<p>Accurate calculations of free energies for molecular association and solvation are important for the understanding of biochemical processes, and are useful in many pharmaceutical applications. In this thesis, molecular dynamics (MD) simulations are used to calculate thermodynamic properties for solvation and ligand binding.</p><p>The thermodynamic integration technique is used to calculate p<i>K</i>_a values for three aspartic acid residues in two different proteins. MD simulations are carried out in explicit and Generalized-Born continuum solvent. The calculated p<i>K</i>_a values are in qualitative agreement with experiment in both cases. A combination of MD simulations and a continuum electrostatics method is applied to examine p<i>K</i>_a shifts in wild-type and mutant epoxide hydrolase. The calculated p<i>K</i>_a values support a model that can explain some of the pH dependent properties of this enzyme.</p><p> Development of the linear interaction energy (LIE) method for calculating solvation and binding free energies is presented. A new model for estimating the electrostatic term in the LIE method is derived and is shown to reproduce experimental free energies of hydration. An LIE method based on a continuum solvent representation is also developed and it is shown to reproduce binding free energies for inhibitors of a malaria enzyme. The possibility of using a combination of docking, MD and the LIE method to predict binding affinities for large datasets of ligands is also investigated. Good agreement with experiment is found for a set of non-nucleoside inhibitors of HIV-1 reverse transcriptase.</p><p>Approaches for decomposing solvation and binding free energies into enthalpic and entropic components are also examined. Methods for calculating the translational and rotational binding entropies for a ligand are presented. The possibility to calculate ion hydration free energies and entropies for alkali metal ions by using rigorous free energy techniques is also investigated and the results agree well with experimental data.</p>

Accurate calculations of free energies for molecular association and solvation are important for the understanding of biochemical processes, and are useful in many pharmaceutical applications. In this thesis, molecular dynamics (MD) simulations are used to calculate thermodynamic properties for solvation and ligand binding. The thermodynamic integration technique is used to calculate pKa values for three aspartic acid residues in two different proteins. MD simulations are carried out in explicit and Generalized-Born continuum solvent. The calculated pKa values are in qualitative agreement with experiment in both cases. A combination of MD simulations and a continuum electrostatics method is applied to examine pKa shifts in wild-type and mutant epoxide hydrolase. The calculated pKa values support a model that can explain some of the pH dependent properties of this enzyme. Development of the linear interaction energy (LIE) method for calculating solvation and binding free energies is presented. A new model for estimating the electrostatic term in the LIE method is derived and is shown to reproduce experimental free energies of hydration. An LIE method based on a continuum solvent representation is also developed and it is shown to reproduce binding free energies for inhibitors of a malaria enzyme. The possibility of using a combination of docking, MD and the LIE method to predict binding affinities for large datasets of ligands is also investigated. Good agreement with experiment is found for a set of non-nucleoside inhibitors of HIV-1 reverse transcriptase. Approaches for decomposing solvation and binding free energies into enthalpic and entropic components are also examined. Methods for calculating the translational and rotational binding entropies for a ligand are presented. The possibility to calculate ion hydration free energies and entropies for alkali metal ions by using rigorous free energy techniques is also investigated and the results agree well with experimental data.

Submitted by LILIAN HERNÁNDEZ ALVAREZ null (lilianhern@gmail.com) on 2017-10-16T13:40:19Z No. of bitstreams: 1 Lilian_dissertacao_final.pdf: 8133270 bytes, checksum: ea7913c9f03bc3c89f0211896c01cc88 (MD5) / Approved for entry into archive by Monique Sasaki (sayumi_sasaki@hotmail.com) on 2017-10-18T17:58:56Z (GMT) No. of bitstreams: 1 hernandezalvarez_l_me_sjrp.pdf: 8133270 bytes, checksum: ea7913c9f03bc3c89f0211896c01cc88 (MD5) / Made available in DSpace on 2017-10-18T17:58:56Z (GMT). No. of bitstreams: 1 hernandezalvarez_l_me_sjrp.pdf: 8133270 bytes, checksum: ea7913c9f03bc3c89f0211896c01cc88 (MD5) Previous issue date: 2017-09-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Trypanosoma cruzi é o agente causal da doença de Chagas, uma infecção negligenciada que afeta milhões de pessoas nas regiões tropicais. A maioria dos fármacos empregados no tratamento desta doença são altamente tóxicos e geram resistência. Na atualidade, o descobrimento de inibidores alostéricos é um tópico emergente dentro da área de desenho computacional de fármacos, pois promove a acessibilidade a medicamentos mais seletivos e menos tóxicos. Neste trabalho foi desenvolvida uma estratégia para a descoberta computacional de inibidores alostéricos a qual foi aplicada à cruzaína, a principal cisteíno protease do T. cruzi. A caracterização molecular da forma livre e ligada da cruzaína foi investigada através do ancoramento molecular, simulações de dinâmica molecular, cálculos de energia livre de ligação e construção de redes de interações entre resíduos. A partir da análise baseada na geometria das estruturas geradas na dinâmica molecular, foram detectados dois potenciais sítios alostéricos na cruzaína. Os resultados sugerem a existência de diferentes mecanismos de regulação exercidos pela ligação de inibidores diferentes no mesmo sítio alostérico. Além disso, foram identificados os resíduos que estabelecem os caminhos de transmissão de informação entre um dos sítios alostéricos identificado e o sítio ativo da enzima. O presente estudo é a primeira aproximação de desenho de inibidores alostéricos da cruzaína e serve para futuras intervenções farmacológicas. Esses resultados constituem uma base para o desenho de inibidores específicos de cisteíno proteases homólogas da papaína. / Trypanosoma cruzi is the causative agent of Chagas disease, a neglected infection affecting millions of people in tropical regions. There are several chemotherapeutic agents for the treatment of this disease, but most of them are highly toxic and generate resistance. Currently, the development of allosteric inhibitors constitutes a promising research field, since it may improve the accessibility to more selective and less toxic medicines. To date, the allosteric drugs prediction is a state-of-the-art topic in rational structure-based computational design. In this work a simulation strategy was developed for computational discovery of allosteric inhibitors, and it was applied for or cruzain, a promising target and the major cysteine protease of T. cruzi. Molecular dynamics simulations, binding free energy calculations and network-based modelling of residue interactions were combined to characterize and compare molecular distinctive features of the apo form and the cruzain-allosteric inhibitor complexes. By using geometry-based detection on trajectory snapshots we determined the existence of two main allosteric sites suitable for drug targeting. The results suggest dissimilar mechanism exerted by the same allosteric site when binding different potential allosteric inhibitors. Finally, we identified the residues involved in suboptimal paths linking the identified site and the orthosteric site. The present study constitutes the first approximation for designing cruzain allosteric inhibitors and may serve for future pharmacological intervention. These findings are particularly relevant for the design of allosteric modulators of papain-like cysteine proteases. / CAPES: 031/2013

Non-steroidal anti-inflammatory drugs (NSAIDs) are one of the most commonly used classes of drugs. They target the cyclooxygenases (COX) 1 and 2 to reduce the physiological responses of pain, fever, and inflammation. Due to their role in inducing angiogenesis, COX proteins have also been identified as targets in cancer therapies. In this thesis, I describe computational protocols of molecular docking, molecular dynamics simulations and free energy calculations. These methods were used in this thesis to determine structure-activity relationships of a diverse set of NSAIDs in binding to their target proteins COX-1 and 2. Binding affinities were calculated and used to predict the binding modes. Based on combinations of molecular dynamics simulations and free energy calculations, binding mechanisms of sub-classes of NSAIDs were also proposed. Two stable conformations of COX were probed to understand how they affect inhibitor affinities. Finally, a brief discussion on selectivity towards either COX isoform is discussed. These results will be useful in future de novo design and testing of third-generation NSAIDs.

Accurate predictions of binding free energies from computer simulations are an invaluable resource for understanding biochemical processes and drug action. The primary aim of the work described in the thesis was to predict and understand ligand binding to several proteins of major pharmaceutical importance using computational methods. We report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 G-protein coupled receptor and a series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Site-directed mutagenesis, homology modelling and docking were further used to characterize agonist binding to the human neuropeptide Y2 receptor, which is important in feeding behavior and an obesity drug target.  In a separate project, homology modelling was also used for rationalization of mutagenesis data for an integron integrase involved in antibiotic resistance. Blockade of the hERG potassium channel by various drug-like compounds, potentially causing serious cardiac side effects, is a major problem in drug development. We have used a homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations are in good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships with implications for design of new compounds. Docking, scoring, molecular dynamics, and the linear interaction energy method were also used to predict binding modes and affinities for a large set of inhibitors to HIV-1 reverse transcriptase. Good agreement with experiment was found and the work provides a validation of the methodology as a powerful tool in structure-based drug design. It is also easily scalable for higher throughput of compounds.

<p>The ability to accurately predict binding free energies from computer simulations is an invaluable resource in understanding biochemical processes and drug action. Several methods based on microscopic molecular dynamics simulations exist, and in this thesis the validation, application, and development of the linear interaction energy (LIE) method is presented.</p><p>For a test case of several hydrophobic ligands binding to P450cam it is found that the LIE parameters do not change when simulations are performed with three different force fields. The nonpolar contribution to binding of these ligands is best reproduced with a constant offset and a previously determined scaling of the van der Waals interactions.</p><p>A new methodology for prediction of binding free energies of protein-protein complexes is investigated and found to give excellent agreement with experimental results. In order to reproduce the nonpolar contribution to binding, a different scaling of the van der Waals interactions is neccesary (compared to small ligand binding) and found to be, in part, due to an electrostatic preorganization effect not present when binding small ligands.</p><p>A new treatment of the electrostatic contribution to binding is also proposed. In this new scheme, the chemical makeup of the ligand determines the scaling of the electrostatic ligand interaction energies. These scaling factors are calibrated using the electrostatic contribution to hydration free energies and proposed to be applicable to ligand binding.</p><p>The issue of codon-anticodon recognition on the ribosome is adressed using LIE. The calculated binding free energies are in excellent agreement with experimental results, and further predict that the Leu2 anticodon stem loop is about 10 times more stable than the Ser stem loop in complex with a ribosome loaded with the Phe UUU codon. The simulations also support the previously suggested roles of A1492, A1493, and G530 in the codon-anticodon recognition process.</p>

The ability to accurately predict binding free energies from computer simulations is an invaluable resource in understanding biochemical processes and drug action. Several methods based on microscopic molecular dynamics simulations exist, and in this thesis the validation, application, and development of the linear interaction energy (LIE) method is presented. For a test case of several hydrophobic ligands binding to P450cam it is found that the LIE parameters do not change when simulations are performed with three different force fields. The nonpolar contribution to binding of these ligands is best reproduced with a constant offset and a previously determined scaling of the van der Waals interactions. A new methodology for prediction of binding free energies of protein-protein complexes is investigated and found to give excellent agreement with experimental results. In order to reproduce the nonpolar contribution to binding, a different scaling of the van der Waals interactions is neccesary (compared to small ligand binding) and found to be, in part, due to an electrostatic preorganization effect not present when binding small ligands. A new treatment of the electrostatic contribution to binding is also proposed. In this new scheme, the chemical makeup of the ligand determines the scaling of the electrostatic ligand interaction energies. These scaling factors are calibrated using the electrostatic contribution to hydration free energies and proposed to be applicable to ligand binding. The issue of codon-anticodon recognition on the ribosome is adressed using LIE. The calculated binding free energies are in excellent agreement with experimental results, and further predict that the Leu2 anticodon stem loop is about 10 times more stable than the Ser stem loop in complex with a ribosome loaded with the Phe UUU codon. The simulations also support the previously suggested roles of A1492, A1493, and G530 in the codon-anticodon recognition process.

Over the last few decades, computer simulation techniques have been established as an essential tool for understanding biochemical processes. This thesis deals mainly with the application of free energy calculations to ribosomal complexes and a cardiac ion channel. The linear interaction energy (LIE) method is used to explore the energetic properties of the essential process of codon–anticodon recognition on the ribosome. The calculations show the structural and energetic consequences and effects of first, second, and third position mismatches in the ribosomal decoding center. Recognition of stop codons by ribosomal termination complexes is fundamentally different from sense codon recognition. Free energy perturbation simulations are used to study the detailed energetics of stop codon recognition by the bacterial ribosomal release factors RF1 and RF2. The calculations explain the vastly different responses to third codon position A to G substitutions by RF1 and RF2. Also, previously unknown highly specific water interactions are identified. The GGQ loop of ribosomal RFs is essential for its hydrolytic activity and contains a universally methylated glutamine residue. The structural effect of this methylation is investigated. The results strongly suggest that the methylation has no effect on the intrinsic conformation of the GGQ loop, and, thus, that its sole purpose is to enhance interactions in the ribosomal termination complex. A first microscopic, atomic level, analysis of blocker binding to the pharmaceutically interesting potassium ion channel Kv1.5 is presented. A previously unknown uniform binding mode is identified, and experimental binding data is accurately reproduced. Furthermore, problems associated with pharmacophore models based on minimized gas phase ligand conformations are highlighted. Generalized Born and Poisson–Boltzmann continuum models are incorporated into the LIE method to enable implicit treatment of solvent, in an effort to improve speed and convergence. The methods are evaluated and validated using a set of plasmepsin II inhibitors.

Biochemical processes all involve associations and dissociations of chemical entities. Understanding these is of substantial importance for many modern pharmaceutical applications. In this thesis, longstanding problems with regard to ligand binding are treated with computational methods, applied to proteins of key pharmaceutical importance. Homology modeling, docking, molecular dynamics simulations and free-energy calculations are used here for quantitative characterization of ligand binding to proteins. By combining computational tools, valuable contributions have been made for pharmaceutically relevant areas: a neglected tropical disease, an ion channel anti-drug-target, and GPCR drug-targets. We report three compounds inhibiting cruzain, the main cysteine protease of the protozoa causing Chagas’ disease. The compounds were found through an extensive virtual screening study and validated with experimental enzymatic assays. The compounds inhibit the enzyme in the μM-range and are therefore valuable in further lead optimization studies. A high-resolution crystal structure of the BRICHOS domain is reported, together with molecular dynamics simulations and hydrogen-deuterium exchange mass spectrometry studies. This work revealed a plausible mechanism for how the chaperone activity of the domain may operate. Rationalization of structure-activity relationships for a set of analogous blockers of the hERG potassium channel is given. A homology model of the ion channel was used for docking compounds and molecular dynamics simulations together with the linear interaction energy method employed for calculating the binding free-energies. The three-dimensional coordinates of two GPCRs, 5HT1B and 5HT2B, were derived from homology modeling and evaluated in the GPCR Dock 2013 assessment. Our models were in good correlation with the experimental structures and all of them placed among the top quarter of all models assessed.  Finally, a computational method, based on molecular dynamics free-energy calculations, for performing alanine scanning was validated with the A2A adenosine receptor bound to either agonist or antagonist. The calculated binding free-energies were found to be in good agreement with experimental data and the method was subsequently extended to non-alanine mutations. With extensive experimental mutation data, this scheme is a valuable tool for quantitative understanding of ligand binding and can ultimately be used for structure-based drug design.

Molecular dynamics (MD) simulations were used to investigate the structural basis for the functions of three proteins: Fc(gamma) receptor III (CD16), von Willebrand factor (VWF), and integrin. CD16, a heavily glycosylated protein expressed on human immune cells, plays a crucial role in immune defense by linking antibody-antigen complexes with cellular effector functions. Glycosylation of CD16 decreases its affinity for IgG. MD simulations were run for CD16-IgG Fc complexes with or without an N-glycan on CD16. The two simulated complexes show different conformations. Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) approach was used to calculate the binding free energy of the CD16-IgG Fc complexes. The calculated binding free energy helped to identify critical residues. VWF, a multimeric multidomain glycoprotein, initiates platelet adhesion at the sites of vascular injury. A specific VWF metalloprotease, A Disintegrin And Metalloprotease with ThromboSpondin motifs member 13 (ADAMTS-13), cleaves the Tyr1605-Met1606 bond in the VWF A2 domain to generate the full spectrum of plasma VWF species. Shear stress or denaturants assist VWF cleavage by ADAMTS-13 due to the unfolding of A2. MD was used to simulate the unfolding processes of A2 under force or high temperature. The beta-strands of A2 were pulled out sequentially by force, during which the cleavage site changed in steps from the fully buried state to the fully exposed state. Thermal unfolding follows a very different pathway. Integrins are adhesion molecules mediating cell-cell, cell-extracellular matrix, and cell-pathogen interactions. Experiments suggest that integrins can undergo a large-scale change from a bent to an extended conformation, associating with a transition from low to high affinity states, i.e., integrin activation. Steered MD was utilized to simulate the bent-to-extended conformational transition in time of aVb3 integrin. The integrin was observed to change smoothly from the bent to the extended conformation. One major energy barrier was overcome, corresponding to the disruption of the interactions at Hybrid/EGF4/bTD interfaces. A partially extended conformation tends to bend back while a fully extended conformation is stabilized by the coordination of Asp457 with Ca2+ at alpha-genu. Unbending with separated legs overcomes more energy barriers.