Abstract Developments in the field of wireless networks have led to the phase where it has now be... more Abstract Developments in the field of wireless networks have led to the phase where it has now become important to offer the members connected in a wireless network with a secure and efficient group key management system for accessing numerous services. A secure ...
In biological macromolecules, structural patterns (motifs) are often repeated across different mo... more In biological macromolecules, structural patterns (motifs) are often repeated across different molecules. Detection of these common motifs in a new molecule can provide useful clues to the functional properties of such a molecule. We formulate the problem of identifying a given structural motif (pattern) in a target protein (example) and discuss the notion of complete matches vis-a-vis partial matches. We describe the precise error criterion that has to be minimized and also discuss different metrics for evaluating the quality of partial matches. Secondly, we present a new polynomial time algorithm for the problem of matching a given motif in a target protein. We also use the sequence and (if available) secondary structure information to annotate the different points in motif and the target protein, thus reducing the search space size. Our algorithm guarantees the detection of a perfect match, if present. Even otherwise, the algorithm computes very good matches. Unlike other methods, the error minimized by our algorithm directly translates to root mean square deviation (RMSD), the most commonly accepted metric for structure matching in biological macromolecules. The algorithm does not involve any preprocessing and is suitable for the detection of both small and large motifs in the target protein. We also present experiments exploring the quality of matches found by the algorithm. We examine its performance in matching (both full and partial) active sites in proteins.
N-Heterocyclic carbenes (NHC) are efficient catalysts for transesterification/acylation reactions... more N-Heterocyclic carbenes (NHC) are efficient catalysts for transesterification/acylation reactions involving secondary alcohols. The catalytic transformations are carried out employing low catalyst loadings in convenient reaction times at room temperature.
Organo-phosphorus compounds S 0080 Synthesis of Phosphorus Esters by Transesterification Mediated... more Organo-phosphorus compounds S 0080 Synthesis of Phosphorus Esters by Transesterification Mediated by N-Heterocyclic Carbenes (NHCs). -N-heterocyclic carbenes, which are versatile nucleophilic organic catalysts, are shown to mediate the transesterification of phosphorus ester (II) under mild conditions; imidazolium salts can also be employed as pre-catalysts. -(SINGH, R.; NOLAN*, S. P.; Chem. Commun. (Cambridge) 2005, 43, 5456-5458; Dep. Chem., Univ. New Orleans, New Orleans, LA 70148, USA; Eng.) -M. Paetzel 12-177
Palladium-catalyzed reactions of aryl bromides with various olefins involving Pd(II)/diazabutadie... more Palladium-catalyzed reactions of aryl bromides with various olefins involving Pd(II)/diazabutadiene (DAB-R) systems have been investigated. The scope of a coupling process using Pd(II) sources and an a-diimine as ligand in the presence of Cs 2 CO 3 as base was tested using various substrates. The Pd(OAc) 2 /DAB-Cy (1, DAB-Cy 0/1,4-dicyclohexyl-diazabutadiene) system presents the highest activity with respect to electron-neutral and electron-deficient aryl bromides in coupling with electron rich olefins. The synthesis and X-ray characterization of a Pd(II)-diazabutadiene ligand is reported. Extensive optimization experiments showed that another Pd(II) source, Pd(acac) 2 (acac 0/acetylacetonate), proved to activate aryl bromides at high temperatures, low catalyst loadings when the appropriate concentration of n Bu 4 NBr additive was employed. The effect of the DAB-Cy ligand is important at very low catalyst loadings and high temperatures. Pd(acac) 2 and Pd(acac) 2 /DAB-Cy precatalysts were very effective for the arylation of various olefins with aryl bromides with respect to reaction rate, catalyst loadings, and functional group tolerance. #
Thermal reactions between [RuCl 2 (diene)] n (diene ) 2,5-norbornadiene, nbd; 1,5-cyclooctadiene,... more Thermal reactions between [RuCl 2 (diene)] n (diene ) 2,5-norbornadiene, nbd; 1,5-cyclooctadiene, cod) with an excess of N,N,N′,N′-tetramethylethylene diamine (tmeda) afforded derivatives [RuCl 2 (diene)(tmeda)] (diene ) nbd, 1; cod, 2) as a mixture of cis and trans isomers. When thermolysis was performed under H 2 mixtures of hydride species [RuCl(H)(diene)(tmeda)] (diene ) nbd, 3; cod, 4) and the bis-tmeda adduct trans-[RuCl 2 (tmeda) 2 ] (5) were obtained in different ratios depending upon the reaction conditions and reaction times. Heating polymeric Ru(II) precursors in toluene in the presence of a 5-fold excess of the bulkier N,N,N′,N′-tetraethylethylene diamine (teeda) resulted in a rare diamine dealkylation process with formation of trans-[RuCl 2 (nbd)(Et 2 NCH 2 CH 2 NHEt)] (6) and trans-[RuCl 2 (cod)(EtHNCH 2 CH 2 NHEt)] (7) in high yields. The presence of N−H functionalities in the coordinated diamine ligands of 6 and 7 was unambiguously established by single-crystal X-ray diffraction studies. The dealkylation process of the teeda ligand seems to proceed intramolecularly as shown by solution NMR studies performed with the soluble Ru(II) precursors trans-[RuCl 2 (amine) 2 (diene)] (diene ) nbd, amine ) morpholine, 9; diene ) cod, amine ) Et 2 NH, 10). The above complexes [RuCl 2 (diene)(diamine)] have been tested as precatalysts in the hydrogenation of ketones both for transfer as well as direct hydrogenation, the latter route being the most effective.
This report provides a critical overview of recent developments in the use of N-heterocyclic carb... more This report provides a critical overview of recent developments in the use of N-heterocyclic carbenes (NHCs) with transition metals. For these NHC ligand-containing complexes, an analysis is focused on their performance and scope in catalysis. There is also an increasing interest in the role of nucleophilic carbenes as organocatalysts; the latest advances in applications of NHCs in organocatalysis are also reviewed.
Simple Imidazol-2-ylidene)-Pd-acetate Complexes as Effective Precatalysts for Sterically Hindered... more Simple Imidazol-2-ylidene)-Pd-acetate Complexes as Effective Precatalysts for Sterically Hindered Suzuki-Miyaura Couplings. -A convenient protocol for the preparation of the title complexes is developed. The coupling reactions are successfully carried out for a broad spectrum of boronic acids and alkyl/aryl halides. -(SINGH, R.; VICIU, M. S.; KRAMAREVA, N.; NAVARRO, O.; NOLAN*, S. P.; Org. Lett. 7 (2005) 9, 1829-1832; Dep. Chem., Univ. New Orleans, New Orleans, LA 70148, USA; Eng.) -Y. Steudel 37-090
We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) ... more We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to maximize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem— identifying many possible alignments, each corresponding to a local region of similarity. IsoRank is guided by the intuition that a protein should be matched with a protein in the other network if and only if the neighbors of the two proteins can also be well matched. We encode this intuition as an eigenvalue problem, in a manner analogous to Google’s PageRank method. We use IsoRank to compute the first known global alignment between the S. cerevisiae and D. melanogaster PPI networks. The common subgraph has 1420 edges and describes conserved functional components between the two species. Comparisons of our results with those of a well-known algorithm for local network alignment indicate that the globally optimized alignment resolves ambiguity introduced by multiple local alignments. Finally, we interpret the results of global alignment to identify functional orthologs between yeast and fly; our functional ortholog prediction method is much simpler than a recently proposed approach and yet provides results that are more comprehensive.
We introduce a computational method to predict and annotate the catalytic residues of a protein u... more We introduce a computational method to predict and annotate the catalytic residues of a protein using only its sequence information, so that we describe both the residues' sequence locations (prediction) and their specific biochemical roles in the catalyzed reaction (annotation). While knowing the chemistry of an enzyme's catalytic residues is essential to understanding its function, the challenges of prediction and annotation have remained difficult, especially when only the enzyme's sequence and no homologous structures are available. Our sequence-based approach follows the guiding principle that catalytic residues performing the same biochemical function should have similar chemical environments; it detects specific conservation patterns near in sequence to known catalytic residues and accordingly constrains what combination of amino acids can be present near a predicted catalytic residue. We associate with each catalytic residue a short sequence profile and define a Kullback-Leibler (KL) distance measure between these profiles, which, as we show, effectively captures even subtle biochemical variations. We apply the method to the class of glycohydrolase enzymes. This class includes proteins from 96 families with very different sequences and folds, many of which perform important functions. In a cross-validation test, our approach correctly predicts the location of the enzymes' catalytic residues with a sensitivity of 80% at a specificity of 99.4%, and in a separate cross-validation we also correctly annotate the biochemical role of 80% of the catalytic residues. Our results compare favorably to existing methods. Moreover, our method is more broadly applicable because it relies on sequence and not structure information; it may, furthermore, be used in conjunction with structure-based methods.
We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) netwo... more We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) networks, the goal being to maximize the overall match across the input networks. The intuition behind our algorithm is that a protein in one PPI network is a good match for a protein in another network if the former's neighbors are good matches for the latter's neighbors. We encode this intuition by constructing an eigenvalue problem for every pair of input networks and then using k-partite matching to extract the final global alignment across all the species. We compute the first known global alignment of PPI networks from five species: yeast, fly, worm, mouse and human. The global alignment immediately suggests functional orthologs across these species; we believe these are the first set of functional orthologs that cover all the five species. We show that these functional orthologs compare favorably with current sequence-only orthology prediction approaches, including better prediction of orthologs for some human disease-related proteins.
Bioinformatics/computer Applications in The Biosciences, 2009
With the increasing availability of large protein-protein interaction networks, the question of p... more With the increasing availability of large protein-protein interaction networks, the question of protein network alignment is becoming central to systems biology. Network alignment is further delineated into two sub-problems: local alignment, to find small conserved motifs across networks, and global alignment, which attempts to find a best mapping between all nodes of the two networks. In this article, our aim is to improve upon existing global alignment results. Better network alignment will enable, among other things, more accurate identification of functional orthologs across species. Results: We introduce IsoRankN (IsoRank-Nibble) a global multiplenetwork alignment tool based on spectral clustering on the induced graph of pairwise alignment scores. IsoRankN outperforms existing algorithms for global network alignment in coverage and consistency on multiple alignments of the five available eukaryotic networks. Being based on spectral methods, IsoRankN is both error tolerant and computationally efficient. Availability: Our software is available freely for non-commercial purposes on request from: http://isorank.
When searching for an optimal protein structure, it is often necessary to generate a set of struc... more When searching for an optimal protein structure, it is often necessary to generate a set of structures similar, e.g., within 4Å Root Mean Square Deviation (RMSD), to some base structure. Current methods to do this are designed to produce only small deviations (< 0.1Å RMSD) and are inefficient for larger deviations. The method proposed in this paper, ChainTweak, can generate conformations with larger deviations from the base much more efficiently. For example, in 18 seconds it can generate 100 backbone conformations, each within 1-4Å RMSD of a given 45-residue conformation. Moreover, each conformation has correct bond lengths, angles and omega torsional angles; its phi-psi angles have energetically favorable values; and there are rarely any backbone steric clashes. The method uses the insight that loop closure techniques can be used to perform compensatory changes of dihedral angles so that only a part of the conformation is changed. It is demonstrated, using decoys from the Decoys 'R Us data-set, that ChainTweak can be used to construct good decoys. It also provides a novel and intuitive way of analyzing the energy landscape of a protein. In addition, ChainTweak can improve the accuracy and performance of the loop modeling program RAPPER by an order of magnitude (1.1 min. vs. 36 min. for an 8-residue chain). Availability & Supp. Info.: http://theory.csail.mit.edu/chaintweak * Corresponding author †Also in the MIT Dept. of Mathematics a Of course, the size of the neighbourhood and, consequently, the exact choice of a RMSD threshold would depend on the problem instance and the size of the protein. Typically, for a 50-residue protein, two conformations within 2Å of each other are considered almost identical. Thus, in this case, the threshold size should be ≥ 2Å.
This paper presents a framework for predicting protein-protein interactions (PPI) that integrates... more This paper presents a framework for predicting protein-protein interactions (PPI) that integrates structure-based information with other functional annotations, e.g. GO, co-expression and co-localization, etc. Given two protein sequences, the structure-based interaction prediction technique threads these two sequences to all the protein complexes in the PDB and then chooses the best potential match. Based on this match, structural information is incorporated into logistic regression to evaluate the probability of these two proteins interacting. This paper also describes a random forest classifier which can effectively combine the structure-based prediction results and other functional annotations together to predict protein interactions. Experimental results indicate that the predictive power of the structurebased method is better than many other information sources. Also, combining the structure-based method with other information sources allows us to achieve a better performance than when structure information is not used. We also tested our method on a set of approximately 1000 yeast genes and, interestingly, the predicted interaction network is a scale-free network. Our method predicted some potential interactions involving yeast homologs of human disease-related proteins. Supplementary Information: http://theory.csail.mit.edu/struct2net * These authors contributed equally to the work †Corresponding author ‡ Also in the MIT Dept. of Mathematics a In this paper, when referring to protein complexes, we consider only those with exactly two components.
We describe a novel probabilistic approach to estimating errors in two-hybrid (2H) experiments. S... more We describe a novel probabilistic approach to estimating errors in two-hybrid (2H) experiments. Such experiments are frequently used to elucidate protein-protein interaction networks in a high-throughput fashion; however, a significant challenge with these is their relatively high error rate, specifically, a high false-positive rate. We describe a comprehensive error model for 2H data, accounting for both random and systematic errors. The latter arise from limitations of the 2H experimental protocol: in theory, the reporting mechanism of a 2H experiment should be activated if and only if the two proteins being tested truly interact; in practice, even in the absence of a true interaction, it may be activated by some proteins -either by themselves or through promiscuous interaction with other proteins. We describe a probabilistic relational model that explicitly models the above phenomenon and use Markov Chain Monte Carlo (MCMC) algorithms to compute both the probability of an observed 2H interaction being true as well as the probability of individual proteins being self-activating/promiscuous. This is the first approach that explicitly models systematic errors in protein-protein interaction data; in contrast, previous work on this topic has modeled errors as being independent and random. By explicitly modeling the sources of noise in 2H systems, we find that we are better able to make use of the available experimental data. In comparison with Bader et al.'s method for estimating confidence in 2H predicted interactions, the proposed method performed 5-10% better overall, and in particular regimes improved prediction accuracy by as much as 76%.
Many time-series experiments seek to estimate some signal as a continuous function of time. In th... more Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which time-points ought to be sampled in order to minimize the cost of data collection. We restrict our attention to a growing class of experiments which measure multiple signals at each time-point and where raw materials/observations are archived initially, and selectively analyzed later, this analysis being the more expensive step. We present an active learning algorithm for iteratively choosing time-points to sample, using the uncertainty in the quality of the currently estimated time-dependent curve as the objective function. Using simulated data as well as gene expression data, we show that our algorithm performs well, and can significantly reduce experimental cost without loss of information.
Proceedings of The National Academy of Sciences, 2008
We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) netwo... more We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) networks, the goal being to maximize the overall match across the input networks. The intuition behind our algorithm is that a protein in one PPI network is a good match for a protein in another network if the former's neighbors are good matches for the latter's neighbors. We encode this intuition by constructing an eigenvalue problem for every pair of input networks and then using k-partite matching to extract the final global alignment across all the species. We compute the first known global alignment of PPI networks from five species: yeast, fly, worm, mouse and human. The global alignment immediately suggests functional orthologs across these species; we believe these are the first set of functional orthologs that cover all the five species. We show that these functional orthologs compare favorably with current sequence-only orthology prediction approaches, including better prediction of orthologs for some human disease-related proteins.
Abstract Developments in the field of wireless networks have led to the phase where it has now be... more Abstract Developments in the field of wireless networks have led to the phase where it has now become important to offer the members connected in a wireless network with a secure and efficient group key management system for accessing numerous services. A secure ...
In biological macromolecules, structural patterns (motifs) are often repeated across different mo... more In biological macromolecules, structural patterns (motifs) are often repeated across different molecules. Detection of these common motifs in a new molecule can provide useful clues to the functional properties of such a molecule. We formulate the problem of identifying a given structural motif (pattern) in a target protein (example) and discuss the notion of complete matches vis-a-vis partial matches. We describe the precise error criterion that has to be minimized and also discuss different metrics for evaluating the quality of partial matches. Secondly, we present a new polynomial time algorithm for the problem of matching a given motif in a target protein. We also use the sequence and (if available) secondary structure information to annotate the different points in motif and the target protein, thus reducing the search space size. Our algorithm guarantees the detection of a perfect match, if present. Even otherwise, the algorithm computes very good matches. Unlike other methods, the error minimized by our algorithm directly translates to root mean square deviation (RMSD), the most commonly accepted metric for structure matching in biological macromolecules. The algorithm does not involve any preprocessing and is suitable for the detection of both small and large motifs in the target protein. We also present experiments exploring the quality of matches found by the algorithm. We examine its performance in matching (both full and partial) active sites in proteins.
N-Heterocyclic carbenes (NHC) are efficient catalysts for transesterification/acylation reactions... more N-Heterocyclic carbenes (NHC) are efficient catalysts for transesterification/acylation reactions involving secondary alcohols. The catalytic transformations are carried out employing low catalyst loadings in convenient reaction times at room temperature.
Organo-phosphorus compounds S 0080 Synthesis of Phosphorus Esters by Transesterification Mediated... more Organo-phosphorus compounds S 0080 Synthesis of Phosphorus Esters by Transesterification Mediated by N-Heterocyclic Carbenes (NHCs). -N-heterocyclic carbenes, which are versatile nucleophilic organic catalysts, are shown to mediate the transesterification of phosphorus ester (II) under mild conditions; imidazolium salts can also be employed as pre-catalysts. -(SINGH, R.; NOLAN*, S. P.; Chem. Commun. (Cambridge) 2005, 43, 5456-5458; Dep. Chem., Univ. New Orleans, New Orleans, LA 70148, USA; Eng.) -M. Paetzel 12-177
Palladium-catalyzed reactions of aryl bromides with various olefins involving Pd(II)/diazabutadie... more Palladium-catalyzed reactions of aryl bromides with various olefins involving Pd(II)/diazabutadiene (DAB-R) systems have been investigated. The scope of a coupling process using Pd(II) sources and an a-diimine as ligand in the presence of Cs 2 CO 3 as base was tested using various substrates. The Pd(OAc) 2 /DAB-Cy (1, DAB-Cy 0/1,4-dicyclohexyl-diazabutadiene) system presents the highest activity with respect to electron-neutral and electron-deficient aryl bromides in coupling with electron rich olefins. The synthesis and X-ray characterization of a Pd(II)-diazabutadiene ligand is reported. Extensive optimization experiments showed that another Pd(II) source, Pd(acac) 2 (acac 0/acetylacetonate), proved to activate aryl bromides at high temperatures, low catalyst loadings when the appropriate concentration of n Bu 4 NBr additive was employed. The effect of the DAB-Cy ligand is important at very low catalyst loadings and high temperatures. Pd(acac) 2 and Pd(acac) 2 /DAB-Cy precatalysts were very effective for the arylation of various olefins with aryl bromides with respect to reaction rate, catalyst loadings, and functional group tolerance. #
Thermal reactions between [RuCl 2 (diene)] n (diene ) 2,5-norbornadiene, nbd; 1,5-cyclooctadiene,... more Thermal reactions between [RuCl 2 (diene)] n (diene ) 2,5-norbornadiene, nbd; 1,5-cyclooctadiene, cod) with an excess of N,N,N′,N′-tetramethylethylene diamine (tmeda) afforded derivatives [RuCl 2 (diene)(tmeda)] (diene ) nbd, 1; cod, 2) as a mixture of cis and trans isomers. When thermolysis was performed under H 2 mixtures of hydride species [RuCl(H)(diene)(tmeda)] (diene ) nbd, 3; cod, 4) and the bis-tmeda adduct trans-[RuCl 2 (tmeda) 2 ] (5) were obtained in different ratios depending upon the reaction conditions and reaction times. Heating polymeric Ru(II) precursors in toluene in the presence of a 5-fold excess of the bulkier N,N,N′,N′-tetraethylethylene diamine (teeda) resulted in a rare diamine dealkylation process with formation of trans-[RuCl 2 (nbd)(Et 2 NCH 2 CH 2 NHEt)] (6) and trans-[RuCl 2 (cod)(EtHNCH 2 CH 2 NHEt)] (7) in high yields. The presence of N−H functionalities in the coordinated diamine ligands of 6 and 7 was unambiguously established by single-crystal X-ray diffraction studies. The dealkylation process of the teeda ligand seems to proceed intramolecularly as shown by solution NMR studies performed with the soluble Ru(II) precursors trans-[RuCl 2 (amine) 2 (diene)] (diene ) nbd, amine ) morpholine, 9; diene ) cod, amine ) Et 2 NH, 10). The above complexes [RuCl 2 (diene)(diamine)] have been tested as precatalysts in the hydrogenation of ketones both for transfer as well as direct hydrogenation, the latter route being the most effective.
This report provides a critical overview of recent developments in the use of N-heterocyclic carb... more This report provides a critical overview of recent developments in the use of N-heterocyclic carbenes (NHCs) with transition metals. For these NHC ligand-containing complexes, an analysis is focused on their performance and scope in catalysis. There is also an increasing interest in the role of nucleophilic carbenes as organocatalysts; the latest advances in applications of NHCs in organocatalysis are also reviewed.
Simple Imidazol-2-ylidene)-Pd-acetate Complexes as Effective Precatalysts for Sterically Hindered... more Simple Imidazol-2-ylidene)-Pd-acetate Complexes as Effective Precatalysts for Sterically Hindered Suzuki-Miyaura Couplings. -A convenient protocol for the preparation of the title complexes is developed. The coupling reactions are successfully carried out for a broad spectrum of boronic acids and alkyl/aryl halides. -(SINGH, R.; VICIU, M. S.; KRAMAREVA, N.; NAVARRO, O.; NOLAN*, S. P.; Org. Lett. 7 (2005) 9, 1829-1832; Dep. Chem., Univ. New Orleans, New Orleans, LA 70148, USA; Eng.) -Y. Steudel 37-090
We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) ... more We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to maximize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem— identifying many possible alignments, each corresponding to a local region of similarity. IsoRank is guided by the intuition that a protein should be matched with a protein in the other network if and only if the neighbors of the two proteins can also be well matched. We encode this intuition as an eigenvalue problem, in a manner analogous to Google’s PageRank method. We use IsoRank to compute the first known global alignment between the S. cerevisiae and D. melanogaster PPI networks. The common subgraph has 1420 edges and describes conserved functional components between the two species. Comparisons of our results with those of a well-known algorithm for local network alignment indicate that the globally optimized alignment resolves ambiguity introduced by multiple local alignments. Finally, we interpret the results of global alignment to identify functional orthologs between yeast and fly; our functional ortholog prediction method is much simpler than a recently proposed approach and yet provides results that are more comprehensive.
We introduce a computational method to predict and annotate the catalytic residues of a protein u... more We introduce a computational method to predict and annotate the catalytic residues of a protein using only its sequence information, so that we describe both the residues&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; sequence locations (prediction) and their specific biochemical roles in the catalyzed reaction (annotation). While knowing the chemistry of an enzyme&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s catalytic residues is essential to understanding its function, the challenges of prediction and annotation have remained difficult, especially when only the enzyme&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s sequence and no homologous structures are available. Our sequence-based approach follows the guiding principle that catalytic residues performing the same biochemical function should have similar chemical environments; it detects specific conservation patterns near in sequence to known catalytic residues and accordingly constrains what combination of amino acids can be present near a predicted catalytic residue. We associate with each catalytic residue a short sequence profile and define a Kullback-Leibler (KL) distance measure between these profiles, which, as we show, effectively captures even subtle biochemical variations. We apply the method to the class of glycohydrolase enzymes. This class includes proteins from 96 families with very different sequences and folds, many of which perform important functions. In a cross-validation test, our approach correctly predicts the location of the enzymes&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; catalytic residues with a sensitivity of 80% at a specificity of 99.4%, and in a separate cross-validation we also correctly annotate the biochemical role of 80% of the catalytic residues. Our results compare favorably to existing methods. Moreover, our method is more broadly applicable because it relies on sequence and not structure information; it may, furthermore, be used in conjunction with structure-based methods.
We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) netwo... more We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) networks, the goal being to maximize the overall match across the input networks. The intuition behind our algorithm is that a protein in one PPI network is a good match for a protein in another network if the former's neighbors are good matches for the latter's neighbors. We encode this intuition by constructing an eigenvalue problem for every pair of input networks and then using k-partite matching to extract the final global alignment across all the species. We compute the first known global alignment of PPI networks from five species: yeast, fly, worm, mouse and human. The global alignment immediately suggests functional orthologs across these species; we believe these are the first set of functional orthologs that cover all the five species. We show that these functional orthologs compare favorably with current sequence-only orthology prediction approaches, including better prediction of orthologs for some human disease-related proteins.
Bioinformatics/computer Applications in The Biosciences, 2009
With the increasing availability of large protein-protein interaction networks, the question of p... more With the increasing availability of large protein-protein interaction networks, the question of protein network alignment is becoming central to systems biology. Network alignment is further delineated into two sub-problems: local alignment, to find small conserved motifs across networks, and global alignment, which attempts to find a best mapping between all nodes of the two networks. In this article, our aim is to improve upon existing global alignment results. Better network alignment will enable, among other things, more accurate identification of functional orthologs across species. Results: We introduce IsoRankN (IsoRank-Nibble) a global multiplenetwork alignment tool based on spectral clustering on the induced graph of pairwise alignment scores. IsoRankN outperforms existing algorithms for global network alignment in coverage and consistency on multiple alignments of the five available eukaryotic networks. Being based on spectral methods, IsoRankN is both error tolerant and computationally efficient. Availability: Our software is available freely for non-commercial purposes on request from: http://isorank.
When searching for an optimal protein structure, it is often necessary to generate a set of struc... more When searching for an optimal protein structure, it is often necessary to generate a set of structures similar, e.g., within 4Å Root Mean Square Deviation (RMSD), to some base structure. Current methods to do this are designed to produce only small deviations (< 0.1Å RMSD) and are inefficient for larger deviations. The method proposed in this paper, ChainTweak, can generate conformations with larger deviations from the base much more efficiently. For example, in 18 seconds it can generate 100 backbone conformations, each within 1-4Å RMSD of a given 45-residue conformation. Moreover, each conformation has correct bond lengths, angles and omega torsional angles; its phi-psi angles have energetically favorable values; and there are rarely any backbone steric clashes. The method uses the insight that loop closure techniques can be used to perform compensatory changes of dihedral angles so that only a part of the conformation is changed. It is demonstrated, using decoys from the Decoys 'R Us data-set, that ChainTweak can be used to construct good decoys. It also provides a novel and intuitive way of analyzing the energy landscape of a protein. In addition, ChainTweak can improve the accuracy and performance of the loop modeling program RAPPER by an order of magnitude (1.1 min. vs. 36 min. for an 8-residue chain). Availability & Supp. Info.: http://theory.csail.mit.edu/chaintweak * Corresponding author †Also in the MIT Dept. of Mathematics a Of course, the size of the neighbourhood and, consequently, the exact choice of a RMSD threshold would depend on the problem instance and the size of the protein. Typically, for a 50-residue protein, two conformations within 2Å of each other are considered almost identical. Thus, in this case, the threshold size should be ≥ 2Å.
This paper presents a framework for predicting protein-protein interactions (PPI) that integrates... more This paper presents a framework for predicting protein-protein interactions (PPI) that integrates structure-based information with other functional annotations, e.g. GO, co-expression and co-localization, etc. Given two protein sequences, the structure-based interaction prediction technique threads these two sequences to all the protein complexes in the PDB and then chooses the best potential match. Based on this match, structural information is incorporated into logistic regression to evaluate the probability of these two proteins interacting. This paper also describes a random forest classifier which can effectively combine the structure-based prediction results and other functional annotations together to predict protein interactions. Experimental results indicate that the predictive power of the structurebased method is better than many other information sources. Also, combining the structure-based method with other information sources allows us to achieve a better performance than when structure information is not used. We also tested our method on a set of approximately 1000 yeast genes and, interestingly, the predicted interaction network is a scale-free network. Our method predicted some potential interactions involving yeast homologs of human disease-related proteins. Supplementary Information: http://theory.csail.mit.edu/struct2net * These authors contributed equally to the work †Corresponding author ‡ Also in the MIT Dept. of Mathematics a In this paper, when referring to protein complexes, we consider only those with exactly two components.
We describe a novel probabilistic approach to estimating errors in two-hybrid (2H) experiments. S... more We describe a novel probabilistic approach to estimating errors in two-hybrid (2H) experiments. Such experiments are frequently used to elucidate protein-protein interaction networks in a high-throughput fashion; however, a significant challenge with these is their relatively high error rate, specifically, a high false-positive rate. We describe a comprehensive error model for 2H data, accounting for both random and systematic errors. The latter arise from limitations of the 2H experimental protocol: in theory, the reporting mechanism of a 2H experiment should be activated if and only if the two proteins being tested truly interact; in practice, even in the absence of a true interaction, it may be activated by some proteins -either by themselves or through promiscuous interaction with other proteins. We describe a probabilistic relational model that explicitly models the above phenomenon and use Markov Chain Monte Carlo (MCMC) algorithms to compute both the probability of an observed 2H interaction being true as well as the probability of individual proteins being self-activating/promiscuous. This is the first approach that explicitly models systematic errors in protein-protein interaction data; in contrast, previous work on this topic has modeled errors as being independent and random. By explicitly modeling the sources of noise in 2H systems, we find that we are better able to make use of the available experimental data. In comparison with Bader et al.'s method for estimating confidence in 2H predicted interactions, the proposed method performed 5-10% better overall, and in particular regimes improved prediction accuracy by as much as 76%.
Many time-series experiments seek to estimate some signal as a continuous function of time. In th... more Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which time-points ought to be sampled in order to minimize the cost of data collection. We restrict our attention to a growing class of experiments which measure multiple signals at each time-point and where raw materials/observations are archived initially, and selectively analyzed later, this analysis being the more expensive step. We present an active learning algorithm for iteratively choosing time-points to sample, using the uncertainty in the quality of the currently estimated time-dependent curve as the objective function. Using simulated data as well as gene expression data, we show that our algorithm performs well, and can significantly reduce experimental cost without loss of information.
Proceedings of The National Academy of Sciences, 2008
We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) netwo... more We describe an algorithm for global alignment of multiple protein-protein interaction (PPI) networks, the goal being to maximize the overall match across the input networks. The intuition behind our algorithm is that a protein in one PPI network is a good match for a protein in another network if the former's neighbors are good matches for the latter's neighbors. We encode this intuition by constructing an eigenvalue problem for every pair of input networks and then using k-partite matching to extract the final global alignment across all the species. We compute the first known global alignment of PPI networks from five species: yeast, fly, worm, mouse and human. The global alignment immediately suggests functional orthologs across these species; we believe these are the first set of functional orthologs that cover all the five species. We show that these functional orthologs compare favorably with current sequence-only orthology prediction approaches, including better prediction of orthologs for some human disease-related proteins.
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Papers by Rohit Singh