Conformational transitions between open/closed or free/bound states in proteins possess functional importance. We propose a technique in which the collective modes obtained from an anisotropic network model (ANM) are used in conjunction with a Monte Carlo (MC) simulation approach, to investigate conformational transition pathways and pathway intermediates. The ANM-MC technique is applied to adenylate kinase (AK) and hemoglobin. The iterative method, in which normal modes are continuously updated during the simulation, proves successful in accomplishing the transition between open-closed conformations of AK and tense-relaxed forms of hemoglobin (C(alpha)-root mean square deviations between two end structures of 7.13 A and 3.55 A, respectively). Target conformations are reached by root mean-square deviations of 2.27 A and 1.90 A for AK and hemoglobin, respectively. The intermediate conformations overlap with crystal structures from the AK family within a 3.0-A root mean-square deviation. In the case of hemoglobin, the transition of tense-to-relaxed passes through the relaxed state. In both cases, the lowest-frequency modes are effective during transitions. The targeted Monte Carlo approach is used without the application of collective modes. Both the ANM-MC and targeted Monte Carlo techniques can explore sequences of events in transition pathways with an efficient yet realistic conformational search.

We performed a detailed analysis of conformational transition pathways for a set of 10 proteins, which undergo large hinge-bending-type motions with 4-12 Å RMSD (root mean-square distance) between open and closed crystal structures. Anisotropic network model-Monte Carlo (ANM-MC) algorithm generates a targeted pathway between two conformations, where the collective modes from the ANM are used for deformation at each iteration and the conformational energy of the deformed structure is minimized via an MC algorithm. The target structure was approached successfully with an RMSD of 0.9-4.1 Å when a relatively low cutoff radius of 10 Å was used in ANM. Even though one predominant mode (first or second) directed the open-to-closed conformational transition, changes in the dominant mode character were observed for most cases along the transition. By imposing radius of gyration constraint during mode selection, it was possible to predict the closed structure for eight out of 10 proteins (with initial 4.1-7.1 Å and final 1.7-2.9 Å RMSD to target). Deforming along a single mode leads to most successful predictions. Based on the previously reported free energy surface of adenylate kinase, deformations along the first mode produced an energetically favorable path, which was interestingly facilitated by a change in mode shape (resembling second and third modes) at key points. Pathway intermediates are provided in our database of conformational transitions (http://safir.prc.boun.edu.tr/anmmc/method/1).

Elastic network model simulations were performed to investigate the conformational changes of MDM2 protein induced by its native substrate p53 and two small molecule inhibitor (NVP-CGM097 and HDM 201) bindings. Residues Phe 19, Trp 23, Leu 26 were observed to reside in the minima of slowest modes of p53, pointing to the accepted three finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct conserved regions are identified in MDM2. Regions I (residues 50–77) and III (residues 90–105) correspond to the binding interface of MDM2 including [Formula: see text] helix-2 ([Formula: see text]), Loop-2 (L2) and [Formula: see text] helix-4 ([Formula: see text]) domains which are stabilized during complex formation. Region II (residues 77–90) is a highly flexible region in both unbound and bound forms exhibiting high amplitude collective motion. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 pointing to induced-fit mechanism. Flexible docking using AutoDock Vina is performed to account for the flexible nature of the receptor and to elucidate the essential interactions in the binding cleft. [Formula: see text] domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states. Inhibitors studied in this work (NVP-CGM097 and HDM201), which are recently undergoing clinical trials, succeed in mimicking p53 behavior which would shed light on the rational design of novel anticancer drugs.

Alzheimer’s disease (AD) is a neurodegenerative disorder considered as a global public health threat influencing many people. Despite the concerning rise in the affected population, there is still a shortage of potent and safe therapeutic agents. The aim of this research is to discover novel natural source molecules with high therapeutic effects, stability and less toxicity for the treatment of AD, specifically targeting acetylcholinesterase (AChE). This research can be divided into two steps: in silico search for molecules by systematic simulations and in vitro experimental validations. We identified five leading compounds, namely Queuine, Etoperidone, Thiamine, Ademetionine and Tetrahydrofolic acid by screening natural molecule database, conducting molecular docking and druggability evaluations. Stability of the complexes were investigated by Molecular Dynamics simulations and free energy calculations were conducted by Molecular Mechanics Generalized Born Surface Area method. All five complexes were stable within the binding catalytic site (CAS) of AChE, with the exception of Queuine which remains stable on the peripheral site (PAS). On the other hand Etoperidone both interacts with CAS and PAS sites showing dual binding properties. Binding free energy values of Queuine and Etoperidone were -71.9 and -91.0 kcal/mol respectively, being comparable to control molecules Galantamine (-71.3 kcal/mol) and Donepezil (-80.9 kcal/mol). Computational results were validated through in vitro experiments using the SH-SY5Y(neuroblastoma) cell line with Real Time Cell Analysis (RTCA) and cell viability assays. The results showed that the selected doses were effective with half inhibitory concentrations estimated to be: Queuine (IC50 = 70,90 μM), Etoperidone (IC50 = 712,80 μM), Thiamine (IC50 = 18780,34 μM), Galantamine (IC50 = 556,01 μM) and Donepezil (IC50 = 222,23 μM), respectively. The promising results for these molecules suggest the development of the next step in vivo animal testing and provide hope for natural therapeutic aids in the treatment of AD.

Targeting the interaction between tumor suppressor p53 and murine double minute 2 (MDM2) protein has been an attractive therapeutic strategy of recent cancer research. There are a few number of MDM2-targeted anticancer drug molecules undergoing clinical trials right now, however none of them have been approved so far. Recently, we analyzed the global dynamics of MDM2 and the conformational changes it undergoes upon ligand binding in cases of both native ligand p53 and small molecule inhibitors. In this study, we employed a new approach in which global dynamics of MDM2 obtained by elastic network models are used as a guide in the generation and validation of the ligand-based pharmacophore model prior to virtual screening in search for novel MDM2 inhibitors. Then, we carried out virtual screening, rigid and induced-fit molecular docking, which accounts for the very flexible and intrinsically disordered nature of MDM2, to capture several hit molecules exhibiting high affinity. We used the knowledge of the binding mechanism while creating the induced-fit docking criteria which can fine tune the docking protocol. Application of a rigorous molecular mechanics-generalized born surface area (MM-GBSA) method provided a more accurate prediction of the binding free energy values. We identified two leading hit molecules which have shown better docking scores, binding free energy values and drug-like molecular properties as compared to seven clinical trial MDM2 inhibitor molecules. These hits exhibited extra intermolecular interactions with MDM2, indicating a stable complex formation. Therefore, combined computational strategy employed in generating a pharmacophore model based on the active available ligands undergoing clinical trials and validating the model by the conformational dynamics background to screen libraries can be a promising tool in the initial stage of drug design for the discovery of potential new hits.