Modeling Protein−Ligand Binding by Mining Minima

Abstract

We present the first application of the mining minima algorithm to protein-small molecule binding. This end-point approach use an empirical force field and implicit solvent models, treats the protein binding-site as fully flexible and estimates free energies as sums over local energy wells. The calculations are found to yield encouraging agreement with experiment for three sets of HIV-1protease inhibitors and a set of phosphodiesterase 10a inhibitors. The contributions of various aspects of the model to its accuracy are examined, and the Poisson-Boltzmann correction is found to be the most critical. Interestingly, the computed changes in configurational entropy upon binding fall roughly along the same entropy-energy correlation previously observed for smaller host-guest systems. Strengths and weaknesses of the method are discussed, as are the prospects for enhancing accuracy and speed.

Quantum mechanical binding free energy calculation for phosphopeptide inhibitors of the Lck SH2 domain

“…16,17 Between the computationally intensive free energy simulations, and the fast though inaccurate docking/scoring approach, end-point methods present an appealing alternative. These methods are rooted in statistical mechanics, 1,[18][19][20][21] and account for adequate conformational flexibility. As they aim to calculate the binding energy using only the initial and final states of the Additional Supporting Information may be found in the online version of this article.…”

Entropy in bimolecular simulations: A comprehensive review of atomic fluctuations-based methods

“…Although it did not affect the results, it contributed only to 2% of the total CPU time. On the other hand, excluding the PB/SA correction revealed a much larger effect in correlating the estimated values and experimental results [96].…”

“…These simulations, however, can identify the local energy minima explored by the system. " Mining" these minima and focusing mainly on the system's configuration at these energy wells can solve the convergence problem and allow for estimating the thermodynamical quantities at points of physiological relevance [83]. For example, June and Maginn used a modified version of MC simulations, namely biased-MC, to calculate the configurational integrals.…”

“…As a way to improve the method and to extend its applications to realistic biomolecular systems, Chen developed a new implementation of the M2 algorithm, namely VM2. The new version is more suitable for protein-ligand affinity calculations [96] and involves more comprehensive search algorithms. To reduce the calculation time, part of the protein can be held rigid, while the ligand binding site is allowed to be flexible.…”

Bioquímica e biofísica computacionais: simulações da reatividade e da estrutura de biomoléculas

“…To this end, ligand−receptor poses would have to be generated by the conformational search procedures found in docking 21,50 or by another method such as mining-minima. 89 Ligand and protein topologies containing connectivity, force field parameters, and polarity descriptors would have to be available or built. Although cumbersome when manually done, this process can be made fairly automatic.…”