å2 (hetero)). It is found that large interfaces have two-fold more interface area and interface size than small interfaces with increasing hydrogen bonding energy to interface size. However, small interfaces have three-fold more electrostatics energy than large interfaces with increasing electrostatics to interface size. Thus, 8% of complexes having small interfaces with limited interface area and sub-dominant vdW energy are rich in electrostatics. It is interesting to observe that complexes having small interfaces are often associated with regulatory function. Hence, the observed structural features with known molecular function provide insights for the better understanding of PPI.Communicated by Ramaswamy H. Sarma.

Structural basis for HLA-A2 supertypes.

The human leukocyte antigen (HLA) alleles are extremely polymorphic among ethnic population, and the peptide-binding specificity varies for different alleles in a combinatorial manner. However, it has been suggested that majority of alleles can be covered within few HLA supertypes, where different members of a supertype bind similar peptides, yet exhibiting distinct repertoires. Nonetheless, the structural basis for HLA supertype-like function is not clearly known. Here, we use structural data to explain the molecular basis for HLA-A2 supertypes.

Grouping of class I HLA alleles using electrostatic distribution maps of the peptide binding grooves.

Human leukocyte antigen (HLA) molecules involved in immune function by binding to short peptides (8-20 residues) have different sequences in different individuals belonging to distinct ethnic population. Hence, the peptide-binding function of HLA alleles is specific. Class I HLA alleles (alternative forms of a gene) are associated with CD8+ T cells, and their allele-specific sequence information is available at the IMGT/HLA database. The available sequences are one-dimensional (ID), and the peptide-binding functional inference often requires 3-dimensional (3D) structural models of respective alleles. Hence, 3D structures were constructed for 1,000 class I HLA alleles (310 A, 570 B, and 120 C) using MODELLER (a comparative protein modeling program for modeling protein structures). The electrostatic distribution maps were generated for each modeled structure using Deep View (Swiss PDB Viewer Version 3.7). The 1,000 models were then grouped into different categories by visual inspection of their electrostatic distribution maps in the peptide binding grooves. The distribution of the models based on electrostatic distribution was 30% negative (300), 1% positive (12), 8% neutral (84), and 60% (604) mixed (random mixture of negative, positive, and neutral). This grouping provides insight toward the inference for functional overlap among HLA alleles.

HLA-peptide binding prediction using structural and modeling principles.

Short peptides binding to specific human leukocyte antigen (HLA) alleles elicit immune response. These candidate peptides have potential utility in peptide vaccine design and development. The binding of peptides to allele-specific HLA molecule is estimated using competitive binding assay and biochemical binding constants. Application of this method for proteome-wide screening in parasites, viruses, and virulent bacterial strains is laborious and expensive. However, short listing of candidate peptides using prediction approaches have been realized lately. Prediction of peptide binding to HLA alleles using structural and modeling principles has gained momentum in recent years. Here, we discuss the current status of such prediction.

Protein-protein interfaces are vdW dominant with selective H-bonds and (or) electrostatics towards broad functional specificity.

Several catalysis, cellular regulation, immune function, cell wall assembly, transport, signaling and inhibition occur through Protein- Protein Interactions (PPI). This is possible with the formation of specific yet stable protein-protein interfaces. Therefore, it is of interest to understand its molecular principles using structural data in relation to known function. Several interface features have been documented using known X-ray structures of protein complexes since 1975. This has improved our understanding of the interface using structural features such as interface area, binding energy, hydrophobicity, relative hydrophobicity, salt bridges and hydrogen bonds. The strength of binding between two proteins is dependent on interface size (number of residues at the interface) and thus its corresponding interface area. It is known that large interfaces have high binding energy (sum of (van der Waals) vdW, H-bonds, electrostatics). However, the selective role played by each of these energy components and more especially that of vdW is not explicitly known. Therefore, it is important to document their individual role in known protein-protein structural complexes. It is of interest to relate interface size with vdW, H-bonds and electrostatic interactions at the interfaces of protein structural complexes with known function using statistical and multiple linear regression analysis methods to identify the prominent force. We used the manually curated non-redundant dataset of 278 hetero-dimeric protein structural complexes grouped using known functions by Sowmya et al. (2015) to gain additional insight to this phenomenon using a robust inter-atomic non-covalent interaction analyzing tool PPCheck (Anshul and Sowdhamini, 2015). This dataset consists of obligatory (enzymes, regulator, biological assembly), immune and nonobligatory (enzyme and regulator inhibitors) complexes. Results show that the total binding energy is more for large interfaces. However, this is not true for its individual energy factors. Analysis shows that vdW energies contribute to about 75% ± 11% on average among all complexes and it also increases with interface size (r2 ranging from 0.67 to 0.89 with p<0.01) at 95% confidence limit irrespective of molecular function. Thus, vdW is both dominant and proportional at the interface independent of molecular function. Nevertheless, H bond energy contributes to 15% ± 6.5% on average in these complexes. It also moderately increases with interface size (r2 ranging from 0.43 to 0.61 with p<0.01) only among obligatory and immune complexes. Moreover, there is about 11.3% ± 8.7% contribution by electrostatic energy. It increases with interface size specifically among non-obligatory regulator-inhibitors (r2 = 0.44). It is implied that both H-bonds and electrostatics are neither dominant nor proportional at the interface. Nonetheless, their presence cannot be ignored in binding. Therefore, H-bonds and (or) electrostatic energy having specific role for improved stability in complexes is implied. Thus, vdW is common at the interface stabilized further with selective H-bonds and (or) electrostatic interactions at an atomic level in almost all complexes. Comparison of this observation with residue level analysis of the interface is compelling. The role by H-bonds (14.83% ± 6.5% and r2 = 0.61 with p<0.01) among obligatory and electrostatic energy (8.8% ± 4.77% and r2 = 0.63 with p <0.01) among non-obligatory complexes within interfaces (class A) having more non-polar residues than surface is influencing our inference. However, interfaces (class B) having less non-polar residues than surface show 1.5 fold more electrostatic energy on average. The interpretation of the interface using inter-atomic (vdW, H-bonds, electrostatic) interactions combined with inter-residue predominance (class A and class B) in relation to known function is the key to reveal its molecular principles with new challenges.

Insights to metabolic network evolution by fusion proteins.

Human fusion proteins consisting of two or more fusion partners of prokaryotic origin exhibit accreted function. Recent studies have elucidated the importance of fusion proteins in complex regulatory networks. The significance of fusion proteins in cellular networks and their evolutionary mechanism is largely unknown. Here, we discuss the association of six fusion proteins with the citric acid cycle. We define possible gene fusion scenarios and show that they produce metabolites with high connectivity for complex networking. Complex networking of metabolites requires proteins with incremental structural architectures and functional capabilities. Such higher order functionality is frequently provided by fusion proteins. Therefore, evolution of fusion proteins capable of producing metabolites with greater connectivity for enhanced cross-talk between pathways is critical for the selection of multiple trajectories in maintaining a stoichiometric balance during regulation. The association of six fusion proteins with the citric acid cycle and their capability to produce metabolites with high connectivity index is intriguing. This suggests that fusion gene products and their evolution have had a key role in the selection of complex multifaceted networks. In addition, we propose that fusion proteins have gained additive biochemical function for a balanced regulation of metabolic networks.

Generation of a dataset for studying ligand effect on homodimer interface.

Protein dimer interfaces (homodimer - same polypeptide and heterodimer - different polypeptide) display geometric and chemical properties that give the non-covalent assembly its stability and specificity. Therefore, it is important to understand the molecular principles of dimer interaction. Several studies on homodimer interaction are available. However, a study on the effect of ligands (i.e. non-peptide compounds) on subunit interactions is not available. Hence, we generated a dataset of 62 identical homodimer pairs (one structure determined with an interface ligand and the other without an interface ligand) and analyzed the effect of interface ligands on dimer interface. The analysis suggests that homodimer interfaces having ligands are less hydrophobic with small interface area compared to those without ligands. We also found that ligands occupying = 7% interface area have negligible effect on dimer interaction.

Identification of critical heterodimer protein interface parameters by multi-dimensional scaling in euclidian space.

Protein subunit dimers are either homodimers (consisting of identical polypeptides) or heterodimers (consisting of different polypeptides). Protein dimers are involved in several cellular processes and an understanding of their molecular principle in complexations (subunit-subunit interaction) is essential. This is generally studied using 3D structures of homodimers and heterodimers determined by X-ray crystallography. However, the current knowledge on subunit interaction is limited due to lack of sufficient 3D dimer structures. It is our interest to study heterodimers using 3D structures to identify interaction parameters that would help in the development of a model to predict heterodimer interaction sites just from protein sequences. The efficiency of such models depends on the weighted contribution of numerous parameters characterizing heterodimer interfaces. Therefore, we studied the salient features of 111 interface parameters in 65 heterodimer structures. In this study, we applied multi-dimensional scaling for dimensionality reduction on these parameters to select the most critical ones that best characterize heterodimer interfaces. The significance of these parameters in subunit interaction is discussed.

Computational prediction of SEG (single exon gene) function in humans.

Human genes are often interrupted by non-coding, intragenic sequences called introns. Hence, the gene sequence is divided into exons (coding segments) and introns (non-coding segments). Consequently, a majority of them are multi exon genes (MEG). However, a considerable amount of single exon genes (SEG) are present in the human genome (approximately 12%). This amount is sizeable and it is important to probe their molecular function and cellular role. Hence, we performed a genome wide functional assignment to 3750 SEG sequences using PFAM (protein family database), PROSITE (database of biologically meaningful signatures or motifs) and SUPERFAMILY (a library covering all proteins of known 3 dimensional structure). PFAM assigned 13% SEG to trans-membrane receptor genes of the G-protein coupled receptor (GPCR) family and showed that a majority of SEG proteins have DNA binding function. PROSITE identified 336 unique motif types in them and this accounts for 25% of all known patterns, with a majority having PHOSPHORYLATION and ACETYLATION signals. SUPERFAMILY assigned 33% SEG to the membrane all alpha (proteins containing alpha helix structural elements according to SCOP (structural classification of proteins) definition). Functional assignment of SEG proteins at multiple levels (sequence signals, sequence families, 3D structures) using PFAM, PROSITE and SUPERFAMILY is envisioned to suggest their selective and predominant molecular function in cellular systems. Their function as DNA binding, phosphorylating, acetylating and house-keeping agents is intriguing. The analysis also showed evidence of SEG expression and retro-transposition. However, this information is inadequate to draw concerted conclusion on the prevalent role played by these proteins in cellular biology. A complete understanding of SEG function will help to explore their role in cellular environment. The derived datasets from these analyses are available at http://sege.ntu.edu.sg/wester/intronless/human/.

Human genome -- from pieces to patterns.

A profile of exon-intron lengths in genes shows a normal distribution. This observation suggests that different genes may have portions of their total exon and/or intron lengths in common. In order to explore the common exon-intron structural patterns that may arise due to common lengths across genes, we compared the exon-intron length patterns of annotated human genes. We discovered 1762278 conserved arrangements of exon-intron length across the otherwise unrelated and diverse genomic landscape. The existence of common exon-intron length patterns across unrelated genes suggests for their role of in gene assemblage and human genome design and architecture.

A framework to sub-type HLA supertypes.

The human leukocyte antigen (HLA) alleles are extremely polymorphic among ethnic population and the peptide binding specificity varies for different alleles in a combinatorial manner. However, it has been suggested that majority of alleles can be covered within few HLA supertypes, where different members of a supertype bind similar peptides, yet exhibiting distinct repertoires. Since the overlap between different members of a supertype appears to be extensive, it is crucial to develop a framework for grouping alleles into supertypes just from sequence information. In this report, we define sub supertypes, where members show functional overlap with identical repertoire, and describe a strategy to group HLA-A, B and C alleles into different categories of sub supertypes. The strategy grouped 47% of 295 A alleles, 44% of 540 B alleles and 35% of 156 C alleles to just 36, 71 and 18 groups, respectively. The grouping is moderately validated using available binding data. However, the validation is limited due to lack of binding data. Hence, the data presented in this article serve as a framework to test specific functional overlap between alleles. The grouping of HLA alleles into different categories of sub supertypes has profound use in the understanding of antigenic peptide selection, degeneration and discrimination during T-cell mediated immune response. A complete knowledge of this phenomenon finds utility in epitope design for the development of HLA based vaccines and immuno-therapeutics.

Genome SEGE: a database for 'intronless' genes in eukaryotic genomes.

BACKGROUND: A number of completely sequenced eukaryotic genome data are available in the public domain. Eukaryotic genes are either 'intron containing' or 'intronless'. Eukaryotic 'intronless' genes are interesting datasets for comparative genomics and evolutionary studies. The SEGE database containing a collection of eukaryotic single exon genes is available. However, SEGE is derived using GenBank. The redundant, incomplete and heterogeneous qualities of GenBank data are a bottleneck for biological investigation in comparative genomics and evolutionary studies. Such studies often require representative gene sets from each genome and this is possible only by deriving specific datasets from completely sequenced genome data. Thus Genome SEGE, a database for 'intronless' genes in completely sequenced eukaryotic genomes, has been constructed. AVAILABILITY: http://sege.ntu.edu.sg/wester/intronless DESCRIPTION: Eukaryotic 'intronless' genes are extracted from nine completely sequenced genomes (four of which are unicellular and five of which are multi-cellular). The complete dataset is available for download. Data subsets are also available for 'intronless' pseudo-genes. The database provides information on the distribution of 'intronless' genes in different genomes together with their length distributions in each genome. Additionally, the search tool provides pre-computed PROSITE motifs for each sequence in the database with appropriate hyperlinks to InterPro. A search facility is also available through the web server. CONCLUSIONS: The unique features that distinguish Genome SEGE from SEGE is the service providing representative 'intronless' datasets for completely sequenced genomes. 'Intronless' gene sets available in this database will be of use for subsequent bio-computational analysis in comparative genomics and evolutionary studies. Such analysis may help to revisit the original genome data for re-examination and re-annotation.

Can ends justify the means? Digging deep for human fusion genes of prokaryotic origin.

Gene fusion has been described as an important evolutionary phenomenon. This report focuses on identifying, analyzing, and tabulating human fusion proteins of prokaryotic origin. These fusion proteins are found to mimic operons, simulate protein-protein interfaces in prokaryotes, exhibiting multiple functions and alternative splicing in humans. The accredited biological functions for each of these proteins is made available as a database at http://sege.ntu.edu.sg/wester/fusion/

A report on single exon genes (SEG) in eukaryotes.

Single exon genes (SEG) are archetypical of prokaryotes. Hence, their presence in intron-rich, multi-cellular eukaryotic genomes is perplexing. Consequently, a study on SEG origin and evolution is important. Towards this goal, we took the first initiative of identifying and counting SEG in nine completely sequenced eukaryotic organisms--four of which are unicellular (E. cuniculi, S. cerevisiae, S. pombe, P. falciparum) and five of which are multi-cellular (C. elegans, A. thaliana, D. melanogaster, M. musculus, H. sapiens). This exercise enabled us to compare their proportion in unicellular and multi-cellular genomes. The comparison suggests that the SEG fraction decreases with gene count (r = -0.80) and increases with gene density (r = 0.88) in these genomes. We also examined the distribution patterns of their protein lengths in different genomes.

Types of inter-atomic interactions at the MHC-peptide interface: identifying commonality from accumulated data.

BACKGROUND: Quantitative information on the types of inter-atomic interactions at the MHC-peptide interface will provide insights to backbone/sidechain atom preference during binding. Qualitative descriptions of such interactions in each complex have been documented by protein crystallographers. However, no comprehensive report is available to account for the common types of inter-atomic interactions in a set of MHC-peptide complexes characterized by variation in MHC allele and peptide sequence. The available x-ray crystallography data for these complexes in the Protein Databank (PDB) provides an opportunity to identify the prevalent types of such interactions at the binding interface. RESULTS: We calculated the percentage distributions of four types of interactions at varying inter-atomic distances. The mean percentage distribution for these interactions and their standard deviation about the mean distribution is presented. The prevalence of SS and SB interactions at the MHC-peptide interface is shown in this study. SB is clearly dominant at an inter-atomic distance of 3A. CONCLUSION: The prevalently dominant SB interactions at the interface suggest the importance of peptide backbone conformation during MHC-peptide binding. Currently, available algorithms are developed for protein sidechain prediction upon fixed backbone template. This study shows the preference of backbone atoms in MHC-peptide binding and hence emphasizes the need for accurate peptide backbone prediction in quantitative MHC-peptide binding calculations.