Molecular dynamics simulation-based trinucleotide and tetranucleotide level structural and energy characterization of the functional units of genomic DNA.

Genomes of most organisms on earth are written in a universal language of life, made up of four units - adenine (A), thymine (T), guanine (G), and cytosine (C), and understanding the way they are put together has been a great challenge to date. Multiple efforts have been made to annotate this wonderfully engineered string of DNA using different methods but they lack a universal character. In this article, we have investigated the structural and energetic profiles of both prokaryotes and eukaryotes by considering two essential genomic sites, viz., the transcription start sites (TSS) and exon-intron boundaries. We have characterized these sites by mapping the structural and energy features of DNA obtained from molecular dynamics simulations, which considers all possible trinucleotide and tetranucleotide steps. For DNA, these physicochemical properties show distinct signatures at the TSS and intron-exon boundaries. Our results firmly convey the idea that DNA uses the same dialect for prokaryotes and eukaryotes and that it is worth going beyond sequence-level analyses to physicochemical space to determine the functional destiny of DNA sequences.

Intron exon boundary junctions in human genome have in-built unique structural and energetic signals.

Precise identification of correct exon-intron boundaries is a prerequisite to analyze the location and structure of genes. The existing framework for genomic signals, delineating exon and introns in a genomic segment, seems insufficient, predominantly due to poor sequence consensus as well as limitations of training on available experimental data sets. We present here a novel concept for characterizing exon-intron boundaries in genomic segments on the basis of structural and energetic properties. We analyzed boundary junctions on both sides of all the exons (3 28 368) of protein coding genes from human genome (GENCODE database) using 28 structural and three energy parameters. Study of sequence conservation at these sites shows very poor consensus. It is observed that DNA adopts a unique structural and energy state at the boundary junctions. Also, signals are somewhat different for housekeeping and tissue specific genes. Clustering of 31 parameters into four derived vectors gives some additional insights into the physical mechanisms involved in this biological process. Sites of structural and energy signals correlate well to the positions playing important roles in pre-mRNA splicing.

A small molecule targeting hepatitis B surface antigen inhibits clinically relevant drug-resistant hepatitis B virus.

BACKGROUND: Currently approved oral antivirals for chronic HBV infection target the reverse transcriptase (RT) domain of the HBV polymerase. Emergence of drug resistance has been reported in a small proportion of chronic HBV patients on prolonged treatment with antivirals. We recently reported ZINC20451377, a small molecule targeting hepatitis B surface antigen (HBsAg) that effectively inhibits both WT HBV and tenofovir-resistant HBV. Due to the partial overlap between the RT domain and HBsAg, drug-resistant mutants are associated with corresponding mutations in HBsAg. OBJECTIVES: To evaluate the efficacy of ZINC20451377 against nine clinically relevant drug-resistant HBV mutants that lead to simultaneous mutations in the overlapping HBsAg gene. METHODS: Huh7 cells were transfected with 1.2× HBV replicons corresponding to WT HBV or drug-resistant HBV mutants and treated with different concentrations of ZINC20451377. We assessed the IC50 values of ZINC20451377 for HBsAg levels in the culture supernatants using ELISAs. HBV secretion was measured by immunocapture of secreted virions followed by real-time PCR quantitation of virion-associated DNA. RESULTS: ZINC20451377 led to a dose-dependent inhibition of secreted HBsAg encoded by WT HBV and all nine drug-resistant mutants tested and the IC50 values were in the low micromolar range. ZINC20451377 inhibited HBV secretion from drug-resistant mutants except for mutants harbouring the rtL180M + rtM204V (MV) mutation. CONCLUSIONS: The small molecule ZINC20451377 inhibits HBsAg and virion secretion in some of the clinically relevant drug-resistant HBV mutants. ZINC20451377 has a modest overall effect, and it was not effective against the MV mutants (lamivudine- and entecavir-resistant mutants).

A novel method SEProm for prokaryotic promoter prediction based on DNA structure and energetics.

MOTIVATION: Despite conservation in general architecture of promoters and protein-DNA interaction interface of RNA polymerases among various prokaryotes, identification of promoter regions in the whole genome sequences remains a daunting challenge. The available tools for promoter prediction do not seem to address the problem satisfactorily, apparently because the biochemical nature of promoter signals is yet to be understood fully. Using 28 structural and 3 energetic parameters, we found that prokaryotic promoter regions have a unique structural and energy state, quite distinct from that of coding regions and the information for this signature state is in-built in their sequences. We developed a novel promoter prediction tool from these 31 parameters using various statistical techniques. RESULTS: Here, we introduce SEProm, a novel tool that is developed by studying and utilizing the in-built structural and energy information of DNA sequences, which is applicable to all prokaryotes including archaea. Compared to five most recent, diverged and current best available tools, SEProm performs much better, predicting promoters with an 'F-value' of 82.04 and 'Precision' of 81.08. The next best 'F-value' was obtained with PromPredict (72.14) followed by BProm (68.37). On the basis of 'Precision' value, the next best 'Precision' was observed for Pepper (75.39) followed by PromPredict (72.01). SEProm maintained the lead even when comparison was done on two test organisms (not involved in training for SEProm). AVAILABILITY AND IMPLEMENTATION: The software is freely available with easy to follow instructions (www.scfbio-iitd.res.in/software/TSS_Predict.jsp). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Stimulation of heat shock protein 90 chaperone function through binding of a novobiocin analog KU-32.

Heat shock protein 90 (Hsp90) is a eukaryotic chaperone responsible for the folding and functional activation of numerous client proteins, many of which are oncoproteins. Thus, Hsp90 inhibition has been intensely pursued, resulting in the development of many potential Hsp90 inhibitors, not all of which are well-characterized. Hsp90 inhibitors not only abrogate its chaperone functions, but also could help us gain insight into the structure-function relationship of this chaperone. Here, using biochemical and cell-based assays along with isothermal titration calorimetry, we investigate KU-32, a derivative of the Hsp90 inhibitor novobiocin (NB), for its ability to modulate Hsp90 chaperone function. Although NB and KU-32 differ only slightly in structure, we found that upon binding, they induce completely opposite conformational changes in Hsp90. We observed that NB and KU-32 both bind to the C-terminal domain of Hsp90, but surprisingly, KU-32 stimulated the chaperone functions of Hsp90 via allosteric modulation of its N-terminal domain, responsible for the chaperone's ATPase activity. In vitro and in silico studies indicated that upon KU-32 binding, Hsp90 undergoes global structural changes leading to the formation of a "partially closed" intermediate that selectively binds ATP and increases ATPase activity. We also report that KU-32 promotes HeLa cell survival and enhances the refolding of an Hsp90 substrate inside the cell. This discovery explains the effectiveness of KU-32 analogs in the management of neuropathies and may facilitate the design of molecules that promote cell survival by enhancing Hsp90 chaperone function and reducing the load of misfolded proteins in cells.

Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.

Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein-ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-metallo and metallo PL complexes. Bappl+ outperforms other state-of-the-art scoring functions, achieving a high Pearson correlation coefficient of up to ~ 0.76 with low standard deviations. The biggest contributors to the increased performance are the use of a machine-learning model and the enlarged training dataset. We have also evaluated the performance of Bappl+ on target-specific proteins, which highlighted the limitations of our function and provides a way for further improvements. We believe that Bappl+ methodology could prove valuable in ranking candidate molecules against a target metallo or non-metallo protein by reliably predicting their binding affinities, thus helping in the drug discovery process.

Active repurposing of drug candidates for melanoma based on GWAS, PheWAS and a wide range of omics data.

BACKGROUND: Drug repurposing is a swift, safe, and cheap drug discovery method. Melanoma disorders present low survival and high mortality rates and are challenging to diagnose and treat. Moreover, there is a high volume of worldwide investigations that are attempting to find melanoma-related genes of influence, which can be identified as responsive targets for reliable treatment. METHOD: In this study, we used a wide range of data analyses to analyze over 1100 genes and proteins of influence with respect to cutaneous malignant melanoma. Our analysis included various investigational results from genome- and phenome-wide association studies (GWAS and PheWAS, respectively), biomedical, transcriptomic, and metabolomic datasets. We then researched the DrugBank for potential melanoma targets from the selected list. We excluded known melanoma targets to obtain a list of druggable proteins. We performed a precise analysis of the drugs' pathogenesis and checked the expression profiles of the selected drugs having high associations with known anti-melanoma drugs. RESULT: We found 35 drugs that interacted with 20 unique targets. These drugs appear to have high melanoma treatment potentials. We confirmed our results with previous studies and found supporting references for 30 of these drugs. In conclusion, this investigation can be applied to various diseases for the efficient and economical repurposing of various drug compounds. For further validation, the results may be applicable for in vivo tests and clinical trials.

C5' omitted DNA enhances bendability and protein binding.

Protein-DNA interactions are of great biological importance. The specificity and strength of these intimate contacts are crucial in the proper functioning of a cell, wherein the role of DNA dynamic bendability has been a matter of discussion. We relate DNA bendability to protein binding by introducing some simple modifications in the DNA structure. We removed C5' carbon in first modified structure and the second has an additional carbon between C3' and 3'-OH, hereby pronounced as C(-) and C(+) nucleic acids respectively. We observed that C(+) nucleic acid retains B-DNA duplex as seen by means of 500 ns long molecular dynamics (MD) simulations, structural and energetic calculations, while C(-) nucleic acid attains a highly bend structure. We transferred these observations to a protein-DNA system in order to monitor as to what extent the bendability enhances the protein binding. The energetics of binding is explored by performing 100 ns long MD simulations on control and modified DNA-protein complexes followed by running MM-PBSA/GBSA calculations on the resultant structures. It is observed that C(+) nucleic acid has protein binding in close correspondence to the control system (∼-14 kcal/mol) due to their relatable structure, while the C(-) nucleic acid displayed high binding to the protein (∼-18 kcal/mol). DelPhi based calculations reveal that the high binding could be the result of enhanced electrostatic interactions caused by exposed bases in the bend structure for protein recognition. Such modified oligonucleotides, due to their improved binding to protein and resistance to nuclease degradation, have a great therapeutic value.

Design, synthesis and glycosidase inhibition studies of novel triazole fused iminocyclitol-δ-lactams.

Synthesis of novel triazole fused iminocyclitol-δ-lactams is described. The synthetic sequence involves the intermolecular [3 + 2] cycloaddition reaction of five-membered iminocyclitol derived azides with diethylacetylene dicarboxylate followed by intramolecular lactamisation, decarboxylation/reduction and final deprotection. Compound 3 is found to be a selective inhibitor of α-glucosidase from baker's yeast while two other compounds (2 and 4) that possess an additional hydroxymethyl group in the triazole ring are selective against ß-galactosidase from E. coli. Docking studies suggest the significance of the lactam carbonyl group for effective binding of these inhibitors with the active sites through hydrogen bonding.

Physico-chemical fingerprinting of RNA genes.

We advance here a novel concept for characterizing different classes of RNA genes on the basis of physico-chemical properties of DNA sequences. As knowledge-based approaches could yield unsatisfactory outcomes due to limitations of training on available experimental data sets, alternative approaches that utilize properties intrinsic to DNA are needed to supplement training based methods and to eventually provide molecular insights into genome organization. Based on a comprehensive series of molecular dynamics simulations of Ascona B-DNA consortium, we extracted hydrogen bonding, stacking and solvation energies of all combinations of DNA sequences at the dinucleotide level and calculated these properties for different types of RNA genes. Considering ∼7.3 million mRNA, 255 524 tRNA, 40 649 rRNA (different subunits) and 5250 miRNA, 3747 snRNA, gene sequences from 9282 complete genome chromosomes of all prokaryotes and eukaryotes available at NCBI, we observed that physico-chemical properties of different functional units on genomic DNA differ in their signatures.

Where Informatics Lags Chemistry Leads.

The fact that amino acid sequences dictate the tertiary structures of proteins has been known for more than five decades. While the molecular pathways to tertiary structure are still being worked out, with the axiom that similar sequences adopt similar structures, computational methods are being developed continually in parallel, utilizing the Protein Data Bank structural repository and homologue detection strategies to predict structures of sequences of interest. The success of this approach is limited by the ability to unravel the hidden similarities among amino acid sequences. We consider here the 20 amino acids as a complete set of chemical templates in the physicochemical space of proteins and propose a new structural and chemical classification of amino acids. An integration of this perspective into the conventional evolutionary methods of similarity detection leads to an unprecedented increase in the accuracy in homologue detection, resulting in improved protein structure prediction. The performance is validated on a large data set of 11716 unique proteins, and the results are benchmarked against conventional methods. The availability of good quality protein structures helps in structure-based drug design endeavors and in establishing protein structure-function correlations.

A DNA intercalation methodology for an efficient prediction of ligand binding pose and energetics.

MOTIVATION: Drug intercalation is an important strategy for DNA inhibition which is often employed in cancer chemotherapy. Despite its high significance, the field is characterized by limited success in identification of novel intercalator molecules and lack of automated and dedicated drug-DNA intercalation methodology. RESULTS: We report here a novel intercalation methodology (christened ' Intercalate' ) for predicting both the structures and energetics of DNA-intercalator complexes, covering the processes of DNA unwinding and (non-covalent) binding. Given a DNA sequence and intercalation site information, Intercalate generates the 3D structure of DNA, creates the intercalation site, performs docking at the intercalation site and evaluates DNA-intercalator binding energy in an automated way. The structures and energetics of the DNA-intercalator complexes produced by Intercalate methodology are seen to be in good agreement with experiment. The dedicated attempt made in developing a drug-DNA intercalation methodology (compatible with its mechanism) with high accuracy should prove useful in the discovery of potential intercalators for their use as anticancers, antibacterials or antivirals. AVAILABILITY AND IMPLEMENTATION: http://www.scfbio-iitd.res.in/intercalate/. CONTACT: anjali@scfbio-iitd.res.in or bjayaram@chemistry.iitd.ac.in. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A computational protocol for the discovery of lead molecules targeting DNA unique to pathogens.

With the rapid emergence of drug resistant pathogens, it has become imperative to develop alternative medications as well as find new drug targets to overcome this crisis. Hence, this has become prime focus of several academic laboratories and pharmaceutical companies. Here, we report a computational protocol for identifying unique DNA sequence(s) in the pathogen which is absent in human and related non-pathogenic strains of the microbe. In order to use the unique sequence as drug target, the protocol, in the second step, uses virtual screening against a million compound library to identify candidate small molecules which can bind to these unique DNA targets in the pathogen only. Theoretically the molecules identified after screening should not bind to human DNA. This methodology is demonstrated on Mycobacterium tuberculosis H37Rv, wherein a new octamer sequence present only in H37Rv has been identified and a few candidate small molecules as potential drug have been proposed. Being fast and cost effective, this protocol could be of importance in generating new potential drug candidates against infectious organisms for further experimental studies. This methodology is freely available at http://www.scfbio-iitd.res.in/PSDDF/.

ProTSAV: A protein tertiary structure analysis and validation server.

Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of individual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at http://www.scfbio-iitd.res.in/software/proteomics/protsav.jsp.

Design and characterization of symmetric nucleic acids via molecular dynamics simulations.

Asymmetry (5'→3') associated with each strand of the deoxyribonucleic acid (DNA) is inherent in the sugar-phosphate backbone connectivity and is essential for replication and transcription. We note that this asymmetry is due to one single chemical bond (C3' to C2' ) in each nucleotide unit, and the absence of this bond results in directionally symmetric nucleic acids. We also discovered that creation of an extra chemical bond (C5' to C2' ) can lead to a symmetric backbone. Keeping their potential synthetic and therapeutic interest in mind, we designed a few novel symmetric nucleic acids. We investigated their conformational stability and flexibility via detailed all atom explicit solvent 100-ns long molecular dynamics simulations and compared the resulting structures with that of regular B-DNA. Quite interestingly, some of the symmetric nucleic acids retain the overall double helical structure indicating their potential for integration in physiological DNA without causing major structural perturbations.

Protein folding is a convergent problem!

Protein folding, tagged as a grand challenge/NP hard problem, has been an open area of research in diverse fields. Exploring folding from the configurational volume perspective in terms of phi (ϕ), psi(ψ) backbone dihedral angles, we asked ourselves a fundamental question as to when do the neighborhood effects on the allowed ϕ, ψ values of each residue take over to assure convergence of proteins to their observed unique tertiary structures. A mapping of the higher order steric correlations beyond Ramachandran plots from ∼43612 protein structures comprising ∼26.5 million amino acid residues reveals that conformational restrictions on allowed ϕ, ψ values of each amino acid residue due to the N and C terminal neighbors - essentially a consideration of the sterically allowed regions of a tripeptide - ensure convergence of the configurational volume.

Structure guided design of potential inhibitors of human calcium-calmodulin dependent protein kinase IV containing pyrimidine scaffold.

Calmodulin dependent protein kinase IV (CAMKIV) belongs to the serine/threonine protein kinase family and considered as an encouraging target for the development of novel anticancer agents. The interaction and binding behavior of three designed inhibitors of human CAMKIV, containing pyrimidine scaffold, was monitored by in vitro fluorescence titration and molecular docking calculations under physiological condition. In silico docking studies were performed to screen several compounds containing pyrimidine scaffold against CAMKIV. Molecular docking calculation predicted the binding of these ligands in active-site cavity of the CAMKIV structure correlating such interactions with a probable inhibition mechanism. Finally, three active pyrimidine substituted compounds (molecules 1-3) have been successfully synthesized and characterized by (1)H and (13)C NMR. Molecule 3 is showing very high binding-affinity for the CAMKIV, with a binding constant of 2.2×10(8), M(-1) (±0.20). All three compounds are nontoxic to HEK293 cells up to 50 µM. The cell proliferation inhibition study showed that the molecule 3 has lowest IC50 value (46±1.08 µM). The theoretical and experimental observations are significantly correlated. This study reveals some important observations to generate an improved pyrimidine based compound that holds promise as a therapeutic agent for the treatment of cancer and neurodegenerative diseases.

Development of cyanopyridine-triazine hybrids as lead multitarget anti-Alzheimer agents.

A series of new cyanopyridine-triazine hybrids were designed, synthesized and screened as multitargeted anti-Alzheimer's agents. These molecules were designed while using computational techniques and were synthesized via a feasible concurrent synthetic route. Inhibition potencies of synthetic compounds 4a-4h against cholinesterases, Aß1-42 disaggregation, oxidative stress, cytotoxicity, and neuroprotection against Aß1-42-induced toxicity of the synthesized compounds were evaluated. Compounds 4d and 4h showed promising inhibitory activity on acetylcholinesterase (AChE) with IC50 values 0.059 and 0.080µM, respectively, along with good inhibition selectivity against AChE over butyrylcholinesterase (BuChE). Molecular modelling studies revealed that these compounds interacted simultaneously with the catalytic active site (CAS) and the peripheral anionic site (PAS) of AChE. The mixed type inhibition of compound 4d further confirmed their dual binding nature in kinetic studies. Furthermore, the results from neuroprotection studies of most potent compounds 4d and 4h indicate that these derivatives can reduce neuronal death induced by H2O2-mediated oxidative stress and Aß1-42 induced cytotoxicity. In addition, in silico analysis of absorption, distribution, metabolism and excretion (ADME) profile of best compounds 4d and 4h revealed that they have drug like properties. Overall, these cyanopyridine-triazine hybrids can be considered as a candidate with potential impact for further pharmacological development in Alzheimer's therapy.

µABC: a systematic microsecond molecular dynamics study of tetranucleotide sequence effects in B-DNA.

We present the results of microsecond molecular dynamics simulations carried out by the ABC group of laboratories on a set of B-DNA oligomers containing the 136 distinct tetranucleotide base sequences. We demonstrate that the resulting trajectories have extensively sampled the conformational space accessible to B-DNA at room temperature. We confirm that base sequence effects depend strongly not only on the specific base pair step, but also on the specific base pairs that flank each step. Beyond sequence effects on average helical parameters and conformational fluctuations, we also identify tetranucleotide sequences that oscillate between several distinct conformational substates. By analyzing the conformation of the phosphodiester backbones, it is possible to understand for which sequences these substates will arise, and what impact they will have on specific helical parameters.

D2N: Distance to the native.

Root-mean-square-deviation (RMSD), of computationally-derived protein structures from experimentally determined structures, is a critical index to assessing protein-structure-prediction-algorithms (PSPAs). The development of PSPAs to obtain 0Å RMSD from native structures is considered central to computational biology. However, till date it has been quite challenging to measure how far a predicted protein structure is from its native - in the absence of a known experimental/native structure. In this work, we report the development of a metric "D2N" (distance to the native) - that predicts the "RMSD" of any structure without actually knowing the native structure. By combining physico-chemical properties and known universalities in spatial organization of soluble proteins to develop D2N, we demonstrate the ability to predict the distance of a proposed structure to within ±1.5Ǻ error with a remarkable average accuracy of 93.6% for structures below 5Ǻ from the native. We believe that this work opens up a completely new avenue towards assigning reliable structures to whole proteomes even in the absence of experimentally determined native structures. The D2N tool is freely available at http://www.scfbio-iitd.res.in/software/d2n.jsp.