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Protein engineering involves the design of known protein structures to introduce an improved or completely novel function. This is accomplished by either modifying the existing structure (i.e., redesign) to achieve an altered functionality or by introducing a completely new binding site. In this thesis computational modeling is first tested by altering the effector binding specificity of the bacterial transcriptional regulatory protein AraC to molecules other than L-arabinose. A systematic computational formulation was developed and employed to favor the binding of a targeted ligand while suppressing the binding energy of decoy molecules. Next we introduce a modified version of IPRO equipped with different implicit solvation modules to redesign Candida boidinii xylose reductase (CbXR) to use NADH as its cofactor by finding the optimal set of mutations in the CbXR binding pocket. Calculated cofactor binding energy was verified as a good surrogate to computationally drive cofactor alteration. We performed site-directed mutagenesis to redesign CbXR according to the designs predicted by IPRO. Experimental results for predicted mutants as well as control studies quantitatively demonstrated the value of using computations to guide protein redesign for altered cofactor usage. Finally we present the computational procedure OptGraft for placing a novel binding pocket onto a protein structure so as its geometry is minimally perturbed. This was accomplished by introducing a two-level procedure where we first identify where are the most appropriate locations to graft the new binding pocket into the protein fold by minimizing the departure from a set of geometric restraints using mixed-integer linear optimization. Upon identifying the suitable locations that can accommodate the new binding pocket CHARMM energy calculations were employed to identify what mutations in the neighboring residues, if any, are needed to ensure that the minimum energy conformation of the binding pocket conserves the desired geometry. OptGraft was successfully used to guide our experimental studies for transferring a calcium binding pocket from thermitase protein (PDB:1thm) into the first domain of CD2 protein (PDB:1hng).
One of the key goals in the postgenomic era is the elucidation of the mechanisms underlying the relationship between genotype and phenotype. In particular, understanding how human genetic and somatic variations are associated with diseases is still an open problem and its solution is a crucial issue for exploiting the possibilities offered by the modern sequencing techniques in the framework of precision and personalized medicine. The increasing amount of data generated by the sequencing initiatives calls for accurate and reliable computational approaches to predict the impact of mutations on the phenotype, and possibly for methods to correlate them with diseases. From the experimental point of view, disease-causing variants are supposed to directly affect protein function, protein stability as well as the kinetics and thermodynamics of protein-protein recognition, and robust validation at the molecular scale is necessary. This approach can be of invaluable help in facing new challenges such as the fast development of effective vaccines.
Since the dawn of recorded history, and probably even before, men and women have been grasping at the mechanisms by which they themselves exist. Only relatively recently, did this grasp yield anything of substance, and only within the last several decades did the proteins play a pivotal role in this existence. In this expose on the topic of protein structure some of the current issues in this scientific field are discussed. The aim is that a non-expert can gain some appreciation for the intricacies involved, and in the current state of affairs. The expert meanwhile, we hope, can gain a deeper understanding of the topic.
Proteins are fundamental components of life. Over the billions of years of evolution, proteins have evolved to perform certain functions better and faster or to achieve new functions in order to pursue the biological needs under diverse and changing conditions. The field of protein engineering is becoming a research domain of great importance. The interest of proteins with new or improved properties is increasing in health, nano/biotechnology and green chemistry.Computational Protein Design (CPD) plays a critical role in advancing the field of protein engineering and accelerating the delivery of novel proteins displaying high specificity, high efficiency and better stability. The CPD problem can be formalized as an optimization problem. Using an all-atom energy function and a reliable search method, CPD tries to identify amino acid sequences that fold into a target structure and ultimately perform a desired function. The traditional Single State Protein Design (SSD) contrasts with the increasing evidence that proteins do not remain in a unique conformational state but rather sample conformational ensembles. In this thesis we propose a MultiState Design (MSD) method which aims at alleviating SSD limitations by simultaneously considering several conformational states.In the second part of this thesis, MSD was applied on two projects that led to an experimental characterization and validation. These two projects concern two application domains: health and white biotechnologies. The first one targets GH11 Xylanases. To understand the molecular basis underlying its thermal stability and activity, Molecular Dynamics simulations were used and revealed useful characteristics to design this enzyme. This produced GH11 xylanases with improved thermal stability and catalytic activity.The second project concerns the design of a synthetic humanized nanobody scaffold. The resulting nanobody is highly expressed and shows suitable affinity with different CDR loops.
Protein Design: Methods and Applications presents the most up-to-date protein design and engineering strategies so that readers can undertake their own projects with a maximum chance of success. The authors present integrated computational approaches that require various degrees of computational complexity, and the major accomplishments that have been achieved in the design and structural characterization of helical peptides and proteins.
The aim this volume is to present the methods, challenges, software, and applications of this widespread and yet still evolving and maturing field. Computational Protein Design, the first book with this title, guides readers through computational protein design approaches, software and tailored solutions to specific case-study targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Protein Design aims to ensure successful results in the further study of this vital field.
Molecular modeling techniques have been widely used in drug discovery fields for rational drug design and compound screening. Now these techniques are used to model or mimic the behavior of molecules, and help us study formulation at the molecular level. Computational pharmaceutics enables us to understand the mechanism of drug delivery, and to develop new drug delivery systems. The book discusses the modeling of different drug delivery systems, including cyclodextrins, solid dispersions, polymorphism prediction, dendrimer-based delivery systems, surfactant-based micelle, polymeric drug delivery systems, liposome, protein/peptide formulations, non-viral gene delivery systems, drug-protein binding, silica nanoparticles, carbon nanotube-based drug delivery systems, diamond nanoparticles and layered double hydroxides (LDHs) drug delivery systems. Although there are a number of existing books about rational drug design with molecular modeling techniques, these techniques still look mysterious and daunting for pharmaceutical scientists. This book fills the gap between pharmaceutics and molecular modeling, and presents a systematic and overall introduction to computational pharmaceutics. It covers all introductory, advanced and specialist levels. It provides a totally different perspective to pharmaceutical scientists, and will greatly facilitate the development of pharmaceutics. It also helps computational chemists to look for the important questions in the drug delivery field. This book is included in the Advances in Pharmaceutical Technology book series.