Abstract

In recent times, our healthcare system is being challenged by many drug-resistant microorganisms and ageing-associated diseases for which we do not have any drugs or drugs with poor therapeutic profile. With pharmaceutical technological advancements, increasing computational power and growth of related biomedical fields, there have been dramatic increase in the number of drugs approved in general, but still way behind in drug discovery for certain class of diseases. Now, we have access to bigger genomics database, better biophysical methods, and knowledge about chemical space with which we should be able to easily explore and predict synthetically feasible compounds for the lead optimization process. In this chapter, we discuss the limitations and highlights of currently available computational methods used for protein–ligand binding affinities estimation and this includes force-field, ab initio electronic structure theory and machine learning approaches. Since the electronic structure-based approach cannot be applied to systems of larger length scale, the free energy methods based on this employ certain approximations, and these have been discussed in detail in this chapter. Recently, the methods based on electronic structure theory and machine learning approaches also are successfully being used to compute protein–ligand binding affinities and other pharmacokinetic and pharmacodynamic properties and so have greater potential to take forward computer-aided drug discovery to newer heights

Abstract

Hydroxymethylbilane synthase (HMBS), the third enzyme in the heme biosynthesis pathway, catalyzes the formation of 1-hydroxymethylbilane (HMB) by a stepwise polymerization of four molecules of porphobilinogen (PBG) using the dipyrromethane (DPM) cofactor. The mechanism by which HMBS polymerizes four units of PBG has not been elucidated to date. In vitro and in silico studies on HMBS have suggested certain residues with catalytic importance, but their specific role in the catalysis is unclear. To understand the catalytic mechanism of HMBS, quantum mechanical (QM) calculations were performed on model systems obtained from the active site of the human HMBS enzyme. The addition of one molecule of PBG to the DPM cofactor is carried out in four steps: (1) protonation of the substrate, PBG; (2) deamination of PBG; (3) electrophilic addition of the deaminated substrate to the terminal pyrrole ring of the enzyme-bound DPM cofactor and (4) deprotonation of the carbon atom at the a-position of the second ring of DPM. Based on the energy profiles from the QM calculations on cluster models, R26 is proposed to be the best suitable proton donor to the PBG moiety, which aids in the deamination of the substrate. During the electrophilic addition step, the intermediate formed is stabilized by the carboxylate side chain of the D99 residue. In the final deprotonation step, an extra proton from the second ring of DPM is transferred to R26 via the carboxylate side chain of D99, thus completing one cycle of the catalytic mechanism. The residues in the cluster model seem to play an important role in obtaining accurate energy barriers. All the stationary points along the reaction pathway have been characterized using QM calculations. The rate limiting step for the complete mechanism is found to be the deamination of the PBG moiety. The results of this study provide a detailed understanding of the catalytic mechanism and would help design future studies aimed at modulating the activity of HMBS

Abstract

Motivated by the persistent anomalies in the semileptonic B-meson decays, we investigate the competency of LHC data to constrain the RDðÞ -favored parameter space in a charge −1=3 scalar leptoquark (S1) model. We consider some scenarios with one large free coupling to accommodate the RDðÞ anomalies. As a result, some of them dominantly yield nonresonant ττ and τν events at the LHC through the t-channel S1 exchange. So far, no experiment has searched for leptoquarks using these signatures and the relevant resonant leptoquark searches are yet to put any strong exclusion limit on the parameter space. We recast the latest ττ and τν resonance search data to obtain new exclusion limits. The nonresonant processes strongly interfere (destructively in our case) with the Standard Model background and play the determining role in setting the exclusion limits. To obtain precise limits, we include non-negligible effects coming from the subdominant (resonant) pair and inclusive single leptoquark productions systematically in our analysis. To deal with large destructive interference, we make use of the transverse mass distributions from the experiments in our statistical analysis. In addition, we also recast the relevant direct search results to obtain the most stringent collider bounds on these scenarios to date. These are independent bounds and are competitive to other known bounds. Finally, we indicate how one can adopt these bounds to a wide class of models with S1 that are proposed to accommodate the RDðÞ anomalies.

Abstract

The LHC search strategies for leptoquarks that couple dominantly to a top quark are different than for the ones that couple mostly to the light quarks. We consider charge 1=3 (ϕ1) and 5=3 (ϕ5) scalar leptoquarks that can decay to a top quark and a charged lepton (tl) giving rise to a resonance system of a boosted top and a high-pT lepton. We introduce simple phenomenological models suitable for bottom-up studies and explicitly map them to all possible scalar leptoquark models within the Buchmüller-Rückl-Wyler classifications that can have the desired decays. We study pair and single productions of these leptoquarks. Contrary to the common perception, we find that the single production of top-philic leptoquarks ϕ ¼ fϕ1; ϕ5g in association with a lepton and jets could be significant for order one ϕtl coupling in certain scenarios. We propose a strategy of selecting events with at least one hadronic-top and two high-pT same flavor opposite sign leptons. This captures events from both pair and single productions. Our strategy can significantly enhance the LHC discovery potential especially in the high-mass region where single productions become more prominent. Our estimation shows that a scalar leptoquark as heavy as ∼1.7 TeV can be discovered at the 14 TeV LHC with 3 ab−1 of integrated luminosity in the tll þ X channel for 100% branching ratio in the ϕ → tl decay mode. However, in some scenarios, the discovery reach can increase beyond 2 TeV even though the branching ratio comes down to about 50%

Abstract

Metal ions are crucial for folding and function of noncoding RNAs. The fact that RNAs have very specific metal ion binding motifs further implies that contribution of metal ions (like Mg2+) in RNA’s folding is not limited to simple compensation of electrostatic repulsions. Rather, their binding to RNA is driven by very specific contextual requirements. Elucidation of such factors is necessary for a comprehensive understanding of the sequence–structure–function paradigm in RNA. In this work, we have studied the consequences of Mg2+ binding on the geometry and stability of different noncanonical base pairs that shape up the complex structural landscape of RNA. Our results show that majority of the Mg2+ bound nucleobases are also part of a base pair. Interestingly, such base pairs belong only to a specific set of base pairing geometries. Out of them, we are able to identify 14 unique cases for which the native base pairing geometries are unstable under gas phase geometry optimization carried out in the absence of Mg2+ binding. Our density functional theory based calculations, performed using dispersion corrected M05-2X functional, suggest that, depending on its mode of binding, Mg2+ can stabilize and even fine tune a number of such base pairing geometries. These findings not only provide insights into how metal ions modulate the structure and dynamics of RNA molecules, they also provide a basis for improving the RNA structure prediction algorithms.

Abstract

Characterization of native, intermediate, and denatured states is crucial for understanding the factors influencing the stability of proteins. We have carried out molecular dynamics simulations to study the unfolding of three peripheral subunit binding domains (PSBDs): E. coli BBL, Bacillus stearothermophilus E3BD, and human hbSBD, at three different temperatures: 300, 330, and 400 K, and in the presence of two solvents: water and 5 M guanidinium hydrochloride (GndCl) solution. These proteins share similar folds, with two parallel helices, maintained via a hydrophobic core comprising residues from their interconnecting loop. BBL is more sensitive to thermal and chemical denaturation in comparison to hbSBD, and E3BD is the most stable of all of the three proteins. The effect of temperature on the stability of these proteins is more pronounced in “water-only” simulations compared to that in the presence of guanidium hydrochloride in high concentrations. Our results show cooperative unfolding transitions of these proteins, which are triggered by an initial melting of the C-terminal helix H2. The consequent loss of interhelical interactions or native contacts, as observed, leads to the subsequent melting of the N-terminal helix H1.

Abstract

Charged nucleobases have been found to occur in several known RNA molecules and are considered essential for their structure and function. The mechanism of their involvement is however not yet fully understood. Revelation of the role of N7-protonated guanine, in modulating the geometry and stability of noncanonical base pairs formed through its unprotonated edges [Watson−Crick (WC) and sugar], has triggered the need to evaluate the feasibility of similar roles of other protonated nucleobases [Halder et al., Phys Chem Chem Phys, 2015, 17, 26249]. In this context, N3 protonation of guanine makes an interesting case as its influence on the charge distribution of the WC edge is similar to that of N7 protonation, though its thermodynamic cost of protonation is significantly higher. In this work, we have carried out structural bioinformatics analyses and quantum mechanics-based calculations to show that N3 protonation of guanine may take place in a cellular environment, at least in the G:C W:W Trans and G:G W:H Cis base pairs. Our results provide a reasonable starting point for future investigations in order to address the larger mechanistic question.

Abstract

Noncoding RNA molecules are composed of a large variety of noncanonical base pairs that shape up their functionally competent folded structures. Each base pair is composed of at least two interbase hydrogen bonds (H-bonds). It is expected that the characteristic geometry and stability of different noncanonical base pairs are determined collectively by the properties of these interbase H-bonds. We have studied the ground-state electronic properties [using density functional theory (DFT) and DFT-D3-based methods] of all the 118 normal base pairs and 36 modified base pairs, belonging to 12 different geometric families (cis and trans of WW, WH, HH, WS, HS, and SS) that occur in a nonredundant set of high-resolution RNA crystal structures. Having addressed some of the limitations of the earlier approaches, we provide here a comprehensive compilation of the average energies of different types of interbase H-bonds (EHB). We have also characterized each interbase H-bond using 13 different parameters that describe its geometry, charge distribution at its bond critical point (BCP), and n → σ*-type charge transfer from filled π orbitals of the H-bond acceptor to the empty antibonding orbital of the H-bond donor. On the basis of the extent of their linear correlation with the H-bonding energy, we have shortlisted five parameters to model linear equations for predicting EHB values. They are (i) electron density at the BCP: ρ, (ii) its Laplacian: ∇2 ρ, (iii) stabilization energy due to n → σ*-type charge transfer: E(2), (iv) donor−hydrogen distance, and (v) hydrogen−acceptor distance. We have performed single variable and multivariable linear regression analysis over the normal base pairs and have modeled sets of linear relationships between these five parameters and EHB. Performance testing of our model over the set of modified base pairs shows promising results, at least for the moderately strong H-bonds.

Abstract

Identification and characterization of base-multiplets, which are essentially mediated by base-pairing interactions, can provide insights into the diversity in the structure and dynamics of complex functional RNAs, and thus facilitate hypothesis driven biological research. The necessary nomenclature scheme, an extension of the geometric classification scheme for base-pairs by Leontis and Westhof, is however available only for base-triplets. In the absence of information on topology, this scheme is not applicable to quartets and higher order multiplets. Here we propose a topology-based classification scheme which, in conjunction with a graph-based algorithm, can be used for the automated identification and characterization of higher order base-multiplets in RNA structures. Here, the RNA structure is represented as a graph, where nodes represent nucleotides and edges represent base-pairing connectivity. Sets of connected components (of n nodes) within these graphs constitute subgraphs representing multiplets of “n” nucleotides. The different topological variants of the RNA multiplets thus correspond to different nonisomorphic forms of these subgraphs. To annotate RNA base-multiplets unambiguously, we propose a set of topology-based nomenclature rules for quartets, which are extendable to higher multiplets. We also demonstrate the utility of our approach toward the identification and annotation of higher order RNA multiplets, by investigating the occurrence contexts of selected examples in order to gain insights regarding their probable functional roles.

Abstract

Understanding the structure-function relationships of RNA has become increasingly important given the realization of its functional role in various cellular processes. Chemical denaturation of RNA by urea has been shown to be beneficial in investigating RNA stability and folding. Elucidation of the mechanism of unfolding of RNA by urea is important for understanding the folding pathways. In addition to studying denaturation of RNA in aqueous urea, it is important to understand the nature and strength of interactions of the building blocks of RNA. In this study, a systematic examination of the structural features and energetic factors involving interactions between nucleobases and urea is presented. Results from molecular dynamics (MD) simulations on each of the five DNA/RNA bases in water and eight different concentrations of aqueous urea, and free energy calculations using the thermodynamic integration method are presented. The interaction energies between all the nucleobases with the solvent environment and the transfer free energies become more favorable with respect to increase in the concentration of urea. Preferential interactions of urea versus water molecules with all model systems determined using Kirkwood-Buff integrals and two-domain models indicate preference of urea by nucleobases in comparison to water. The modes of interaction between urea and the nucleobases were analyzed in detail. In addition to the previously identified hydrogen bonding and stacking interactions between urea and nucleobases that stabilize the unfolded states of RNA in aqueous solution, NH-π interactions are proposed to be important. Dynamic properties of each of these three modes of interactions have been presented. The study provides fundamental insights into the nature of interaction of urea molecules with nucleobases and how it disrupts nucleic acids.