Mask blast with a new chemical logic of amino acids for improved protein function prediction.

With the exponential increase in protein sequence data, there is an urgency to acquire a knowledge of function of the millions of sequences, using automated methods with high reliability. Conventional methods for annotating a protein sequence transfer the function of a homologous sequence with known functions based on evolutionary information. Here, we present a newer way of classifying amino acids based on chemical measures and demonstrate that, when integrated with mask BLAST, the chemical properties identified outperform current classifications of amino acids as well as evolutionary measures in function detection.

Toward a Universal Structural and Energetic Model for Prokaryotic Promoters.

With almost no consensus promoter sequence in prokaryotes, recruitment of RNA polymerase (RNAP) to precise transcriptional start sites (TSSs) has remained an unsolved puzzle. Uncovering the underlying mechanism is critical for understanding the principle of gene regulation. We attempted to search the hidden code in ∼16,500 promoters of 12 prokaryotes representing two kingdoms in their structure and energetics. Twenty-eight fundamental parameters of DNA structure including backbone angles, basepair axis, and interbasepair and intrabasepair parameters were used, and information was extracted from x-ray crystallography data. Three parameters (solvation energy, hydrogen-bond energy, and stacking energy) were selected for creating energetics profiles using in-house programs. DNA of promoter regions was found to be inherently designed to undergo a change in every parameter undertaken for the study, in all prokaryotes. The change starts from some distance upstream of TSSs and continues past some distance from TSS, hence giving a signature state to promoter regions. These signature states might be the universal hidden codes recognized by RNAP. This observation was reiterated when randomly selected promoter sequences (with little sequence conservation) were subjected to structure generation; all developed into very similar three-dimensional structures quite distinct from those of conventional B-DNA and coding sequences. Fine structural details at important motifs (viz. -11, -35, and -75 positions relative to TSS) of promoters reveal novel to our knowledge and pointed insights for RNAP interaction at these locations; it could be correlated with how some particular structural changes at the -11 region may allow insertion of RNAP amino acids in interbasepair space as well as facilitate the flipping out of bases from the DNA duplex.

A component analysis of the free energies of folding of 35 proteins: A consensus view on the thermodynamics of folding at the molecular level.

What factors favor protein folding? This is a textbook question. Parsing the experimental free energies of folding/unfolding into diverse enthalpic and entropic components of solute and solvent favoring or disfavoring folding is not an easy task. In this study, we present a computational protocol for estimating the free energy contributors to protein folding semi-quantitatively using ensembles of unfolded and native states generated via molecular dynamics simulations. We tested the methodology on 35 proteins with diverse structural motifs and sizes and found that the calculated free energies correlate well with experiment (correlation coefficient ∼ 0.85), enabling us to develop a consensus view of the energetics of folding. As a more sensitive test of the methodology, we also investigated the free energies of folding of an additional 33 single point mutants and obtained a correlation coefficient of 0.8. A notable observation is that the folding free energy components appear to carry signatures of the fold (SCOP classification) of the protein. © 2017 Wiley Periodicals, Inc.

A homology/ab initio hybrid algorithm for sampling near-native protein conformations.

One of the major challenges for protein tertiary structure prediction strategies is the quality of conformational sampling algorithms, which can effectively and readily search the protein fold space to generate near-native conformations. In an effort to advance the field by making the best use of available homology as well as fold recognition approaches along with ab initio folding methods, we have developed Bhageerath-H Strgen, a homology/ab initio hybrid algorithm for protein conformational sampling. The methodology is tested on the benchmark CASP9 dataset of 116 targets. In 93% of the cases, a structure with TM-score ≥ 0.5 is generated in the pool of decoys. Further, the performance of Bhageerath-H Strgen was seen to be efficient in comparison with different decoy generation methods. The algorithm is web enabled as Bhageerath-H Strgen web tool which is made freely accessible for protein decoy generation (http://www.scfbio-iitd.res.in/software/Bhageerath-HStrgen1.jsp).

NeuroDNet - an open source platform for constructing and analyzing neurodegenerative disease networks.

BACKGROUND: Genetic networks control cellular functions. Aberrations in normal cellular function are caused by mutations in genes that disrupt the fine tuning of genetic networks and cause disease or disorder. However, the large number of signalling molecules, genes and proteins that constitute such networks, and the consequent complexity of interactions, has restrained progress in research elucidating disease mechanisms. Hence, carrying out a systematic analysis of how diseases alter the character of these networks is important. We illustrate this through our work on neurodegenerative disease networks. We created a database, NeuroDNet, which brings together relevant information about signalling molecules, genes and proteins, and their interactions, for constructing neurodegenerative disease networks. DESCRIPTION: NeuroDNet is a database with interactive tools that enables the creation of interaction networks for twelve neurodegenerative diseases under one portal for interrogation and analyses. It is the first of its kind, which enables the construction and analysis of neurodegenerative diseases through protein interaction networks, regulatory networks and Boolean networks. The database has a three-tier architecture - foundation, function and interface. The foundation tier contains the human genome data with 23857 protein-coding genes linked to more than 300 genes reported in clinical studies of neurodegenerative diseases. The database architecture was designed to retrieve neurodegenerative disease information seamlessly through the interface tier using specific functional information. Features of this database enable users to extract, analyze and display information related to a disease in many different ways. CONCLUSIONS: The application of NeuroDNet was illustrated using three case studies. Through these case studies, the construction and analyses of a PPI network for angiogenin protein in amyotrophic lateral sclerosis, a signal-gene-protein interaction network for presenilin protein in Alzheimer's disease and a Boolean network for a mammalian cell cycle was demonstrated. NeuroDNet is accessible at http://bioschool.iitd.ac.in/NeuroDNet/.

Bases immediate upstream of the TATAAT box of the sigma 70 promoter of Escherichia coli significantly influence the activity of a model promoter by altering the bending angle of DNA.

Different workers have found different bases of the spacer of the sigma 70 promoter of Escherichia coli to be important, depending on the base sequence of the two hexameric boxes of the naturally occurring promoter they were working on. Besides, there was no clue as to why particular bases worked better than others in particular positions. This necessitated a fresh look at the spacer region of a model promoter comprising all the consensus promoter elements. Randomisation of the three bases of the spacer in positions -15 to -13 with respect to the transcription initiation site, has elicited more than 50-fold variation in activity of the promoter, the highest and the lowest activities being 14,391(the three bases being GCA) and 264 Miller units (the three bases being AAA) respectively. Pairs of promoters of very similar activities were observed, even when the bases in these three positions were very different. The promoters with similar activities had similar three dimensional structures of the promoter DNA, as determined by molecular dynamics simulations. Randomisation of the three bases in positions -18 to -16 of the promoter that contained the triplet GCA in positions -15 to -13, resulted in promoters with highest activity of 15,759 (the triplet upstream of GCA being TAT) and lowest activity of 1,882 (the triplet upstream of GCA being AAA). Good correlation between the bending angles of the promoter DNAs and promoter activities could be observed, the R2 value being 0.8724. Retardation of electrophoretic mobility of the promoter DNAs correlated well with activity.

Estradiol induces allosteric coupling and partitioning of sex-hormone-binding globulin monomers among conformational states.

Sex-hormone-binding globulin (SHBG) regulates the transport and bioavailability of estradiol. The dynamics of estradiol's binding to SHBG are incompletely understood, although it is believed that estradiol binds to each monomer of SHBG dimer with identical affinity (Kd ∼2 nM). Contrary to the prevalent view, we show that estradiol's binding to SHBG is nonlinear, and the "apparent" Kd changes with varying estradiol and SHBG concentrations. Estradiol's binding to each SHBG monomer influences residues in the ligand-binding pocket of both monomers and differentially alters the conformational and energy landscapes of both monomers. Monomers are not energetically or conformationally equivalent even in fully bound state. Estradiol's binding to SHBG involves bidirectional, inter-monomeric allostery that changes the distribution of both monomers among various energy and conformational states. Inter-monomeric allostery offers a mechanism to extend the binding range of SHBG and regulate hormone bioavailability as estradiol concentrations vary widely during life.

Evaluation of novobiocin and telmisartan for anti-CHIKV activity.

Chikungunya has re-emerged as an epidemic with global distribution and high morbidity, necessitating the need for effective therapeutics. We utilized already approved drugs with a good safety profile used in other diseases for their new property of anti-chikungunya activity. It provides a base for a fast and efficient approach to bring a novel therapy from bench to bedside by the process of drug-repositioning. We utilized an in-silico drug screening with FDA approved molecule library to identify inhibitors of the chikungunya nsP2 protease, a multifunctional and essential non-structural protein required for virus replication. Telmisartan, an anti-hypertension drug, and the antibiotic novobiocin emerged among top hits on the screen. Further, SPR experiments revealed strong in-vitro binding of telmisartan and novobiocin to nsP2 protein. Additionally, small angle x-ray scattering suggested binding of molecules to nsP2 and post-binding compaction and retention of monomeric state in the protein-inhibitor complex. Protease activity measurement revealed that both compounds inhibited nsP2 protease activity with IC50 values in the low micromolar range. More importantly, plaque formation assays could show the effectiveness of these drugs in suppressing virus propagation in host cells. We propose novobiocin and telmisartan as potential inhibitors of chikungunya replication. Further research is required to establish the molecules as antivirals of clinical relevance against chikungunya.

Toward development of generic inhibitors against the 3C proteases of picornaviruses.

Development of novel antivirals, which requires knowledge of the viral life cycle in molecular detail, is a daunting task, involving extensive investments, and frequently resulting in failure. As there exist significant commonalities among virus families in the manner of host interaction, identifying and targeting common rather than specific features may lead to the development of broadly useful antivirals. Here, we have targeted the 3C protease of Hepatitis A Virus (HAV), a feco-orally transmitted virus of the family Picornaviridae, for identification of potential antivirals. The 3C protease is a viable drug target as it is required by HAV, as well as by other picornaviruses, for post-translational proteolysis of viral polyproteins and for inhibiting host innate immune pathways. Computational screening, followed by chemical synthesis and experimental validation resulted in identification of a few compounds which, at low micromolar concentrations, could inhibit HAV 3C activity. These compounds were further tested experimentally against the 3C protease of Human Rhinovirus, another member of the Picornaviridae family, with comparable results. Computational studies on 3C proteases from other members of the picornavirus family have indicated that the compounds identified could potentially be generic inhibitors for picornavirus 3C proteases.

Nonsteroidal estrogen receptor isoform-selective biphenyls.

Estrogen receptor (ER) has been a therapeutic target to treat ER-positive breast cancer, most notably by agents known as selective estrogen receptor modulators (SERMs). However, resistance and severe adverse effects of known drugs gave impetus to the search for newer agents with better therapeutic profile. ERα and ERß are two isoforms sharing 56% identity and having different physiological functions and expressions in various tissues. Only two residues differ in the active sites of the two isoforms motivating us to design isoform-selective ligands. Guided by computational docking and molecular dynamics simulations, we have designed, synthesized, and tested, substituted biphenyl-2,6-diethanones and their derivatives as potential agents targeting ERα. Four of the molecules synthesized exhibited preferential cytotoxicity in ERα+ cell line (MCF-7) compared to ERß+ cell line (MDA-MB-231). Molecular dynamics (MD) in combination with molecular mechanics-generalized Born surface area (MM-GBSA) methods could account for binding selectivity. Further cotreatment and E-screen studies with known ER ligands-estradiol (E2 ) and tamoxifen (Tam)-indicated isoform-selective anti-estrogenicity in ERα+ cell line which might be ER-mediated. ERα siRNA silencing experiments further confirmed the ER selective nature of ligands.

Prediction of functional loss of human angiogenin mutants associated with ALS by molecular dynamics simulations.

Several missense mutations in the coding region of angiogenin (ANG) gene have been identified in Amyotrophic Lateral Sclerosis (ALS) patients. These mutations lead to loss of either ribonucleolytic activity or nuclear translocation activity or both of ANG (protein encoded by ANG gene) causing ALS. We present here a cohesive and comprehensive picture of the molecular origins of functional loss of all ALS associated ANG mutants, emerging via extensive molecular dynamics simulations. Our method effectively predicts that conformational change of His114 results in loss of ribonucleolytic activity and that reduction of solvent accessible surface area of nuclear localization signal residues (31)RRR(33) results in loss of nuclear translocation activity. These predictions hold true, without exception, for all ANG mutants studied and can be employed to infer whether a new ANG mutation is causative of ALS or benign ahead of experimental findings.

ANGDelMut - a web-based tool for predicting and analyzing functional loss mechanisms of amyotrophic lateral sclerosis-associated angiogenin mutations.

ANGDelMut is a web-based tool for predicting the functional consequences of missense mutations in the angiogenin (ANG) protein, which is associated with amyotrophic lateral sclerosis (ALS). Missense mutations in ANG result in loss of either ribonucleolytic activity or nuclear translocation activity or both of these functions, and in turn cause ALS. However, no web-based tools are available to predict whether a newly identified ANG mutation will possibly lead to ALS. More importantly, no web-implemented method is currently available to predict the mechanisms of loss-of-function(s) of ANG mutants. In light of this observation, we developed the ANGDelMut web-based tool, which predicts whether an ANG mutation is deleterious or benign. The user selects certain attributes from the input panel, which serves as a query to infer whether a mutant will exhibit loss of ribonucleolytic activity or nuclear translocation activity or whether the overall stability will be affected. The output states whether the mutation is deleterious or benign, and if it is deleterious, gives the possible mechanism(s) of loss-of-function. This web-based tool, freely available at http://bioschool.iitd.ernet.in/DelMut/, is the first of its kind to provide a platform for researchers and clinicians, to infer the functional consequences of ANG mutations and correlate their possible association with ALS ahead of experimental findings.

Fast prediction of deleterious angiogenin mutations causing amyotrophic lateral sclerosis.

Certain single nucleotide polymorphisms causing missense mutations in angiogenin result in its loss-of-function and onset of amyotrophic lateral sclerosis (ALS). Although several such associations are reported across diverse ethnic groups, no method is available for predicting if a new mutation is deleterious. We present here a fast molecular dynamics based method for determining the mechanisms of functional loss caused by mutations, and attributes to ascertain whether a mutation causes ALS.

Mechanisms of loss of functions of human angiogenin variants implicated in amyotrophic lateral sclerosis.

BACKGROUND: Mutations in the coding region of angiogenin (ANG) gene have been found in patients suffering from Amyotrophic Lateral Sclerosis (ALS). Neurodegeneration results from the loss of angiogenic ability of ANG (protein coded by ANG). In this work, we performed extensive molecular dynamics (MD) simulations of wild-type ANG and disease associated ANG variants to elucidate the mechanism behind the loss of ribonucleolytic activity and nuclear translocation activity, functions needed for angiogenesis. METHODOLOGY/PRINCIPAL FINDINGS: MD simulations were carried out to study the structural and dynamic differences in the catalytic site and nuclear localization signal residues between WT-ANG (Wild-type ANG) and six mutants. Variants K17I, S28N, P112L and V113I have confirmed association with ALS, while T195C and A238G single nucleotide polymorphisms (SNPs) encoding L35P and K60E mutants respectively, have not been associated with ALS. Our results show that loss of ribonucleolytic activity in K17I is caused by conformational switching of the catalytic residue His114 by 99°. The loss of nuclear translocation activity of S28N and P112L is caused by changes in the folding of the residues (31)RRR(33) that result in the reduction in solvent accessible surface area (SASA). Consequently, we predict that V113I will exhibit loss of angiogenic properties by loss of nuclear translocation activity and L35P by loss of both ribonucleolytic activity and nuclear translocation activity. No functional loss was inferred for K60E. The MD simulation results were supported by hydrogen bond interaction analyses and molecular docking studies. CONCLUSIONS/SIGNIFICANCE: Conformational switching of catalytic residue His114 seems to be the mechanism causing loss of ribonucleolytic activity and reduction in SASA of nuclear localization signal residues (31)RRR(33) results in loss of nuclear translocation activity in ANG mutants. Therefore, we predict that L35P mutant, would exhibit loss of angiogenic functions, and hence would correlate with ALS while K60E would not show any loss.