Accurate Binding Free Energy Predictions in Fragment Optimization.

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Ground state spectroscopy of hydroxyquinolines: evidence for the formation of protonated species in water-rich dioxane-water mixtures.

We have recently used 6-, 7-, and 8-hydroxyquinolines (HQs) as fluorescent probes to study the binding mechanism in one of the drug binding sites of human serum albumin. In the present work we study the absorption spectra of the HQ molecules in neat and binary mixtures of dioxane and water in order to identify the different tautomeric species in the ground state. This study should help in identifying the environment in nanocavities of macromolecules when HQs are used as local reporters. The enol form is shown to be the only tautomer for the three HQs in dioxane and water, with the exception of 7HQ in which both the enol and the zwitterion tautomers exist in equilibrium in water. The results are confirmed by the density functional theory (DFT) calculations using the B3LYP method with a 6-311++G(2d,p) basis set. In water-rich dioxane mixtures, all HQs are protonated. The results were confirmed by comparing the absorption spectra in binary solvents with those in acidic and basic aqueous solutions, and by DFT calculations of the Franck-Condon S1 ← S0 transitions. The number of water molecules solvating the polar sites in each HQ molecule was estimated from the spectral change in the binary solvent mixtures, and structures were calculated by DFT. Mapping the water density around the polar sites in each HQ using molecular dynamics (MD) simulations shows well-defined hydrogen bonds around the N-heteroatom in each HQ molecule. Water density is only well-defined around the hydroxyl group in 8HQ. The MD simulations indicate free rotation of the OH group in 6HQ and 7HQ, and the stability of the cis-isomer in 8HQ. The results point to the unique spectral signatures of 7HQ in water which make this molecule a potential probe to detect the presence of water in nanocavities of macromolecules, and to the ability of the three HQs to detect acidic media in binding sites.

Acylguanidine Beta Secretase 1 Inhibitors: A Combined Experimental and Free Energy Perturbation Study.

A series of acylguanidine beta secretase 1 (BACE1) inhibitors with modified scaffold and P3 pocket substituent was synthesized and studied with free energy perturbation (FEP) calculations. The resulting molecules showed potencies in enzymatic BACE1 inhibition assays up to 1 nM. The correlation between the predicted activity from the FEP calculations and the experimental activity was good for the P3 pocket substituents. The average mean unsigned error (MUE) between prediction and experiment was 0.68 ± 0.17 kcal/mol for the default 5 ns lambda window simulation time improving to 0.35 ± 0.13 kcal/mol for 40 ns. FEP calculations for the P2' pocket substituents on the same acylguanidine scaffold also showed good agreement with experiment and the results remained stable with repeated simulations and increased simulation time. It proved more difficult to use FEP calculations to study the scaffold modification from increasing 5 to 6 and 7 membered-rings. Although prediction and experiment were in agreement for short 2 ns simulations, as the simulation time increased the results diverged. This was improved by the use of a newly developed "Core Hopping FEP+" approach, which also showed improved stability in repeat calculations. The origins of these differences along with the value of repeat and longer simulation times are discussed. This work provides a further example of the use of FEP as a computational tool for molecular design.

A Water-Bridged Cysteine-Cysteine Redox Regulation Mechanism in Bacterial Protein Tyrosine Phosphatases.

The emergence of multidrug-resistant Mycobacterium tuberculosis (Mtb) strains highlights the need to develop more efficacious and potent drugs. However, this goal is dependent on a comprehensive understanding of Mtb virulence protein effectors at the molecular level. Here, we used a post-expression cysteine (Cys)-to-dehydrolanine (Dha) chemical editing strategy to identify a water-mediated motif that modulates accessibility of the protein tyrosine phosphatase A (PtpA) catalytic pocket. Importantly, this water-mediated Cys-Cys non-covalent motif is also present in the phosphatase SptpA from Staphylococcus aureus, which suggests a potentially preserved structural feature among bacterial tyrosine phosphatases. The identification of this structural water provides insight into the known resistance of Mtb PtpA to the oxidative conditions that prevail within an infected host macrophage. This strategy could be applied to extend the understanding of the dynamics and function(s) of proteins in their native state and ultimately aid in the design of small-molecule modulators.

Automated Transition State Search and Its Application to Diverse Types of Organic Reactions.

Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.

Pyrido[4,3-e][1,2,4]triazolo[4,3-a]pyrazines as Selective, Brain Penetrant Phosphodiesterase 2 (PDE2) Inhibitors.

A novel series of pyrido[4,3-e][1,2,4]triazolo[4,3-a]pyrazines is reported as potent PDE2/PDE10 inhibitors with drug-like properties. Selectivity for PDE2 was obtained by introducing a linear, lipophilic moiety on the meta-position of the phenyl ring pending from the triazole. The SAR and protein flexibility were explored with free energy perturbation calculations. Rat pharmacokinetic data and in vivo receptor occupancy data are given for two representative compounds 6 and 12.

Fragment orbital based description of charge transfer in peptides including backbone orbitals.

Charge transfer in peptides and proteins can occur on different pathways, depending on the energetic landscape as well as the coupling between the involved orbitals. Since details of the mechanism and pathways are difficult to access experimentally, different modeling strategies have been successfully applied to study these processes in the past. These can be based on a simple empirical pathway model, efficient tight binding type atomic orbital Hamiltonians or ab initio and density functional calculations. An interesting strategy, which allows an efficient calculations of charge transfer parameters, is based on a fragmentation of the system into functional units. While this works well for systems like DNA, where the charge transfer pathway is naturally divided into distinct molecular fragments, this is less obvious for charge transfer along peptide and protein backbones. In this work, we develop and access a strategy for an effective fragmentation approach, which allows one to compute electronic couplings for large systems along nanosecond time scale molecular dynamics trajectories. The new methodology is applied to a solvated peptide, for which charge transfer properties have been studied recently using an empirical pathway model. As could be expected, dynamical effects turn out to be important, which emphasizes the importance of using effective quantum approaches which allow for sufficient sampling. However, the computed rates are orders of magnitude smaller than experimentally determined, which indicates the shortcomings of present modeling approaches.

Binding of hydroxyquinoline probes to human serum albumin: combining molecular modeling and Förster's resonance energy transfer spectroscopy to understand flexible ligand binding.

Human serum albumin (HSA) is the most abundant protein in blood plasma. It has high relevance for the lipid metabolism, and its ability to bind a large variety of natural and pharmaceutical compounds makes it a crucial determinant of drug pharmaco-kinetics and -dynamics. The drug binding properties of HSA can be characterized by spectroscopic analysis of bound probe molecules. We have recently characterized the subdomain IIA binding site of HSA using three hydroxyquinoline derivatives. In this work, we extend our study by combining data from energy transfer experiments, ligand docking, and long molecular dynamics (MD) simulations. Multiple possible binding locations are found within the subdomain IIA site, and their solvent accessibility and interactions with ligands are analyzed in detail. Binding pockets appear well hydrated during simulations, with ligands in direct contact to water molecules at all times. Binding free energies in good agreement to experiment are calculated. The HSA apoprotein is found to exhibit significant conformational flexibility over 250 ns of simulation time, but individual domains remain structurally stable. Two rotamers of Trp214 were observed on a time scale longer than 50 ns in the MD simulations, supporting the experimental observation of two fluorescence lifetime components. The flexible protein structure and heterogeneous nature of its binding sites explain the ability of HSA to act as a versatile molecular transporter. The combination of experimental and computational molecular distance information allows the conclusion that hydroxyquinoline probes bind in a binding mode similar to the anticoagulant drug warfarin.

Charge transfer in E. coli DNA photolyase: understanding polarization and stabilization effects via QM/MM simulations.

We study fast hole transfer events in E. coli DNA photolyase, a key step in the photoactivation process, using a multiscale computational method that combines nonadiabatic propagation schemes and linear-scaling quantum chemical methods with molecular mechanics force fields. This scheme allows us to follow the time-dependent evolution of the electron hole in an unbiased fashion; that is, no assumptions about hole wave function localization, time scale separation, or adiabaticity of the process have to be made beforehand. DNA photolyase facilitates an efficient long-range charge transport between its flavin adenine dinucleotide (FAD) cofactor and the protein surface via a chain of evolutionary conserved Trp residues on the sub-nanosecond time scale despite the existence of multiple potential trap states. By including a large number of aromatic residues along the charge transfer pathway into the quantum description, we are able to identify the main pathway among alternative possible routes. The simulations show that charge transfer, which is extremely fast in this protein, occurs on the same time scale as the protein response to the electrostatic changes; that is, time-scale separation as often presupposed in charge transfer studies seems to be inappropriate for this system. Therefore, coupled equations of motion, which propagate electrons and nuclei simultaneously, appear to be necessary. The applied computational model is shown to capture the essentials of the reaction kinetics and thermodynamics while allowing direct simulations of charge transfer events on their natural time scale.

Charge transfer in model peptides: obtaining Marcus parameters from molecular simulation.

Charge transfer within and between biomolecules remains a highly active field of biophysics. Due to the complexities of real systems, model compounds are a useful alternative to study the mechanistic fundamentals of charge transfer. In recent years, such model experiments have been underpinned by molecular simulation methods as well. In this work, we study electron hole transfer in helical model peptides by means of molecular dynamics simulations. A theoretical framework to extract Marcus parameters of charge transfer from simulations is presented. We find that the peptides form stable helical structures with sequence dependent small deviations from ideal PPII helices. We identify direct exposure of charged side chains to solvent as a cause of high reorganization energies, significantly larger than typical for electron transfer in proteins. This, together with small direct couplings, makes long-range superexchange electron transport in this system very slow. In good agreement with experiment, direct transfer between the terminal amino acid side chains can be dicounted in favor of a two-step hopping process if appropriate bridging groups exist.