Theoretical design of a specific DNA-Zinc-finger protein interaction with semi-empirical quantum chemical methods

Biomolecular Binding at Aqueous Interfaces of Langmuir Monolayers of Bioconjugated Amphiphilic Mesogenic Molecules: A Molecular Dynamics Study

We report a molecular dynamics (MD) simulation study of protein binding at the aqueous-liquid crystal (LC) interfaces of bioconjugated mesogenic molecules. As a simple model of these interfaces, we use monolayers composed of biotin-conjugated or biotin-free amphiphilic mesogenic molecules and streptavidin in water. The all-atom MD simulations reveal that the binding of streptavidin to the biotin mesogenic monolayer is significantly stronger than that to biotin-free mesogenic monolayers. Although specific protein binding marginally increases the overall orientational order and the tilt of the biotin-conjugated mesogenic molecules of the monolayer, significant changes in tilt were observed near the bound protein (in contrast to the protein interaction with the monolayer without biotin). We also observe that specific protein binding changes the dynamic properties of the mesogens within the monolayer (e.g., lateral diffusion coefficients) and associated water. Overall, these MD simulations advance our understanding of the molecular-level phenomena involved in the binding of biomolecules and subsequent dynamic changes at the aqueous-LC interfaces. These results provide guidance to future molecular-level designs of biofunctional LC interfaces.

SQM/COSMO Scoring Function: Reliable Quantum-Mechanical Tool for Sampling and Ranking in Structure-Based Drug Design

Quantum mechanical (QM) methods have been gaining importance in structure-based drug design where a reliable description of protein-ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM-based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM-based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof-of-concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure-based drug design.

Implementing QM in docking calculations: is it a waste of computational time?

The greatest challenge in molecular docking (MD) is the deficiency of scoring functions (SFs), which limits their reliability. SFs are too simplified to represent the true features of the complex free energy of protein-ligand interactions. Investigations of docking functions have traded accuracy for speed through the use of approximations and simplifications. Consequently, there has been an increase in the popularity of quantum-mechanical (QM)-based methods as reference points for the development of fast, reliable, valuable, yet inexpensive, tools. As we discuss here, one significant QM-based parameter used to predict docking is the accuracy of atomic partial charges, which is strongly related to the accuracy of the SF prediction.

Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

Semiempirical (SE) methods can be derived from either Hartree-Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems.

Enhanced semiempirical QM methods for biomolecular interactions

Recent successes and failures of the application of 'enhanced' semiempirical QM (SQM) methods are reviewed in the light of the benefits and backdraws of adding dispersion (D) and hydrogen-bond (H) correction terms. We find that the accuracy of SQM-DH methods for non-covalent interactions is very often reported to be comparable to dispersion-corrected density functional theory (DFT-D), while computation times are about three orders of magnitude lower. SQM-DH methods thus open up a possibility to simulate realistically large model systems for problems both in life and materials science with comparably high accuracy.

Design of a colicin E7 based chimeric zinc-finger nuclease

Colicin E7 is a natural bacterial toxin. Its nuclease domain (NColE7) enters the target cell and kills it by digesting the nucleic acids. The HNH-motif as the catalytic centre of NColE7 at the C-terminus requires the positively charged N-terminal loop for the nuclease activity-offering opportunities for allosteric control in a NColE7-based artificial nuclease. Accordingly, four novel zinc finger nucleases were designed by computational methods exploiting the special structural features of NColE7. The constructed models were subjected to MD simulations. The comparison of structural stability and functional aspects showed that these models may function as safely controlled artificial nucleases. This study was complemented by random mutagenesis experiments identifying potentially important residues for NColE7 function outside the catalytic region.

Quantum mechanics-based scoring rationalizes the irreversible inactivation of parasitic Schistosoma mansoni cysteine peptidase by vinyl sulfone inhibitors

The quantum mechanics (QM)-based scoring function that we previously developed for the description of noncovalent binding in protein-ligand complexes has been modified and extended to treat covalent binding of inhibitory ligands. The enhancements are (i) the description of the covalent bond breakage and formation using hybrid QM/semiempirical QM (QM/SQM) restrained optimizations and (ii) the addition of the new ΔG(cov)' term to the noncovalent score, describing the "free" energy difference between the covalent and noncovalent complexes. This enhanced QM-based scoring function is applied to a series of 20 vinyl sulfone-based inhibitory compounds inactivating the cysteine peptidase cathepsin B1 of the Schistosoma mansoni parasite (SmCB1). The available X-ray structure of the SmCB1 in complex with a potent vinyl sulfone inhibitor K11017 is used as a template to build the other covalently bound complexes and to model the derived noncovalent complexes. We present the correlation of the covalent score and its constituents with the experimental binding data. Four outliers are identified. They contain bulky R1' substituents structurally divergent from the template, which might induce larger protein rearrangements than could be accurately modeled. In summary, we propose a new computational approach and an optimal protocol for the rapid evaluation and prospective design of covalent inhibitors with a conserved binding mode.

Towards artificial metallonucleases for gene therapy: recent advances and new perspectives

The process of DNA targeting or repair of mutated genes within the cell, induced by specifically positioned double-strand cleavage of DNA near the mutated sequence, can be applied for gene therapy of monogenic diseases. For this purpose, highly specific artificial metallonucleases are developed. They are expected to be important future tools of modern genetics. The present state of art and strategies of research are summarized, including protein engineering and artificial ‘chemical’ nucleases. From the results, we learn about the basic role of the metal ions and the various ligands, and about the DNA binding and cleavage mechanism. The results collected provide useful guidance for engineering highly controlled enzymes for use in gene therapy.