Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization. File list (2) download file view on ChemRxiv preprint_manuscript_raman_etal.pdf (2.16 MiB) download file view on ChemRxiv raman_etal_Supporting_Info.pdf (572.82 KiB)

To elucidate the involvement of individual and inter-related pathological factors [i.e., amyloid-β (Aβ), metals, and oxidative stress] in the pathogenesis of Alzheimer’s disease (AD), chemical tools have been developed. Characteristics required for such tool construction, however, have not been clearly identified; thus, the optimization of available tools or new design has been limited. Here, key structural properties and mechanisms that can determine tools’ regulatory reactivities with multiple pathogenic features found in AD are reported. A series of small molecules was built up through rational structural selection and variations onto the framework of a tool useful for in vitro and in vivo metal–Aβ investigation. Variations include: (i) location and number of an Aβ interacting moiety; (ii) metal binding site; and (iii) denticity and structural flexibility. Detailed biochemical, biophysical, and computational studies were able to provide a foundation of how to originate molecular formulas to devise chemical tools capable of controlling the reactivities of various pathological components through distinct mechanisms. Overall, this multidisciplinary investigation illustrates a structure–mechanism-based strategy of tool invention for such a complicated brain disease.

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CONSPECTUS: The selective hydrolysis of a peptide or amide bond (-(O═)C-NH-) by a synthetic metallopeptidase is required in a wide range of biological, biotechnological, and industrial applications. In nature, highly specialized enzymes known as proteases and peptidases are used to accomplish this daunting task. Currently, many peptide bond cleaving enzymes and synthetic reagents have been utilized to achieve efficient peptide hydrolysis. However, they possess some serious limitations. To overcome these inadequacies, a variety of metal complexes have been developed that mimic the activities of natural enzymes (metallopeptidases). However, in comparison to metallopeptidases, the hydrolytic reactions facilitated by their existing synthetic analogues are considerably slower and occur with lower catalytic turnover. This could be due to the following reasons: (1) they lack chemical properties of amino acid residues found within enzyme active sites; (2) they contain a higher metal coordination number compared with naturally occurring enzymes; and (3) they do not have access to second coordination shell residues that provide substantial rate enhancements in enzymes. Additionally, the critical structural and mechanistic information required for the development of the next generation of synthetic metallopeptidases cannot be readily obtained through existing experimental techniques. This is because most experimental techniques cannot follow the individual chemical steps in the catalytic cycle due to the fast rate of enzymes. They are also limited by the fact that the diamagnetic d(10) Zn(II) center is silent to electronic, electron spin resonance, and (67)Zn NMR spectroscopies. Therefore, we have employed molecular dynamics (MD), quantum mechanics (QM), and hybrid quantum mechanics/molecular mechanics (QM/MM) techniques to derive this information. In particular, the role of the metal ions, ligands, and microenvironment in the functioning of mono- and binuclear metal center containing enzymes such as insulin degrading enzyme (IDE) and bovine lens leucine aminopeptidase (BILAP), respectively, and their synthetic analogues have been investigated. Our results suggested that in the functioning of IDE, the chemical nature of the peptide bond played a role in the energetics of the reaction and the peptide bond cleavage occurred in the rate-limiting step of the mechanism. In the cocatalytic mechanism used by BILAP, one metal center polarized the scissile peptide bond through the formation of a bond between the metal and the carbonyl group of the substrate, while the second metal center delivered the hydroxyl nucleophile. The Zn(N3) [Zn(His, His, His)] core of matrix metalloproteinase was better than the Zn(N2O) [Zn(His, His, Glu)] core of IDE for peptide hydrolysis. Due to the synergistic interaction between the two metal centers, the binuclear metal center containing Pd2(μ-OH)([18]aneN6)](4+) complex was found to be ∼100 times faster than the mononuclear [Pd(H2O)4](2+) complex. A successful small-molecule synthetic analogue of a ...

In this combined experimental (deep ultraviolet resonance Raman (DUVRR) spectroscopy and atomic force microscopy (AFM)) and theoretical (molecular dynamics (MD) simulations and stress–strain (SS)) study, the structural and mechanical properties of amyloid beta (Aβ40) fibrils have been investigated. The DUVRR spectroscopy and AFM experiments confirmed the formation of linear, unbranched and β-sheet rich fibrils. The fibrils (Aβ40)n, formed using n monomers, were equilibrated using all-atom MD simulations. The structural properties such as β-sheet character, twist, interstrand distance, and periodicity of these fibrils were found to be in agreement with experimental measurements. Furthermore, Young’s modulus (Y) = 4.2 GPa computed using SS calculations was supported by measured values of 1.79 ± 0.41 and 3.2 ± 0.8 GPa provided by two separate AFM experiments. These results revealed size dependence of structural and material properties of amyloid fibrils and show the utility of such combined experimental and theoretical studies in the design of precisely engineered biomaterials.