DESC:DESCRIPTION:
Field of the invention:
[0001] The present disclosure generally relates to the technical field of bio-inorganic chemistry, in particular, relates to a method for investigating metal-ligand complexes, which investigates metal ion speciation and amino acid complexation in biological systems for catalyzing new breakthroughs in fields such as biomedicine, pharmacology, and environmental science.
Background of the invention:
[0002] Metal ions play essential roles in a wide range of biological processes, including metabolism, signaling, and gene expression. They function as vital cofactors for enzymes, actively participate in signal transduction pathways, and contribute significantly to maintaining cellular homeostasis. Simultaneously, amino acids, serving as fundamental protein building blocks, also act as crucial ligands within metal-ion coordination complexes. By understanding the metal ion interaction with amino acids, the metal ion function in biological systems can be understood. Many metal-related diseases, such as Wilson's disease and hemochromatosis, are caused by the accumulation of metal ions in the body. By investigating metal ion speciation and amino acid complexation in biological samples, metal-related diseases can be diagnosed and the effectiveness of treatments monitored.
[0003] By understanding the metal ion interaction with amino acids, new drugs and other therapies are designed that target specific metal-amino acid interactions. This could lead to new and more effective treatments for a variety of diseases, including cancer, neurodegenerative diseases, and infectious diseases. Many environmental pollutants, such as heavy metals and pesticides, can interact with metal ions and amino acids in biological systems. By investigating metal ion speciation and amino acid complexation, the safety of environmental pollutants can be assessed, and new strategies can be developed to protect human health and the environment.
[0004] A variety of analytical techniques can be used to study metal ion forms and their intricate interactions with amino acids. Analytical techniques play a vital role in the study of metal ion forms and their interactions with amino acids. By understanding the interactions between metal ions and amino acids, the biological roles of metal ions are known to help develop new ways to diagnose and treat metal-related diseases. Some of the most common techniques include atomic absorption spectroscopy (AAS), inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and infrared (IR) spectroscopy.
[0005] Atomic absorption spectroscopy (AAS) is a technique that measures the amount of light absorbed by a sample at specific wavelengths. This technique can be used to quantify the concentration of metal ions in a sample and to identify the specific metal ions present. Inductively coupled plasma optical emission spectroscopy (ICP-OES) is a technique that measures the amount of light emitted by a sample when it is excited by a high-temperature plasma. This technique can be used to quantify the concentration of metal ions in a sample and to identify the specific metal ions present.
[0006] Inductively coupled plasma mass spectrometry (ICP-MS) is a technique that measures the mass-to-charge ratio of ions. This technique can be used to quantify the concentration of metal ions in a sample and to identify the specific metal ions present. X-ray crystallography is a technique that determines the three-dimensional structure of crystals. This technique can be used to determine the structure of metal-amino acid complexes, which can provide insights into the intricate interactions between metal ions and amino acids. Nuclear magnetic resonance (NMR) spectroscopy is a technique that uses a magnetic field and radio waves to probe the molecular structure of a sample. This technique can be used to identify the metal and amino acid species in metal-amino acid complexes and to determine the geometry of the complex.
[0007] Infrared (IR) spectroscopy is a technique that measures the vibrational frequencies of a sample. Metal-amino acid complexes often have characteristic IR spectra, which can be used to identify them and study the interactions between the metal ions and amino acids. In addition to these techniques, a number of other methods can be used to study metal ion forms and their interactions with amino acids, such as potentiometry, calorimetry, and chromatography. The choice of technique will depend on the specific nature of the sample and the information that is needed.
[0008] However, traditional analytical techniques often prove inadequate in providing comprehensive insights into the diverse metal ion forms and their intricate interactions with amino acids. This constraint impedes a thorough comprehension of the fundamental mechanisms governing metal-ion-dependent processes in living organisms.
[0009] By addressing all the above-mentioned problems, there is a need for a method for investigating metal-ligand complexes that investigates metal ion speciation and amino acid complexation in biological systems, catalyzing new breakthroughs in fields such as biomedicine, pharmacology, and environmental science. There is also a need for a method that integrates pH metry and MINIQUAD computer programming for investigating metal ion speciation and amino acid complexation in biological systems. There is also a need for a method that offers a more comprehensive and detailed view of metal ion speciation and amino acid complexation than the existing analytical techniques, allowing researchers to explore a wider range of coordination states and binding interactions.
[0010] There is also a need for a method that integrates multiple spectroscopic and separation techniques, enabling a thorough understanding of complex interactions. There is also a need for a method that provides high-resolution data that can distinguish subtle differences in metal-ligand complexes, leading to more accurate and nuanced characterizations. There is also a need for a method that develops tools like streamline data analysis and modeling, facilitating the interpretation of intricate speciation patterns and binding mechanisms.
Objectives of the invention:
[0011] The primary objective of the present invention is to provide a method for investigating metal-ligand complexes, which investigates metal ion speciation and amino acid complexation in biological systems for catalyzing new breakthroughs in fields such as biomedicine, pharmacology, and environmental science.
[0012] Another objective of the present invention is to provide a method that integrates pH metry and MINIQUAD computer programming for investigating metal ion speciation and amino acid complexation in biological systems.

[0013] Another objective of the present invention is to provide a method that offers a more comprehensive and detailed view of metal ion speciation and amino acid complexation than the existing analytical techniques, allowing researchers to explore a wider range of coordination states and binding interactions.
[0014] Yet another objective of the present invention is to provide a method that integrates multiple spectroscopic and separation techniques, enabling a more thorough understanding of complex interactions.
[0015] Another objective of the present invention is to provide a method that provides high-resolution data, which can distinguish subtle differences in metal-ligand complexes, leading to more accurate and nuanced characterizations.
[0016] Yet another objective of the present invention is to provide a method that is versatile and adaptable to various biological samples, making it applicable to diverse research contexts, from isolated biomolecules to complex cellular extracts.
[0017] Another objective of the present invention is to provide a method that develop tools like streamline data analysis and modelling, facilitating the interpretation of intricate speciation patterns and binding mechanisms.
[0018] Yet another objective of the present invention is to provide a method for investigating metal-ligand complexes, which can contribute a better understanding of environmental impacts and ecosystem health.
[0019] Another objective of the present invention is to provide a method for investigating metal-ligand complexes that provides a holistic approach to studying metal-ligand interactions, bridging the gap between traditional analytical methods and the complex reality of biological systems.
[0020] Yet another objective of the present invention is to provide a method that opens avenues for novel discoveries, hypotheses, and further research in the field of bioinorganic chemistry.
[0021] Further objective of the present invention is to provide a method that represents a significant advancement in the field, pushing the boundaries of investigating metal ion speciation and amino acid complexation and contributing to the broader advancement of analytical and bioinorganic chemistry.
Summary of the invention:
[0022] The present disclosure proposes a method for investigating metal-ligand complexes. The following presents a simplified summary in order to provide a basic understanding of some aspects of the claimed subject matter. This summary is not an extensive overview. It is not intended to identify key/critical elements or to delineate the scope of the claimed subject matter. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
[0023] In order to overcome the above deficiencies of the prior art, the present disclosure is to solve the technical problem to provide a method for investigating metal-ligand complexes, which investigates metal ion speciation and amino acid complexation in biological systems for catalyzing new breakthroughs in fields such as biomedicine, pharmacology, and environmental science.
[0024] According to one aspect, the invention provides a method for investigating metal-ligand complexes in biological systems. In one embodiment herein, the method integrates pH metry and MINIQUAD computer programming for investigating metal ion speciation and amino acid complexation in biological systems. The method offers a more comprehensive and detailed view of metal ion speciation and amino acid complexation than the existing analytical techniques, allowing researchers to explore a wider range of coordination states and binding interactions.
[0025] At one step, one or more metal ions are identified based on potential biological relevance and plurality of amino acids are selected to interact with the one or more metal ions. In one embodiment herein, the plurality of amino acids includes L-Cysteine (Cys) and L-threonine (Thr). At other step, the one or more metal ions interaction with the plurality of amino acids is analyzed using one or more analytical techniques, thereby obtaining plurality of complex datasets.
[0026] At another step, pH values of the one or more metal ions and the plurality of amino acids are measured via a potentiometry technique and the measured pH values are analyzed using at least one computational model, thereby obtaining protonation constant values. In one embodiment herein, the at least one computational model is a SCPHD15, which is configured to analyze the measured pH values for obtaining protonation constant values.
[0027] Further at other step, the obtained protonation constant values are analyzed using a MINIQUAD model, thereby interpreting speciation patterns, identifying specific metal-ligand complexes and modeling binding interactions between the one or more metal ions and the plurality of amino acids. In one embodiment herein, the MINIQUAD model is used to refine the protonation constant values of the L-Cysteine (Cys) and the L-threonine (Thr) in one or more surfactant-water mixtures. In one embodiment, the one or more surfactant mixtures include sodium lauryl sulphate (SLS), cetyltrimethylammonium bromide (CTAB), triton X-100, and other water mixtures. In one embodiment, the method develops tools like streamline data analysis and modelling, facilitating the interpretation of intricate speciation patterns and binding mechanisms. The method is versatile and adaptable to various biological samples and applicable to diverse research contexts, from isolated biomolecules to complex cellular extracts.
[0028] Further, objects and advantages of the present invention will be apparent from a study of the following portion of the specification, the claims, and the attached drawings.
Detailed description of drawings:
[0029] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate an embodiment of the invention, and, together with the description, explain the principles of the invention.
[0030] FIG. 1 illustrates a flowchart of a method for investigating metal-ligand complexes in biological systems, in accordance to an exemplary embodiment of the invention.
[0031] FIGs. 2A-2B illustrate graphs representing alkalimetric titration curves for L-Cysteine (Cys) and L-threonine (Thr) in aqueous medium, in accordance to an exemplary embodiment of the invention.
[0032] FIGs. 3A-3C illustrate graphs representing alkalimetric titration curves for L-Cysteine (Cys) in 2.5%w/v SLS water medium, in accordance to an exemplary embodiment of the invention.
[0033] FIGs. 4A-4C illustrate graphs representing alkalimetric titration curves for L-threonine (Thr) in 2.5%w/v SLS water medium, in accordance to an exemplary embodiment of the invention.
[0034] FIGs. 5A-5D illustrate graphs representing formation curves of L-Cysteine (Cys) and L-threonine (Thr) in 1.5%w/v SLS water medium, in accordance to an exemplary embodiment of the invention.
[0035] FIGs. 6A-6B illustrate graphs representing simulated and experimental alkalimetric titration curves of L-Cysteine (Cys) and L-threonine (Thr) in 0.5%w/v SLS water medium, in accordance to an exemplary embodiment of the invention.
[0036] FIGs. 7A-7B illustrate reaction diagrams of protonation and deprotonation for L-Cysteine (Cys) and L-threonine (Thr), in accordance to an exemplary embodiment of the invention.
[0037] FIGs. 8A-8B illustrate graphs representing distribution diagrams of L-Cysteine (Cys) in SLS water medium, in accordance to an exemplary embodiment of the invention.
[0038] FIGs. 9A-9B illustrate graphs representing distribution diagrams of L-threonine (Thr) in SLS water medium, in accordance to an exemplary embodiment of the invention.
Detailed invention disclosure:
[0039] Various embodiments of the present invention will be described in reference to the accompanying drawings. Wherever possible, same or similar reference numerals are used in the drawings and the description to refer to the same or like parts or steps.
[0040] The present disclosure has been made with a view towards solving the problem with the prior art described above, and it is an object of the present invention to provide a method for investigating metal-ligand complexes, which investigates metal ion speciation and amino acid complexation in biological systems for catalyzing new breakthroughs in fields such as biomedicine, pharmacology, and environmental science.
[0041] According to one exemplary embodiment of the invention, FIG. 1 refers to a flowchart 100 of a method for investigating metal-ligand complexes in biological systems. In one embodiment herein, the method integrates pH metry and MINIQUAD computer programming for investigating metal ion speciation and amino acid complexation in biological systems. The method offers a more comprehensive and detailed view of metal ion speciation and amino acid complexation than the existing analytical techniques, allowing researchers to explore a wider range of coordination states and binding interactions. At step 102, one or more metal ions are identified based on potential biological relevance and plurality of amino acids are selected to interact with the one or more metal ions. In one embodiment herein, the plurality of amino acids includes L-Cysteine (Cys) and L-threonine (Thr). At step 104, the one or more metal ions interaction with the plurality of amino acids is analyzed using one or more analytical techniques, thereby obtaining plurality of complex datasets.
[0042] At step 106, pH values of the one or more metal ions and the plurality of amino acids are measured via a potentiometry technique and the measured pH values are analyzed using at least one computational model, thereby obtaining protonation constant values. In one embodiment herein, the at least one computational model is a SCPHD15, which is configured to analyze the measured pH values for obtaining protonation constant values. Further at step 108, the obtained protonation constant values are analyzed using a MINIQUAD model, thereby interpreting speciation patterns, identifying specific metal-ligand complexes and modeling binding interactions between the one or more metal ions and the plurality of amino acids. In one embodiment herein, the MINIQUAD model is used to refine the protonation constant values of the L-Cysteine (Cys) and the L-threonine (Thr) in one or more surfactant-water mixtures.
[0043] In one embodiment herein, the one or more surfactant mixtures include sodium lauryl sulphate (SLS), cetyltrimethylammonium bromide (CTAB), triton X-100, and other water mixtures.In one embodiment herein, the method develops tools like streamline data analysis and modelling, facilitating the interpretation of intricate speciation patterns and binding mechanisms. The method is versatile and adaptable to various biological samples and applicable to diverse research contexts, from isolated biomolecules to complex cellular extracts.
[0044] According to one exemplary embodiment of the invention, FIGs. 2A-2B refer to graphs (200, 202) representing alkalimetric titration curves for L-Cysteine (Cys) and L-threonine (Thr) in aqueous medium. In one embodiment herein, the L-Cysteine (Cys) and the L-threonine (Thr) are subjected in a miscellar media, which includes one or more surfactant water mixtures. In one embodiment herein, the protonation constant values of the plurality of amino acids could be determined by analysis of acid-base titrations. Vast data is available on the protonation and stability constants of the amino acids and simple peptides in water and organic solvents. However, the protonation constants of amino acids and carboxylic acids in micellar media are often different from those in water, as micellar media tend to be amphiphilic rather than hydrophilic or lipophilic. It has been suggested that mixture of solvents such as micellar–water mixtures provide a better model for in vivo reactions.
[0045] In one embodiment herein, the L-Cystenine (Cys) have three functional groups in the order amino followed by one carboxylic and one thiol groups. The Cys have tridentate behavior resulting in five membered ring structures. Nitrogen donor atoms associate with hydrogen ions in physiological pH ranges. The L-Threonine (Thr) has only two functional groups which are protonated, amino followed by carboxylic group. Thr is a bidentate ligand resulting in five membered ring structures. There is often significant competition between hydrogen and metal ion for the donor sites. This situation results in the simultaneous existence of a number of equilibria, producing an array of successively protonated complexes. The protonation-deprotonation equilibria of Cys and Thr is necessary before an attempt is made to investigate the metal-ligand equilibria associated with Cys and Thr. In one embodiment herein, the protonation constant values of Cys and Thr reported are given in Table 1 respectively. There is a considerable difference in the protonation constant values reported under similar conditions. The protonation equilibria of Cys and Thr in micellar media and the effect of mole fraction of the medium on protonation constant values are investigated.
[0046] Table 1:
S. No log ß
Ionic
strength Instrumental method Ref.
011 012 013
L-Cysteine
1. 8.37 10.29 10.70 0.1M 7
2. 8.32 10.26 10.48 0.1M pH metry 8,9
3. 8.71 11.11 10.69 3.0M " 10
4. 9.52 13.69 16.00 1.0M " 10
5. 9.51 13.62 15.74 0.1M - 11
L-Threonie
1. 9.12 18.34 0.2M pH metry 12
2. 9.14 17.32 0.2M " 13
3. 9.14 18.30 0.2M “ 14

[0047] According to one exemplary embodiment of the invention, FIGs. 3A-3C refer to graphs (300, 302, 304) representing alkalimetric titration curves for L-Cysteine (Cys) in 2.5%w/v SLS water medium with ligand concentrations 0.25 mmol, 0.375 mmol, 0.50 mmol. In one embodiment herein, the alkalimetric titration curves of Cys and Thr in aqueous and SLS, CTAB, and TX-100 water mixtures are shown in the graphs (300, 302, and 304). The titration curves reveals that the acid-basic equilibria are active in the pH range 2.0-11.0. The computer program SCPHD15 is used to prone the data obtained in different experiments so that it contains more information than noise and the log ßs given by the program are used as initial values for final refinement. According to one exemplary embodiment of the invention, FIGs. 4A-4C refer to graphs (400, 402, 404) representing alkalimetric titration curves for L-threonine (Thr) in 2.5%w/v SLS water medium with ligand concentrations 0.25 mmol, 0.375 mmol, 0.50 mmol.
[0048] According to one exemplary embodiment of the invention, FIGs. 5A-5D refer to graphs (500, 502, 504, 506) representing formation curves of L-Cysteine (Cys) and L-threonine (Thr) in 1.5%w/v SLS water medium with ligand concentrations 0.25 mmol, 0.375 mmol, 0.50 mmol. The formation function, n?H (average number of moles of protons bound per mole of ligand) is a useful parameter for the detection of polymeric species (L2Hx).If there are no polymeric species a plot of n?H versus pH should overlap. Any deviation indicates the presence of polymeric species. FIGs. 5A-5B depict that there is no polymerization of Cys and Thr. The number of moles of alkali consumed per mole of the ligand is denoted by “a”. It is another secondary function like n?H. The negative values of “a” correspond to the excess of mineral acid present in the titrant and the number of associable protons. The positive values correspond to the dissociable protons. The maximum value of “a” is 1 for Cys (as shown in FIG. 5C) and 1 for Thr (as shown in FIG. 5D), which indicates that Cys has 1 dissociable protons and Thr has 1 dissociable proton.
[0049] According to one exemplary embodiment of the invention, FIGs. 6A-6B refer to graphs (600, 602) representing simulated and experimental alkalimetric titration curves of L-Cysteine (Cys) and L-threonine (Thr) in 0.5%w/v SLS water medium. In one embodiment herein, the complex datasets are fit into the models and categorized into one or more residuals. The residuals are tested for normal distribution in plurality of tests, which include are x2 test, Crystallographic R-test, skewness test, and kurtosiss test. In one embodiment herein, the alkalimetric titration data are simulated using the model parameters. These data are compared with the experimental alkalimetric titration data to verify the sufficiency of the models. The simulated primary data curve generated by using the stability constants of the best fit model overlapped with the experimental ones, which supports the validity of models. In one embodiment herein, Best fit chemical models of protonation equilibria of Cys and Thr in SLS-water mixtures Temp = 303 K, Ionic strength = 0.16 mol dm-3 is shown in Table 2.
[0050] Table 2:
SLS
% w/v log ßmlh (SD) NP Ucorr
*108 ?2 Skew-ness Kurt-osis R-factor
11 12 13
Cys(pH range 2.0-9.0)
0.0 10.55(2) 18.51(10) 20.30(1) 150 1.67 92.11 -0.12 5.45 0.016293
0.5 10.43(8) 20.44(17) 22.44(16) 166 6.04 74.75 -0.71 5.67 0.055456
1.0 9.96(3) 18.59(6) 23.99(14) 106 4.47 57.96 2.65 11.17 0.046660
1.5 9.85(13) 19.15(11) 26.41(11) 118 2.53 63.55 2.22 6.58 0.065385
2.0 9.96(6) 18.97(5) 26.62(5) 79 4.51 55.28 2.15 17.36 0.026856
2.5 10.53(7) 20.86(4) 28.61(3) 91 3.84 22.17 0.88 12.62 0.020767
Thr(pH range 2.0-9.0)
0.0 10.73(12) 20.99(13) ------- 66 1.39 3.64 0.29 3.83 0.080140
0.5 11.05(6) 20.15(6) ------- 30 0.76 5.64 0.96 3.38 0.014309
1.0 11.16(23) 22.15(6) ------- 72 1.08 11.11 1.48 5.44 0.072574
1.5 11.40(2) 19.70(2) ------- 50 1.68 20.64 -0.77 2.62 0.039641
2.0 11.49(4) 20.25(4) ------- 36 2.43 1.78 -0.19 3.32 0.008756
2.5 11.42(6) 20.56(6) -------- 39 0.41 1.18 0.88 3.63 0.018840

[0051] In one embodiment herein, Best fit chemical models of protonation equilibria of Cys and Thr in TX-100-water mixtures Temp= 303 K, Ionic strength=0.16 mol dm-3 is shown in Table 3.

[0052] Table 3:
TX-100
% v/v log ßmlh (SD) NP Ucorr
*108 ?2 Skew-ness Kurt-osis R-factor
11 12 13
Cys(pH range 2.0-10.0)
0.0 6.55(5) 9.55(9) 11.52(7) 88 1.67 10.45 1.07 5.46 0.027553
0.5 6.85(5) 9.45(9) 11.62(7) 114 4.47 6.53 -0.02 4.41 0.035294
1.0 6.46(5) 8.58(11) 10.86(6) 128 2.53 13.56 0.82 5.48 0.033943
1.5 6.36(5) 7.49(61) 10.79(6) 160 2.53 11.85 0.91 5.17 0.032458
2.0 6.38(11) 8.56(13) 10.67(11) 88 4.51 10.45 1.07 5.46 0.027559
2.5 8.07(5) 9.79(26) 12.71(4) 157 3.84 26.08 0.18 4.17 0.042808
Thr (pH range 2.0-11.0)
0.0 10.53(13) 18.48(28) ------- 33 1.39 2.00 -1.17 4.95 0.080021
0.5 9.64(5) 17.68(4) ------- 34 0.76 6.59 -0.42 2.42 0.012863
1.0 10.30(7) 18.43(15) ------- 70 0.76 81.83 2.21 9.41 0.013517
1.5 9.81(4) 17.52(5) ------- 40 1.08 7.60 -0.34 2.85 0.034648
2.0 10.66(3) 19.12(5) ------- 57 2.43 7.82 0.71 6.20 0.037041
2.5 10.65(4) 19.37(5) -------- 34 0.41 2.59 -0.73 4.18 0.033488

[0053] In one embodiment herein, Best fit chemical models of protonation equilibria of Cys and Thr in in CTAB-water mixtures Temp= 303 K, Ionic strength=0.16 mol dm-3 is shown in Table 4.
[0054] Table 4:
CTAB
% w/v log ßmlh (SD) NP Ucorr
*108 ?2 Skew-ness Kurt-osis R-factor
11 12 13
Cys (pH range 2.0-10.0)
0.0 6.38(11) 8.56(13) 10.67(11) 88 1.67 10.45 1.07 5.46 0.027553
0.5 6.83(4) 9.36(7) 11.28(5) 102 6.04 16.00 -0.82 8.22 0.028409
1.0 6.85(5) 9.45(6) 11.62(7) 114 4.47 6.53 -0.02 4.41 0.035294
1.5 6.46(5) 8.58(11) 10.86(6) 128 2.53 13.56 0.82 5.48 0.033943
2.0 6.38(11) 8.56(13) 10.67(11) 88 4.51 10.45 1.07 5.46 0.027559
2.5 6.85(6) 9.45(10) 11.62(7) 118 3.84 13.90 -0.58 5.06 0.038645
Thr (pH range 2.0-11.0)
0.0 10.53(13) 18.48(28) ------- 33 1.39 2.00 -1.17 4.95 0.080021
0.5 11.49(8) 20.80(8) ------- 21 0.76 3.14 -1.63 6.05 0.005049
1.0 11.56(10) 20.65(10) ------- 46 1.08 10.29 0.16 3.21 0.040013
1.5 10.99(2) 20.28(1) ------- 39 1.68 25.38 -1.64 7.40 0.028288
2.0 15.54(7) 24.94(7) ------- 25 2.43 7.60 1.58 6.03 0.005682
2.5 11.56(10) 20.65(10) -------- 48 0.41 10.18 0.26 2.31 0.010004

[0055] According to one exemplary embodiment of the invention, FIGs. 7A-7B refer to reaction diagrams (700, 702) of protonation and deprotonation for L-Cysteine (Cys) and L-threonine (Thr). The protonation equilibria of these acids have a significant influence on their metabolism. Anions of SLS bind to the main peptide chain at a ratio of one SLS anion for every two amino acid residues. This effectively imparts a negative charge on the protein that is proportional to the mass of that protein (about 1.4 g SLS/g protein). The electrostatic repulsion created by the binding of SLS causes proteins to unfold into a rod-like shape, thereby eliminating the differences in shape as a factor for separation in the gel. The apparent shift in the magnitude of protonation constant values in micellar media compared to aqueous solutions is attributed to the creation of a concentration gradient of protons between the interface and the bulk solution. Further, the presence of micelles is known to alter the dielectric constant of the medium, which has a direct influence on the protonation-deprotonation equilibria.
[0056] According to one exemplary embodiment of the invention, FIGs. 8A-8B refer to graphs (800, 802) representing distribution diagrams of L-Cysteine (Cys) in SLS water medium. In one embodiment herein, the distribution diagram of percentage species as a function of free concentrations of ingredients (pH, pL or pM) is not only of theoretical interest but also finds practical utility in a variety of chemical problems. The three functional groups of Cys and two functional groups of Thr participate in protonation equilibria. Their distribution plots in SLS-water medium, as shown in FIGs. 9A-9B, exhibits the existence of LH3+,LH2, LH- and L2- forms of Cys and XH2+, XH and X- forms of Thr. The XH form of Thr is present to an extent of 80-90% in the pH range of 2.5–10.5 and the LH-form of Cys is present to an extent of 80–90% in the pH range of 4.0–10.5. According to one exemplary embodiment of the invention, FIGs. 9A-9B refer to graphs (900, 902) representing distribution diagrams of L-threonine (Thr) in SLS water medium.
[0057] Numerous advantages of the present disclosure may be apparent from the discussion above. In accordance with the present disclosure a method for investigating metal-ligand complexes, is disclosed. The proposed invention provides a method for investigating metal-ligand complexes, which investigates metal ion speciation and amino acid complexation in biological systems for catalyzing new breakthroughs in fields such as biomedicine, pharmacology, and environmental science. The proposed invention provides a method that integrates pH metry and MINIQUAD computer programming for investigating metal ion speciation and amino acid complexation in biological systems.The method offers a more comprehensive and detailed view of metal ion speciation and amino acid complexation than the existing analytical techniques, allowing researchers to explore a wider range of coordination states and binding interactions. The method integrates multiple spectroscopic and separation techniques, enabling a more thorough understanding of complex interactions. The method provides high-resolution data, which can distinguish subtle differences in metal-ligand complexes, leading to more accurate and nuanced characterizations.
[0058] The method is versatile and adaptable to various biological samples, making it applicable to diverse research contexts, from isolated biomolecules to complex cellular extracts. The method develops tools like streamline data analysis and modelling, facilitating the interpretation of intricate speciation patterns and binding mechanisms. The method investigates metal-ligand complexes, which can contribute a better understanding of environmental impacts and ecosystem health.The method provides a holistic approach to studying metal-ligand interactions, bridging the gap between. The method opens avenues for novel discoveries, hypotheses, and further research in the field of bioinorganic chemistry. The method represents a significant advancement in the field, pushing the boundaries of investigating metal ion speciation and amino acid complexation and contributing to the broader advancement of analytical and bioinorganic chemistry.
[0059] It will readily be apparent that numerous modifications and alterations can be made to the processes described in the foregoing examples without departing from the principles underlying the invention, and all such modifications and alterations are intended to be embraced by this application.
,CLAIMS:CLAIMS:
I/We Claim:
1. A method for investigating metal-ligand complexes in biological systems, comprising:
identifying one or more metal ions based on potential biological relevance and selecting plurality of amino acids to interact with the one or more metal ions;
analyzing the one or more metal ions interaction with the plurality of amino acids using one or more analytical techniques, thereby obtaining plurality of complex datasets;
providing one or more coordination states and plurality of speciation patterns of the one or more metal ions in the biological systems based on the complex data sets;
measuring pH values of the one or more metal ions and the plurality of amino acids through a potentiometry technique and analyzing the measured pH values using at least one computational model, thereby obtaining protonation constant values; and
analyzing the obtained protonation constant values using a MINIQUAD model, thereby interpreting speciation patterns, identifying specific metal-ligand complexes and modeling binding interactions between the one or more metal ions and the plurality of amino acids.
2. The method as claimed in claim 1, wherein the at least one computational model is a SCPHD15, which is configured to analyze the measured pH values for obtaining protonation constant values.
3. The method as claimed in claim 1, wherein the plurality of amino acids includes L-Cysteine (Cys) and L-threonine (Thr).
4. The method as claimed in claim 1, wherein the MINIQUAD model is used to refine the protonation constant values of the L-Cysteine (Cys) and the L-threonine (Thr) in one or more surfactant-water mixtures.
5. The method as claimed in claim 4, wherein the one or more surfactant mixtures include sodium lauryl sulphate (SLS), cetyltrimethylammonium bromide (CTAB), triton X-100, and other water mixtures.
6. The method as claimed in claim 1, wherein the method provides high-resolution data that can distinguish subtle differences in metal-ligand complexes, leading to more accurate and nuanced characterizations.
7. The method as claimed in claim 1, wherein the method develops tools like streamline data analysis and modelling, facilitating the interpretation of intricate speciation patterns and binding mechanisms.
8. The method as claimed in claim 1, wherein the method is versatile and adaptable to various biological samples and applicable to diverse research contexts, from isolated biomolecules to complex cellular extracts.