Shuntaro Chiba

Evaluation of protein-ligand binding free energy focused on its entropic components.

The binding free energy for FK506‐binding protein‐ligand systems is evaluated as a sum of two entropic components, the water‐entropy gain, and the configurational‐entropy loss for the protein and ligand molecules upon the binding. The two entropic components are calculated using morphometric thermodynamics combined with a statistical‐mechanical theory for molecular liquids and the normal mode analysis, respectively. We find that there is an excellent correlation between the calculated and experimental values of the binding free energy. This result is compared with those of several other binding‐free energy calculation methods, including MM‐PB/SA. The binding can well be elucidated by competition of the two entropic components. Upon the protein‐ligand binding, the total volume available to the translational displacement of the coexisting water molecules increases, leading to an increase in the number of accessible configurations of the water. The water‐entropy gain, by which the binding is driven, originates primarily from this effect. This study sheds new light on the theoretical prediction of the protein‐ligand binding free energy.

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target.

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

ATP-induced conformational changes of nucleotide-binding domains in an ABC transporter. Importance of the water-mediated entropic force.

ATP binding cassette (ABC) proteins belong to a superfamily of active transporters. Recent experimental and computational studies have shown that binding of ATP to the nucleotide binding domains (NBDs) of ABC proteins drives the dimerization of NBDs, which, in turn, causes large conformational changes within the transmembrane domains (TMDs). To elucidate the active substrate transport mechanism of ABC proteins, it is first necessary to understand how the NBD dimerization is driven by ATP binding. In this study, we selected MalKs (NBDs of a maltose transporter) as a representative NBD and calculated the free-energy change upon dimerization using molecular mechanics calculations combined with a statistical thermodynamic theory of liquids, as well as a method to calculate the translational, rotational, and vibrational entropy change. This combined method is applied to a large number of snapshot structures obtained from molecular dynamics simulations containing explicit water molecules. The results suggest that the NBD dimerization proceeds with a large gain of water entropy when ATP molecules bind to the NBDs. The energetic gain arising from direct NBD-NBD interactions is canceled by the dehydration penalty and the configurational-entropy loss. ATP hydrolysis induces a loss of the shape complementarity between the NBDs, which leads to the dissociation of the dimer, due to a decrease in the water-entropy gain and an increase in the configurational-entropy loss. This interpretation of the NBD dimerization mechanism in concert with ATP, especially focused on the water-mediated entropy force, is potentially applicable to a wide variety of the ABC transporters.

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes

We propose a new iterative screening contest method to identify target protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-protein kinase Yes as an example target protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.

Kirkwood–Buff Integrals for Aqueous Urea Solutions Based upon the Quantum Chemical Electrostatic Potential and Interaction Energies

Cosolvents, such as urea, affect protein folding and binding, and the solubility of solutes. The modeling of cosolvents has been facilitated significantly by the rigorous Kirkwood-Buff (KB) theory of solutions, which can describe structural thermodynamics over the entire composition range of aqueous cosolvent mixtures based only on the solution density and the KB integrals (KBIs), i.e., the net excess radial distribution functions from the bulk. Using KBIs to describe solution thermodynamics has given rise to a clear guideline that an accurate prediction of KBIs is equivalent to accurate modeling of cosolvents. Taking urea as an example, here we demonstrate that an improvement in the prediction of KBIs comes from an improved reproduction of high-level quantum chemical (QC) electrostatic potential and molecular pairwise interaction energies. This rational approach to the improvement of the KBI prediction stems from a comparison of existing force fields, AMOEBA, and the generalized AMBER force field, as well as the further optimization of the former to enable better agreement with QC interaction energies. Such improvements would pave the way toward a rational and systematic determination of the transferable force field parameters for a number of important small molecule cosolvents.

Evaluation of protein‐ligand binding free energy focused on its entropic components [J. Comp. Chem. 33, 550–560]

[a] S.Chiba,M.Sakurai Center for Biological Resources and Informatics, Tokyo Institute of Technology,Yokohama 226-8501, Japan Fax: þ81-45-924-5795 E-mail:msakurai@bio.titech.ac.jp [b] Y.Harano Institute for Protein Research,Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan [c] R.Roth Institut fur Theoretische Physik,Universita t Erlangen-Nurnberg, Staudtstrasse 7, 91058 Erlangen,Germany [d] M.Kinoshita Institute of Advanced Energy,Kyoto University,Uji, Kyoto 611-0011, Japan