Structural Bioinformatics Methods Research Articles

#2263 Computational drug repurposing screen targeting PLA2R antibody binding

Abstract Background and Aims Approximately 60% of patients with membranous nephropathy have antibodies against the phospholipase A2 receptor (PLA2R). The cysteine rich (CysR) epitope of PLA2R is a likely site of protein-antibody interaction. Current treatment regimens for membranous nephropathy involve maximal conservative management or systemic immunosuppression in severe cases. We have developed protocols and programs for an in silico high-throughput repurposing screen using structural modelling, docking, and molecular dynamics (MD). Uniquely, our approach uses a bespoke interface on Google Colab for graphic processing units to run the MD simulations. We describe their application to a repurposing screen aiming to identify larger licensed drug molecules capable of impeding antibody-protein interactions at the site of the CysR epitope. Method A complete model of PLA2R was obtained from I-TASSER using the canonical sequence on the UNIPROT database. This structure was equilibrated using a five nanosecond molecular dynamics (MD) simulation. The simulation was prepared using CHARMM-GUI and run on the GROMACS-ON-COLAB platform. The centroid of the MD system between three and five nanoseconds was used for docking experiments using PLANTS PLP with a study area that included the CysR epitope. A library of compounds listed in the British National Formulary was used for the docking studies. The results would be analysed by PLANTS energy and by key residue overlap score. Results Viable docking results were obtained for 891 of the 1510 compounds tested. 60 of these compounds were in contact with at least 10% of the residues in the CysR region. By restricting these results to compounds in the lowest 20% of the total sample for calculated binding energy, 22 compounds remained. 16 of these compounds have been assessed for their safety for oral or intravenous use. These sixteen compounds were then identified for further investigation by MD to assess the stability of the identified interactions. The sixteen compounds include Lymecycline, Trazodone, Mirabegron, Sulfasalazine, Methotrexate, Rosuvastatin and Montelukast. Conclusion Structural bioinformatics methods provide a relatively fast and economical option for identifying protein-drug interactions that could result in new treatment strategies. The compounds identified for investigation are used for an array of different health conditions. However, they all share the chemical properties of large molecular weight and have the potential to form multiple hydrogen bonds. If validated experimentally, these compounds could provide new treatment options for PLA2R antibody positive membranous nephropathy.

PH-Dependent conformational stability of SpeB from Thermus thermophilus HB8: insights from molecular dynamics simulation

ABSTRACT N(1)-aminopropyl agmatine ureohydrolase (SpeB) is considered an essential enzyme for the growth and survival of thermophiles, it is involved in the biosynthesis of polyamines. The present study investigates the conformational stability and flexibility of Thermus thermophilus HB8 SpeB and its interactions with substrate, N1-aminopropyl agmatine at different physiological conditions to probe the optimal conditions that provide insights on biotechnological applications. As the 3D structure of SpeB is yet to be crystallized, it was modelled and validated using structural bioinformatics methods. To understand the conformational dynamics and also to assess the impact of pH and temperature variables on the tertiary structure of SpeB , atomistic molecular dynamics simulation (MDS) was employed. The MD investigation revealed that 300 K is not optimal for SpeB (apo form) at both acidic pH 4.5, and alkaline pH 8.5, since it exhibited decreased stability and compactness with higher residual flexibility. Further, the stable and strong binding of N1-aminopropyl agmatine with SpeB was observed at following conditions, neutral pH 7 at 353.15 K and alkaline pH 11 at 300 K. Thus, this in silico study provides significant insights into the structural investigations on SpeB along with optimal pH as well as temperature for its ideal enzymatic function. Highlights Structural and dynamic characteristics of T. thermophilus SpeB have been explored in detail Comparative Molecular dynamics simulations were performed to evaluate the effects of both pH and temperature on the structural stability of SpeB SpeB showed pH and temperature-dependent conformational changes that potentially affect substrate binding Structural stability of apo form of SpeB is not optimal at high temperature (363.15 K) in both acidic (pH 5.5) and neutral pH Stable and strong binding affinity of substrate molecule was observed in a neutral pH 7 at 353 K and alkaline pH 11 at 300K

Quantum evaluation and therapeutic activity of (E)-N-(4-methoxyphenyl)-2-(4-(3-oxo-3-phenylprop-1-en-1-yl) phenoxy)acetamide and its modified derivatives against EGFR and VEGFR-2 in the treatment of triple-negative cancer via in silico approach.

The most dangerous subtype of breast cancer, triple-negative breast cancer (TNBC), accounts for 25% of all breast cancer-related deaths and 15% of all breast cancer cases. TNBC is distinguished by the lack of immunohistochemical expression of HER2, progesterone receptors, or oestrogen receptors. Although it has been reported that upregulation of EGFR and VEGFR-2 is associated with TNBC progression, no proven effective targeted therapy exists at this time. We used structural bioinformatics methods, including density functional theory, molecular docking, molecular dynamic simulation, pharmacokinetic and drug-likeness models, to identify promising EGFR/VEGFR-2 inhibitors from N-(4-methoxyphenyl)-2-[4-(3-oxo-3-phenylprop-1-en-1-yl) phenoxy] acetamide and six of its modified derivatives in light of the lack of effective targets inhibitor Version 14 of Spartan software was used to analyse density functional theory. The Schrodinger software suite 2018's Maestro interface was used for the molecular docking analysis, and the admetSAR and swissADME servers were used for drug-likeness and absorption, distribution,metabolism, excretion, and toxicity. All of the compounds showed strong electronic characteristics. Additionally, all of the tested compounds met the ADMET and drug-likeness requirements without a single instance of Lipinski's rule of five violations. Additionally, the molecules' levels of affinity for the target proteins varied. The highest binding affinities were demonstrated by the MOLb-VEGFR-2 complex (- 9.925kcal/mol) and the MOLg-EGFR complex (- 5.032kcal/mol). The interaction of the molecules in the domain of the EGFR and VEGFR-2 receptors was also better understood through molecular dynamic simulation of the complex.

Structural and molecular insights into the mechanism of resistance to enzalutamide by the clinical mutants in androgen receptor (AR) in castration-resistant prostate cancer (CRPC) patients

Androgen receptor (AR) is a key contributing element in the prostate cancer (PCa) instigation, progression and it is among the vastly discovered target for prostate cancer. Numerous mechanisms trigger the expansion of CRPC among which the aberrant AR gene is considered as the prime factor. Recently three essential substitutions H875Y, F877L, and T878A are reported to cause resistance to Enzalutamide. However, no detailed study is available to explore the key events that contribute to the resistance. Hence, considering the applicability of structural bioinformatics and molecular simulation-based methods in the current study, we assessed the impact of these mutations on the binding of Enzalutamide. Using a long-run simulation approach the binding stability, residues flexibility, hydrogen bonding, and protein compactness for each complex were determined to reveal the dynamic variations induced by these mutations. We discovered that the binding mode of Enzalutamide is altered by these mutations which misstarget the key residues required for the antagonistic activity. Molecular simulation of each complex revealed that the wild type H11 and H12 are more flexible moving outside and provides more volume for the ligand optimization. In the mutant complexes, the H12 remained tighter pushing out enzalutamide from the key residues which then essentially misstarget the correct orientation for the antagonist activity. The binding free energy (BFE) for the wild type was computed to be −59.92 ± 0.18 kcal/mol, for H875Y the BFE was −55.92 ± 0.18 kcal/mol, −54.82 ± 0.15 kcal/mol for F877L and −53.87 ± 0.18 kcal/mol for T878A, which further demonstrate that these mutations have destabilized the binding of enzalutamide. The proteins' motion and FEL further validated the aforementioned findings where the wild type reported different dynamic features than the mutant complexes. In conclusion, this study provides a structural basis for the resistance to Enzalutamide, which can be used to design novel effective drugs using structure-based and rationale approaches.

Site Density Functional Theory and Structural Bioinformatics Analysis of the SARS-CoV Spike Protein and hACE2 Complex.

The entry of the SARS-CoV-2, a causative agent of COVID-19, into human host cells is mediated by the SARS-CoV-2 spike (S) glycoprotein, which critically depends on the formation of complexes involving the spike protein receptor-binding domain (RBD) and the human cellular membrane receptor angiotensin-converting enzyme 2 (hACE2). Using classical site density functional theory (SDFT) and structural bioinformatics methods, we investigate binding and conformational properties of these complexes and study the overlooked role of water-mediated interactions. Analysis of the three-dimensional reference interaction site model (3DRISM) of SDFT indicates that water mediated interactions in the form of additional water bridges strongly increases the binding between SARS-CoV-2 spike protein and hACE2 compared to SARS-CoV-1-hACE2 complex. By analyzing structures of SARS-CoV-2 and SARS-CoV-1, we find that the homotrimer SARS-CoV-2 S receptor-binding domain (RBD) has expanded in size, indicating large conformational change relative to SARS-CoV-1 S protein. Protomer with the up-conformational form of RBD, which binds with hACE2, exhibits stronger intermolecular interactions at the RBD-ACE2 interface, with differential distributions and the inclusion of specific H-bonds in the CoV-2 complex. Further interface analysis has shown that interfacial water promotes and stabilizes the formation of CoV-2/hACE2 complex. This interaction causes a significant structural rigidification of the spike protein, favoring proteolytic processing of the S protein for the fusion of the viral and cellular membrane. Moreover, conformational dynamics simulations of RBD motions in SARS-CoV-2 and SARS-CoV-1 point to the role in modification of the RBD dynamics and their impact on infectivity.

Glucosamine-6-phosphate synthase de Mycobacterium tuberculosis um estudo in silico para predição de um modelo tridimensional refinado

Tuberculosis is one of the main causes of death by an infectious agent in the world, according to the World Health Organization. Studies indicate that enzymes involved in the biosynthesis of uridine diphosphate-N-acetylglucosamine are essential for the life cycle of the bacterium. One of these enzymes is glucosamine-6-phosphate synthase (GlmS), which does not have a three-dimensional structure available in the protein database on the internet. In this work, structural bioinformatics methods (comparative modeling and molecular refinement) were used to build a refined three-dimensional model for the GlmS enzyme of Mycobacterium tuberculosis. The model was generated using four templatestructures (crystallographic). The results obtained for the stereochemical and general parameters of the refined model were better than the original model and similarto those templatestructures, validating the refined model.

Discovery of new promising USP14 inhibitors: computational evaluation of the thumb-palm pocket

Ubiquitin-specific protease 14 (USP14) is a member of the deubiquitinating enzymes (DUBs) involved in disrupting the ubiquitin-proteasome regulation system, responsible for the degradation of impaired and misfolded proteins, which is an essential mechanism in eukaryotic cells. The involvement of USP14 in cancer progression and neurodegenerative disorders has been reported. Thereof USP14 is a prime therapeutic target; hence, designing efficacious inhibitors against USP14 is central in curbing these conditions. Herein, we relied on structural bioinformatics methods incorporating molecular docking, molecular mechanics generalized born surface area (MM-GBSA), molecular dynamics simulation (MD simulation), and ADME to identify potential allosteric USP14 inhibitors. A library of over 733 compounds from the PubChem repository with >90% match to the IU1 chemical structure was screened in a multi-step framework to attain prospective drug-like inhibitors. Two potential lead compounds (CID 43013232 and CID 112370349) were shown to record better binding affinity compared to IU1, but with subtle difference to IU1-47, a 10-fold potent compound when compared to IU1. The stability of the lead molecules complexed with USP14 was studied via MD simulation. The molecules were found to be stable within the binding site throughout the 50 ns simulation time. Moreover, the protein–ligand interactions across the simulation run time suggest Phe331, Tyr476, and Gln197 as crucial residues for USP14 inhibition. Furthermore, in-silico pharmacological evaluation revealed the lead compounds as pharmacological sound molecules. Overall, the methods deployed in this study revealed two novel candidates that may show selective inhibitory activity against USP14, which could be exploited to produce potent and harmless USP14 inhibitors. Communicated by Ramaswamy H. Sarma

Comparative Analysis of NS5 Protein for Tick Borne Encephalitis Virus Strains in three Virus Subtypes

Non-structural protein 5 (NS5) of tick-borne encephalitis virus is an enzyme which is responsible for a copying of viral RNA, and it has a strong structural similarity to RNA polymerases of another RNA virus families. The strains of the virus are separated into three subtypes, which differ by specific mutations in virus proteins, including NS5 protein. The methods of structural bioinformatics allow to construct a model of NS5 protein for several strains of the virus.The paper presents the comparative analysis of sequences and structures of NS5 protein, for three subtypes of the tick-borne encephalitis virus. The segments of protein were identified where the highest difference between subtypes and within subtypes is observed. These segments, where most of the mutations are accumulated, are located in methyltransferase domain, in the inter-domain interface, and in the three subdomains of polymerase domain. The association between the locations of mutations in NS5 protein and the flexibility of a protein backbone was observed using normal mode analysis. Namely, the most important mutations are located in the parts of protein where the amplitude of synchronous oscillations estimated using normal mode analysis is the highest: in the second zinc binding pocket within polymerase domain, in the N-terminal extension within inter-domain interface, and around an active site of methyltransferase domain.

Protein kinase KIN10 from Arabidopsis thaliana as a potential regulator of primary microtubule nucleation centers in plants

The nearest plant homologues of animal protein kinase BRSK were identified using the methods of classical and structural bioinformatics. The selection was performed based on the sequence comparison, results of phylogenetic clustering, and analysis of domain architecture. Spatial structures of human BRSK1 and KIN10 from A. thaliana were compared. The relationship between KIN10 and the regulation of primary microtubule nucleation centers in A. thaliana was revealed. Obvious homology of plant KIN10 and mammalian BRSK1 evidence to suggest that this plant protein kinase is associated with the regulation of the structure and function of primary microtubule nucleation centers and is able to phosphorylate γ-tubulin from Arabidopsis (TUBG1 and TUBG2) at Ser131, affecting the γTuSC monomer structure as well as the γTuRC complex assembly. The effect of the modification on the TUBG1-GACP3 interaction was suggested.

Observation selection bias in contact prediction and its implications for structural bioinformatics

Next Generation Sequencing is dramatically increasing the number of known protein sequences, with related experimentally determined protein structures lagging behind. Structural bioinformatics is attempting to close this gap by developing approaches that predict structure-level characteristics for uncharacterized protein sequences, with most of the developed methods relying heavily on evolutionary information collected from homologous sequences. Here we show that there is a substantial observational selection bias in this approach: the predictions are validated on proteins with known structures from the PDB, but exactly for those proteins significantly more homologs are available compared to less studied sequences randomly extracted from Uniprot. Structural bioinformatics methods that were developed this way are thus likely to have over-estimated performances; we demonstrate this for two contact prediction methods, where performances drop up to 60% when taking into account a more realistic amount of evolutionary information. We provide a bias-free dataset for the validation for contact prediction methods called NOUMENON.

A comparative analysis of the spatial structure of nonspecific porins from Yersinia ruckeri using optical spectroscopy and molecular modeling

The spatial organization of outer-membrane porins is studied by optical spectroscopy and molecular modeling. It was found that the OmpF and OmpC porins from Yеrsiniа ruckeri are β-structured membrane proteins typical of the pore-forming proteins of other Gram-negative bacteria. The spatial structures of monomers and trimers of the OmpC and OmpF porins from Y. ruckeri are simulated using methods of structural bioinformatics. It was found that the structural stability of the more thermostable OmpF trimer is sustained by a greater number of hydrogen bonds and hydrophobic interactions. The main differences of the spatial structures of the test porins are observed in the structure of their outer loops. There are three tryptophan residues in the molecules of the OmpC and OmpF porins of Y. ruckeri. It is demonstrated by moleculardynamics methods that after thermal denaturation the solvent accessibility of the Trp212 residue in OmpF porin increased by two times, while the solvent accessibility of a Trp184 residue in OmpC porin was not increased. It is hypothesized that the red-shifted tryptophan fluorescence spectrum of OmpF porin during thermal denaturation is due to the behavior of the Trp212 residue.

The Bio3D Project: Interactive Tools for Structural Bioinformatics

We present extensive updates to Bio3D, a package for both interactive and batch analysis of biomolecular structure, sequence and molecular simulation data. These updates include unique high-throughput ensemble normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, new consensus methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis, interactive structure ensemble visualization as well as multicore support for many time intensive tasks. We demonstrate a new online WebApp server powered by Bio3D for comparative protein structure analysis. This server facilitates: (1) The identification of related protein structures to user specified thresholds of similarity; (2) Their alignment and structure superposition; (3) Sequence and structure conservation analysis; (4) Inter-conformer relationship mapping with principal component analysis, and (5) ensemble normal mode analysis for comparison of predicted deformations across protein families. The WebApp offer unparalleled capabilities for ensemble analysis of protein structures in a user friendly web browser environment from http://thegrantlab.org/bio3d/webapps. The previous version of Bio3D has been downloaded by over 13,700 researchers and cited over 200 times in the last six years. Merging these new methods with the existing Bio3D infrastructure represents an important advance that we hope will further stimulate biophysicists to use structural bioinformatics methods as an aid in solving their research problems. The Bio3D package and associated WebApps are distributed with full source code and extensive documentation under a GPL2 license from http://thegrantlab.org/bio3d/.

Recent progress on structural bioinformatics research of cytochrome P450 and its impact on drug discovery.

Cytochrome P450 is predominantly responsible for human drug metabolism, which is of critical importance for drug discovery and development. Structural bioinformatics focuses on analysis and prediction of three-dimentional structure of biological macromolecules and elucidation of structure-function relationship as well as identification of important binding interactions. Rapid advancement of structural bioinformatics has been made over the last decade. With more information available for CYP structures, the methods of structural bioinformatics may be used in the CYP field. In this review, we demonstrate three previous studies on CYP using the methods of structural bioinformatics, including the investigation of reasons for decrease of enzymatic activity of CYP1A2 caused by a peripheral mutation, the construction of a pharmacophore model specific to active site of CYP1A2 and the prediction of the functional consequences of single residue mutation in CYP. By illustrating these studies we attempt to show the potential role of structural bioinformatics in CYP research and help better understanding the importance of structural bioinformatics in drug designing.

Introduction to structural bioinformatics.

Structural Bioinformatics is one of the hot spots of interdisciplinary sciences and obtained amazing advances in recent years. The first chapter overviews the concept of structural bioinformatics, and briefly describe the contents of this book. The interdisciplinary corporations make it difficult to further divide structural bioinformatics, so the chapters in this book are roughly separated according to the different fields of their applications. That is, fundamental developments in methods of structural bioinformatics, tertiary structure prediction and folding mechanism analysis, the binding mechanism and the interactions between biological macromolecules and ligands, structure-based functional analysis of biological macromolecules, as well as the applications in drug design.

Evidence supporting the existence of a NUPR1-like family of helix-loop-helix chromatin proteins related to, yet distinct from, AT hook-containing HMG proteins.

NUPR1, a small chromatin protein, plays a critical role in cancer development, progression, and resistance to therapy. Here, using a combination of structural bioinformatics and molecular modeling methods, we report several novel findings that enhance our understanding of the biochemical function of this protein. We find that NUPR1 has been conserved throughout evolution, and over time it has undergone duplications and transpositions to form other transcriptional regulators. Using threading, homology-based molecular modeling, molecular mechanics calculations, and molecular dynamics simulations, we generated structural models for four of these proteins: NUPR1a, NUPR1b, NUPR2, and the NUPR-like domain of GTF2-I. Comparative analyses of these models combined with extensive linear motif identification reveal that these four proteins, though similar in their propensities for folding, differ in size, surface changes, and sites amenable for posttranslational modification. Lastly, taking NUPR1a as the paradigm for this family, we built models of a NUPR–DNA complex. Additional structural comparisons revealed that NUPR1 defines a new family of small-groove-binding proteins that share structural features with, yet are distinct from, helix-loop-helix AT-hook-containing HMG proteins. These models and inferences should lead to a better understanding of the function of this group of chromatin proteins, which play a critical role in the development of human malignant diseases.Electronic supplementary materialThe online version of this article (doi:10.1007/s00894-014-2357-7) contains supplementary material, which is available to authorized users.

The Bio3D Package: New Interactive Tools for Structural Bioinformatics

We present extensive updates to Bio3D, a package for the interactive analysis of biomolecular structure, sequence and molecular simulation data. Features include the ability to read and write biomolecular structure, sequence and dynamic trajectory data, query and search online sequence and structure databases, perform alignment, structural superposition, rigid core and dynamic domain identification, sequence and conformational clustering, distance and correlation matrix analysis, conservation analysis, normal mode analysis, principal component analysis, and many other common structural bioinformatics tasks. Bio3D also leverages the extensive graphical and statistical capabilities of the R environment (http://www.r-project.org) and thus provides a useful framework for the exploratory interactive analysis of biomolecular sequence and structure data. Recent notable additions to the package include consensus dynamical community analysis of network based coupled motions, enhanced coarse grained force fields and methods for normal mode analysis, and multicore support for many time intensive tasks. Here we describe these new capabilities with example applications. The previous version of Bio3D has been downloaded by over 13,700 researchers and cited over 100 times in the last six years. Merging these new methods represents an important advance that we hope will further stimulate biophysicists to use structural bioinformatics methods as an aid in solving their research problems. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/.

Функционально-значимая конформационная динамика водорастворимых белков

A study is reported of the functional-relevant dynamics of three typical water-soluble proteins: Calmodulin, Src-tyrosine kinase as well as repressor of Trp operon. Application of the state-of-art methods of structural bioinformatics allowed to identify dynamics seen in the X-ray structures of the investigated proteins associated with their specific biological functions. In addition, Normal Mode analysis technique revealed the most probable directions of the functionally-relevant motions for all that proteins were also predicted. Importantly, overall type of the motions observed on the lowest-frequency modes was very similar to the motions seen from the analysis of the X-ray data of the examined macromolecules. Thereby it was shown that the large-scale as well as local conformational motions of the proteins might be predetermined already at the level of their tertiary structures. In particular, the determining factor might be the specific fold of the alpha-helixes. Thus functionally-relevant in vivo dynamics of the investigated proteins might be evolutionally formed by means of natural selection at the level of the spatial topology.

Classification of rhodopsin structures by modern methods of structural bioinformatics

We report a classification of the crystallographic structures of bovine and squid rhodopsins corresponding to different stages of their photocycles. Using the resource Protein (Structure) Comparison, Knowledge, Similarity, and Information server (ProCKSI, http://www.procksi.net/), selected spatial structures were compared on the basis of classification schemes (dendrograms). To compare the spatial structures of transmembrane proteins, optimal consensus was developed from methods implemented in ProCKSI. Structures were also clustered using principal component analysis, resulting in good agreement with the classification based on the ProCKSI consensus method. Analysis of the results revealed the basic movements of individual transmembrane domains of these proteins that we were able to relate to different stages of the photoactivation of rhodopsin. A combination of methods identified in this study can be used as an up-to-date analytical tool to study the conformational dynamics of membrane receptors.

Simultaneous use of solution, solid-state NMR and X-ray crystallography to study the conformational landscape of the Crh protein during oligomerization and crystallization

We explore, using the Crh protein dimer as a model, how information from solution NMR, solid-state NMR and X-ray crystallography can be combined using structural bioinformatics methods, in order to get insights into the transition from solution to crystal. Using solid-state NMR chemical shifts, we filtered intra-monomer NMR distance restraints in order to keep only the restraints valid in the solid state. These filtered restraints were added to solid-state NMR restraints recorded on the dimer state to sample the conformational landscape explored during the oligomerization process. The use of non-crystallographic symmetries then permitted the extraction of converged conformers subsets. Ensembles of NMR and crystallographic conformers calculated independently display similar variability in monomer orientation, which supports a funnel shape for the conformational space explored during the solution-crystal transition. Insights into alternative conformations possibly sampled during oligomerization were obtained by analyzing the relative orientation of the two monomers, according to the restraint precision. Molecular dynamics simulations of Crh confirmed the tendencies observed in NMR conformers, as a paradoxical increase of the distance between the two β1a strands, when the structure gets closer to the crystallographic structure, and the role of water bridges in this context.

On ARS-interacting multifunctional protein p18

AbstractNine aminoacyl-tRNA synthetases with three auxiliary components are forming a multisynthetase complex which is essential component of protein biosynthesis machinery. The smallest auxiliary component p18 takes part in biosynthesis channeling. It is also a regulator of p53 and has tumor suppressing function. Particular structure of this protein is still unknown. Here methods of structural bioinformatics were applied to generate a model of p18 spatial structure suitable for further research. The structure was created using homology modeling. DNA-binding residues of p18 were also derived both from raw sequence and from three-dimensional structure model.