Modelagem molecular na caracterização eletrônica de oligopeptídeos e na descrição quântica da interação fármaco-receptor

In this dissertation, the theoretical principles governing the molecular modeling were applied for electronic characterization of oligopeptide α3 and its variants (5Q, 7Q)-α3, as well as in the quantum description of the interaction of the aminoglycoside hygromycin B and the 30S subunit of bacterial ribosome. In the first study, the linear and neutral dipeptides which make up the mentioned oligopeptides were modeled and then optimized for a structure of lower potential energy and appropriate dihedral angles. In this case, three subsequent geometric optimization processes, based on classical Newtonian theory, the semi-empirical and density functional theory (DFT), explore the energy landscape of each dipeptide during the search of ideal minimum energy structures. Finally, great conformers were described about its electrostatic potential, ionization energy (amino acids), and frontier molecular orbitals and hopping term. From the hopping terms described in this study, it was possible in subsequent studies to characterize the charge transport propertie of these peptides models. It envisioned a new biosensor technology capable of diagnosing amyloid diseases, related to an accumulation of misshapen proteins, based on the conductivity displayed by proteins of the patient. In a second step of this dissertation, a study carried out by quantum molecular modeling of the interaction energy of an antibiotic ribosomal aminoglicosídico on your receiver. It is known that the hygromycin B (hygB) is an aminoglycoside antibiotic that affects ribosomal translocation by direct interaction with the small subunit of the bacterial ribosome (30S), specifically with nucleotides in helix 44 of the 16S ribosomal RNA (16S rRNA). Due to strong electrostatic character of this connection, it was proposed an energetic investigation of the binding mechanism of this complex using different values of dielectric constants (ε = 0, 4, 10, 20 and 40), which have been widely used to study the electrostatic properties of biomolecules. For this, increasing radii centered on the hygB centroid were measured from the 30S-hygB crystal structure (1HNZ.pdb), and only the individual interaction energy of each enclosed nucleotide was determined for quantum calculations using molecular fractionation with conjugate caps (MFCC) strategy. It was noticed that the dielectric constants underestimated the energies of individual interactions, allowing the convergence state is achieved quickly. But only for ε = 40, the total binding energy of drug-receptor interaction is stabilized at r = 18A, which provided an appropriate binding pocket because it encompassed the main residues that interact more strongly with the hygB - C1403, C1404, G1405, A1493, G1494, U1495, U1498 and C1496. Thus, the dielectric constant ≈ 40 is ideal for the treatment of systems with many electrical charges. By comparing the individual binding energies of 16S rRNA nucleotides with the experimental tests that determine the minimum inhibitory concentration (MIC) of hygB, it is believed that those residues with high binding values generated bacterial resistance to the drug when mutated. With the same reasoning, since those with low interaction energy do not influence effectively the affinity of the hygB in its binding site, there is no loss of effectiveness if they were replaced.

Estudo in silico da interação da albumina de soro humano com o ibuprofeno

Currently, computational methods have been increasingly used to aid in the characterization of molecular biological systems, especially when they relevant to human health. Ibuprofen is a nonsteroidal antiinflammatory or broadband use in the clinic. Once in the bloodstream, most of ibuprofen is linked to human serum albumin, the major protein of blood plasma, decreasing its bioavailability and requiring larger doses to produce its antiinflamatory action. This study aimes to characterize, through the interaction energy, how is the binding of ibuprofen to albumin and to establish what are the main amino acids and molecular interactions involved in the process. For this purpouse, it was conducted an in silico study, by using quantum mechanical calculations based on Density Functional Theory (DFT), with Generalized Gradient approximation (GGA) to describe the effects of exchange and correlation. The interaction energy of each amino acid belonging to the binding site to the ligand was calculated the using the method of molecular fragmentation with conjugated caps (MFCC). Besides energy, we calculated the distances, types of molecular interactions and atomic groups involved. The theoretical models used were satisfactory and show a more accurate description when the dielectric constant ε = 40 was used. The findings corroborate the literature in which the Sudlow site I (I-FA3) is the primary binding site and the site I-FA6 as secondary site. However, it differs in identifying the most important amino acids, which by interaction energy, in order of decreasing energy, are: Arg410, Lys414, Ser 489, Leu453 and Tyr411 to the I-Site FA3 and Leu481, Ser480, Lys351, Val482 and Arg209 to the site I-FA6. The quantification of interaction energy and description of the most important amino acids opens new avenues for studies aiming at manipulating the structure of ibuprofen, in order to decrease its interaction with albumin, and consequently increase its distribution

Reconhecimento de voz através de unidades menores do que a palavra, utilizando Wavelet Packet e SVM, em uma nova estrutura hierárquica de decisão

The automatic speech recognition by machine has been the target of researchers in the past five decades. In this period have been numerous advances, such as in the field of recognition of isolated words (commands), which has very high rates of recognition, currently. However, we are still far from developing a system that could have a performance similar to the human being (automatic continuous speech recognition). One of the great challenges of searches for continuous speech recognition is the large amount of pattern. The modern languages such as English, French, Spanish and Portuguese have approximately 500,000 words or patterns to be identified. The purpose of this study is to use smaller units than the word such as phonemes, syllables and difones units as the basis for the speech recognition, aiming to recognize any words without necessarily using them. The main goal is to reduce the restriction imposed by the excessive amount of patterns. In order to validate this proposal, the system was tested in the isolated word recognition in dependent-case. The phonemes characteristics of the Brazil s Portuguese language were used to developed the hierarchy decision system. These decisions are made through the use of neural networks SVM (Support Vector Machines). The main speech features used were obtained from the Wavelet Packet Transform. The descriptors MFCC (Mel-Frequency Cepstral Coefficient) are also used in this work. It was concluded that the method proposed in this work, showed good results in the steps of recognition of vowels, consonants (syllables) and words when compared with other existing methods in literature

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Estudo in silico das interações da protease NS3-NS2B de DENV-2 com o inibidor peptídico Bz-nKRR-H com finalidades terapêuticas

Dengue virus is an important patogen that causes Dengue desease in all world, and belongs to Flavivirus gender. The virus consists of enveloped RNA with a single strand positive sense, 11Kb genome. The RNA is translated into a polyprotein precursor, wich is cleaved into 3 structural proteins (C, prM e E) and 7 non-structural proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B e NS5). The NS3 is a multifunctional protein, that besides to promote the polyprotein precursor cleavage, also have NTPase, helicase and RTPase activity. The NS3 needs a hydrophilic segment of 40 residues from the transmembrane NS2B protein (who acts like cofator) to realize this functions. Actually, there's no vacines available on the market, and the treatment are just symptomatic. The tetrapeptide inhibitor Bz-Nle-Lys-Arg-Arg-H (Ki de 5,8-7,0 M) was showed as a potent inhibitor μ for NS3prot in Dengue virus. That is a inteligent alternative to treat the dengue desease. The present work aimed analyse the interactions of the ligand bounded to the activity site to provid a clear and depth vision of that interaction. For this purpouse, it was conducted an in silico study, by using quantum mechanical calculations based on Density Functional Theory (DFT), with Generalized Gradient approximation (GGA) to describe the effects of exchange and correlation. The interaction energy of each amino acid belonging to the binding site to the ligand was calculated the using the method of molecular fragmentation with conjugated caps (MFCC). Besides energy, we calculated the distances, types of molecular interactions and atomic groups involved. The theoretical models used were satisfactory and show a more accurate description when the dielectric constant = 20 ε and 80 was used. The results demonstrate that the interaction energy of the system reached convergence at 13.5 A. Within a radius of 13,5A the most important residues were identified. Met49, Met84 and Asp81 perform interactions of hydrogen with the ligant. The Asp79 and Asp75 residues present high energy of attraction. Arg54, Arg85 and Lys 131 perform hydrogen interactions with the ligand, however, appear in BIRD graph having high repulsion energy with the inhibitor. The data also emphasizes the importance of residue Tyr161 and the involvement of the catalytic triad composed by Asp75, His51 and Ser135

Bioquímica quântica na diferenciação dos níveis de ativação de receptores AMPA por agonistas parciais Wilardina

In the central nervous system (CNS) of mammalian, fast synaptic transmission between nerve cells is performed primarily by α-amino-3-hydroxy-5-methyl-4- isoxazolepropionic acid (AMPA) receptors, an ionotropic glutamate receptor that is related with learning, memory and homeostasis of the nervous system. Impairments in their functions are correlated with development of many brain desorders, such as epilepsy, schizophrenia, autism, Parkinson and Alzheimer. The use of willardiine analogs has been shown a powerful tool to understanding of activation and desensitization mechanisms of this receptors, because the modification of a single ligand atom allows the observation of varying levels of efficacy. In this work, taking advantage of Fluorine Willardiine (1.35Å), Hydrogen Willardiine (1.65Å), Bromine Willardiine (1.8Å) and Iodine Willardiine (2.15Å) structures co-crystalized with GluA2 with codes 1MQI, 1MQJ, 1MQH and 1MQG, we attempted to energetically differentiate the four ligands efficacy. The complexes were submitted to energetic calculations based on density functional theory (DFT), under the optics of molecular fractionation with conjugate caps (MFCC) method. Obtained results show a relationship between the energetic values and willardiines efficacy order (FW> HW > BrW > IW), also show the importance of E705, R485, Y450, S654, T655, T480 e P478 as the amino acids that contribute most strongly with the interaction of four partial agonists. Furthermore, we outlined the M708 behaviour, attracted by FW and HW ligands, and repels by BrW and IW. With the datas reported on this work, it is possible for a better understanding of the AMPA receptor, which can serve as an aid in the development of new drugs for this system.