Simple models of protein folding and of non--conventional drug design

While all the information required for the folding of a protein is contained in its amino acid sequence, one has not yet learned how to extract this information to predict the three--dimensional, biologically active, native conformation of a protein whose sequence is known. Using insight obtained from simple model simulations of the folding of proteins, in particular of the fact that this phenomenon is essentially controlled by conserved (native) contacts among (few) strongly interacting ("hot"), as a rule hydrophobic, amino acids, which also stabilize local elementary structures (LES, hidden, incipient secondary structures like $\alpha$--helices and $\beta$--sheets) formed early in the folding process and leading to the postcritical folding nucleus (i.e., the minimum set of native contacts which bring the system pass beyond the highest free--energy barrier found in the whole folding process) it is possible to work out a succesful strategy for reading the native structure of designed proteins from the knowledge of only their amino acid sequence and of the contact energies among the amino acids. Because LES have undergone millions of years of evolution to selectively dock to their complementary structures, small peptides made out of the same amino acids as the LES are expected to selectively attach to the newly expressed (unfolded) protein and inhibit its folding, or to the native (fluctuating) native conformation and denaturate it. These peptides, or their mimetic molecules, can thus be used as effective non--conventional drugs to those already existing (and directed at neutralizing the active site of enzymes), displaying the advantage of not suffering from the uprise of resistance

SCREENING INTERACTIONS BETWEEN PROTEINS AND DISORDERED PEPTIDES BY A NOVEL COMPUTATIONAL METHOD

Concerted interactions between proteins in cells form the basis of most biological processes. Biophysicists study protein–protein association by measuring thermodynamic and kinetic properties. Naively, strong binding affinity should be preferred in protein–protein binding to conduct certain biological functions. However, evidence shows that regulatory interactions, such as those between adapter proteins and intrinsically disordered proteins, communicate via low affinity but high complementarity interactions. PDZ domains are one class of adapters that bind linear disordered peptides, which play key roles in signaling pathways. The misregulation of these signals has been implicated in the progression of human cancers. To understand the underlying mechanism of protein-peptide binding interactions and to predict new interactions, in this thesis I have developed: (a) a unique biophysical-derived model to estimate their binding free energy; (b) a novel semi-flexible structure-based method to dock disordered peptides to PDZ domains; (c) predictions of the peptide binding landscape; and, (d) an automated algorithm and web-interface to predict the likelihood that a given linear sequence of amino acids binds to a specific PDZ domain. The docking method, PepDock, takes a peptide sequence and a PDZ protein structure as input, and outputs docked conformations and their corresponding binding affinity estimation, including their optimal free energy pathway. We have applied PepDock to screen several PDZ protein domains. The results not only validated the capabilities of PepDock to accurately discriminate interactions, but also explored the underlying binding mechanism. Specifically, I showed that interactions followed downhill free energy pathways, reconciling a relatively fast association mechanism of intrinsically disordered peptides. The pathways are such that initially the peptide’s C-terminal motif binds non-specifically, forming a weak intermediate, whereas specific binding is achieved only by a subsequent network of contacts (7–9 residues in total). This mechanism allows peptides to quickly probe PDZ domains, rapidly releasing those that do not attain sufficient affinity during binding. Further kinetic analysis indicates that disorder enhanced the specificity of promiscuous interactions between proteins and peptides, while achieving association rates comparable to interactions between ordered proteins

Simulating Molecular Mechanisms Of the Mdm2-Mediated Regulatory Interactions: a Conformational Selection Model Of the Mdm2 Lid Dynamics

Diversity and complexity of MDM2 mechanisms govern its principal function as the cellular antagonist of the p53 tumor suppressor. Structural and biophysical studies have demonstrated that MDM2 binding could be regulated by the dynamics of a pseudo-substrate lid motif. However, these experiments and subsequent computational studies have produced conflicting mechanistic models of MDM2 function and dynamics. We propose a unifying conformational selection model that can reconcile experimental findings and reveal a fundamental role of the lid as a dynamic regulator of MDM2-mediated binding. In this work, structure, dynamics and energetics of apo-MDM2 are studied as a function of posttranslational modifications and length of the lid. We found that the dynamic equilibrium between closed and semi-closed lid forms may be a fundamental characteristic of MDM2 regulatory interactions, which can be modulated by phosphorylation, phosphomimetic mutation as well as by the lid size. Our results revealed that these factors may regulate p53-MDM2 binding by fine-tuning the thermodynamic equilibrium between preexisting conformational states of apo-MDM2. In agreement with NMR studies, the effect of phosphorylation on MDM2 interactions was more pronounced with the truncated lid variant that favored the thermodynamically dominant closed form. The phosphomimetic mutation S17D may alter the lid dynamics by shifting the thermodynamic equilibrium towards the ensemble of semi-closed conformations. The dominant semi-closed lid form and weakened dependence on the phosphorylation seen in simulations with the complete lid can provide a rationale for binding of small p53-based mimetics and inhibitors without a direct competition with the lid dynamics. The results suggested that a conformational selection model of preexisting MDM2 states may provide a robust theoretical framework for understanding MDM2 dynamics. Probing biological functions and mechanisms of MDM2 regulation would require further integration of computational and experimental studies and may help to guide drug design of novel anti-cancer therapeutics

Enumeration, conformation sampling and population of libraries of peptide macrocycles for the search of chemotherapeutic cardioprotection agents

Peptides are uniquely endowed with features that allow them to perturb previously difficult to drug biomolecular targets. Peptide macrocycles in particular have seen a flurry of recent interest due to their enhanced bioavailability, tunability and specificity. Although these properties make them attractive hit-candidates in early stage drug discovery, knowing which peptides to pursue is non‐trivial due to the magnitude of the peptide sequence space. Computational screening approaches show promise in their ability to address the size of this search space but suffer from their inability to accurately interrogate the conformational landscape of peptide macrocycles. We developed an in‐silico compound enumerator that was tasked with populating a conformationally laden peptide virtual library. This library was then used in the search for cardio‐protective agents (that may be administered, reducing tissue damage during reperfusion after ischemia (heart attacks)). Our enumerator successfully generated a library of 15.2 billion compounds, requiring the use of compression algorithms, conformational sampling protocols and management of aggregated compute resources in the context of a local cluster. In the absence of experimental biophysical data, we performed biased sampling during alchemical molecular dynamics simulations in order to observe cyclophilin‐D perturbation by cyclosporine A and its mitochondrial targeted analogue. Reliable intermediate state averaging through a WHAM analysis of the biased dynamic pulling simulations confirmed that the cardio‐protective activity of cyclosporine A was due to its mitochondrial targeting. Paralleltempered solution molecular dynamics in combination with efficient clustering isolated the essential dynamics of a cyclic peptide scaffold. The rapid enumeration of skeletons from these essential dynamics gave rise to a conformation laden virtual library of all the 15.2 Billion unique cyclic peptides (given the limits on peptide sequence imposed). Analysis of this library showed the exact extent of physicochemical properties covered, relative to the bare scaffold precursor. Molecular docking of a subset of the virtual library against cyclophilin‐D showed significant improvements in affinity to the target (relative to cyclosporine A). The conformation laden virtual library, accessed by our methodology, provided derivatives that were able to make many interactions per peptide with the cyclophilin‐D target. Machine learning methods showed promise in the training of Support Vector Machines for synthetic feasibility prediction for this library. The synergy between enumeration and conformational sampling greatly improves the performance of this library during virtual screening, even when only a subset is used

A Computational Study of Procyanidin Binding to Histatin 5 and Thermodynamic Properties of Hofmeister-Anion Binding to a Hydrophobic Cavitand

Various studies suggest tannins act as antioxidants, anticarcinogens, cardio-protectants, anti-inflammatory agents, and antimicrobials. However, more investigation is needed to examine the bioavailability of tannins. Tannins bind to salivary peptides by hydrophilic and hydrophobic mechanisms. Electrospray Ionization Mass Spectrometry (ESI-MS) has been used to assess both hydrophilic and hydrophobic components of protein complexes. ESI-MS could potentially be an effective tool for screening the bioavailability of tannins. Weaker binding tannins are predicted to be more highly absorbed by the body, and should therefore exhibit greater bioavailability. Rannulu and Cole have used ESI-MS to measure binding affinities of procyanidin tannin stereoisomers for salivary peptides in aqueous solution. The condensed tannins procyanidin B1, B2, B3, and B4 demonstrated significantly different binding affinities (binding strengths) for the Histatin 5 salivary peptide. The procyanidin-Histatin 5 binding mechanisms in the ESI-MS experiments by Rannulu and Cole were investigated using the FRED docking program combined with molecular dynamics optimization in the AMBER software suite. The simulations suggest residual liquid-phase binding interactions in procyanidin-Histatin 5 complexes are maintained in the gas phase under conditions resembling those in ESI-MS experiments, though the gas-phase interaction energies were enhanced. Increased hydrogen bonding and decreased π-π stacking interactions were also detected in gas versus liquid-phase procyanidin-Histatin 5 complexes. In addition, simulation results suggest multiple conformations of procyanidins bind Histatin 5 at several sites and procyanidin binding does not fix the Histatin 5 peptide backbone. The simulations agree with previous studies which indicate aromatic Histatin 5 residues are responsible for procyanidin-Histatin 5 binding and tannins can bind salivary peptides in multiple conformations. The effects of Hofmeister salts on complexation of an amphiphilic guest adamantane carboxylic acid to the hydrophobic surface of a deep-cavity cavitand have been investigated by Gibb et al. Adamantane-cavitand binding was found to be largely enthalpically driven, though adamantane binding in the presence of the salting-in anions perchlorate and thiocyanate was entropically driven. Gibb et al. also found that perchlorate-cavitand binding was enthalpically favorable, though entropically unfavorable. Potential-of-mean-force (PMF) calculations for perchlorate-cavitand and thiocyanate-cavitand complexation were performed using umbrella sampling with a modified version of the sander module from the Amber 9 software suite to further investigate the thermodynamic properties of Hofmeister-anion binding to the hydrophobic cavitand. The enthalpy for salting-in anion-cavitand complexation was calculated from the potential energy difference between the bound and unbound state (the potential energy of binding) along with the entropy. The binding entropy and enthalpy were also calculated using a finite difference approximation to the entropy. The enthalpy for perchlorate-cavitand complexation calculated from the binding energy and the finite difference approximation to the entropy was favorable with an unfavorable entropy. The binding enthalpy and entropy for thiocyanate-cavitand complexation calculated from the binding energy and finite difference approximation to the entropy were unfavorable and favorable, respectively, perhaps due to a classical hydrophobic effect. The orientation of the ligand, the number of water molecules displaced from the ligand and cavitand upon complexation, and the number of nearest-neighbor atom contacts between the ligand and the cavitand were also calculated. Additionally, the energetics of various interactions involved in salting-in anion-cavitand complexation including the anion-cavitand, anion-water, cavitand-water, and water-water interactions were assessed, though the data were inconclusive