Predicting protein-DNA interactions by full search computational docking

Considering both small and large scale motions of vascular endothelial growth factor (VEGF) is crucial for reliably predicting its binding affinities to DNA aptamers

Considering both small and large scale motions of VEGF is crucial to predict its relative binding affinities to DNA aptamer variants with docking.

Computational structure modeling for diverse categories of macromolecular interactions

Computational protein-protein docking is one of the most intensively studied topics in structural bioinformatics. The field has made substantial progress through over three decades of development. The development began with methods for rigid-body docking of two proteins, which have now been extended in different directions to cover the various macromolecular interactions observed in a cell. Here, we overview the recent developments of the variations of docking methods, including multiple protein docking, peptide-protein docking, and disordered protein docking methods.

Molecular Modeling Applied to Nucleic Acid-Based Molecule Development

Molecular modeling by means of docking and molecular dynamics (MD) has become an integral part of early drug discovery projects, enabling the screening and enrichment of large libraries of small molecules. In the past decades, special emphasis was drawn to nucleic acid (NA)-based molecules in the fields of therapy, diagnosis, and drug delivery. Research has increased dramatically with the advent of the SELEX (systematic evolution of ligands by exponential enrichment) technique, which results in single-stranded DNA or RNA sequences that bind with high affinity and specificity to their targets. Herein, we discuss the role and contribution of docking and MD to the development and optimization of new nucleic acid-based molecules. This review focuses on the different approaches currently available for molecular modeling applied to NA interaction with proteins. We discuss topics ranging from structure prediction to docking and MD, highlighting their main advantages and limitations and the influence of flexibility on their calculations.

Combining H/D Exchange Mass Spectrometry and Computational Docking To Derive the Structure of Protein-Protein Complexes

Protein-protein interactions are essential for biological function, but structures of protein-protein complexes are difficult to obtain experimentally. To derive the protein complex of the DNA-repair enzyme human uracil-DNA-glycosylase (hUNG) with its protein inhibitor (UGI), we combined rigid-body computational docking with hydrogen/deuterium exchange mass spectrometry (DXMS). Computational docking of the unbound protein structures provides a list of possible three-dimensional models of the complex; DXMS identifies solvent-protected protein residues. DXMS showed that unbound hUNG is compactly folded, but unbound UGI is loosely packed. An increased level of solvent protection of hUNG in the complex was localized to four regions on the same face. The decrease in the number of incorporated deuterons was quantitatively interpreted as the minimum number of main-chain hUNG amides buried in the protein-protein interface. The level of deuteration of complexed UGI decreased throughout the protein chain, indicating both tighter packing and direct solvent protection by hUNG. Three UGI regions showing the greatest decreases were best interpreted leniently, requiring just one main-chain amide from each in the interface. Applying the DXMS constraints as filters to a list of docked complexes gave the correct complex as the largest favorable energy cluster. Thus, identification of approximate protein interfaces was sufficient to distinguish the protein complex. Surprisingly, incorporating the DXMS data as added favorable potentials in the docking calculation was less effective in finding the correct complex. The filtering method has greater flexibility, with the capability to test each constraint and enforce simultaneous contact by multiple regions, but with the caveat that the list from the unbiased docking must include correct complexes.

A fragment-based docking simulation for investigating peptide–protein bindings

We developed a fragment-based docking strategy for long peptide docking simulations, which separates a long peptide into halves for docking, and then recombined to rebuild whole-peptide docking conformations. With further screening, optimizations and MM/GBSA scoring, our method was capable of efficiently predicting the near-native peptide binding conformations.

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

A human transcription factor in search mode

Transcription factors (TF) can change shape to bind and recognize DNA, shifting the energy landscape from a weak binding, rapid search mode to a higher affinity recognition mode. However, the mechanism(s) driving this conformational change remains unresolved and in most cases high-resolution structures of the non-specific complexes are unavailable. Here, we investigate the conformational switch of the human mitochondrial transcription termination factor MTERF1, which has a modular, superhelical topology complementary to DNA. Our goal was to characterize the details of the non-specific search mode to complement the crystal structure of the specific binding complex, providing a basis for understanding the recognition mechanism. In the specific complex, MTERF1 binds a significantly distorted and unwound DNA structure, exhibiting a protein conformation incompatible with binding to B-form DNA. In contrast, our simulations of apo MTERF1 revealed significant flexibility, sampling structures with superhelical pitch and radius complementary to the major groove of B-DNA. Docking these structures to B-DNA followed by unrestrained MD simulations led to a stable complex in which MTERF1 was observed to undergo spontaneous diffusion on the DNA. Overall, the data support an MTERF1-DNA binding and recognition mechanism driven by intrinsic dynamics of the MTERF1 superhelical topology.

C-Terminal Domain of Integrase Binds between the Two Active Sites

HIV integrase (HIV-IN), one of three HIV enzymes, is a target for the treatment of AIDS, but the full biological assembly has been difficult to characterize, hampering inhibitor design. The recent crystallographic structures of integrase from prototype foamy virus (PFV-IN) with bound DNA were a breakthrough, revealing how viral DNA organizes two integrase dimers into a tetramer that has the two active sites appropriately spaced for insertion of the viral DNA into host DNA. The organization of domains within each PFV-IN protein chain, however, varies significantly from that found in HIV-IN structures. With the goal of identifying shared structural characteristics, the interactions among components of the PFV-IN and HIV-IN assemblies were investigated with the macromolecular docking program DOT. DOT performs an exhaustive, rigid-body search between two macromolecules. Computational docking reproduced the crystallographic interactions of the PFV-IN catalytic and N-terminal domains with viral DNA and found similar viral DNA interactions for HIV-IN. Computational docking did not reproduce the crystallographic interactions of the PFV-IN C-terminal domain (CTD). Instead, two symmetry-related positions were found for the PFV-IN CTD that indicate formation of a CTD dimer between the two active sites. Our predicted CTD dimer is consistent with cross-linking studies showing interactions of the CTD with viral DNA that appear to be blocked in the PFV-IN structures. The CTD dimer can insert two arginine-rich loops between the two bound vDNA molecules and the host DNA, a region that is unoccupied in the PFV-IN crystallographic structures. The positive potential from these two loops would alleviate the large negative potential created by the close proximity of two viral vDNA ends, helping to bring together the two active sites and assisting host DNA binding. This study demonstrates the ability of computational docking to evaluate complex crystallographic assemblies, identify interactions that are influenced by the crystal environment, and provide plausible alternatives.

In Silico Characterization and Analysis of RTBP1 and NgTRF1 Protein Through MD Simulation and Molecular Docking: A Comparative Study

Gaining access to sequence and structure information of telomere-binding proteins helps in understanding the essential biological processes involve in conserved sequence-specific interaction between DNA and the proteins. Rice telomere-binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix-turn-helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain, but till now there is very less communication on the in silico studies of these complete proteins. Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK Web server. By digging up all the facts about the proteins, it was revealed that around 120 amino acids in the tail part were showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicate the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA-binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

RNA-LIM: a novel procedure for analyzing protein/single-stranded RNA propensity data with concomitant estimation of interface structure

RNA-LIM is a procedure that can analyze various pseudo-potentials describing the affinity between single-stranded RNA (ssRNA) ribonucleotides and surface amino acids to produce a coarse-grained estimate of the structure of the ssRNA at the protein interface. The search algorithm works by evolving an ssRNA chain, of known sequence, as a series of walks between fixed sites on a protein surface. Optimal routes are found by application of a set of minimal "limiting" restraints derived jointly from (i) selective sampling of the ribonucleotide amino acid affinity pseudo-potential data, (ii) limited surface path exploration by prior determination of surface arc lengths, and (iii) RNA structural specification obtained from a statistical potential gathered from a library of experimentally determined ssRNA structures. We describe the general approach using a NAST (Nucleic Acid Simulation Tool)-like approximation of the ssRNA chain and a generalized pseudo-potential reflecting the location of nucleic acid binding residues. Minimum and maximum performance indicators of the methodology are established using both synthetic data, for which the pseudo-potential defining nucleic acid binding affinity is systematically degraded, and a representative real case, where the RNA binding sites are predicted by the amplified antisense RNA (aaRNA) method. Some potential uses and extensions of the routine are discussed. RNA-LIM analysis programs along with detailed instructions for their use are available on request from the authors.

In silico characterization and analysis of RTBP1 and NgTRF1 protein through MD simulation and molecular docking - A comparative study

Gaining access to sequence and structure information of telomere binding proteins helps in understanding the essential biological processes involve in conserved sequence specific interaction between DNA and the proteins. Rice telomere binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix turn helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain but till now there is very less communication on the in silico studies of these complete proteins.Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK web server.Digging up all the facts about the proteins it was reveled that around 120 amino acids in the tail part was showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicates the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and Energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

Advances in Human Biology: Combining Genetics and Molecular Biophysics to Pave the Way for Personalized Diagnostics and Medicine

Advances in several biology-oriented initiatives such as genome sequencing and structural genomics, along with the progress made through traditional biological and biochemical research, have opened up a unique opportunity to better understand the molecular effects of human diseases. Human DNA can vary significantly from person to person and determines an individual’s physical characteristics and their susceptibility to diseases. Armed with an individual’s DNA sequence, researchers and physicians can check for defects known to be associated with certain diseases by utilizing various databases. However, for unclassified DNA mutations or in order to reveal molecular mechanism behind the effects, the mutations have to be mapped onto the corresponding networks and macromolecular structures and then analyzed to reveal their effect on the wild type properties of biological processes involved. Predicting the effect of DNA mutations on individual’s health is typically referred to as personalized or companion diagnostics. Furthermore, once the molecular mechanism of the mutations is revealed, the patient should be given drugs which are the most appropriate for the individual genome, referred to as pharmacogenomics. Altogether, the shift in focus in medicine towards more genomic-oriented practices is the foundation of personalized medicine. The progress made in these rapidly developing fields is outlined.