Inorganic and Physical Chemistry (IPC)
https://etd.iisc.ac.in/handle/2005/11
Fri, 18 Jun 2021 03:10:22 GMT2021-06-18T03:10:22ZInorganic and Physical Chemistry (IPC)https://etd.iisc.ac.in:443/bitstream/id/400f184d-0434-4c33-b08f-af554e17f516/
https://etd.iisc.ac.in/handle/2005/11
Ab Initio Molecular Dynamics Studies of Bronsted Acid-Base Chemistry in Aqueous Solutions
https://etd.iisc.ac.in/handle/2005/3943
Ab Initio Molecular Dynamics Studies of Bronsted Acid-Base Chemistry in Aqueous Solutions
Tummanapelli, Anil Kumar
Knowledge of the dissociation constants of the ionizable protons of weak acids in aqueous media is of fundamental importance in many areas of chemistry and biochemistry. The pKa value, or equilibrium dissociation constant, of a molecule determines the relative concentration of its protonated and deprotonated forms at a speciﬁed pH and is therefore an important descriptor of its chemical reactivity. Considerable eﬀorts have been devoted to the determination of pKa values by deferent experimental techniques. Although in most cases the determination of pKa values from experimental is straightforward, there are situations where interpretation is diﬃcult and the results ambiguous. It is, therefore, not surprising that the capability to provide accurate estimates of the pKa value has been a central goal in theoretical chemistry and there has been a large eﬀort in developing methodologies for predicting pKa values for a variety of chemical systems by diﬀering quantum chemical techniques. A prediction accuracy within 0.5 pKa units of experiment is the desirable level of accuracy. This is a non-trivial exercise, for an error of 1 kcal/mol in estimates of the free energy value would result in an error of 0.74 pKa units.
In this thesis ab initio Car-Parrinello molecular dynamics (CPMD) has been used for investigating the Brϕnsted acid-base chemistry of weak acids in aqueous solution. A key issue in any dissociation event is how the solvating water molecules arrange themselves spatially and dynamically around the neutral and dissociated acid molecule. Ab initio methods have the advantage that all solvent water molecules can, in principle, be con- sidered explicitly. One of the factors that has inhibited the widespread use of ab initio MD methods to study the dissociation reaction is that dissociation of weak acids are rare events that require extremely long simulation times before one is observed. The metady- namics formalism provides a solution to this conundrum by preventing the system from revisiting regions of conﬁguration space where it has been in the past. The formalism allows the system to escape the free-energy minima by biasing the dynamics with a history dependent potential (or force) that acts on select degrees of freedom, referred to as collective variables. The bias potentials, modeled by repulsive inverted Gaussians that are dropped during propagation, drive the system out of any free-energy minima and allow it to explore the conﬁguration space by a relatively quick and eﬃcient sampling. The the- sis deals with a detailed investigation of the Brϕnsted acid-base chemistry of weak acids in aqueous solutions by the CPMD-metadynamics procedure.
In Chapter 1, current approaches for the theoretical estimation of pKa values are summarized while in Chapter 2 the simulation methodology and the metadynamics sampling techniques used in thisstudy are described.
The potential of the CPMD-metadynamics procedure to provide estimates of the acid dissociation constant (pKa) is explored in Chapter 3, using acetic acid as a test sys- tem. Using the bond-distance dependent coordination number of protons bound to the dissociating carboxylic groups as the collective variable, the free-energy proﬁle for the dissociation reaction of acetic acid in water was computed. Convergence of the free-energy proﬁles and barriers for the simulations parameters is demonstrated. The free-energy proﬁles exhibit two distinct minima corresponding to the dissociated and neutral states of the acid and the deference in their values provides the estimate for pKa. The estimated value of pKa for acetic acid from the simulations, 4.80, is in good agreement with the experiment at value of 4.76. It is shown that the good agreement with experiment is a consequence of the cancellation of errors, as the pKa values are computed as the diﬀerence in the free energy values at the minima corresponding to the neutral and dissociated state. The chapter further explores the critical factors required for obtaining accurate estimates of the pKa values by the CPMD-metadynamics procedure. It is shown that having water molecules suﬃcient to complete three hydration shells as well as maintaining water density in the simulation cell as close to unity is important.
In Chapter 4, the CPMD-metadynamics procedure described in Chapter-3 has been used to investigate the dissociation of a series of weak organic acids in aqueous solutions. The acids studied were chosen to highlight some of the major factors that inﬂuence the dissociation constant. These include the inﬂuence of the inductive eﬀect, the stabilization of the dissociated anion by H-bonding as well as the presence of multiple ionizable groups. The acids investigated were aliphatic carboxylic acids, chlorine-substituted carboxylic acids, cid and trans-butenedioic, the isomers of hydroxybenzoic acid and phthalic acids and its isomers. It was found that in each of these examples the CPMD-metadynamics procedure correctly estimates the pKa values, indicating that the formulism is capable of capturing these inﬂuences and equally importantly indicating that the cancellation of errors is indeed universal. Further, it is shown that the procedure can provide accurate estimates of the successive pKa values of polypro tic acids as well as the subtle deference in their values for deterrent isomers of the acid molecule.
Changes in protonation-deprotonation of amino acid residues in proteins play a key role in many biological processes and pathways. It is shown that CPMD simulations in conjunction with metadynamics calculations of the free energy proﬁle of the protonation- deprotonation reaction can provide estimates of the multiple pKa values of the 20 canonical α-amino acids in aqueous solutions in good agreement with experiment (Chapter 5). The distance-dependent coordination number of the protons bound to the hydroxyl oxygen of the carboxylic and the amine groups is used as the collective variable to explore the free energy proﬁles of the Brϕnsted acid-base chemistry of amino acids in aqueous solutions. Water molecules, suﬃcient to complete three hydration shells surrounding the acid molecule were included explicitly in the computation procedure. The method works equally well for amino acids with neutral, acidic and basic side chains and provides estimates of the multiple pKa values with a mean relative error with respect to experimental results, of 0.2 pKa units.
The tripeptide Glutathione (GSH) is one of the most abundant peptides and the major repository for non-protein sulfur in both animal and plant cells. It plays a critical role in intracellular oxidative stress management by the reversible formation of glutathione disulﬁde with the thioldisulﬁde pair acting as a redox buﬀer. The state of charge of the ionizable groups of GSH can inﬂuences the redox couple and hence the pKa value of the cysteine residue of GSH is critical to its functioning. In Chapter 6, it has been reported that ab initio Car-Parrinello Molecular Dynamics simulations of glutathione solvated by 200 water molecules, all of which are considered in the simulation. It is shown that the free-energy landscape for the protonation - deprotonation reaction of the cysteine residue of GSH computed using metadynamics sampling provides accurate estimates of the pKa and correctly predicts the shift in the dissociation constant values as compared to the isolated cysteine amino acid.
The dissociation constants of weak acids are commonly determined from pH-titration
curves. For simple acids the determination of the pKa from the titration curves using the Henderson-Hasselbalch equation is relatively straightforward. There are situations, however, especially in polypro tic acids with closely spaced dissociation constants, where titration curves do not exhibit clear inﬂexion and equivalence stages and consequently the estimation of multiple pKa values from a single titration curve is no longer straightfor-
ward resulting in uncertainties in the determined pKa values. In Chapter 7, the multiple
dissociation constant of the hexapeptide glutathione disulﬁde (GSSG) with six ionizable groups and six associated dissociation constants has been investigated. The six pKa values of GSSG were estimated using the CPMD-metadynamics procedure from the free-energy proﬁles for each dissociation reaction computed using the appropriate collective variable. The six pKa values of GSSG were estimated and the theoretical pH-titration curve was then compared with the experimentally measured pH-titration curve and found to be in excellent agreement. The object of the exercise was to establish whether interpretation of pH-titration curves of complex molecules with multiple ionizable groups could be facilitated using results of ab initio molecular dynamics simulations.
Sat, 11 Aug 2018 00:00:00 GMThttps://etd.iisc.ac.in/handle/2005/39432018-08-11T00:00:00ZActivation of H-X (X = H, Si, B, C) Sigma Bonds in Small Molecules by Transition Metal Pincer Complexes
https://etd.iisc.ac.in/handle/2005/3795
Activation of H-X (X = H, Si, B, C) Sigma Bonds in Small Molecules by Transition Metal Pincer Complexes
Ramaraj, A
Thu, 05 Jul 2018 00:00:00 GMThttps://etd.iisc.ac.in/handle/2005/37952018-07-05T00:00:00ZAncillary Ligand Effects On The Anticancer Activity Of Ruthenium(II) Piano Stool Complexes
https://etd.iisc.ac.in/handle/2005/998
Ancillary Ligand Effects On The Anticancer Activity Of Ruthenium(II) Piano Stool Complexes
Das, Sangeeta
The thesis “Ancillary Ligand Effects on the Anticancer Activity of Ruthenium (II) Piano Stool Complexes” is an effort to design better antitumor metallodrugs based on ruthenium(II) complexes with various H-bond donor/acceptor ligands and to understand their mechanism of action.
Chapter 1 presents a brief review of metallodrugs and their mechanism of action. Different classes of metallodrugs are discussed. A short discussion on ruthenium based anticancer drugs and their established mechanism of action is also included in this chapter.
Chapter 2 deals with the synthesis, characterization and anticancer activity of Ru(II) complexes with P(III) and P(V) ligands. The effect of a strong hydrogen bond acceptor on the cytotoxicity of the complexes has been investigated which allows comparison of complexes with ligands possessing a strong hydrogen bond donor or hydrogen bond acceptor. Partial oxidation of the tertiary phosphine ligands leads to a decrease in cytotoxicity of the ligand, while coordination to ruthenium resulted in a significant increase in the cytotoxicity. A molecular mechanism of action for these complexes was suggested on the basis of various biophysical studies. These complexes bind DNA through non-intercalative interactions which lead to the destabilization of the double helix of the DNA and also unwinding of the negatively supercoiled DNA. Results show that the presence of a hydrogen bond acceptor on the ligand is not capable of enhancing interactions with DNA in comparison with hydrogen bond donor groups. Cellular studies of these complexes showed that inhibition of DNA synthesis and apoptosis occur on treatment with these complexes. Interestingly, these complexes are found to be not only cytotoxic but also antimetastatic.
Chapter 3 deals with the synthesis, characterization and anticancer activity of Ru(II) complexes with biologically active S containing heterocyclic ligands and their mechanistic study. Complexation of ruthenium with mercaptobenzothiazole (MBT) gave the most cytotoxic complex (H3) in the series. Heterocyclic Ru(II) complexes behave differently as evidenced by cellular and biophysical studies. Unlike phosphine complexes, H3 shows biphasic melting of DNA at higher concentrations which suggests two different types of interaction with DNA.
Chapter 4 deals with synthesis and characterization of water soluble multiruthenated hydrophilic ruthenium(II) complexes with urotropine. An increase in cytotoxicity and binding affinity has been observed with increase in the number of ruthenium atoms per molecule. The complex with three ruthenium atoms showed the best activity. However cytotoxicity of the complexes decreases with decrease in the lipophilicity of the complexes.
Chapter 5 describes studies on the interaction of Ru complexes with water, ss-DNA, AMP, GMP and GSH by various spectroscopic techniques. Hydrolysis of Ru-Cl bond in the complexes correlates with the cytotoxicity.
Chapter 6 reports the summary of the observations of the thesis and the future prospects of metallodrugs.
Mon, 17 Jan 2011 00:00:00 GMThttps://etd.iisc.ac.in/handle/2005/9982011-01-17T00:00:00ZAnomalous Diffusion in a Rearranging Medium Diffusing Diffusivity Models
https://etd.iisc.ac.in/handle/2005/4151
Anomalous Diffusion in a Rearranging Medium Diffusing Diffusivity Models
Jain, Rohit
Diffusion processes, because of their applications to a wide range of phenomena, have been a subject of great scientific interest ever since Einstein formulated the celebrated theory of Brownian motion. Brownian motion is the most commonly known class of diffusion and is the dominant form of molecular transport in physical systems which are usually driven by thermal noise e.g. dissolution of sugar in water. It is also the simplest case of a random process where it is assumed that the time scale of motion of diffusing particle is much larger than that of the solvent molecules. This causes an extreme separation of time scales- one associated with the slower diffusing particle, and the other associated with the faster solvent molecules. This in turn leads to two fundamental laws of Brownian motion : (1) the mean square displacement (MSD) of particle is proportional to the time lapsed, i.e. hx2i / T . It is usually referred to as Fickian motion and (2) the probability distribution function (pdf) of displacements is Gaussian with the width of distribution
p-scaling as T (this is equivalent to say that the motion is Fickian). However, there are many other diffusion processes which can not be classified as Brownian motion and hence are termed as anomalous diffusion. A diffusion process can be termed as anomalous if any one or both the laws of Brownian motion are violated.
There are a lot of phenomena in which is diffusion is anomalous, i.e. where the pdf is not Gaussian but a stable distribution with a functional form f(jxj=T =2) such that the width of distribution increases like T =2 with 6= 1. The Brownian motion, on the other hand, would lead to a Gaussian distribution with = 1. In the past, it has been usually assumed that if 6= 1, i.e. if the diffusion is non-Fickian, then the distribution would also be non-Gaussian. Conversely, if = 1, then the distribution would be Gaussian. This was so well accepted that it was almost never tested until recently. In a series of experiments from Granick's group [1, 2] where the environment undergoes structural rearrangement on a time scale less than that of observation of diffusion, non-Gaussian distributions have been realized. Even more interesting, coexisting with this non-Gaussian distribution was observed a MSD which was found to be vary linearly in time at all times irrespective of the actual form of the distribution. In these experiments, the pdf was found to be exponential at short times which then crossed over to being Gaussian at large enough time scales.
Chubynsky and Slater [3] have analyzed the \di using diffusivity" model, in which dif-fusion coefficient changes as a stochastic function of time, because of the rearrangement of environment. Assuming an exponential distribution of diffusivity at small time scales, these authors showed analytically that (1) the diffusion is Fickian and (2) the distribution of displacements, after averaging the Gaussian pdf over the exponential distribution of diffusivity, becomes non-Gaussian (exponential). The width of this non-Gaussian distribution increases as T . At larger time scales, they performed simulations and the result was a cross over to Gaussian distribution. Following their work, we have proposed a class of \diffusing diffusivity" models which we have been able to solve analytically at all time scales, using the methods of path integrals [4]. In the thesis, we are interested in developing models of diffusing diffusivity that could be used to describe different kinds of anomalous diffusion processes. We show that our model of diffusing diffusivity is equivalent to another important class of physical processes, i.e. that of the Brownian motion with absorption, or the reaction- diffusion process. In reaction-diffusion models, the concentration of a chemical substance changes in space and time because of its reaction with another substance while the diffusion causes the spread in the concentrations of various substances. The connection of diffusing diffusivity model to the reaction-diffusion model is particularly useful as one can now have different models of diffusivity describing its diffusion while, interestingly the reaction term remains unchanged.
In our first model, diffusivity is modeled as a simple Brownian process. More precisely, we take D(t) = 2(t) where is the position vector of an n-dimensional harmonic oscillator executing Brownian motion. For the case n = 2, the equilibrium distribution of diffusivity is an exponential, thereby making this particular case an ideal choice to compare our results with the numerical results of Chubynsky and Slater [3]. We have shown that our results are in very good agreement with theirs [5]. Further, our model is quite generic and it is possible to nd exact analytical solution with arbitrary value of n. The non-Gaussianity parameter, which is a measure of deviation from normality, has been evaluated exactly as a function of time and n. At short times, the value of parameter is non-zero, signifying non-Gaussian dynamics which eventually becomes zero in the large time limit, marking an onset of Gaussian dynamics. For larger values of n, the non-Gaussianity starts disappearing faster implying an earlier onset of Gaussian behavior.
The model has been applied to the problem of calculating survival probability of a free particle in crowded, rearranging and bounded regions. We have obtained exact results for this problem where we have shown that for larger compartments and faster relaxation of the surroundings, diffusion inside a crowded, rearranging medium is similar to the diffusion in a homogeneous medium with a constant diffusivity. We have also studied the model for rotational diffusion process. We have obtained simple analytical expressions for the probability distribution and the mean square angular displacement in arbitrary dimensions. As in the case of translation diffusion, a non-Gaussianity parameter quanties the extent of deviation from Gaussian dynamics, we have defined in a similar fashion a non-normal parameter for rotational diffusion. This could be useful in analyzing the experimental data to find the extent of deviation from normal diffusion. In another study, we have used the model of diffusing diffusivity for the diffusion of a harmonic oscillator in crowded, rearranging environment. We have obtained two interesting results here namely (1) the expression for the MSD in case of diffusing diffusivity is of same kind as that for the case of constant diffusivity and (2) the probability distribution function remains non-Gaussian even in the limit of very large time unlike the previous cases where it eventually crosses over to become Gaussian.
In our model of diffusivity, and also in the model of Chubynsky and Slater [3], the distribution of diffusivity decays to zero exponentially fast, implying that the probability of having a large value of D is rather small. However, there are cases where the distribution of D is broad and therefore D can occasionally have a large value with a sizable probability. We have analyzed a model of diffusivity where it evolves as a Levy flight process. More with this modelxiv is found to be a stable distribution with a time dependent width. The width of the p distribution increases as T , as in the case of Fickian dynamics but at longer times it increases at a much faster rate as T 1=2 . Thus, the dynamics is Fickian at short times and super diffusive at long times.
After studying the models of diffusivity where it evolves as a Brownian process and as a Levy flight process, respectively, we have also studied a model of diffusivity where it evolves as a sub diffusive process. For that we have modeled diffusivity as a continuous time random walk (CTRW) process such that it attains an exponential distribution in the equilibrium limit. This model is actually a generalization of our first model of diffusing diffusivity with a parameter 2 (0; 1]. The problem of diffusing diffusivity, in this case, is shown to be equivalent to a class of models known as reaction-sub diffusion systems. We have analyzed two such models of reaction-sub diffusion. With both these models, we get all the results of our first model of diffusivity if = 1. Within the first model, the MSD is found to increase linearly in time at all the time scales and for all values of 2 (0; 1], thereby confirming a Fickian dynamics. Although the probability distribution function also becomes Gaussian in the limit of very large time for all values of as is our first model of diffusing diffusivity yet the evolution of pdf from a non-Gaussian function to Gaussian is a very slow process. Smaller is the value of , slower is the transition from non-Gaussian to Gaussian dynamics. The second model leads to sub diffusive dynamics in position space. The MSD here is shown to increase as T with a non-Gaussian pdf at all the time scales.
https://etd.iisc.ac.in/handle/2005/4151