@article {78096, title = {Dataset for the combined transcriptome assembly of and functional annotation.}, journal = {Data Brief}, volume = {30}, year = {2020}, month = {2020 Jun}, pages = {105416}, abstract = {

In this paper, we present the data acquired during transcriptome analysis of the Moringa oleifera [1] from five different tissues (root, stem, leaf, flower and seed) by RNA sequencing. A total of 271 million reads were assembled with an N50 of 2094 bp. The combined transcriptome was assessed for transcript abundance across five tissues. The protein coding genes identified from the transcripts were annotated and used for orthology analysis. Further, enzymes involved in the biosynthesis of select medicinally important secondary metabolites, vitamins and ion transporters were identified and their expression levels across tissues were examined. The data generated by RNA sequencing has been deposited to NCBI public repository under the accession number PRJNA394193 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA394193).

}, issn = {2352-3409}, doi = {10.1016/j.dib.2020.105416}, author = {Shafi, K Mohamed and Joshi, Adwait G and Meenakshi, Iyer and Pasha, Shaik Naseer and Harini, K and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {83641, title = {A knowledge-driven protocol for prediction of proteins of interest with an emphasis on biosynthetic pathways.}, journal = {MethodsX}, volume = {7}, year = {2020}, month = {2020}, pages = {101053}, abstract = {

This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on transcriptome to identify proteins involved in secondary metabolite and vitamin biosynthesis and ion transport. This knowledge-driven protocol identifies proteins using an integrated approach involving sensitive sequence search and evolutionary relationships. We make use of functionally important residues (FIR) specific for the query protein family identified through its homologous sequences and literature. We screen protein hits based on the clustering with true homologues through phylogenetic tree reconstruction complemented with the FIR mapping. The protocol was validated for the protein hits through qRT-PCR and transcriptome quantification. Our protocol demonstrated a higher specificity as compared to other methods, particularly in distinguishing cross-family hits. This protocol was effective in transcriptome data analysis of as described in Pasha et al.{\textbullet}Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner.{\textbullet}Use of functionally important residues for screening of true hits.{\textbullet}Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

}, issn = {2215-0161}, doi = {10.1016/j.mex.2020.101053}, author = {Joshi, Adwait G and Harini, K and Meenakshi, Iyer and Shafi, K Mohamed and Pasha, Shaik Naseer and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {57789, title = {The transcriptome enables the identification of candidate genes behind medicinal value of Drumstick tree (Moringa oleifera).}, journal = {Genomics}, volume = {112}, year = {2020}, month = {01/2020}, pages = {621-628}, abstract = {

Moringa oleifera is a plant well-known for its nutrition value, drought resistance and medicinal properties. cDNA libraries from five different tissues (leaf, root, stem, seed and flower) of M. oleifera cultivar Bhagya were generated and sequenced. We developed a bioinformatics pipeline to assemble transcriptome, along with the previously published M. oleifera genome, to predict 17,148 gene models. Few candidate genes related to biosynthesis of secondary metabolites, vitamins and ion transporters were identified. Expressions were further confirmed by real-time quantitative PCR experiments for few promising leads. Quantitative estimation of metabolites, as well as elemental analysis, was also carried out to support our observations. Enzymes in the biosynthesis of vitamins and metabolites like quercetin and kaempferol are highly expressed in leaves, flowers and seeds. The expression of iron transporters and calcium storage proteins were observed in root and leaves. In general, leaves retain the highest amount of small molecules of interest.

}, issn = {1089-8646}, doi = {10.1016/j.ygeno.2019.04.014}, author = {Pasha, Shaik Naseer and Shafi, K Mohamed and Joshi, Adwait G and Meenakshi, Iyer and Harini, K and Mahita, Jarjapu and Sajeevan, Radha Sivarajan and Karpe, Snehal D and Ghosh, Pritha and Nitish, Sathyanarayanan and Gandhimathi, A and Mathew, Oommen K and Prasanna, Subramanian Hari and Malini, Manoharan and Mutt, Eshita and Naika, Mahantesha and Ravooru, Nithin and Rao, Rajas M and Shingate, Prashant N and Sukhwal, Anshul and Sunitha, Margaret S and Upadhyay, Atul K and Vinekar, Rithvik S and Sowdhamini, Ramanathan} } @article {65300, title = {Small protein-protein interfaces rich in electrostatic are often linked to regulatory function.}, journal = {J Biomol Struct Dyn}, year = {2019}, month = {2019 Sep 09}, pages = {1-20}, abstract = {

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 {\textpm} 87 (homo) and 137 {\textpm} 76 (hetero) residues) and interface area (1622 {\textpm} 1135 {\r A} (homo) and 1579 {\textpm} 1060 {\r A} (hetero)). However, a proportion (8\%) of interfaces have sub-dominant vdW energy with small interface size (85 {\textpm} 46 (homo) and 88 {\textpm} 36 (hetero) residues) and interface area (823 {\textpm} 538 {\r A} (homo) and 881 {\textpm} 377 {\r A} (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.

}, issn = {1538-0254}, doi = {10.1080/07391102.2019.1657040}, author = {Nilofer, Christina and Sukhwal, Anshul and Mohanapriya, Arumugam and Sakharkar, Meena Kishore and Kangueane, Pandjassarame} } @article {20956, title = {Protein-protein interfaces are vdW dominant with selective H-bonds and (or) electrostatics towards broad functional specificity.}, journal = {Bioinformation}, volume = {13}, year = {2017}, month = {2017}, pages = {164-173}, abstract = {

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\% {\textpm} 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\% {\textpm} 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\% {\textpm} 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\% {\textpm} 6.5\% and r2 = 0.61 with p\<0.01) among obligatory and electrostatic energy (8.8\% {\textpm} 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.

}, issn = {0973-2063}, doi = {10.6026/97320630013164}, author = {Nilofer, Christina and Sukhwal, Anshul and Mohanapriya, Arumugam and Kangueane, Pandjassarame} } @article {12269, title = {Specificity and stability of transient protein-protein interactions.}, journal = {Curr Opin Struct Biol}, volume = {44}, year = {2017}, month = {2017 Jan 11}, pages = {77-86}, abstract = {

Remarkable features that are achieved in a protein-protein complex to precise levels are stability and specificity. Deviation from the normal levels of specificity and stability, which is often caused by mutations, could result in disease conditions. Chemical nature, 3-D arrangement and dynamics of interface residues code for both specificity and stability. This article reviews roles of interfacial residues in transient protein-protein complexes. It is proposed that aside from hotspot residues conferring stability to the complex, a small set of {\textquoteright}rigid{\textquoteright} residues at the interface that maintain conformation between complexed and uncomplexed forms, play a major role in conferring specificity. Exceptionally, {\textquoteright}super hotspot{\textquoteright} residues, which confer both stability and specificity, are attractive sites for interaction with small molecule inhibitors.

}, issn = {1879-033X}, doi = {10.1016/j.sbi.2016.12.010}, author = {Vishwanath, Sneha and Sukhwal, Anshul and Sowdhamini, Ramanathan and Srinivasan, Narayanaswamy} } @article {161, title = {Genome sequencing of herb Tulsi (Ocimum tenuiflorum) unravels key genes behind its strong medicinal properties.}, journal = {BMC Plant Biol}, volume = {15}, year = {2015}, month = {2015}, pages = {212}, abstract = {

BACKGROUND: Krishna Tulsi, a member of Lamiaceae family, is a herb well known for its spiritual, religious and medicinal importance in India. The common name of this plant is {\textquoteright}Tulsi{\textquoteright} (or {\textquoteright}Tulasi{\textquoteright} or {\textquoteright}Thulasi{\textquoteright}) and is considered sacred by Hindus. We present the draft genome of Ocimum tenuiflurum L (subtype Krishna Tulsi) in this report. The paired-end and mate-pair sequence libraries were generated for the whole genome sequenced with the Illumina Hiseq 1000, resulting in an assembled genome of 374~Mb, with a genome coverage of 61~\% (612~Mb estimated genome size). We have also studied transcriptomes (RNA-Seq) of two subtypes of O. tenuiflorum, Krishna and Rama Tulsi and report the relative expression of genes in both the varieties.

RESULTS: The pathways leading to the production of medicinally-important specialized metabolites have been studied in detail, in relation to similar pathways in Arabidopsis thaliana and other plants. Expression levels of anthocyanin biosynthesis-related genes in leaf samples of Krishna Tulsi were observed to be relatively high, explaining the purple colouration of Krishna Tulsi leaves. The expression of six important genes identified from genome data were validated by performing q-RT-PCR in different tissues of five different species, which shows the high extent of urosolic acid-producing genes in young leaves of the Rama subtype. In addition, the presence of eugenol and ursolic acid, implied as potential drugs in the cure of many diseases including cancer was confirmed using mass spectrometry.

CONCLUSIONS: The availability of the whole genome of O.tenuiflorum and our sequence analysis suggests that small amino acid changes at the functional sites of genes involved in metabolite synthesis pathways confer special medicinal properties to this herb.

}, issn = {1471-2229}, doi = {10.1186/s12870-015-0562-x}, author = {Upadhyay, Atul K and Chacko, Anita R and Gandhimathi, A and Ghosh, Pritha and Harini, K and Joseph, Agnel P and Joshi, Adwait G and Karpe, Snehal D and Kaushik, Swati and Kuravadi, Nagesh and Lingu, Chandana S and Mahita, J and Malarini, Ramya and Malhotra, Sony and Malini, Manoharan and Mathew, Oommen K and Mutt, Eshita and Naika, Mahantesha and Nitish, Sathyanarayanan and Pasha, Shaik Naseer and Raghavender, Upadhyayula S and Rajamani, Anantharamanan and Shilpa, S and Shingate, Prashant N and Singh, Heikham Russiachand and Sukhwal, Anshul and Sunitha, Margaret S and Sumathi, Manojkumar and Ramaswamy, S and Gowda, Malali and Sowdhamini, Ramanathan} } @article {1032, title = {PPCheck: A Webserver for the Quantitative Analysis of Protein-Protein Interfaces and Prediction of Residue Hotspots.}, journal = {Bioinform Biol Insights}, volume = {9}, year = {2015}, month = {2015}, pages = {141-51}, abstract = {

BACKGROUND: Modeling protein-protein interactions (PPIs) using docking algorithms is useful for understanding biomolecular interactions and mechanisms. Typically, a docking algorithm generates a large number of docking poses, and it is often challenging to select the best native-like pose. A further challenge is to recognize key residues, termed as hotspots, at protein-protein interfaces, which contribute more in stabilizing a protein-protein interface.

RESULTS: We had earlier developed a computer algorithm, called PPCheck, which ascribes pseudoenergies to measure the strength of PPIs. Native-like poses could be successfully identified in 27 out of 30 test cases, when applied on a separate set of decoys that were generated using FRODOCK. PPCheck, along with conservation and accessibility scores, was able to differentiate {\textquoteright}native-like and non-native-like poses from 1883 decoys of Critical Assessment of Prediction of Interactions (CAPRI) targets with an accuracy of 60\%. PPCheck was trained on a 10-fold mixed dataset and tested on a 10-fold mixed test set for hotspot prediction. We obtain an accuracy of 72\%, which is in par with other methods, and a sensitivity of 59\%, which is better than most existing methods available for hotspot prediction that uses similar datasets. Other relevant tests suggest that PPCheck can also be reliably used to identify conserved residues in a protein and to perform computational alanine scanning.

CONCLUSIONS: PPCheck webserver can be successfully used to differentiate native-like and non-native-like docking poses, as generated by docking algorithms. The webserver can also be a convenient platform for calculating residue conservation, for performing computational alanine scanning, and for predicting protein-protein interface hotspots. While PPCheck can differentiate the generated decoys into native-like and non-native-like decoys with a fairly good accuracy, the results improve dramatically when features like conservation and accessibility are included. The method can be successfully used in ranking/scoring the decoys, as obtained from docking algorithms.

}, issn = {1177-9322}, doi = {10.4137/BBI.S25928}, author = {Sukhwal, Anshul and Sowdhamini, Ramanathan} }