Cryptic intermediates and metastable states of proteins as predicted by OneG computational method.

Understanding structural excursions of proteins under folding conditions is crucial to map energy landscapes of proteins. In the present study, OneG computational tool has been used for analyzing possible existence of cryptic intermediates and metastable states of 26 proteins for which three prerequisite inputs of the OneG such as atomic coordinates of proteins, free energy of unfolding (ΔGU) and free energy of exchange (ΔGHX) determined in the absence of denaturant were available during the course of the study. The veraciousness of the tool on predicting the partially folded states of the proteins has been comprehensively described using experimental data available for 15 of the 26 proteins. Meanwhile, possible existence of partially structured states in the folding pathways of 11 other proteins has also been delineated as predicted by the OneG. In addition to mapping the folding pathways of proteins, the salient merits of the tool on systematically addressing the discrepancy between the ΔGU and the ΔGHX of the proteins have also been dealt.Communicated by Ramaswamy H. Sarma.

Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers.

Efficient and rapid prediction of domain regions from amino acid sequence information alone is often required for swift structural and functional characterization of large multi-domain proteins. Here we introduce Fast H-DROP, a thirty times accelerated version of our previously reported H-DROP (Helical Domain linker pRediction using OPtimal features), which is unique in specifically predicting helical domain linkers (boundaries). Fast H-DROP, analogously to H-DROP, uses optimum features selected from a set of 3000 ones by combining a random forest and a stepwise feature selection protocol. We reduced the computational time from 8.5 min per sequence in H-DROP to 14 s per sequence in Fast H-DROP on an 8 Xeon processor Linux server by using SWISS-PROT instead of Genbank non-redundant (nr) database for generating the PSSMs. The sensitivity and precision of Fast H-DROP assessed by cross-validation were 33.7 and 36.2%, which were merely ~2% lower than that of H-DROP. The reduced computational time of Fast H-DROP, without affecting prediction performances, makes it more interactive and user-friendly. Fast H-DROP and H-DROP are freely available from http://domserv.lab.tuat.ac.jp/ .

In silico methods for designing antagonists to anti-apoptotic members of Bcl-2 family proteins.

Designing antagonists to anti-apoptotic proteins of Bcl-2 family has become an important strategy in cancer chemotherapy. Using experimental techniques and computational methods, a few numbers of lead inhibitors to the antiapoptotic proteins have been reported in the literature and a few of them are under clinical trials. In this review, the lead inhibitors designed using in silico methodologies are exclusively covered, systematically organized and critically evaluated. An orchestrated in silico strategy for screening and identifying efficient antagonists to the anti-apoptotic proteins has also been brought into fore.

OneG: a computational tool for predicting cryptic intermediates in the unfolding kinetics of proteins under native conditions.

Understanding the relationships between conformations of proteins and their stabilities is one key to address the protein folding paradigm. The free energy change (ΔG) of unfolding reactions of proteins is measured by traditional denaturation methods and native hydrogen-deuterium (H/D) exchange methods. However, the free energy of unfolding (ΔG(U)) and the free energy of exchange (ΔG(HX)) of proteins are not in good agreement, though the experimental conditions of both methods are well matching to each other. The anomaly is due to any one or combinations of the following reasons: (i) effects of cis-trans proline isomerisation under equilibrium unfolding reactions of proteins (ii) inappropriateness in accounting the baselines of melting curves (iii) presence of cryptic intermediates, which may elude the melting curve analysis and (iv) existence of higher energy metastable states in the H/D exchange reactions of proteins. Herein, we have developed a novel computational tool, OneG, which accounts the discrepancy between ΔG(U) and ΔG(HX) of proteins by systematically accounting all the four factors mentioned above. The program is fully automated and requires four inputs: three-dimensional structures of proteins, ΔG(U), ΔG(U)(*) and residue-specific ΔG(HX) determined under EX2-exchange conditions in the absence of denaturants. The robustness of the program has been validated using experimental data available for proteins such as cytochrome c and apocytochrome b(562) and the data analyses revealed that cryptic intermediates of the proteins detected by the experimental methods and the cryptic intermediates predicted by the OneG for those proteins were in good agreement. Furthermore, using OneG, we have shown possible existence of cryptic intermediates and metastable states in the unfolding pathways of cardiotoxin III and cobrotoxin, respectively, which are homologous proteins. The unique application of the program to map the unfolding pathways of proteins under native conditions have been brought into fore and the program is publicly available at http://sblab.sastra.edu/oneg.html.

In silico analysis reveals 75 members of mitogen-activated protein kinase kinase kinase gene family in rice.

Mitogen-Activated Protein Kinase Kinase Kinases (MAPKKKs) are important components of MAPK cascades, which are universal signal transduction modules and play important role in plant growth and development. In the sequenced Arabidopsis genome 80 MAPKKKs were identified and currently being analysed for its role in different stress. In rice, economically important monocot cereal crop only five MAPKKKs were identified so far. In this study using computational analysis of sequenced rice genome we have identified 75 MAPKKKs. EST hits and full-length cDNA sequences (from KOME or Genbank database) of 75 MAPKKKs supported their existence. Phylogenetic analyses of MAPKKKs from rice and Arabidopsis have classified them into three subgroups, which include Raf, ZIK and MEKK. Conserved motifs in the deduced amino acid sequences of rice MAPKKKs strongly supported their identity as members of Raf, ZIK and MEKK subfamilies. Further expression analysis of the MAPKKKs in MPSS database revealed that their transcripts were differentially regulated in various stress and tissue-specific libraries.