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.

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).

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.

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.

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.

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 from the structural analysis of protein heterodimer interfaces.

Protein heterodimer complexes are often involved in catalysis, regulation, assembly, immunity and inhibition. This involves the formation of stable interfaces between the interacting partners. Hence, it is of interest to describe heterodimer interfaces using known structural complexes. We use a non-redundant dataset of 192 heterodimer complex structures from the protein databank (PDB) to identify interface residues and describe their interfaces using amino-acids residue property preference. Analysis of the dataset shows that the heterodimer interfaces are often abundant in polar residues. The analysis also shows the presence of two classes of interfaces in heterodimer complexes. The first class of interfaces (class A) with more polar residues than core but less than surface is known. These interfaces are more hydrophobic than surfaces, where protein-protein binding is largely hydrophobic. The second class of interfaces (class B) with more polar residues than core and surface is shown. These interfaces are more polar than surfaces, where binding is mainly polar. Thus, these findings provide insights to the understanding of protein-protein interactions.

Structural inferences for Cholera toxin mutations in Vibrio cholerae.

Cholera is a global disease that has persisted for millennia. The cholera toxin (CT) from Vibrio cholerae is responsible for the clinical symptoms of cholera. This toxin is a hetero-hexamer (AB(5)) complex consisting of a subunit A (CTA) with a pentamer (B(5)) of subunit B (CTB). The importance of the AB(5) complex for pathogenesis is established for the wild type O1 serogroup using known structural and functional data. However, its role is not yet documented in other known serogroups harboring sequence level residue mutations. The sequences for the toxin from different serogroups are available in GenBank (release 177). Sequence analysis reveals mutations at several sequence positions in the toxin across serogroups. Therefore, it is of interest to locate the position of these mutations in the AB(5) structure to infer complex assembly for its functional role in different serogroups. We show that mutations in the CTA are at the solvent exposed regions of the AB(5) complex, whereas those in the CTB are at the CTB/CTB interface of the homo-pentamer complex. Thus, the role of mutations at the CTB/CTB interface for B(5) complex assembly is implied. It is observed that these mutations are often non-synonymous (e.g. polar to non-polar or vice versa). The formation of the AB(5) complex involves inter-subunit residue-residue interactions at the protein-protein interfaces. Hence, these mutations, at the structurally relevant positions, are of importance for the understanding of pathogenesis by several serogroups. This is also of significance in the improvement of recombinant CT protein complex analogs for vaccine design and their use against multiple serogroups.

A HLA-DRB supertype chart with potential overlapping peptide binding function.

HLA-DRB alleles are class II alleles that are associated with CD4+ T-cell immune response. DRB alleles are polymorphic and currently there are about 622 named in the IMGT/HLA sequence database. Each allele binds short peptides with high sensitivity and specificity. However, it has been suggested that majority of HLA alleles can be covered within few HLA supertypes, where different members of a supertype bind similar peptides showing distinct repertoires. Definition of DRB supertypes using binding data is limited to few (about 29) known alleles (< 5% of all known DRB alleles). Hence, we describe a strategy using structurally defined virtual pockets to group all known DRB alleles with regard to their overlapping peptide binding specificity.

Interaction modes at protein hetero-dimer interfaces.

Hetero dimer (different monomers) interfaces are involved in catalysis and regulation through the formation of interface active sites. This is critical in cell and molecular biology events. The physical and chemical factors determining the formation of the interface active sites is often large in numbers. The combined role of interacting features is frequently combinatorial and additive in nature. Therefore, it is important to determine the physical and chemical features of such interactions. A number of such features have been documented in literature since 1975. However, the use of such interaction features in the prediction of interaction partners and sites given their sequences is still a challenge. In a non-redundant dataset of 156 hetero-dimer structures determined by X-ray crystallography, the interacting partners are often varying in size and thus, size variation between subunits is an important factor in determining the mode of interface formation. The size of protein subunits interacting are either small-small, largelarge, medium-medium, large-small, large-medium and small-medium. It should also be noted that the interface formed between subunits have physical interactions at N terminal (N), C terminal (C) and middle (M) region of the protein with reference to their sequences in one dimension. These features are believed to have application in the prediction of interaction partners and sites from sequences. However, the use of such features for interaction prediction from sequence is not currently clear.

Structural features for homodimer folding mechanism.

The homodimers have essential role in catalysis and regulation. The homodimer folding mechanism through 2-state without stable intermediate (2S), 3-state with monomer intermediate (3SMI) and 3-state with dimer intermediate (3SDI) is fascinating. 23MI and 3SDI constitute 3-state (3S). Hence, it is important to differentiate 2S, 3SMI and 3SDI homodimers using structural features. We used the dataset of Li et al. [L. Li, K. Gunasekaran, J.G. Gan, C. Zhanhua, P. Shapshak, M.K. Sakharkar, P. Kangueane, Structural features differentiate the mechanisms between 2S and 3S folding of homodimers, Bioinformation 1 (2005) 42-49] consisting of twenty-five 2S, ten 3SMI and six 3SDI homodimer structures for the study. Interface to total (I/T) residues ratio is large for 2S than 3SMI and 3SDI. Interface to total residues ratio is similar for 3SMI (mean monomer length (ML)=208) and 3SDI (mean monomer length (ML)=404) despite difference in mean monomer size. Interface residues correlate with monomer size in 2S (Pearson's correlation coefficient (r); r(2)=0.41) and 3SMI (r(2)=0.52). This is not true for 3SDI with interface residues and monomer length (r(2)=0.17). Interface area (B/2) does not correlate with interface residues (r(2)<0.001) and monomer size (r(2)=0.023) in 2S. This is despite a relationship with interface residues and monomer size (r(2)=0.41) in 2S. However, this is not true for 3SMI (r(2)=0.61 with interface residues and r(2)=0.25 with monomer size). In 3SDI, a different relationship is seen (r(2)=0.28 with interface residues and r(2)=0.09 with size). The mean hydrophobicity factor (H(f)) is 3-fold less in 3S than 2S. H(f) does not correlate with interface area in 2S (r(2)=0.03) and 3SDI (r(2)=0.0). However, a weak causal relation is seen in 3SMI (r(2)=0.23). Hydrophilic amino acid residues (E, R, K, S and Q) are prominent in 2S than 3S. Charged negative amino acid residues (D, E) are more than positive amino acid residues (R, K, H) in 2S and charged positive amino acid residues (R, K, H) are more than negative amino acid residues (D, E) in 3S. These features help to distinguish 2S, 3SMI and 3SDI providing insights to homodimer folding and binding.

Class II HLA-peptide binding prediction using structural principles.

The precise prediction of class II human leukocyte antigen (HLA) peptide binding finds application in epitope design for the development of vaccines and diagnostics of diseases associated with CD4+ T-cellular immunity. HLA II binding peptides have an extended conformation at the binding groove unlike class I. This increases peptide binding combinations of varying length at the groove, having an eventual effect in the host immune response to infectious agents. Here we describe the development of a prediction model using information gleaned from HLA II-peptide (HLA II-p) structural data. We created a manually curated dataset of 15 HLA II-p structural complexes from Protein databank (PDB). The dataset was used to develop virtual binding pockets for accommodating HLA-II-specific short peptides. The binding of peptides to the virtual pockets is estimated using the Q matrix (a quantitative matrix based on amino acid residue properties). Internal cross-validation of the model using the 15 HLA II-p structural complexes produced an accuracy of 53% with a sensitivity of 53%. The model was further evaluated using a dataset of 3676 class II-specific peptides consisting of 1188 binders and 2488 nonbinders derived from MHCBN (a database of HLA binders and nonbinders). The model produced an accuracy of 53% with 70.8% specificity and 27.6% sensitivity. The positive predictive value (PPV) was 62% and the negative predictive value (NPV) 58%. A 62% PPV suggests that the model fairly predicts a good number of binders among predicted binders and thus that the success rate among predicted binder for further verification is good. The described model is simple and rapid, with large HLA allele coverage representing the sampled global population, despite weak prediction accuracy. The ability of the model to predict a wide array of defined class II alleles is found to be applicable for proteome-wide scanning of parasitic genomes.

Types of interfaces for homodimer folding and binding.

Homodimers have a role in catalysis and regulation through the formation of stable interfaces. These interfaces are formed through different folding mechanisms such as 2-state without stable intermediate (2S), 3-state with monomer intermediate (3SMI) and 3-state with dimer intermediate (3SDI). Therefore, it is of interest to understand folding mechanism using structural features at the interfaces. Several studies have documented the significance of structural features for the understanding of homodimer folding mechanisms. However, the known features provide limited information for understanding homodimer folding mechanisms. Hence, we created an extended dataset of 47 homodimers (twenty eight 2S, twelve 3SMI and seven 3SDI) to examine the types of interfaces in protein homodimers. 2S are usually small sized, 3SMI are often medium sized and 3SDI often exist as large sized proteins. The ratio of interface to total (I/T) residue is large in 2S and small in 3SMI and 3SDI. Hence, we used I/T measure to group 2S, 3SMI and 3SDI into categories with large I/T (>> 50%), moderate I/T (50 - 25%) and small I/T (<< 25%) interfaces. The grouping is further sub-grouped based on the type of physical interaction visualized at the interface using representations in two dimensions (2D). 2D representation of the interface shows eight different forms of interactions in these homodimers. 2S homodimers frequently have large I/T and thus, utilize the entire protein structure in the formation of the interface where the individual subunits are heavily inter communicated with each other. This is not true in the case of 3SMI and 3SDI. 3SMI subunits usually interact with each other at the interface with a gentle touch-like contact and hence, they have low I/T ratio. 3SDI are often quite different in interaction compared to 3SMI and their subunits do deeply interact at the interface with only one part of the surface and hence also having low I/T ratio.

A decision tree model for the prediction of homodimer folding mechanism.

The formation of protein homodimer complexes for molecular catalysis and regulation is fascinating. The homodimer formation through 2S (2 state), 3SMI (3 state with monomer intermediate) and 3SDI (3 state with dimer intermediate) folding mechanism is known for 47 homodimer structures. Our dataset of forty-seven homodimers consists of twenty-eight 2S, twelve 3SMI and seven 3SDI. The dataset is characterized using monomer length, interface area and interface/total (I/T) residue ratio. It is found that 2S are often small in size with large I/T ratio and 3SDI are frequently large in size with small I/T ratio. Nonetheless, 3SMI have a mixture of these features. Hence, we used these parameters to develop a decision tree model. The decision tree model produced positive predictive values (PPV) of 72% for 2S, 58% for 3SMI and 57% for 3SDI in cross validation. Thus, the method finds application in assigning homodimers with folding mechanism.

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.

Huge proteins in the human proteome and their participation in hereditary diseases.

Protein lengths vary considerably from a few to thousands of amino acids and length variations are documented to have multiple effects. A computational approach to investigate the functional impact of protein length variation in genetic disorders is presented. The genes for huge proteins are found to have more introns. Our analysis also shows greater involvement of huge proteins in hereditary diseases.