Information-driven protein-DNA docking using HADDOCK: it is a matter of flexibility

Identification of potential mutational hotspots in serratiopeptidase to address its poor pH tolerance issue

Serratiopeptidase is the multifunctionality metalloendopeptidase extensively employed in biopharmaceutical and industrial biotechnology. Despite its poor pH tolerance, serratiopeptidase must withstand the highly acidic environment of the gastrointestinal tract to be used as a potent anti-inflammatory and analgesic medication. In earlier studies, post-translational deamination related mutations showed alteration in the net charge of protein's surface. Therefore, the current study aimed to enhance the acid resistance of serratiopeptidase via implementing computational interventions to screen out the most stable mutational hotspot. The methodology used in this study is as follows: (a) Higher accessibility to surface (b) 4 Å away from active site region to avoid interference with its proteolytic activity, and (c) By converting non-conserved amide residues to acidic residues. A docking study has been conducted to establish the substrate specificity and binding affinity to native and mutant proteins. The docking outcomes were then validated using molecular dynamic simulations to clarify each mutant's molecular stability and conformation while preserving their activity. The results showed that N412D is the best-screened mutant with negative electrostatic potential that can alter the overall charge on the protein's surface with increased H+ ions. Alteration in overall charge leads to protein surface more acidic that causes a common ion effect in stomach pH and act as a buffer which could stabilize the serratiopeptidase amid extreme pH.Communicated by Ramaswamy H. Sarma.

Profiling the disintegration of BRPs released by massive wasp stings using serratiopeptidase: An in-silico insight

Serratiopeptidase is a multifaceted therapeutic enzyme renowned for its anti-inflammatory, analgesic, anti-biofilm, fibrinolytic, and anti-edemic properties. It is vital to uncover more about the assets of such efficacious enzyme in order to facilitate their contribution in all health-related issues, notably inflammatory ailments. The current study sought to determine whether serratiopeptidase would disintegrate bradykinin related peptides (BRPs) from wasp venom in the same manner as it does with human bradykinin. To accomplish this objective, we docked selected BRPs onto the binding pocket of wild and previously identified mutant (N412D) of serratiopeptidase. Based on their docked scores, the top two BRPs were selected, and their conformational behavior was analyzed employing molecular dynamics studies. Additionally, thermodynamics end-state energy analysis reported that both the complexes exhibited higher stability and identical ΔG values when compared to the reference complex. Further, we condemned the external pulling forces on both peptides to observe the force needed in the disassociation process to endorse the binding affinity findings in terms of unbinding mechanism. This analysis suggested that BRP-7 (Wasp kinin PMM1) peptide was tightly anchored and laid out the highest pulling force to get detach from the active pocket of serratiopeptidase in contrast to the BRP-6 peptide. The current study endorses up the present findings and paves the way for serratiopeptidase to be used as an anti-angioedemic peptidase as well as a fixed-dose combination (FDC) in hypotensive drugs.

Dissecting the Enantioselective Neurotoxicity of Isocarbophos: Chiral Insight from Cellular, Molecular, and Computational Investigations

Chiral organophosphorus pollutants are found abundantly in the environment, but the neurotoxicity risks of these asymmetric chemicals to human health have not been fully assessed. Using cellular, molecular, and computational toxicology methods, this story is to explore the static and dynamic toxic actions and its stereoselective differences of chiral isocarbophos toward SH-SY5Y nerve cells mediated by acetylcholinesterase (AChE) and further dissect the microscopic basis of enantioselective neurotoxicity. Cell-based assays indicate that chiral isocarbophos exhibits strong enantioselectivity in the inhibition of the survival rates of SH-SY5Y cells and the intracellular AChE activity, and the cytotoxicity of (S)-isocarbophos is significantly greater than that of (R)-isocarbophos. The inhibitory effects of isocarbophos enantiomers on the intracellular AChE activity are dose-dependent, and the half-maximal inhibitory concentrations (IC₅₀) of (R)-/(S)-isocarbophos are 6.179/1.753 μM, respectively. Molecular experiments explain the results of cellular assays, namely, the stereoselective toxic actions of isocarbophos enantiomers on SH-SY5Y cells are stemmed from the differences in bioaffinities between isocarbophos enantiomers and neuronal AChE. In the meantime, the modes of neurotoxic actions display that the key amino acid residues formed strong noncovalent interactions are obviously different, which are related closely to the molecular structural rigidity of chiral isocarbophos and the conformational dynamics and flexibility of the substrate binding domain in neuronal AChE. Still, we observed that the stable "sandwich-type π-π stacking" fashioned between isocarbophos enantiomers and aromatic Trp-86 and Tyr-337 residues is crucial, which notably reduces the van der Waals' contribution (ΔG_vdW) in the AChE-(S)-isocarbophos complexes and induces the disparities in free energies during the enantioselective neurotoxic conjugations and thus elucidating that (S)-isocarbophos mediated by synaptic AChE has a strong toxic effect on SH-SY5Y neuronal cells. Clearly, this effort can provide experimental insights for evaluating the neurotoxicity risks of human exposure to chiral organophosphates from macroscopic to microscopic levels.

Ceftriaxone induces glial EAAT-2 promotor region via NF-kB conformational changes: An interaction analysis using HADDOCK

Excitotoxicity, depletion of energy metabolites, and ionic imbalance are the major factors involved in neurodegeneration mediated through excitatory amino acid transporter-2 (EAAT-2) dysfunction in ischemic insult. Recent studies have revealed that ceftriaxone expresses EAAT-2 via nuclear transcription factor kappa-B (NF-kB) signaling pathway, stimulation of EAAT-2 expression in the ischemic, and excitotoxic conditions that could provide potential benefits to control neurodegeneration. In this study, we have predicted the in silico model for interaction between NF-kB and EAAT-2 promoter region to rule out the conformational changes for the expression of EAAT-2 protein. Using homology-built model of NF-kB, we identified ceftriaxone-induced conformational changes in gene locus -272 of DNA where NF-kB binding with EAAT-2 promoter region through protein-DNA docking calculation. The interaction profile and conformational dynamics occurred between ceftriaxone predocked and postdocked conformations of NF-kB with DNA employing HADDOCK 2.2 web server followed by 250 ns long all atom explicit solvent molecular dynamics simulations. Both the protein and DNA exhibited modest conformational changes with respect to HADDOCK score, energy terms (desolvation energy [E_desolv ]), van der waal energy (E_vdw ), electrostatic energy (E_elec ), restraints energy (E_air ), buried surface area, root mean square deviation, RMSF, radius of gyration, total hydrogen bonds when ceftriaxone pre- and postdocked NF-kB conformations were bound to DNA. Hence, the conformational changes in the C-terminal domain could be the reason for EAAT-2 expression through ceftriaxone specific binding pocket of -272 of DNA.

Computationally Designed Anti-LuxP DNA Aptamer Suppressed Flagellar Assembly- and Quorum Sensing-Related Gene Expression in Vibrio parahaemolyticus

(1) Background: Quorum sensing (QS) is the chemical communication between bacteria that sense chemical signals in the bacterial population to control phenotypic changes through the regulation of gene expression. The inhibition of QS has various potential applications, particularly in the prevention of bacterial infection. QS can be inhibited by targeting the LuxP, a periplasmic receptor protein that is involved in the sensing of the QS signaling molecule known as the autoinducer 2 (AI-2). The sensing of AI-2 by LuxP transduces the chemical information through the inner membrane sensor kinase LuxQ protein and activates the QS cascade. (2) Methods: An in silico approach was applied to design DNA aptamers against LuxP in this study. A method combining molecular docking and molecular dynamics simulations was used to select the oligonucleotides that bind to LuxP, which were then further characterized using isothermal titration calorimetry. Subsequently, the bioactivity of the selected aptamer was examined through comparative transcriptome analysis. (3) Results: Two aptamer candidates were identified from the ITC, which have the lowest dissociation constants (Kd) of 0.2 and 0.5 micromolar. The aptamer with the lowest Kd demonstrated QS suppression and down-regulated the flagellar-assembly-related gene expression. (4) Conclusions: This study developed an in silico approach to design an aptamer that possesses anti-QS properties.

In silico optimization of RNA-protein interactions for CRISPR-Cas13-based antimicrobials

RNA–protein interactions are crucial for diverse biological processes. In prokaryotes, RNA–protein interactions enable adaptive immunity through CRISPR-Cas systems. These defence systems utilize CRISPR RNA (crRNA) templates acquired from past infections to destroy foreign genetic elements through crRNA-mediated nuclease activities of Cas proteins. Thanks to the programmability and specificity of CRISPR-Cas systems, CRISPR-based antimicrobials have the potential to be repurposed as new types of antibiotics. Unlike traditional antibiotics, these CRISPR-based antimicrobials can be designed to target specific bacteria and minimize detrimental effects on the human microbiome during antibacterial therapy. In this study, we explore the potential of CRISPR-based antimicrobials by optimizing the RNA–protein interactions of crRNAs and Cas13 proteins. CRISPR-Cas13 systems are unique as they degrade specific foreign RNAs using the crRNA template, which leads to non-specific RNase activities and cell cycle arrest. We show that a high proportion of the Cas13 systems have no colocalized CRISPR arrays, and the lack of direct association between crRNAs and Cas proteins may result in suboptimal RNA–protein interactions in the current tools. Here, we investigate the RNA–protein interactions of the Cas13-based systems by curating the validation dataset of Cas13 protein and CRISPR repeat pairs that are experimentally validated to interact, and the candidate dataset of CRISPR repeats that reside on the same genome as the currently known Cas13 proteins. To find optimal CRISPR-Cas13 interactions, we first validate the 3-D structure prediction of crRNAs based on their experimental structures. Next, we test a number of RNA–protein interaction programs to optimize the in silico docking of crRNAs with the Cas13 proteins. From this optimized pipeline, we find a number of candidate crRNAs that have comparable or better in silico docking with the Cas13 proteins of the current tools. This study fully automatizes the in silico optimization of RNA–protein interactions as an efficient preliminary step for designing effective CRISPR-Cas13-based antimicrobials.

Evaluation of immune evasion in SARS-CoV-2 Delta and Omicron variants

Emerging SARS-CoV-2 variants with higher transmissibility and immune escape remain a persistent threat across the globe. This is evident from the recent outbreaks of the Delta (B.1.617.2) and Omicron variants. These variants have originated from different continents and spread across the globe. In this study, we explored the genomic and structural basis of these variants for their lineage defining mutations of the spike protein through computational analysis, protein modeling, and molecular dynamic (MD) simulations. We further experimentally validated the importance of these deletion mutants for their immune escape using a pseudovirus-based neutralization assay, and an antibody (4A8) that binds directly to the spike protein's NTD. Delta variant with the deletion and mutations in the NTD revealed a better rigidity and reduced flexibility as compared to the wild-type spike protein (Wuhan isolate). Furthermore, computational studies of 4A8 monoclonal antibody (mAb) revealed a reduced binding of Delta variant compared to the wild-type strain. Similarly, the MD simulation data and virus neutralization assays revealed that the Omicron also exhibits immune escape, as antigenic beta-sheets appear to be disrupted. The results of the present study demonstrate the higher possibility of immune escape and thereby achieved better fitness advantages by the Delta and Omicron variants, which warrants further demonstrations through experimental evidences. Our study, based on in-silico computational modelling, simulations, and pseudovirus-based neutralization assay, highlighted and identified the probable mechanism through which the Delta and Omicron variants are more pathogenically evolved with higher transmissibility as compared to the wild-type strain.

Human Coronavirus Spike Protein Based Multi-Epitope Vaccine against COVID-19 and Potential Future Zoonotic Coronaviruses by Using Immunoinformatic Approaches

Zoonotic coronaviruses (CoV) have emerged twice and have caused severe respiratory diseases in humans. Due to the frequent outbreaks of different human coronaviruses (HCoVs), the development of a pan-HCoV vaccine is of great importance. Various conserved epitopes shared by HCoVs are reported to induce cross-reactive T-cell responses. Therefore, this study aimed to design a multi-epitope vaccine, targeting the HCoV spike protein. Genetic analysis revealed that the spike region is highly conserved among SARS-CoV-2, bat SL-CoV, and SARS-CoV. By employing the immunoinformatic approach, we prioritized 20 MHC I and 10 MHCII conserved epitopes to design a multi-epitope vaccine. This vaccine candidate is anticipated to strongly elicit both humoral and cell-mediated immune responses. These results warrant further development of this vaccine into real-world application.

Searching for Low Probability Opening Events in a DNA Sliding Clamp

The β subunit of E. coli DNA polymererase III is a DNA sliding clamp associated with increasing the processivity of DNA synthesis. In its free form, it is a circular homodimer structure that can accomodate double-stranded DNA in a nonspecific manner. An open state of the clamp must be accessible before loading the DNA. The opening mechanism is still a matter of debate, as is the effect of bound DNA on opening/closing kinetics. We use a combination of atomistic, coarse-grained, and enhanced sampling strategies in both explicit and implicit solvents to identify opening events in the sliding clamp. Such simulations of large nucleic acid and their complexes are becoming available and are being driven by improvements in force fields and the creation of faster computers. Different models support alternative opening mechanisms, either through an in-plane or out-of-plane opening event. We further note some of the current limitations, despite advances, in modeling these highly charged systems with implicit solvent.

Structure, dynamics, and function of SrnR, a transcription factor for nickel-dependent gene expression

Streptomyces griseus, a bacterium producing antibacterial drugs and featuring possible application in phytoremediation, expresses two metal-dependent superoxide dismutase (SOD) enzymes, containing either Fe(II) or Ni(II) in their active site. In particular, the alternative expression of the two proteins occurs in a metal-dependent mode, with the Fe(II)-enzyme gene (sodF) repressed at high intracellular Ni(II) concentrations by a two-component system (TCS). This complex involves two proteins, namely SgSrnR and SgSrnQ, which represent the transcriptional regulator and the Ni(II) sensor of the system, respectively. SgSrnR belongs to the ArsR/SmtB family of metal-dependent transcription factors; in the apo-form and in the absence of SgSrnQ, it can bind the DNA operator of sodF, upregulating gene transcription. According to a recently proposed hypothesis, Ni(II) binding to SgSrnQ would promote its interaction with SgSrnR, causing the release of the complex from DNA and the consequent downregulation of the sodF expression. SgSrnQ is predicted to be highly disordered, thus the understanding, at the molecular level, of how the SgSrnR/SgSrnQ TCS specifically responds to Ni(II) requires the knowledge of the structural, dynamic, and functional features of SgSrnR. These were investigated synergistically in this work using X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, atomistic molecular dynamics calculations, isothermal titration calorimetry, and in silico molecular docking. The results reveal that the homodimeric apo-SgSrnR binds to its operator in a two-step process that involves the more rigid globular portion of the protein and leaves its largely disordered regions available to possibly interact with the disordered SgSrnQ in a Ni-dependent process.

Structural Characterization of the Interaction of Hypoxia Inducible Factor-1 with Its Hypoxia Responsive Element at the -964G > A Variation Site of the HLA-G Promoter Region

Human Antigen Leukocyte-G (HLA-G) gene encodes an immune checkpoint molecule that has restricted tissue expression in physiological conditions; however, the gene may be induced in hypoxic conditions by the interaction with the hypoxia inducible factor-1 (HIF1). Hypoxia regulatory elements (HRE) located at the HLA-G promoter region and at exon 2 are the major HIF1 target sites. Since the G allele of the −964G > A transversion induces higher HLA-G expression when compared to the A allele in hypoxic conditions, here we analyzed HIF1-HRE complex interaction at the pair-atom level considering both −964G > A polymorphism alleles. Mouse HIF2 dimer crystal (Protein Data Bank ID: 4ZPK) was used as template to perform homology modelling of human HIF1 quaternary structure using MODELLER v9.14. Two 3D DNA structures were built from 5′GCRTG’3 HRE sequence containing the −964G/A alleles using x3DNA. Protein-DNA docking was performed using the HADDOCK v2.4 server, and non-covalent bonds were computed by DNAproDB server. Molecular dynamic simulation was carried out per 200 ns, using Gromacs v.2019. HIF1 binding in the HRE containing −964G allele results in more hydrogen bonds and van der Waals contact formation than HRE with −964A allele. Protein-DNA complex trajectory analysis revealed that HIF1-HRE-964G complex is more stable. In conclusion, HIF1 binds in a more stable and specific manner at the HRE with G allele.

Definition of the Binding Architecture to a Target Promoter of HP1043, the Essential Master Regulator of Helicobacter pylori

HP1043 is an essential orphan response regulator of Helicobacter pylori orchestrating multiple crucial cellular processes. Classified as a member of the OmpR/PhoB family of two-component systems, HP1043 exhibits a highly degenerate receiver domain and evolved to function independently of phosphorylation. Here, we investigated the HP1043 binding mode to a target sequence in the hp1227 promoter (P_hp1227). Scanning mutagenesis of HP1043 DNA-binding domain and consensus sequence led to the identification of residues relevant for the interaction of the protein with a target DNA. These determinants were used as restraints to guide a data-driven protein-DNA docking. Results suggested that, differently from most other response regulators of the same family, HP1043 binds in a head-to-head conformation to the P_hp1227 target promoter. HP1043 interacts with DNA largely through charged residues and contacts with both major and minor grooves of the DNA are required for a stable binding. Computational alanine scanning on molecular dynamics trajectory was performed to corroborate our findings. Additionally, in vitro transcription assays confirmed that HP1043 positively stimulates the activity of RNA polymerase.

In-Silico analysis reveals lower transcription efficiency of C241T variant of SARS-CoV-2 with host replication factors MADP1 and hnRNP-1

Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more than 3.3 million lives worldwide and still counting. As per the GISAID database, the genomics of SARS-CoV-2 has been extensively studied, with more than 500 genome submissions per day. Out of several hotspot mutations within the SARS-CoV-2 genome, recent research has focused mainly on the missense variants. Moreover, significantly less attention has been accorded to delineate the role of the untranslated regions (UTRs) of the SARS-CoV-2 genome in the disease progression and etiology. One of the most frequent 5' UTR variants in the SARS-CoV-2 genome is the C241T, with a global frequency of more than 95 %. In the present study, the effect of the C241T mutation has been studied with respect to the changes in RNA structure and its interaction with the host replication factors MADP1 Zinc finger CCHC-type and RNA-binding motif 1 (hnRNP1). The results obtained from molecular docking and molecular dynamics simulation indicated weaker interaction of C241T mutant stem-loops with the host transcription factor MADP1, indicating a reduced replication efficiency. The results are also correlated with increased recovery rates and decreased death rates of global SARS-CoV-2 cases.

In silico molecular docking in DNA aptamer development

Aptamers are single-stranded DNA or RNA oligonucleotides generated by SELEX that exhibit binding affinity and specificity against a wide variety of target molecules. Compared to RNA aptamers, DNA aptamers are much more stable and therefore are widely adopted in a number of applications especially in diagnostics. The tediousness and rigor associated with certain steps of the SELEX intensify the efforts to adopt in silico molecular docking approaches together with in vitro SELEX procedures in developing DNA aptamers. Inspired by these endeavors, we carry out an overview of the in silico molecular docking approaches in DNA aptamer generation, by detailing the stepwise procedures as well as shedding some light on the various softwares used. The in silico maturation strategy and the limitations of the in silico approaches are also underscored.

The ancillary N-terminal region of the yeast AP-1 transcription factor Yap8 contributes to its DNA binding specificity

Activator protein 1 (AP-1) is one of the largest families of basic leucine zipper (bZIP) transcription factors in eukaryotic cells. How AP-1 proteins achieve target DNA binding specificity remains elusive. In Saccharomyces cerevisiae, the AP-1-like protein (Yap) family comprises eight members (Yap1 to Yap8) that display distinct genomic target sites despite high sequence homology of their DNA binding bZIP domains. In contrast to the other members of the Yap family, which preferentially bind to short (7–8 bp) DNA motifs, Yap8 binds to an unusually long DNA motif (13 bp). It has been unclear what determines this unique specificity of Yap8. In this work, we use molecular and biochemical analyses combined with computer-based structural design and molecular dynamics simulations of Yap8–DNA interactions to better understand the structural basis of DNA binding specificity determinants. We identify specific residues in the N-terminal tail preceding the basic region, which define stable association of Yap8 with its target promoter. We propose that the N-terminal tail directly interacts with DNA and stabilizes Yap8 binding to the 13 bp motif. Thus, beside the core basic region, the adjacent N-terminal region contributes to alternative DNA binding selectivity within the AP-1 family.

MARTINI-Based Protein-DNA Coarse-Grained HADDOCKing

Modeling biomolecular assemblies is an important field in computational structural biology. The inherent complexity of their energy landscape and the computational cost associated with modeling large and complex assemblies are major drawbacks for integrative modeling approaches. The so-called coarse-graining approaches, which reduce the degrees of freedom of the system by grouping several atoms into larger “pseudo-atoms,” have been shown to alleviate some of those limitations, facilitating the identification of the global energy minima assumed to correspond to the native state of the complex, while making the calculations more efficient. Here, we describe and assess the implementation of the MARTINI force field for DNA into HADDOCK, our integrative modeling platform. We combine it with our previous implementation for protein-protein coarse-grained docking, enabling coarse-grained modeling of protein-nucleic acid complexes. The system is modeled using MARTINI topologies and interaction parameters during the rigid body docking and semi-flexible refinement stages of HADDOCK, and the resulting models are then converted back to atomistic resolution by an atom-to-bead distance restraints-guided protocol. We first demonstrate the performance of this protocol using 44 complexes from the protein-DNA docking benchmark, which shows an overall ~6-fold speed increase and maintains similar accuracy as compared to standard atomistic calculations. As a proof of concept, we then model the interaction between the PRC1 and the nucleosome (a former CAPRI target in round 31), using the same information available at the time the target was offered, and compare all-atom and coarse-grained models.

Structural approaches for the DNA binding motifs prediction in Bacillus thuringiensis sigma-E transcription factor (σETF)

The sigma-E transcription factor (σ^ETF) can be found in most of the bacteria cells including Bacillus thuringiensis. However, the cellular regulatory mechanisms of these transcription factors in the mass production of δ-endotoxins during sporulation stage are yet to be revealed. In addition, the recognition of DNA towards σ^ETF DNA binding motifs that led to the transcription activities is also being poorly studied. Therefore, this work studied the possible DNA binding motifs of σ^ETF by utilising in silico approaches. The structure of σ^ETF was first built via three different computational methods. A cognate DNA sequence was then docked to the predicted σ^ETF DNA-binding motifs. The binding free energy calculated using molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) for triplicate 50 ns simulation of σ^ETF-DNA complex revealed favourable binding energy of DNA to σ^ETF (average ∆G_bind = -34.57 kcal/mol) mainly driven by non-polar interactions. This study revealed that σ^ETF LYS131, ARG133, PHE138, TRP146, ARG222, LYS225 and ARG226 are most likely the key residues upon the binding and recognition of DNA prior to transcription actives. Since determination of genome-regulating protein which recognises specific DNA sequence is important to discriminate between the proteins preferences for different genes, this study might provide some understanding on the possible σ^ETF-DNA recognition prior to transcription initiated for the δ-endotoxins production.

Rational design of an XNA ligase through docking of unbound nucleic acids to toroidal proteins

Xenobiotic nucleic acids (XNA) are nucleic acid analogues not present in nature that can be used for the storage of genetic information. In vivo XNA applications could be developed into novel biocontainment strategies, but are currently limited by the challenge of developing XNA processing enzymes such as polymerases, ligases and nucleases. Here, we present a structure-guided modelling-based strategy for the rational design of those enzymes essential for the development of XNA molecular biology. Docking of protein domains to unbound double-stranded nucleic acids is used to generate a first approximation of the extensive interaction of nucleic acid processing enzymes with their substrate. Molecular dynamics is used to optimise that prediction allowing, for the first time, the accurate prediction of how proteins that form toroidal complexes with nucleic acids interact with their substrate. Using the Chlorella virus DNA ligase as a proof of principle, we recapitulate the ligase's substrate specificity and successfully predict how to convert it into an XNA-templated XNA ligase.

Molecular Modelling of the Ni(II)-Responsive Synechocystis PCC 6803 Transcriptional Regulator InrS in the Metal Bound Form

InrS (internal nickel-responsive sensor) is a transcriptional regulator found in cyanobacteria that represses the transcription of the nickel exporter NrsD in the apo form and de-represses expression of the exporter upon Ni(II) binding. Although a crystal structure of apo-InrS from Synechocystis PCC 6803 has been reported, no structure of the protein with metal ions bound is available. Here we report the results of a computational study aimed to reconstruct the metal binding site by taking advantage of recent X-ray absorption spectroscopy (XAS) data and to envisage the structural rearrangements occurring upon Ni(II) binding. The modelled Ni(II) binding site shows a square planar geometry consistent with experimental data. The structural details of the conformational changes occurring upon metal binding are also discussed in the framework of trying to rationalize the different affinity of the apo- and holo-forms of the protein for DNA.

An SVM-based method for assessment of transcription factor-DNA complex models

Background

Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models.

Results

We present here a Support Vector Machine (SVM)-based approach for quality assessment of the predicted transcription factor (TF)-DNA complex models. Besides a knowledge-based protein-DNA interaction potential DDNA3, we applied several structural features that have been shown to play important roles in binding specificity between transcription factors and DNA molecules to quality assessment of complex models. To address the issue of unbalanced positive and negative cases in the training dataset, we applied hard-negative mining, an iterative training process that selects an initial training dataset by combining all of the positive cases and a random sample from the negative cases. Results show that the SVM model greatly improves prediction accuracy (84.2%) over two knowledge-based protein-DNA interaction potentials, orientation potential (60.8%) and DDNA3 (68.4%). The improvement is achieved through reducing the number of false positive predictions, especially for the hard docking cases, in which a docking algorithm fails to produce any near-native complex models.

Conclusions

A learning-based SVM scoring model with structural features for specific protein-DNA binding and an atomic-level protein-DNA interaction potential DDNA3 significantly improves prediction accuracy of complex models by successfully identifying cases without near-native structural models.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2538-y) contains supplementary material, which is available to authorized users.

Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges. As an alternative, computational prediction of RNP interactions can be carried out. Structural models obtained by theoretical predictive methods are, in general, less reliable compared to models based on experimental measurements but they can be sufficiently accurate to be used as a basis for to formulating functional hypotheses. In this article, we present an overview of computational methods for 3D structure prediction of RNP complexes. We discuss currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular. Additionally, we also review benchmarks that have been developed to assess the accuracy of these methods.

Poly (ADP-Ribose) Polymerase 1 Mediated Arginase II Activation Is Responsible for Oxidized LDL-Induced Endothelial Dysfunction

It is well known that arginase II leads to decreased synthesis of nitric oxide (NO) by competing with endothelial nitric oxide synthase (eNOS) for their same substrate L-arginine. However, the regulatory mechanisms of arginase II production remain unclear. In this study, we hypothesized that poly- (ADP-ribose) transferase/polymerase-1 (PARP-1) may be a critical factor responsible for ox-LDL (oxidized Low Density Lipoprotein)-enhanced arginase II activity. We used serial deletions within plasmid constructs and found that a core promoter region of arginase II was located at the element of -774 to -738 bp and PARP-1 was identified specifically binding to this region. Inhibition of PARP-1 markedly reduced the endogenous arginase II expression and enhanced eNOS and NO production. Similarly, ox-LDL-induced increase in arginase II production and eNOS and NO reduction was substantially abolished by PARP-1 inhibition both in vitro and in vivo. Significant decrease in arginase II expression and increase in eNOS expression and NO levels, as well as improved endothelial function were observed in PARP-1-/- mice. The underlying mechanisms of ox-LDL-induced changes of PARP-1 expression involved migration of phosphorylated ERK2 into nuclei and direct interaction with PARP-1 which dramatically enhanced PARP-1 production, followed by histone acetylation to activate arginase II transcription process. Our studies demonstrated for the first time that PARP-1 regulates basal transcription process and ox-LDL-induced up-regulation of arginase II. These results demonstrated that PARP-1 offers a promising therapeutic target for endothelial dysfunction and atherosclerosis.

Reducing Mutant Huntingtin Protein Expression in Living Cells by a Newly Identified RNA CAG Binder

Expanded CAG trinucleotide repeats in Huntington's disease (HD) are causative for neurotoxicity. The mutant CAG repeat RNA encodes neurotoxic polyglutamine proteins and can lead to a toxic gain of function by aberrantly recruiting RNA-binding proteins. One of these is the MID1 protein, which induces aberrant Huntingtin (HTT) protein translation upon binding. Here we have identified a set of CAG repeat binder candidates by in silico methods. One of those, furamidine, reduces the level of binding of HTT mRNA to MID1 and other target proteins in vitro. Metadynamics calculations, fairly consistent with experimental data measured here, provide hints about the binding mode of the ligand. Importantly, furamidine also decreases the protein level of HTT in a HD cell line model. This shows that small molecules masking RNA-MID1 interactions may be active against mutant HTT protein in living cells.

Molecular principles for heparin oligosaccharide-based inhibition of neutrophil elastase in cystic fibrosis

Cystic fibrosis (CF) is a multifactorial disease in which dysfunction of protease-antiprotease balance plays a key role. The current CF therapy relies on dornase α, hypertonic saline, and antibiotics and does not address the high neutrophil elastase (NE) activity observed in the lung and sputum of CF patients. Our hypothesis is that variants of heparin, which potently inhibit NE but are not anticoagulant, would help restore the protease-antiprotease balance in CF. To realize this concept, we studied molecular principles governing the effectiveness of different heparins, especially 2-O,3-O-desulfated heparin (ODSH), in the presence of sputum components and therapeutic agents. Using sputa from CF patients and an NE activity assay, we found that heparins are ineffective if used in the absence of dornase. This is true even when mucolytics, such as DTT or N-acetylcysteine, were used. Computational modeling suggested that ODSH and DNA compete for binding to an overlapping allosteric site on NE, which reduces the anti-NE potential of ODSH. NE inhibition of both DNA and ODSH is chain length-dependent, but ODSH chains exhibit higher potency per unit residue length. Likewise, ODSH chains exhibit higher NE inhibition potential compared with DNA chains in the presence of saline. These studies suggest fundamental differences in DNA and ODSH recognition and inhibition of NE despite engaging overlapping sites and offer unique insights into molecular principles that could be used in developing antiprotease agents in the presence of current treatments, such as dornase and hypertonic saline.

Insights into the RNA binding mechanism of human L1-ORF1p: a molecular dynamics study

The recognition and binding of nucleic acids by ORF1p, an L1 retrotransposon protein, have not yet been clearly understood due to the lack of structural knowledge. The present study attempts to identify the probable single-stranded RNA binding pathway of trimeric ORF1p using computational methods like ligand mapping methodology combined with molecular dynamics simulations. Using the ligand mapping methodology, the possible RNA interacting sites on the surface of the trimeric ORF1p were identified. The crystal structure of the ORF1p timer and an RNA molecule of 29 nucleotide bases in length were used to generate the structure of the ORF1p complex based on information on predicted binding sites as well as the functional states of the CTD. The various complexes of ORF1p-RNA were generated using polyU, polyA and L1RNA sequences and were simulated for a period of 75 ns. The observed stable interaction pattern was used to propose the possible binding pathway. Based on the binding free energy for complex formation, both polyU and L1RNA complexes were identified as stable complexes, while the complex formed with polyA was the least stable one. Furthermore, the importance of the residues in the CC domain (Lys137 and Arg141), the RRM loop (Arg206, Arg210 and Arg211) and the CTD (Arg 261 and Arg262) of all three chains in stabilizing the wrapped RNA has been highlighted in this study. The presence of several electrostatic interactions including H-bond interactions increases the affinity towards RNA and hence plays a vital role in retaining the wrapped position of RNA around ORF1p. Altogether, this study presents one of the possible RNA binding pathways of ORF1p and clearly highlights the functional state of ORF1p visited during RNA binding.

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

The C-Terminal Zinc Fingers of ZBTB38 are Novel Selective Readers of DNA Methylation

Methyl-CpG binding proteins play an essential role in translating DNA methylation marks into a downstream transcriptional response, which has implications for both normal cell function as well as disease. Although for many of these proteins, a detailed mechanistic understanding for how this cellular process is mediated remains to be determined. ZBTB38 is an under-characterized member of the zinc finger (ZF) family of methyl-CpG binding proteins. Functional knowledge has been gained for its conserved methylated DNA binding N-terminal ZF region; however, a specific role for the C-terminal set of five ZFs remains to be elucidated. Here we demonstrate for the first time that a subset of the C-terminal ZBTB38 ZFs exhibit high-affinity DNA interactions and that preferential targeting of the consensus DNA site is methyl specific. Utilizing a hybrid approach, a model for the C-terminal ZBTB38 ZFs in complex with its cognate DNA target is proposed, providing insight into a possible novel mode of methylated DNA recognition. Furthermore, it is shown that the C-terminal ZFs of ZBTB38 can directly occupy promoters harboring the newly identified sequence motif in cell in a methyl-dependent manner and, depending on the gene context, contribute to modulating transcriptional response. Combined, these findings provide evidence for a key and novel physiological function for the C-terminal ZF domain of ZBTB38.

Protein complex analysis: From raw protein lists to protein interaction networks

The elucidation of molecular interaction networks is one of the pivotal challenges in the study of biology. Affinity purification-mass spectrometry and other co-complex methods have become widely employed experimental techniques to identify protein complexes. These techniques typically suffer from a high number of false negatives and false positive contaminants due to technical shortcomings and purification biases. To support a diverse range of experimental designs and approaches, a large number of computational methods have been proposed to filter, infer and validate protein interaction networks from experimental pull-down MS data. Nevertheless, this expansion of available methods complicates the selection of the most optimal ones to support systems biology-driven knowledge extraction. In this review, we give an overview of the most commonly used computational methods to process and interpret co-complex results, and we discuss the issues and unsolved problems that still exist within the field. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:600-614, 2017.

Wing phosphorylation is a major functional determinant of the Lrs14-type biofilm and motility regulator AbfR1 in Sulfolobus acidocaldarius

In response to a variety of environmental cues, prokaryotes can switch between a motile and a sessile, biofilm-forming mode of growth. The regulatory mechanisms and signaling pathways underlying this switch are largely unknown in archaea but involve small winged helix-turn-helix DNA-binding proteins of the archaea-specific Lrs14 family. Here, we study the Lrs14 member AbfR1 of Sulfolobus acidocaldarius. Small-angle X-ray scattering data are presented, which are consistent with a model of dimeric AbfR1 in which dimerization occurs via an antiparallel coiled coil as suggested by homology modeling. Furthermore, solution structure data of AbfR1-DNA complexes suggest that upon binding DNA, AbfR1 induces deformations in the DNA. The wing residues tyrosine 84 and serine 87, which are phosphorylated in vivo, are crucial to establish stable protein-DNA contacts and their substitution with a negatively charged glutamate or aspartate residue inhibits formation of a nucleoprotein complex. Furthermore, mutation abrogates the cellular abundance and transcription regulatory function of AbfR1 and thus affects the resulting biofilm and motility phenotype of S. acidocaldarius. This work establishes a novel wHTH DNA-binding mode for Lrs14-like proteins and hints at an important role for protein phosphorylation as a signal transduction mechanism for the control of biofilm formation and motility in archaea.

Studies of protein-protein interactions in Fanconi anemia pathway to unravel the DNA interstrand crosslink repair mechanism

Fanconi anemia (FA), a cancer predisposition syndrome exhibits hallmark feature of radial chromosome formation, and hypersensitivity to DNA crosslinking agents. A set of FA pathway proteins mainly FANCI, FANCD2 and BRCA2 are expressed to repair the covalent crosslink between the dsDNA. However, FA, BRCA pathways play an important role in DNA ICL repair as well as in homologous recombination repair, but the presumptive role of FA-BRCA proteins has not clearly explored particularly in context to function associated protein-protein interactions (PPIs). Here, in-vivo, in-vitro and in-silico studies have been performed for functionally relevant domains of FANCI, FANCD2 and BRCA2. To our conclusion, FANCI ARM repeat interacts with FANCD2 CUE domain and BRCA2 C-terminal region. Interestingly, FANCD2 CUE domain also interacts strongly with BRCA2 C-terminal region. Interactions between BRCA2 CTR and functionally relevant mutations Ser222Ala (cell cycle checkpoint mutant) and Leu231Arg (DNA ICL repair mutant) present in FANCD2 CUE domain have been analysed. To our finding, these mutations abrogate the binding between FANCD2 CUE domain and BRCA2 CTR. Furthermore, (1) different domain of FANCI, FANCD2 and BRCA2 are playing important role in PPIs, (2) mutations cause the impairment in the PPIs which in turn may disrupt the DNA ICL repair mechanism.

Different Types of Molecular Docking Based on Variations of Interacting Molecules

Molecular docking plays an important role in drug discovery research by facilitating target identification, target validation, virtual screening for lead identification and lead optimization. Depending upon the nature of the disease of interest, targets can be either protein or DNA while drugs are mostly organic small molecules. Different types of molecular docking techniques like protein-protein or protein-DNA or protein-small molecule or DNA-small molecule are employed for achieving the above mentioned objectives. This chapter provides a clear idea of the position of molecular docking in drug discovery with detailed discussion on different types of molecular docking based on the varieties of interacting partners. Subsequently the authors provide a detailed list of tools that can be used for docking in drug discovery and discus some examples of molecular docking in drug discovery before concluding with a remark on future areas of improvement in molecular docking related to drug discovery.

Study of DNA binding and bending by Bacillus subtilis GabR, a PLP-dependent transcription factor

BACKGROUND

GabR is a transcriptional regulator belonging to the MocR/GabR family, characterized by a N-terminal wHTH DNA-binding domain and a C-terminal effector binding and/or oligomerization domain, structurally homologous to aminotransferases (ATs). In the presence of γ-aminobutyrate (GABA) and pyridoxal 5'-phosphate (PLP), GabR activates the transcription of gabT and gabD genes involved in GABA metabolism.

METHODS

Here we report a biochemical and atomic force microscopy characterization of Bacillus subtilis GabR in complex with DNA. Complexes were assembled in vitro to study their stoichiometry, stability and conformation.

RESULTS

The fractional occupancy of the GabR cognate site suggests that GabR binds as a dimer with Kd of 10nM. Upon binding GabR bends the DNA by 80° as measured by anomalous electrophoretic mobility. With GABA we observed a decrease in affinity and conformational rearrangements compatible with a less compact nucleo-protein complex but no changes of the DNA bending angle. By employing promoter and GabR mutants we found that basic residues of the positively charged groove on the surface of the AT domain affect DNA affinity.

CONCLUSIONS

The present data extend current understanding of the GabR-DNA interaction and the effect of GABA and PLP. A model for the GabR-DNA complex, corroborated by a docking simulation, is proposed.

GENERAL SIGNIFICANCE

Characterization of the GabR DNA binding mode highlights the key role of DNA bending and interactions with bases outside the canonical direct repeats, and might be of general relevance for the action mechanism of MocR transcription factors.

Streptococcus pneumoniae Genome-wide Identification and Characterization of BOX Element-binding Domains

The BOX elements are short repetitive DNA sequences that distribute randomly in intergenic regions of the Streptococcus pneumoniae genome. The function and origin of such elements are still unknown, but they were found to modulate expression of neighboring genes. Evidences suggested that the modulation's mechanism can be fulfilled by sequence-specific interaction of BOX elements with transcription factor family proteins. However, the type and function of these BOX-binding proteins still remain largely unexplored to date. In the current study we described a synthetic protocol to investigate the recognition and interaction between a highly conserved site of BOX elements and the DNA-binding domains of a variety of putative transcription factors in the pneumococcal genome. With the protocol we were able to predict those high-affinity domain binders of the conserved BOX DNA site (BOX DNA) in a high-throughput manner, and analyzed sequence-specific interaction in the domainDNA recognition at molecular level. Consequently, a number of putative transcription factor domains with both high affinity and specificity for the BOX DNA were identified, from which the helix-turn-helix (HTH) motif of a small heat shock factor was selected as a case study and tested for its binding capability toward the double-stranded BOX DNA using fluorescence anisotropy analysis. As might be expected, a relatively high affinity was detected for the interaction of HTH motif with BOX DNA with dissociation constant at nanomolar level. Molecular dynamics simulation, atomic structure examination and binding energy analysis revealed a complicated network of intensive nonbonded interactions across the complex interface, which confers both stability and specificity for the complex architecture.

Dynamic Local Polymorphisms in the Gbx1 Homeodomain Induced by DNA Binding

The Gastrulation Brain Homeobox 1 (Gbx1) gene encodes the Gbx1 homeodomain that targets TAATTA motifs in double-stranded DNA (dsDNA). Residues Glu17 and Arg52 in Gbx1 form a salt bridge, which is preserved in crystal structures and molecular dynamics simulations of homologous homeodomain-DNA complexes. In contrast, our nuclear magnetic resonance (NMR) studies show that DNA binding to Gbx1 induces dynamic local polymorphisms, which include breaking of the Glu17-Arg52 salt bridge. To study this interaction, we produced a variant with Glu17Arg and Arg52Glu mutations, which exhibited the same fold as the wild-type protein, but a 2-fold reduction in affinity for dsDNA. Analysis of the NMR structures of the Gbx1 homeodomain in the free form, the Gbx1[E17R,R52E] variant, and a Gbx1 homeodomain-DNA complex showed that stabilizing interactions of the Arg52 side chain with the DNA backbone are facilitated by transient breakage of the Glu17-Arg52 salt bridge in the DNA-bound Gbx1.

Conformational Heterogeneity of Unbound Proteins Enhances Recognition in Protein-Protein Encounters

To understand cellular processes at the molecular level we need to improve our knowledge of protein-protein interactions, from a structural, mechanistic, and energetic point of view. Current theoretical studies and computational docking simulations show that protein dynamics plays a key role in protein association and support the need for including protein flexibility in modeling protein interactions. Assuming the conformational selection binding mechanism, in which the unbound state can sample bound conformers, one possible strategy to include flexibility in docking predictions would be the use of conformational ensembles originated from unbound protein structures. Here we present an exhaustive computational study about the use of precomputed unbound ensembles in the context of protein docking, performed on a set of 124 cases of the Protein-Protein Docking Benchmark 3.0. Conformational ensembles were generated by conformational optimization and refinement with MODELLER and by short molecular dynamics trajectories with AMBER. We identified those conformers providing optimal binding and investigated the role of protein conformational heterogeneity in protein-protein recognition. Our results show that a restricted conformational refinement can generate conformers with better binding properties and improve docking encounters in medium-flexible cases. For more flexible cases, a more extended conformational sampling based on Normal Mode Analysis was proven helpful. We found that successful conformers provide better energetic complementarity to the docking partners, which is compatible with recent views of binding association. In addition to the mechanistic considerations, these findings could be exploited for practical docking predictions of improved efficiency.

Biophysical Aspect of Huntingtin Protein During polyQ: An In Silico Insight

Huntington's disease (HD) is a neurodegenerative disorder that is caused by an abnormal elongation of the polyglutamine (polyQ) chain in the Huntington (Htt) protein. At present, the normal function of Htt of neurons as well as the mechanism by which selective neurodegeneration is caused by the expanded polyQ chain in Htt remains ambiguous. A gain of function as a result of the elongated polyQ chain can lead to abnormal interaction of the Htt protein with its interacting partners, thereby resulting in the neuropathological changes seen in the Huntington's disease. Recent research indicates protein kinase C and casein kinase substrate in neurons protein 1 (PACSIN1) as one of the interacting partners of Htt protein. It has proven experimentally that the mutant Htt and PACSIN1 formed aggregates in the cytoplasm. This aggregation is believed to be a cause for Huntington's disease. In our study, we performed in silico investigations to predict the biomolecular mechanism of Htt/PACSIN1 interaction that could be one of the major triggers of the disease. Biomolecular interaction and molecular dynamics simulation analysis were performed to understand the dynamic behavior of native and mutant structures at the atomic level. Mutant Htt showed more interaction with its biological partner than the native Htt due to its expansion of interaction surface and flexible nature of binding residues. Our investigation of native and mutant Htt clearly shows that the structural and functional consequences of the polyQ elongation cause HD. Because of the central role of the Htt-PACSIN1 complex in maintaining connections between neurons, these differences likely contribute to the mechanism responsible for HD progression.

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.

The Binding of Syndapin SH3 Domain to Dynamin Proline-rich Domain Involves Short and Long Distance Elements

Dynamin is a GTPase that mediates vesicle fission during synaptic vesicle endocytosis. Its long C-terminal proline-rich domain contains 13 PXXP motifs, which orchestrate its interactions with multiple proteins. The SH3 domains of syndapin and endophilin bind the PXXP motifs called Site 2 and 3 (Pro-786-Pro-793) at the N-terminal end of the proline-rich domain, whereas the amphiphysin SH3 binds Site 9 (Pro-833-Pro-836) toward the C-terminal end. In some proteins, SH3/peptide interactions also involve short distance elements, which are 5-15 amino acid extensions flanking the central PXXP motif for high affinity binding. Here we found two previously unrecognized elements in the central and the C-terminal end of the dynamin proline-rich domain that account for a significant increase in syndapin binding affinity compared with a previously reported Site 2 and Site 3 PXXP peptide alone. The first new element (Gly-807-Gly-811) is short distance element on the C-terminal side of Site 2 PXXP, which might contact a groove identified under the RT loop of the SH3 domain. The second element (Arg-838-Pro-844) is located about 50 amino acids downstream of Site 2. These two elements provide additional specificity to the syndapin SH3 domain outside of the well described polyproline-binding groove. Thus, the dynamin/syndapin interaction is mediated via a network of multiple contacts outside the core PXXP motif over a previously unrecognized extended region of the proline-rich domain. To our knowledge this is the first example among known SH3 interactions to involve spatially separated and extended long-range elements that combine to provide a higher affinity interaction.

Different Types of Molecular Docking Based on Variations of Interacting Molecules

Molecular docking plays an important role in drug discovery research by facilitating target identification, target validation, virtual screening for lead identification and lead optimization. Depending upon the nature of the disease of interest, targets can be either protein or DNA while drugs are mostly organic small molecules. Different types of molecular docking techniques like protein-protein or protein-DNA or protein-small molecule or DNA-small molecule are employed for achieving the above mentioned objectives. This chapter provides a clear idea of the position of molecular docking in drug discovery with detailed discussion on different types of molecular docking based on the varieties of interacting partners. Subsequently the authors provide a detailed list of tools that can be used for docking in drug discovery and discus some examples of molecular docking in drug discovery before concluding with a remark on future areas of improvement in molecular docking related to drug discovery.

Integrating multi-scale data on homologous recombination into a new recognition mechanism based on simulations of the RecA-ssDNA/dsDNA structure

RecA protein is the prototypical recombinase. Members of the recombinase family can accurately repair double strand breaks in DNA. They also provide crucial links between pairs of sister chromatids in eukaryotic meiosis. A very broad outline of how these proteins align homologous sequences and promote DNA strand exchange has long been known, as are the crystal structures of the RecA-DNA pre- and postsynaptic complexes; however, little is known about the homology searching conformations and the details of how DNA in bacterial genomes is rapidly searched until homologous alignment is achieved. By integrating a physical model of recognition to new modeling work based on docking exploration and molecular dynamics simulation, we present a detailed structure/function model of homology recognition that reconciles extremely quick searching with the efficient and stringent formation of stable strand exchange products and which is consistent with a vast body of previously unexplained experimental results.

Molecular view of ligands specificity for CAG repeats in anti-Huntington therapy

Huntington's disease is a fatal and devastating neurodegenerative genetic disorder for which there is currently no cure. It is characterized by Huntingtin protein's mRNA transcripts with 36 or more CAG repeats. Inhibiting the formation of pathological complexes between these expanded transcripts and target proteins may be a valuable strategy against the disease. Yet, the rational design of molecules specifically targeting the expanded CAG repeats is limited by the lack of structural information. Here, we use well-tempered metadynamics-based free energy calculations to investigate pose and affinity of two ligands targeting CAG repeats for which affinities have been previously measured. The first consists of two 4-guanidinophenyl rings linked by an ester group. It is the most potent ligand identified so far, with Kd = 60(30) nM. The second consists of a 4-phenyl dihydroimidazole and 4-1H-indole dihydroimidazole connected by a C-C bond (Kd = 700(80) nM). Our calculations reproduce the experimental affinities and uncover the recognition pattern between ligands' and their RNA target. They also provide a molecular basis for the markedly different affinity of the two ligands for CAG repeats as observed experimentally. These findings may pave the way for a structure-based hit-to-lead optimization to further improve ligand selectivity toward CAG repeat-containing mRNAs.

Modeling of Plasmodium falciparum Telomerase Reverse Transcriptase Ternary Complex: Repurposing of Nucleoside Analog Inhibitors

The Plasmodium falciparum telomerase reverse transcriptase (PfTERT) is a ribonucleoprotein that assists the maintenance of the telomeric ends of chromosomes by reverse transcription of its own RNA subunit. It represents an attractive therapeutic target for eradication of the plasmodial parasite at the asexual liver stage. Automated modeling using MUSTER and knowledge-based techniques were used to obtain a three-dimensional model of the active site of reverse transcriptase domain of PfTERT, which is responsible for catalyzing the addition of incoming dNTPs to the growing DNA strand in presence of divalent magnesium ions. Further, the ternary complex of the active site of PfTERT bound to a DNA-RNA duplex was also modeled using Haddock server and represents the functional form of the enzyme. Initially, established nucleoside analog inhibitors of PfTERT, AZTTP, and ddGTP were docked in the modeled binding site of the PfTERT ternary complex using AutoDock v4.2. Subsequently, docking studies were carried out with 14 approved nucleoside analog inhibitors. Docking studies predicted that floxuridine, gemcitabine, stavudine, and vidarabine have high affinity for the PfTERT ternary complex. Further analysis on the basis of known side effects led us to propose repositioning of vidarabine as a suitable drug candidate for inhibition of PfTERT.