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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 set up, execute, and analyze multisite 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 data set 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, which 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 100 ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150 ns 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 multisite 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 the chemical space around a lead compound and thus are of utility in lead optimization.

When the electrostatic environment surrounding binding partners changes between unbound and bound states, the net uptake or release of a proton is possible by either binding partner. This process is pH-dependent in that the free energy required to uptake or release the proton varies with pH. This pH-dependence is typically not considered in conventional free energy methods where the use of fixed protonation states is the norm. In the present paper, we apply a simple two-step approach to calculate the pH-dependent binding free energy of a model cucubit[7]uril host/guest system. By use of λ-dynamics with an enhanced sampling protocol, adaptive landscape flattening, pKa shifts and reference binding free energies upon complexation were determined. This information enables the construction of pH-dependent binding profiles that accurately capture the pKa shifts and reproduce binding free energies at the different pH conditions that were observed experimentally. Our calculations illustrate a general framework for computing pH-dependent binding free energies but also point to some issues in modeling the molecular charge distributions within this series of molecules with CGenFF. However, by introducing some minor charge modifications to the CGenFF force field, we saw significant improvement in accuracy of the calculated pKa shifts.

Abstract: In this computational study, we have combined molecular docking and molecular dynamics (MD) simulation techniques to explore interactions of monomeric and aggregated forms of Alzheimer's amyloid beta (A[β.sub.40]) with [...]

In this study, mechanisms of hydrolysis of all four chemically diverse cleavage sites of human serum albumin (HSA) by [Zr(OH)(PW11O39)]4− (ZrK) have been investigated using the hybrid two‐layer QM/MM (ONIOM) method. These reactions have been proposed to occur through the following two mechanisms: internal attack (IA) and water assisted (WA). In both mechanisms, the cleavage of the peptide bond in the Cys392‐Glu393 site of HSA is predicted to occur in the rate‐limiting step of the mechanism. With the barrier of 27.5 kcal/mol for the hydrolysis of this site, the IA mechanism is found to be energetically more favorable than the WA mechanism (barrier = 31.6 kcal/mol). The energetics for the IA mechanism are in line with the experimentally measured values for the cleavage of a wide range of dipeptides. These calculations also suggest an energetic preference (Cys392‐Glu393, Ala257‐Asp258, Lys313‐Asp314, and Arg114‐Leu115) for the hydrolysis of all four sites of HSA. © 2018 Wiley Periodicals, Inc. Mechanisms for the hydrolysis of all four chemically distinct cleavage sites of human serum albumin (HSA) catalyzed by a Zr‐containing polyoxometalate [Zr(OH)(PW11O39)]4−. They are proposed using the hybrid two‐layer QM/MM (ONIOM) calculations. [ABSTRACT FROM AUTHOR]

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