Attila Gursoy | Koç University (original) (raw)

Papers by Attila Gursoy

Research paper thumbnail of Review Structural Pathways of Cytokines May Illuminate Their Roles in Regulation of Cancer Development and Immunotherapy

Cytokines are messengers between tissues and the immune system. They play essential roles in canc... more Cytokines are messengers between tissues and the immune system. They play essential roles in cancer initiation, promotion, metastasis, and immunotherapy. Structural pathways of cytokine signaling which contain their interactions can help understand their action in the tumor microenvironment. Here, our aim is to provide an overview of the role of cytokines in tumor development from a structural perspective. Atomic details of protein-protein interactions can help in understanding how an upstream signal is transduced; how higher-order oligomerization modes of proteins can influence their function; how mutations, inhibitors or antagonists can change cellular consequences; why the same protein can lead to distinct outcomes, and which alternative parallel pathways can take over. They also help to design drugs/inhibitors against proteins de novo or by mimicking natural antagonists as in the case of interferon-γ. Since the structural database (PDB) is limited, structural pathways are largely built from a series of predicted binary protein-protein interactions. Below, to illustrate how protein-protein interactions can help illuminate roles played by cytokines, we model some cytokine interaction complexes exploiting a powerful algorithm (PRotein Interactions by Structural Matching-PRISM).

Research paper thumbnail of Unraveling the molecular mechanism of interactions of the Rho GTPases Cdc42 and Rac1 with the scaffolding protein IQGAP2

The Journal of biological chemistry, Jan 22, 2018

IQ motif-containing GTPase-activating protein (IQGAP) scaffolding proteins play central roles in ... more IQ motif-containing GTPase-activating protein (IQGAP) scaffolding proteins play central roles in cell-cell adhesion, polarity, and motility. The Rho GTPases Cdc42 and Rac1, in their GTP-bound active forms, interact with all three human IQGAPs. The IQGAP-Cdc42 interaction promotes metastasis by enhancing actin polymerization. However, despite their high sequence identity, Cdc42 and Rac1 differ in their interactions with IQGAP. Two Cdc42 molecules can bind to the Ex-domain and the RasGAP site of the GTPase-activating protein (GAP)-related domain (GRD) of IQGAP and promote IQGAP dimerization. Only one Rac1 molecule might bind to the RasGAP site of GRD and may not facilitate the dimerization, and the exact mechanism of Cdc42 and Rac1 binding to IQGAP is unclear. Using all-atom molecular dynamics simulations, site-directed mutagenesis, and Western blotting, we unraveled the detailed mechanisms of Cdc42 and Rac1 interactions with IQGAP2. We observed that Cdc42 binding to the Ex-domain of ...

Research paper thumbnail of Enriching Traditional Protein-protein Interaction Networks with Alternative Conformations of Proteins

Scientific Reports, 2017

Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation,... more Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation, lack some valuable information about the mechanistic details of biological processes. Mapping protein structures to these PPI networks not only provides structural details of each interaction but also helps us to find the mutual exclusive interactions. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different interactions, functions, and downstream signalling. In this study, we proposed a new representation for structural PPI networks inspecting the alternative conformations of proteins. We performed a large-scale study by creating breast cancer metastasis network and equipped it with different conformers of proteins. Our results showed that although 88% of proteins in our network has at least two structures in Protein Data Bank (PDB), only 22% of them have alternative conformations and the remaining proteins have different regions saved in PDB. However, using even this small set of alternative conformations we observed a considerable increase in our protein docking predictions. Our protein-protein interaction predictions increased from 54% to 76% using the alternative conformations. We also showed the benefits of investigating structural data and alternative conformations of proteins through three case studies.

Research paper thumbnail of Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information

Methods in molecular biology (Clifton, N.J.), 2017

Structural details of protein interactions are invaluable to the understanding of cellular proces... more Structural details of protein interactions are invaluable to the understanding of cellular processes. However, the identification of interactions at atomic resolution is a continuing challenge in the systems biology era. Although the number of structurally resolved complexes in the Protein Databank increases exponentially, the complexes only cover a small portion of the known structural interactome. In this chapter, we review the PRISM system that is a protein-protein interaction (PPI) prediction tool-its rationale, principles, and applications. We further discuss its extensions to discover the effect of single residue mutations, to model large protein assemblies, to improve its performance by exploiting conformational protein ensembles, and to reconstruct large PPI networks or pathway maps.

Research paper thumbnail of PATIKA: Pathway Analysis Tool for Integration and Knowledge Acquisition

Research paper thumbnail of Avoiding Algorithmic Obfuscation in a Message-Driven Parallel MD Code

Lecture Notes in Computational Science and Engineering, 1999

Parallel molecular dynamics programs employing shared memory or replicated data architectures enc... more Parallel molecular dynamics programs employing shared memory or replicated data architectures encounter problems scaling to large numbers of processors. Spatial decomposition schemes offer better performance in theory, but often suffer from complexity of implementation and difficulty in load balancing. In the program NAMD 2, we have addressed these issues with a hybrid decomposition scheme in which atoms are distributed among processors in regularly sized patches while the work involved in computing interactions between patches is decomposed into independently assignable compute objects. When needed, patches are represented on remote processors by proxies. The execution of compute objects takes place in a prioritized message-driven manner, allowing maximum overlap of work and communication without significant programmer effort. In order to avoid obfuscation of the simulation algorithm by the parallel framework, the algorithm associated with a patch is encapsulated by a single function executing in a separate thread. Output and calculations requiring globally reduced quantities are similarly isolated in a single thread executing on the master node. This combination of features allows us to make efficient use of large parallel machines and clusters of multiprocessor workstations while presenting minimal barriers to method development and implementation.

Research paper thumbnail of The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer

PLoS computational biology, 2014

Interleukin-1 (IL-1) is a large cytokine family closely related to innate immunity and inflammati... more Interleukin-1 (IL-1) is a large cytokine family closely related to innate immunity and inflammation. IL-1 proteins are key players in signaling pathways such as apoptosis, TLR, MAPK, NLR and NF-κB. The IL-1 pathway is also associated with cancer, and chronic inflammation increases the risk of tumor development via oncogenic mutations. Here we illustrate that the structures of interfaces between proteins in this pathway bearing the mutations may reveal how. Proteins are frequently regulated via their interactions, which can turn them ON or OFF. We show that oncogenic mutations are significantly at or adjoining interface regions, and can abolish (or enhance) the protein-protein interaction, making the protein constitutively active (or inactive, if it is a repressor). We combine known structures of protein-protein complexes and those that we have predicted for the IL-1 pathway, and integrate them with literature information. In the reconstructed pathway there are 104 interactions betwe...

Research paper thumbnail of Inhibitor peptide design for NF-кB: Markov model & genetic algorithm

2010 5th International Symposium on Health Informatics and Bioinformatics, 2010

ABSTRACT

Research paper thumbnail of Hot spots in protein–protein interfaces: Towards drug discovery

Progress in Biophysics and Molecular Biology, 2014

Identification of drug-like small molecules that alter proteineprotein interactions might be a ke... more Identification of drug-like small molecules that alter proteineprotein interactions might be a key step in drug discovery. However, it is very challenging to find such molecules that target interface regions in protein complexes. Recent findings indicate that such molecules usually target specifically energetically favored residues (hot spots) in proteineprotein interfaces. These residues contribute to the stability of proteineprotein complexes. Computational prediction of hot spots on bound and unbound structures might be useful to find druggable sites on target interfaces. We review the recent advances in computational hot spot prediction methods in the first part of the review and then provide examples on how hot spots might be crucial in drug design.

Research paper thumbnail of Computational analysis of the binding free energy of H3K9me3 peptide to the tandem tudor domains of JMJD2A

2010 5th International Symposium on Health Informatics and Bioinformatics, 2010

Abstract JMJD2A is a histone lysine demethylase enzyme which plays a prominent role in the develo... more Abstract JMJD2A is a histone lysine demethylase enzyme which plays a prominent role in the development of prostate and esophageal squamous cancers. Consisting of a JmjC, a JmjN, two PHD and two tandem tudor domains, JMJD2A recognizes and binds to four different methylated histone peptides: H3K4me3, H4K20me3, H4K20me2 and H3K9me3, via its tudor domains. Of the four histone peptides, only recognition of the H3K4me3 and H4K20me3 by JMJD2A-tudor has been identified. In this study, we investigated the ...

Research paper thumbnail of Structural Pathways of Cytokines May Illuminate Their Roles in Regulation of Cancer Development and Immunotherapy

Cancers, 2014

Cytokines are messengers between tissues and the immune system. They play essential roles in canc... more Cytokines are messengers between tissues and the immune system. They play essential roles in cancer initiation, promotion, metastasis, and immunotherapy. Structural pathways of cytokine signaling which contain their interactions can help understand their action in the tumor microenvironment. Here, our aim is to provide an overview of the role of cytokines in tumor development from a structural perspective. Atomic details of protein-protein interactions can help in understanding how an upstream signal is transduced; how higher-order oligomerization modes of proteins can influence their function; how mutations, inhibitors or antagonists can change cellular consequences; why the same protein can lead to distinct outcomes, and which alternative parallel pathways can take over. They also help to design drugs/inhibitors against proteins de novo or by mimicking natural antagonists as in the case of interferon-γ. Since the structural database (PDB) is limited, structural pathways are largely built from a series of predicted binary protein-protein interactions. Below, to illustrate how protein-protein interactions can help illuminate roles played by cytokines, we model some cytokine interaction complexes exploiting a powerful algorithm (PRotein Interactions by Structural Matching-PRISM).

Research paper thumbnail of The structural network of Interleukin-10 and its implications in inflammation and cancer

BMC Genomics, 2014

Background: Inflammation has significant roles in all phases of tumor development, including init... more Background: Inflammation has significant roles in all phases of tumor development, including initiation, progression and metastasis. Interleukin-10 (IL-10) is a well-known immuno-modulatory cytokine with an antiinflammatory activity. Lack of IL-10 allows induction of pro-inflammatory cytokines and hinders anti-tumor immunity, thereby favoring tumor growth. The IL-10 network is among the most important paths linking cancer and inflammation. The simple node-and-edge network representation is useful, but limited, hampering the understanding of the mechanistic details of signaling pathways. Structural networks complete the missing parts, and provide details. The IL-10 structural network may shed light on the mechanisms through which disease-related mutations work and the pathogenesis of malignancies. Results: Using PRISM (a PRotein Interactions by Structural Matching tool), we constructed the structural network of IL-10, which includes its first and second degree protein neighbor interactions. We predicted the structures of complexes involved in these interactions, thereby enriching the available structural data. In order to reveal the significance of the interactions, we exploited mutations identified in cancer patients, mapping them onto key proteins of this network. We analyzed the effect of these mutations on the interactions, and demonstrated a relation between these and inflammation and cancer. Our results suggest that mutations that disrupt the interactions of IL-10 with its receptors (IL-10RA and IL-10RB) and α2macroglobulin (A2M) may enhance inflammation and modulate anti-tumor immunity. Likewise, mutations that weaken the A2M-APP (amyloid precursor protein) association may increase the proliferative effect of APP through preventing β-amyloid degradation by the A2M receptor, and mutations that abolish the A2M-Kallikrein-13 (KLK13) interaction may lead to cell proliferation and metastasis through the destructive effect of KLK13 on the extracellular matrix. Conclusions: Prediction of protein-protein interactions through structural matching can enrich the available cellular pathways. In addition, the structural data of protein complexes suggest how oncogenic mutations influence the interactions and explain their potential impact on IL-10 signaling in cancer and inflammation.

Research paper thumbnail of NAMD User's Guide

Research paper thumbnail of Relationships between amino acid sequence and backbone torsion angle preferences

Proteins: Structure, Function, and Bioinformatics, 2004

Statistical averages and correlations for backbone torsion angles of chymotrypsin inhibitor 2 are... more Statistical averages and correlations for backbone torsion angles of chymotrypsin inhibitor 2 are calculated by using the Rotational Isomeric States model of chain statistics. Statistical weights of torsional states of pairs, needed for the statistics of the full chain, are obtained in two different ways: 1) by using knowledge-based pairwise dependent energy maps from Protein Data Bank (PDB) and 2) by collecting torsion angle data from a large number of random coil configurations of an all-atom protein model with volume exclusion. Results obtained by using PDB data show strong correlations between adjacent torsion angle pairs belonging to both the same and different residues. These correlations favor the choice of the nativestate torsion angles, and they are strongly context dependent, determined by the specific amino acid sequence of the protein. Excluded volume or steric clashes, only, do not introduce context-dependent correlations into the chain that would affect the choice of native-state torsional angles. Proteins 2004; 55:992-998.

Research paper thumbnail of Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

PLoS ONE, 2013

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interacti... more Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotypephenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the "guilt-by-association" principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis.

Research paper thumbnail of Non-Redundant Unique Interface Structures as Templates for Modeling Protein Interactions

PLoS ONE, 2014

Improvements in experimental techniques increasingly provide structural data relating to protein-... more Improvements in experimental techniques increasingly provide structural data relating to protein-protein interactions. Classification of structural details of protein-protein interactions can provide valuable insights for modeling and abstracting design principles. Here, we aim to cluster protein-protein interactions by their interface structures, and to exploit these clusters to obtain and study shared and distinct protein binding sites. We find that there are 22604 unique interface structures in the PDB. These unique interfaces, which provide a rich resource of structural data of protein-protein interactions, can be used for template-based docking. We test the specificity of these non-redundant unique interface structures by finding protein pairs which have multiple binding sites. We suggest that residues with more than 40% relative accessible surface area should be considered as surface residues in template-based docking studies. This comprehensive study of protein interface structures can serve as a resource for the community. The dataset can be accessed at http://prism. ccbb.ku.edu.tr/piface.

Research paper thumbnail of A Comparative Molecular Dynamics Study of Methylation State Specificity of JMJD2A

PLoS ONE, 2011

Histone modifications have great importance in epigenetic regulation. JMJD2A is a histone demethy... more Histone modifications have great importance in epigenetic regulation. JMJD2A is a histone demethylase which is selective for di-and trimethyl forms of residues Lys9 and Lys36 of Histone 3 tail (H3K9 and H3K36). We present a molecular dynamics simulations of mono-, di-and trimethylated histone tails in complex with JMJD2A catalytic domain to gain insight into how JMJD2A discriminates between the methylation states of H3K9. The methyl groups are located at specific distances and orientations with respect to Fe(II) in methylammonium binding pocket. For the trimethyllysine the mechanism which provides the effectual orientation of methyl groups is the symmetry, whereas for the dimethyllysine case the determining factors are the interactions between methyllysine head and its environment and subsequently the restriction on angular motion. The occurrence frequency of methyl groups in a certain proximity of Fe(II) comes out as the explanation of the enzyme activity difference on di-and tri-methylated peptides. Energy analysis suggests that recognition is mostly driven by van der Waals and followed by Coulombic interactions in the enzyme-substrate interface. The number (mono, di or tri) and orientations of methyl groups and water molecules significantly affect the extent of van der Waals interaction strengths. Hydrogen bonding analysis suggests that the interaction between JMJD2A and its substrates mainly comes from main chain-side chain interactions. Binding free energy analysis points out Arg8 as an important residue forming an intrasubstrate hydrogen bond with tri and dimethylated Lys9 of the H3 chain. Our study provides new insights into how JMJD2A discriminates between its substrates from both a structural and dynamical point of view.

Research paper thumbnail of PRISM: a web server and repository for prediction of protein–protein interactions and modeling their 3D complexes

Nucleic Acids Research, 2014

The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs).... more The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs). The prediction algorithm is knowledge-based. It combines structural similarity and accounts for evolutionary conservation in the template interfaces. The predicted models are stored in its repository. Given two protein structures, PRISM will provide a structural model of their complex if a matching template interface is available. Users can download the complex structure, retrieve the interface residues and visualize the complex model. The PRISM web server is user friendly, free and open to all users at http: //cosbi.ku.edu.tr/prism.

Research paper thumbnail of Modeling Protein Assemblies in the Proteome

Molecular & Cellular Proteomics, 2014

Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the s... more Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high-and low-resolution scales. Existing computational methods have made substantial progress toward this aim; however, current approaches are still limited. Some involve manual adjustment of experimental data; some are automated docking methods, which are computationally expensive and not applicable to large-scale proteome studies; and still others exploit the symmetry of the complexes and thus are not applicable to nonsymmetrical complexes. Our study aims to take steps toward overcoming these limitations. We have developed a strategy for the construction of protein assemblies computationally based on binary interactions predicted by a motif-based protein interaction prediction tool, PRISM (Protein Interactions by Structural Matching). Previously, we have shown its power in predicting pairwise interactions. Here we take a step toward multimolecular assemblies, reflecting the more prevalent cellular scenarios. With this method we are able to construct homo-/ hetero-complexes and symmetric/asymmetric complexes without a limitation on the number of components. The method considers conformational changes and is applicable to large-scale studies. We also exploit electron microscopy density maps to select a solution from among the predictions. Here we present the method, illustrate its results, and highlight its current limitations. Molecular & Cellular

Research paper thumbnail of Exploiting Conformational Ensembles in Modeling Protein–Protein Interactions on the Proteome Scale

Journal of Proteome Research, 2013

Cellular functions are performed through protein−protein interactions; therefore, identification ... more Cellular functions are performed through protein−protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledgebased approaches are more useful than "blind" docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited an ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested "difficult" cases in a docking-benchmark data set, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ∼26 to 66%, and 57% of the interactions were successfully predicted in an "unbiased" scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein−protein interaction predictions on an interactome scale. We constructed the structural network of ERK interacting proteins as a case study.

Research paper thumbnail of Review Structural Pathways of Cytokines May Illuminate Their Roles in Regulation of Cancer Development and Immunotherapy

Cytokines are messengers between tissues and the immune system. They play essential roles in canc... more Cytokines are messengers between tissues and the immune system. They play essential roles in cancer initiation, promotion, metastasis, and immunotherapy. Structural pathways of cytokine signaling which contain their interactions can help understand their action in the tumor microenvironment. Here, our aim is to provide an overview of the role of cytokines in tumor development from a structural perspective. Atomic details of protein-protein interactions can help in understanding how an upstream signal is transduced; how higher-order oligomerization modes of proteins can influence their function; how mutations, inhibitors or antagonists can change cellular consequences; why the same protein can lead to distinct outcomes, and which alternative parallel pathways can take over. They also help to design drugs/inhibitors against proteins de novo or by mimicking natural antagonists as in the case of interferon-γ. Since the structural database (PDB) is limited, structural pathways are largely built from a series of predicted binary protein-protein interactions. Below, to illustrate how protein-protein interactions can help illuminate roles played by cytokines, we model some cytokine interaction complexes exploiting a powerful algorithm (PRotein Interactions by Structural Matching-PRISM).

Research paper thumbnail of Unraveling the molecular mechanism of interactions of the Rho GTPases Cdc42 and Rac1 with the scaffolding protein IQGAP2

The Journal of biological chemistry, Jan 22, 2018

IQ motif-containing GTPase-activating protein (IQGAP) scaffolding proteins play central roles in ... more IQ motif-containing GTPase-activating protein (IQGAP) scaffolding proteins play central roles in cell-cell adhesion, polarity, and motility. The Rho GTPases Cdc42 and Rac1, in their GTP-bound active forms, interact with all three human IQGAPs. The IQGAP-Cdc42 interaction promotes metastasis by enhancing actin polymerization. However, despite their high sequence identity, Cdc42 and Rac1 differ in their interactions with IQGAP. Two Cdc42 molecules can bind to the Ex-domain and the RasGAP site of the GTPase-activating protein (GAP)-related domain (GRD) of IQGAP and promote IQGAP dimerization. Only one Rac1 molecule might bind to the RasGAP site of GRD and may not facilitate the dimerization, and the exact mechanism of Cdc42 and Rac1 binding to IQGAP is unclear. Using all-atom molecular dynamics simulations, site-directed mutagenesis, and Western blotting, we unraveled the detailed mechanisms of Cdc42 and Rac1 interactions with IQGAP2. We observed that Cdc42 binding to the Ex-domain of ...

Research paper thumbnail of Enriching Traditional Protein-protein Interaction Networks with Alternative Conformations of Proteins

Scientific Reports, 2017

Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation,... more Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation, lack some valuable information about the mechanistic details of biological processes. Mapping protein structures to these PPI networks not only provides structural details of each interaction but also helps us to find the mutual exclusive interactions. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different interactions, functions, and downstream signalling. In this study, we proposed a new representation for structural PPI networks inspecting the alternative conformations of proteins. We performed a large-scale study by creating breast cancer metastasis network and equipped it with different conformers of proteins. Our results showed that although 88% of proteins in our network has at least two structures in Protein Data Bank (PDB), only 22% of them have alternative conformations and the remaining proteins have different regions saved in PDB. However, using even this small set of alternative conformations we observed a considerable increase in our protein docking predictions. Our protein-protein interaction predictions increased from 54% to 76% using the alternative conformations. We also showed the benefits of investigating structural data and alternative conformations of proteins through three case studies.

Research paper thumbnail of Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information

Methods in molecular biology (Clifton, N.J.), 2017

Structural details of protein interactions are invaluable to the understanding of cellular proces... more Structural details of protein interactions are invaluable to the understanding of cellular processes. However, the identification of interactions at atomic resolution is a continuing challenge in the systems biology era. Although the number of structurally resolved complexes in the Protein Databank increases exponentially, the complexes only cover a small portion of the known structural interactome. In this chapter, we review the PRISM system that is a protein-protein interaction (PPI) prediction tool-its rationale, principles, and applications. We further discuss its extensions to discover the effect of single residue mutations, to model large protein assemblies, to improve its performance by exploiting conformational protein ensembles, and to reconstruct large PPI networks or pathway maps.

Research paper thumbnail of PATIKA: Pathway Analysis Tool for Integration and Knowledge Acquisition

Research paper thumbnail of Avoiding Algorithmic Obfuscation in a Message-Driven Parallel MD Code

Lecture Notes in Computational Science and Engineering, 1999

Parallel molecular dynamics programs employing shared memory or replicated data architectures enc... more Parallel molecular dynamics programs employing shared memory or replicated data architectures encounter problems scaling to large numbers of processors. Spatial decomposition schemes offer better performance in theory, but often suffer from complexity of implementation and difficulty in load balancing. In the program NAMD 2, we have addressed these issues with a hybrid decomposition scheme in which atoms are distributed among processors in regularly sized patches while the work involved in computing interactions between patches is decomposed into independently assignable compute objects. When needed, patches are represented on remote processors by proxies. The execution of compute objects takes place in a prioritized message-driven manner, allowing maximum overlap of work and communication without significant programmer effort. In order to avoid obfuscation of the simulation algorithm by the parallel framework, the algorithm associated with a patch is encapsulated by a single function executing in a separate thread. Output and calculations requiring globally reduced quantities are similarly isolated in a single thread executing on the master node. This combination of features allows us to make efficient use of large parallel machines and clusters of multiprocessor workstations while presenting minimal barriers to method development and implementation.

Research paper thumbnail of The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer

PLoS computational biology, 2014

Interleukin-1 (IL-1) is a large cytokine family closely related to innate immunity and inflammati... more Interleukin-1 (IL-1) is a large cytokine family closely related to innate immunity and inflammation. IL-1 proteins are key players in signaling pathways such as apoptosis, TLR, MAPK, NLR and NF-κB. The IL-1 pathway is also associated with cancer, and chronic inflammation increases the risk of tumor development via oncogenic mutations. Here we illustrate that the structures of interfaces between proteins in this pathway bearing the mutations may reveal how. Proteins are frequently regulated via their interactions, which can turn them ON or OFF. We show that oncogenic mutations are significantly at or adjoining interface regions, and can abolish (or enhance) the protein-protein interaction, making the protein constitutively active (or inactive, if it is a repressor). We combine known structures of protein-protein complexes and those that we have predicted for the IL-1 pathway, and integrate them with literature information. In the reconstructed pathway there are 104 interactions betwe...

Research paper thumbnail of Inhibitor peptide design for NF-кB: Markov model & genetic algorithm

2010 5th International Symposium on Health Informatics and Bioinformatics, 2010

ABSTRACT

Research paper thumbnail of Hot spots in protein–protein interfaces: Towards drug discovery

Progress in Biophysics and Molecular Biology, 2014

Identification of drug-like small molecules that alter proteineprotein interactions might be a ke... more Identification of drug-like small molecules that alter proteineprotein interactions might be a key step in drug discovery. However, it is very challenging to find such molecules that target interface regions in protein complexes. Recent findings indicate that such molecules usually target specifically energetically favored residues (hot spots) in proteineprotein interfaces. These residues contribute to the stability of proteineprotein complexes. Computational prediction of hot spots on bound and unbound structures might be useful to find druggable sites on target interfaces. We review the recent advances in computational hot spot prediction methods in the first part of the review and then provide examples on how hot spots might be crucial in drug design.

Research paper thumbnail of Computational analysis of the binding free energy of H3K9me3 peptide to the tandem tudor domains of JMJD2A

2010 5th International Symposium on Health Informatics and Bioinformatics, 2010

Abstract JMJD2A is a histone lysine demethylase enzyme which plays a prominent role in the develo... more Abstract JMJD2A is a histone lysine demethylase enzyme which plays a prominent role in the development of prostate and esophageal squamous cancers. Consisting of a JmjC, a JmjN, two PHD and two tandem tudor domains, JMJD2A recognizes and binds to four different methylated histone peptides: H3K4me3, H4K20me3, H4K20me2 and H3K9me3, via its tudor domains. Of the four histone peptides, only recognition of the H3K4me3 and H4K20me3 by JMJD2A-tudor has been identified. In this study, we investigated the ...

Research paper thumbnail of Structural Pathways of Cytokines May Illuminate Their Roles in Regulation of Cancer Development and Immunotherapy

Cancers, 2014

Cytokines are messengers between tissues and the immune system. They play essential roles in canc... more Cytokines are messengers between tissues and the immune system. They play essential roles in cancer initiation, promotion, metastasis, and immunotherapy. Structural pathways of cytokine signaling which contain their interactions can help understand their action in the tumor microenvironment. Here, our aim is to provide an overview of the role of cytokines in tumor development from a structural perspective. Atomic details of protein-protein interactions can help in understanding how an upstream signal is transduced; how higher-order oligomerization modes of proteins can influence their function; how mutations, inhibitors or antagonists can change cellular consequences; why the same protein can lead to distinct outcomes, and which alternative parallel pathways can take over. They also help to design drugs/inhibitors against proteins de novo or by mimicking natural antagonists as in the case of interferon-γ. Since the structural database (PDB) is limited, structural pathways are largely built from a series of predicted binary protein-protein interactions. Below, to illustrate how protein-protein interactions can help illuminate roles played by cytokines, we model some cytokine interaction complexes exploiting a powerful algorithm (PRotein Interactions by Structural Matching-PRISM).

Research paper thumbnail of The structural network of Interleukin-10 and its implications in inflammation and cancer

BMC Genomics, 2014

Background: Inflammation has significant roles in all phases of tumor development, including init... more Background: Inflammation has significant roles in all phases of tumor development, including initiation, progression and metastasis. Interleukin-10 (IL-10) is a well-known immuno-modulatory cytokine with an antiinflammatory activity. Lack of IL-10 allows induction of pro-inflammatory cytokines and hinders anti-tumor immunity, thereby favoring tumor growth. The IL-10 network is among the most important paths linking cancer and inflammation. The simple node-and-edge network representation is useful, but limited, hampering the understanding of the mechanistic details of signaling pathways. Structural networks complete the missing parts, and provide details. The IL-10 structural network may shed light on the mechanisms through which disease-related mutations work and the pathogenesis of malignancies. Results: Using PRISM (a PRotein Interactions by Structural Matching tool), we constructed the structural network of IL-10, which includes its first and second degree protein neighbor interactions. We predicted the structures of complexes involved in these interactions, thereby enriching the available structural data. In order to reveal the significance of the interactions, we exploited mutations identified in cancer patients, mapping them onto key proteins of this network. We analyzed the effect of these mutations on the interactions, and demonstrated a relation between these and inflammation and cancer. Our results suggest that mutations that disrupt the interactions of IL-10 with its receptors (IL-10RA and IL-10RB) and α2macroglobulin (A2M) may enhance inflammation and modulate anti-tumor immunity. Likewise, mutations that weaken the A2M-APP (amyloid precursor protein) association may increase the proliferative effect of APP through preventing β-amyloid degradation by the A2M receptor, and mutations that abolish the A2M-Kallikrein-13 (KLK13) interaction may lead to cell proliferation and metastasis through the destructive effect of KLK13 on the extracellular matrix. Conclusions: Prediction of protein-protein interactions through structural matching can enrich the available cellular pathways. In addition, the structural data of protein complexes suggest how oncogenic mutations influence the interactions and explain their potential impact on IL-10 signaling in cancer and inflammation.

Research paper thumbnail of NAMD User's Guide

Research paper thumbnail of Relationships between amino acid sequence and backbone torsion angle preferences

Proteins: Structure, Function, and Bioinformatics, 2004

Statistical averages and correlations for backbone torsion angles of chymotrypsin inhibitor 2 are... more Statistical averages and correlations for backbone torsion angles of chymotrypsin inhibitor 2 are calculated by using the Rotational Isomeric States model of chain statistics. Statistical weights of torsional states of pairs, needed for the statistics of the full chain, are obtained in two different ways: 1) by using knowledge-based pairwise dependent energy maps from Protein Data Bank (PDB) and 2) by collecting torsion angle data from a large number of random coil configurations of an all-atom protein model with volume exclusion. Results obtained by using PDB data show strong correlations between adjacent torsion angle pairs belonging to both the same and different residues. These correlations favor the choice of the nativestate torsion angles, and they are strongly context dependent, determined by the specific amino acid sequence of the protein. Excluded volume or steric clashes, only, do not introduce context-dependent correlations into the chain that would affect the choice of native-state torsional angles. Proteins 2004; 55:992-998.

Research paper thumbnail of Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

PLoS ONE, 2013

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interacti... more Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotypephenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the "guilt-by-association" principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis.

Research paper thumbnail of Non-Redundant Unique Interface Structures as Templates for Modeling Protein Interactions

PLoS ONE, 2014

Improvements in experimental techniques increasingly provide structural data relating to protein-... more Improvements in experimental techniques increasingly provide structural data relating to protein-protein interactions. Classification of structural details of protein-protein interactions can provide valuable insights for modeling and abstracting design principles. Here, we aim to cluster protein-protein interactions by their interface structures, and to exploit these clusters to obtain and study shared and distinct protein binding sites. We find that there are 22604 unique interface structures in the PDB. These unique interfaces, which provide a rich resource of structural data of protein-protein interactions, can be used for template-based docking. We test the specificity of these non-redundant unique interface structures by finding protein pairs which have multiple binding sites. We suggest that residues with more than 40% relative accessible surface area should be considered as surface residues in template-based docking studies. This comprehensive study of protein interface structures can serve as a resource for the community. The dataset can be accessed at http://prism. ccbb.ku.edu.tr/piface.

Research paper thumbnail of A Comparative Molecular Dynamics Study of Methylation State Specificity of JMJD2A

PLoS ONE, 2011

Histone modifications have great importance in epigenetic regulation. JMJD2A is a histone demethy... more Histone modifications have great importance in epigenetic regulation. JMJD2A is a histone demethylase which is selective for di-and trimethyl forms of residues Lys9 and Lys36 of Histone 3 tail (H3K9 and H3K36). We present a molecular dynamics simulations of mono-, di-and trimethylated histone tails in complex with JMJD2A catalytic domain to gain insight into how JMJD2A discriminates between the methylation states of H3K9. The methyl groups are located at specific distances and orientations with respect to Fe(II) in methylammonium binding pocket. For the trimethyllysine the mechanism which provides the effectual orientation of methyl groups is the symmetry, whereas for the dimethyllysine case the determining factors are the interactions between methyllysine head and its environment and subsequently the restriction on angular motion. The occurrence frequency of methyl groups in a certain proximity of Fe(II) comes out as the explanation of the enzyme activity difference on di-and tri-methylated peptides. Energy analysis suggests that recognition is mostly driven by van der Waals and followed by Coulombic interactions in the enzyme-substrate interface. The number (mono, di or tri) and orientations of methyl groups and water molecules significantly affect the extent of van der Waals interaction strengths. Hydrogen bonding analysis suggests that the interaction between JMJD2A and its substrates mainly comes from main chain-side chain interactions. Binding free energy analysis points out Arg8 as an important residue forming an intrasubstrate hydrogen bond with tri and dimethylated Lys9 of the H3 chain. Our study provides new insights into how JMJD2A discriminates between its substrates from both a structural and dynamical point of view.

Research paper thumbnail of PRISM: a web server and repository for prediction of protein–protein interactions and modeling their 3D complexes

Nucleic Acids Research, 2014

The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs).... more The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs). The prediction algorithm is knowledge-based. It combines structural similarity and accounts for evolutionary conservation in the template interfaces. The predicted models are stored in its repository. Given two protein structures, PRISM will provide a structural model of their complex if a matching template interface is available. Users can download the complex structure, retrieve the interface residues and visualize the complex model. The PRISM web server is user friendly, free and open to all users at http: //cosbi.ku.edu.tr/prism.

Research paper thumbnail of Modeling Protein Assemblies in the Proteome

Molecular & Cellular Proteomics, 2014

Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the s... more Most (if not all) proteins function when associated in multimolecular assemblies. Attaining the structures of protein assemblies at the atomic scale is an important aim of structural biology. Experimentally, structures are increasingly available, and computations can help bridge the resolution gap between high-and low-resolution scales. Existing computational methods have made substantial progress toward this aim; however, current approaches are still limited. Some involve manual adjustment of experimental data; some are automated docking methods, which are computationally expensive and not applicable to large-scale proteome studies; and still others exploit the symmetry of the complexes and thus are not applicable to nonsymmetrical complexes. Our study aims to take steps toward overcoming these limitations. We have developed a strategy for the construction of protein assemblies computationally based on binary interactions predicted by a motif-based protein interaction prediction tool, PRISM (Protein Interactions by Structural Matching). Previously, we have shown its power in predicting pairwise interactions. Here we take a step toward multimolecular assemblies, reflecting the more prevalent cellular scenarios. With this method we are able to construct homo-/ hetero-complexes and symmetric/asymmetric complexes without a limitation on the number of components. The method considers conformational changes and is applicable to large-scale studies. We also exploit electron microscopy density maps to select a solution from among the predictions. Here we present the method, illustrate its results, and highlight its current limitations. Molecular & Cellular

Research paper thumbnail of Exploiting Conformational Ensembles in Modeling Protein–Protein Interactions on the Proteome Scale

Journal of Proteome Research, 2013

Cellular functions are performed through protein−protein interactions; therefore, identification ... more Cellular functions are performed through protein−protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledgebased approaches are more useful than "blind" docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited an ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested "difficult" cases in a docking-benchmark data set, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ∼26 to 66%, and 57% of the interactions were successfully predicted in an "unbiased" scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein−protein interaction predictions on an interactome scale. We constructed the structural network of ERK interacting proteins as a case study.