Pemra Ozbek

Community-wide assessment of protein-interface modeling suggests improvements to design methodology

The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

Hot Spots in a Network of Functional Sites

It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation.

DynaFace: Discrimination between Obligatory and Non-obligatory Protein- Protein Interactions Based on the Complex's Dynamics

Protein-protein interfaces have been evolutionarily-designed to enable transduction between the interacting proteins. Thus, we hypothesize that analysis of the dynamics of the complex can reveal details about the nature of the interaction, and in particular whether it is obligatory, i.e., persists throughout the entire lifetime of the proteins, or not. Indeed, normal mode analysis, using the Gaussian network model, shows that for the most part obligatory and non-obligatory complexes differ in their decomposition into dynamic domains, i.e., the mobile elements of the protein complex. The dynamic domains of obligatory complexes often mix segments from the interacting chains, and the hinges between them do not overlap with the interface between the chains. In contrast, in non-obligatory complexes the interface often hinges between dynamic domains, held together through few anchor residues on one side of the interface that interact with their counterpart grooves in the other end. In automatic analysis, 117 of 139 obligatory (84.2%) and 203 of 246 non-obligatory (82.5%) complexes are correctly classified by our method: DynaFace. We further use DynaFace to predict obligatory and non-obligatory interactions among a set of 300 putative protein complexes. DynaFace is available at: http://safir.prc.boun.edu.tr/dynaface.

Dynamic characterization of HLA-B*44 Alleles

Human Leukocyte Antigens (HLA) are highly polymorphic proteins that play a key role in the immune system. HLA molecule is present on the cell membrane of antigen-presenting cells of the immune system and presents short peptides, originating from the proteins of invading pathogens or self-proteins, to the T-cell Receptor (TCR) molecule of the T-cells. In this study, peptide-binding characteristics of HLA-B*44:02, 44:03, 44:05 alleles bound to three nonameric peptides were studied using molecular dynamics simulations. Polymorphisms among these alleles (Asp116Tyr and Asp156Leu) result in major differences in the allele characteristics. While HLA-B*44:02 (Asp116, Asp156) and HLA-B*44:03 (Asp116, Leu156) depend on tapasin for efficient peptide loading, HLA-B*44:05 (Tyr116, Asp156) is tapasin independent. On the other hand, HLA-B*44:02 and HLA-B*44:03 mismatch is closely related to transplant rejection and acute-graft-versus-host disease. In order to understand the dynamic characteristics, the simulation trajectories were analyzed by applying Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) calculations and hydrogen bonding analysis. Binding dynamics of the three HLA-B*44 alleles and peptide sequences are comparatively discussed. In general, peptide binding stability is found to depend on the peptide rather than the allele type for HLA-B*44 alleles.

gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations

Abstract Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid residues and the role played by each in the context of MD simulations, we present a stand-alone software called gRINN (get Residue Interaction eNergies and Networks). gRINN features graphical user interfaces (GUIs) and a command-line interface for generating and analyzing pairwise residue interaction energies and energy correlations from protein MD simulation trajectories. gRINN utilizes the features of NAMD or GROMACS MD simulation packages and automatizes the steps necessary to extract residue-residue interaction energies from user-supplied simulation trajectories, greatly simplifying the analysis for the end-user. A GUI, including an embedded molecular viewer, is provided for visualization of interaction energy time-series, distributions, an interaction energy matrix, interaction energy correlations and a residue correlation matrix. gRINN additionally offers construction and analysis of Protein Energy Networks, providing residue-based metrics such as degrees, betweenness-centralities, closeness centralities as well as shortest path analysis. gRINN is free and open to all users without login requirement at http://grinn.readthedocs.io.

Computational characterization of residue couplings and micropolymorphism-induced changes in the dynamics of two differentially disease-associated human MHC class-I alleles

Human major histocompatibility complex class I (MHC I) – or human leukocyte antigen (HLA) – proteins present intracellularly processed peptides to cytotoxic T lymphocytes in the adaptive immune response to pathogens. A high level of polymorphism in human MHC I proteins defines the peptide-binding specificity of thousands of different MHC alleles. However, polymorphism as well as the peptide ligand can also affect the global dynamics of the complex. In this study, we conducted classical molecular dynamics simulations of two HLA alleles, the ankylosing spondylitis (AS) associated/tapasin-dependent HLA-B*27:05 and nondisease-associated/tapasin-independent HLA-B*27:09, both in peptide-free forms as well as complex with four different peptides ligands. Our results indicate that in peptide-free form, the single amino acid substitution distinguishing the two alleles (D116H), leads to a weaker dynamic coupling of residues in the tapasin-dependent HLA-B*27:05. In peptide-bound form, several residues of the binding-groove, mostly in A and B pockets, show hinge-like behavior in the global motion of the MHC. Moreover, allele-dependent changes are shown in residue interactions, affecting the B-pocket as well as the beta-2-microglobulin (β2m)-facing residues of the HLA chain.

How Do Mutations and Allosteric Inhibitors Modulate Caspase-7 Activity? A Molecular Dynamics Study

Abstract Caspases are members of a highly regulated aspartate-cysteine protease family which have important roles in apoptosis. Pharmaceutical studies focused on these molecules since they are involved in diseases such as cancer and neurodegenerative disorders. A small molecule which binds to the dimeric interface away from the binding site induces a conformational change that resembles the pro-caspase form of the molecule by shifting loop positions. The fluctuation mechanisms caused by mutations or binding of a ligand can explain the key mechanism for the function of that molecule. In this study, we performed molecular dynamics simulations on wild-type and mutated structures (C290N, R187M, Y223A, G188L and G188P) as well as allosterically inhibited structure (DICA-bound caspase-7) to observe the effects of the single mutations on intrinsic dynamics. The results show that previously known changes in catalytic activity upon mutations or allosteric ligand binding are reflected in corresponding changes in the global dynamics of caspase-7. Communicated by Ramaswamy H. Sarma

HLA Proteinlerinin GNM Metodu ile Dinamik Karakterizasyonu

Anahtar Kelimeler Protein dinamiği, Gaussian ağ yapı modeli, HLA, Hızlı modlar Özet: Biyolojik sistemler, birbirleri ile sürekli bilgi alışverişinde bulunan ağyapılar, biyolojik moleküller de bu yapının temel noktaları olarak tanımlanabilirler. Yaşamsal süreklilik açısından sistemin herhangi bir noktasında oluşacak bir sinyalin, hücreler arasında, hücre içinde veya hücre dışından hücre içine iletilmesi büyük önem taşımaktadır. Bu çalışmada, sistematik bir çerçevede HLA (İnsan Lökosit Antijenleri-Human Leukocyte Antigen) molekülleri üzerinde çalışılmıştır. HLAlar hücrelere yapışan yabancı proteinleri tanıyarak kendinden olan ve olmayanı ayırmakta kullanılır, bağışıklık sisteminin temelini oluştururlar. Çalışma kapsamında hesapsal bir yöntem olan Gaussian Ağ yapı modeli uygulanarak HLA sınıf 1 grubuna mensup yapıların yüksek frekanslarda öne çıkan bölgeleri tespit edilmiştir. Tüm moleküllerde hızlı modlarda aynı rezidülerin ön plana çıktığı görülmekte olup bu rezidülerin arasında bir iletişim patikası olduğu düşünülmektedir.

A computational docking study on the pH dependence of peptide binding to HLA-B27 sub-types differentially associated with ankylosing spondylitis

A single amino acid difference (Asp116His), having a key role in a pathogenesis pathway, distinguishes HLA-B*27:05 and HLA-B*27:09 sub-types as associated and non-associated with ankylosing spondylitis, respectively. In this study, molecular docking simulations were carried out with the aim of comprehending the differences in the binding behavior of both alleles at varying pH conditions. A library of modeled peptides was formed upon single point mutations aiming to address the effect of 20 naturally occurring amino acids at the binding core peptide positions. For both alleles, computational docking was applied using Autodock 4.2. Obtained free energies of binding (FEB) were compared within the peptide library and between the alleles at varying pH conditions. The amino acid preferences of each position were studied enlightening the role of each on binding. The preferred amino acids for each position of pVIPR were found to be harmonious with experimental studies. Our results indicate that, as the pH is lowered, the capacity of HLA-B*27:05 to bind peptides in the library is largely lost. Hydrogen bonding analysis suggests that the interaction between the main anchor positions of pVIPR and their respective binding pocket residues are affected from the pH the most, causing an overall shift in the FEB profiles.