K Varun Gopal

Computational Characterization of CNT-Papain Interactions for Developing a Biosensor

THC and its metabolites are detectable in body fluids and could be used to detect marijuana use. This research work reveals the possibility of using a carbon nano tube (CNT) based enzyme sensor for the detection of 9-carboxy tetrahydrocannabinol (9 THC-COOH) in urine using a cysteine protease obtained from papaya plant called papain. A comparative study of armchair and zigzag conformation of CNTs with the protein was carried out and the suitable conformer of CNT has been identified. The electrostatic energy variations and the thermodynamic energy differences of CNTs have been computed. A characteristic gradient in electrostatic potential has been identified for the CNT-protein complexes which could be effectively sensed using electrochemical sensors. The computational analysis of CNT-papain interaction supports the possibility of developing a biosensor using papain coated carbon nano tubes for the detection of THC-COOH in urine of the suspected marijuana consumed persons. A comparative analysis of the interaction energies of arm-chair and zig-zag conformations of carbon nano tubes with the cysteine protease enzyme papain has been carried out. The arm chair conformation with configuration index 18, 18 (m, n) has been identified as keeping the highest interaction energy of 45.218 kcal/mol. With this conformer designing of an electrochemical sensor has been suggested.

Computational study on metabolomic consequences of antifolate drug treatment and resistance in malarial organisms

Antimalarial antifolates have been the central drugs for prophylaxis and treatment of malaria. Plasmodium falciparum readily develops resistance to the antifolates pyrimethamine and proguanil through a particular set of mutations in the dihydrofolate reductase (DHFR) gene that results in the less competitive drug binding at the site of the enzyme. Similar mutations can be found in the DHFR gene in Plasmodium vivax (DHFR) also. The aim of this research work is to reveal the interactions of the DHFR inhibitors with the target proteins and to investigate the effect of mutations computationally. Commonly used antifolate drugs against malaria such as trimethoprim, pyrimethamine, proguanil and WR99210 have been considered for the analysis. Proteins which are targeted by the antifolate drugs in malarial organisms have been identified and characterized. Interaction studies of the wild and mutated DHFR proteins with the known drugs have been made. It has been found that the ligand binding to mutated proteins is considerably low compared to that of the wild proteins in most of the cases except WR99210 drug. This discloses the inadequacy of the antifolate drugs and the need to improve the antimalarial antifolate in vivo effectiveness and to recognize powerful novel antifolate agents. From the interaction studies of antifolate drugs against the target DHFR in malarial parasites Plasmodium vivax and Plasmodium falciparum it has been identified that these parasites show resistance to the chemotherapeutic antifolate drugs. A combination of antifolate drugs can be effective against malarial parasites or a designing of a new antifolate drug.

Insilico modeling and simulation of magnetic nanoparticles for the biological cell isolation technique

Magnetic nanoparticles (MNPs) can be used in a wide variety of biomedical applications like contrast agents for magnetic resonance imaging, magnetic labeling, controlled drug release, hyperthermia, and in cell isolation. Most of these applications need distinct and controllable interactions between the MNPs and living cells and can be made possible by a proper functionalization technique. This paper describes a computational approach for the identification of magnetic nanoparticles for the development, design, and demonstration of a novel, incorporated system for selective and rapid removal of biological, chemical, and radioactive biohazards from human body. The attraction between an external magnetic field and the MNPs facilitate separation of a wide variety of biological materials. This principle can be used for the isolation and aggregation of wandering cancer cells from the blood or the bone marrow to make a proper and early diagnosis of leukemia. Similarly, toxins, kidney stones, and other unwanted particles in the human body can be easily diagnosed and removed by the same technique. Nanoparticle-sized iron oxides have been studied in this work by computational modeling and molecular dynamic (MD) simulation techniques. Structural, thermodynamic, and magnetic properties have been formulated. In this work, nanoparticles of size varying from 0.5 to 2.5 nm have been analyzed. Cell isolation ability of the nanoparticles has been compared based on the computational results. MNPs are biologically activated and permitted to bind with the targeted cells through various pathways, thereby allowing certain cellular compartments to be specifically addressed. Once the cells are identified, the preferred cellular compartments can be magnetically isolated and removed with the help of an external magnetic field. Out of the iron oxides analyzed in this work, 1.1 nm Fe3O4 is found to be most interacting with leukemia protein. Hence, leukemia cells can be effectively targeted, separated, and removed using Fe3O4 of the suggested dimension.

Investigating multi target drug action of Aloe vera using computational analysis

Aloe vera has an immense role as a natural fighter against all kinds of infection. This is an effective wound healing activator and an efficient anti-oxidant to all type of digestion related problems, arthritis, stress, diabetes, cancer and AIDS. The present study attempts to reveal the multi therapeutic properties of Aloe vera by computational analysis. The interaction analysis of the some of the derived phytochemicals with various targets including proteins involved in Alzheimers and its role in curing such ailments has been examined. The interaction energy result suggests that Aloe emodin, Emodin, Aloin, Rhein, Coumarin, and Acemannan have an effective role in curing the pandemic conditions. The interaction anlaysis of Acemannan is greatest among all the results, suggesting that this ligand enhance the wound healing capacity. Acemannan was found to be a potent inhibitor of HIV virus replication. Anti inflammatory diseases like arthritis, asthma, hay fever can be cured to some extent by using Emodin, which is an efficient anti-inflammatory agent. Aloe Emodin can be used as an activator of apoptotic pathway in cancer cells as well as an anti sepsis agent.

Designing a Promotor for a Novel Target Site Identified in Caspases for Initiating Apoptosis in Cancer Cells

Caspases are enzymes that can cleave other proteins and control normal and abnormal cell death. Cancer cells generally lack apoptosis. In this research work, a computational approach has been adopted to design a promotor that targets the inactivated caspases particularly Pro-caspase-3 or caspase-7, which are the effector caspases that cleave the downstream substrates like lamin-A, ICAD and PARP. Out of the 38 anti-carcinomic compounds selected for the analysis, some of them are found to have positive charged substituents similar to the known drug; PAC1, which cleaves the safety catch mode that blocks the IETD active site. Site specific interactions of the proteins with these ligands were performed. From the interaction analysis, it was found that 3 compounds; Choline, Glaziovine, Dasatinib can effectively target caspases and activate them. It has been suggested that these compounds favor the activation of the effector caspase proteins, thereby giving a better option in cancer therapy.

Quantum Mechanical Characterization of Single Walled Carbon Nanotube (SWCNT) to Evaluate Stability and Conductivity

Single Walled Carbon Nanotube (SWCNT) is known to have unique thermodynamic and electrical properties which mainly depends upon the chiral index values (n, m). Quantum mechanical modeling and simulation studies were conducted for these samples to characterize the above properties. The energy gap of conducting carbon nano tubes has been found to be negligibly small. Armchair configuration with (n=m) is found to be highly stable. All these samples are found to be conducting. Structures with n and m values (8,7), (7,8), (7,6), (7,2), (6,5), (5,3) (4,5) and (3,5) are found to be unstable and are all semiconductors.

Thermal Analysis of Nanofluids Using Modeling and Molecular Dynamics Simulation

Nanofluids are nanotechnology‐based heat transfer fluids obtained by suspending nanometer‐sized particles in conventional heat transfer fluids in a stable manner. In many of the physical phenomena such as boiling and properties such as latent heat, thermal conductivity and heat transfer coefficient, there is significant change on addition of nanoparticles. These exceptional qualities of Nanofluids mainly depend on the atomic level mechanisms, which in turn govern all mechanical properties like strength, Young’s modulus, Poisson’s ratio, compressibility etc. Control over the fundamental thermo physical properties of the working medium will help to understand these unique phenomena of nanofluids to a great extent. Macroscopic modeling approaches, which are based on conventional relations of thermodynamics, have been proved to be incompetent to explain this difference. Atomistic ‘modeling and simulation’ has been emerged out as an efficient alternative for this. The enhancement of thermal conductivity of wat...