Molecular dynamics simulations of the Escherichia coli HPPK apo-enzyme reveal a network of conformational transitions

Molecular Dynamics Investigations Suggest a Non-specific Recognition Strategy of 14-3-3σ Protein by Tweezer: Implication for the Inhibition Mechanism

The supramolecular complex formed between protein and designed molecule has become one of the most efficient ways to modify protein functions. As one of the more well-studied model systems, 14-3-3 family proteins play an important role in regulating intracellular signaling pathways via protein-protein interactions. In this work, we selected 14-3-3σ as the target protein. Molecular dynamics simulations and binding free energy calculations were applied to identify the possible binding sites and understand its recognition ability of the supramolecular inhibitor, the tweezer molecule (CLR01). On the basis of our simulation, major interactions between lysine residues and CLR01 come from the van der Waals interactions between the long alkyl chain of lysine and the cavity formed by the norbornadiene and benzene rings of the inhibitor. Apart from K214, which was found to be crystallized with this inhibitor, other lysine sites have also shown their abilities to form inclusion complexes with the inhibitor. Such non-specific recognition features of CLR01 against 14-3-3σ can be used in the modification of protein functions via supramolecular chemistry.

Generative network complex (GNC) for drug discovery

It remains a challenging task to generate a vast variety of novel compounds with desirable pharmacological properties. In this work, a generative network complex (GNC) is proposed as a new platform for designing novel compounds, predicting their physical and chemical properties, and selecting potential drug candidates that fulfill various druggable criteria such as binding affinity, solubility, partition coefficient, etc. We combine a SMILES string generator, which consists of an encoder, a drug-property controlled or regulated latent space, and a decoder, with verification deep neural networks, a target-specific three-dimensional (3D) pose generator, and mathematical deep learning networks to generate new compounds, predict their drug properties, construct 3D poses associated with target proteins, and reevaluate druggability, respectively. New compounds were generated in the latent space by either randomized output, controlled output, or optimized output. In our demonstration, 2.08 million and 2.8 million novel compounds are generated respectively for Cathepsin S and BACE targets. These new compounds are very different from the seeds and cover a larger chemical space. For potentially active compounds, their 3D poses are generated using a state-of-the-art method. The resulting 3D complexes are further evaluated for druggability by a championing deep learning algorithm based on algebraic topology, differential geometry, and algebraic graph theories. Performed on supercomputers, the whole process took less than one week. Therefore, our GNC is an efficient new paradigm for discovering new drug candidates.

Insights into the mechanism of the PIK3CA E545K activating mutation using MD simulations

Phosphoinositide 3-kinase alpha (PI3Kα) is involved in fundamental cellular processes including cell proliferation and differentiation and is frequently mutated in human malignancies. One of the most common mutations is E545K, which results in an amino acid substitution of opposite charge. It has been recently proposed that in this oncogenic charge-reversal mutation, the interactions between the protein catalytic and regulatory subunits are abrogated, resulting in loss of regulation and constitutive PI3Kα activity, which can lead to oncogenesis. To assess the mechanism of the PI3Kα E545K activating mutation, extensive Molecular Dynamics simulations were performed to examine conformational changes differing between the wild type (WT) and mutant proteins as they occur in microsecond simulations. In the E545K mutant PI3Kα, we observe a spontaneous detachment of the nSH2 PI3Kα domain (regulatory subunit, p85α) from the helical domain (catalytic subunit, p110α) causing significant loss of communication between the regulatory and catalytic subunits. We examine the allosteric network of the two proteins and show that a cluster of residues around the mutation is important for delivering communication signals between the catalytic and regulatory subunits. Our results demonstrate the dynamical and structural effects induced by the p110α E545K mutation in atomic level detail and indicate a possible mechanism for the loss of regulation that E545K confers on PI3Kα.

Folate biosynthesis pathway: mechanisms and insights into drug design for infectious diseases

Folate pathway is a key target for the development of new drugs against infectious diseases since the discovery of sulfa drugs and trimethoprim. The knowledge about this pathway has increased in the last years and the catalytic mechanism and structures of all enzymes of the pathway are fairly understood. In addition, differences among enzymes from prokaryotes and eukaryotes could be used for the design of specific inhibitors. In this review, we show a panorama of progress that has been achieved within the folate pathway obtained in the last years. We explored the structure and mechanism of enzymes, several genetic features, strategies, and approaches used in the design of new inhibitors that have been used as targets in pathogen chemotherapy.

Exploration of Multistate Conformational Dynamics upon Ligand Binding of a Monomeric Enzyme Involved in Pyrophosphoryl Transfer

HPPK (6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase) is a monomeric protein with 158 residues, which undergoes large-scale conformational changes between apo, open, and holo states responding to ligand binding for its function. It has been explored widely as an excellent target for potential antibacterial drug development. However, little is known about how conformational dynamics between the native states influences the substrate recognition and the functionality of enzymatic catalysis. Here, we report a coarse-grained triple-basin structure-based model upon ligand binding to describe such multiple-state system by the molecular dynamics simulation. With our model, we have made theoretical predictions that are in good agreement with the experimental measurements. Our results revealed the intrinsic conformational fluctuations between apo and open states without ligand binding. We found that HPPK can switch to the activated holo state upon the ordered binding of the two ligands (ATP and HP). We uncovered the underlying mechanism by which major induced fit and minor population shift pathways coexist upon ligand binding by quantitative flux analysis. Additionally, we pointed out the structural origin for the conformational changes and identified the key residues as well as contact interactions. We further explored the temperature effect on the conformational distributions and pathway weights. It gave strong support that higher temperatures promote population shift, while the induced fit pathway is always the predominant activation route of the HPPK system. These findings will provide significant insights of the mechanisms of the multistate conformational dynamics of HPPK upon ligand binding.

Elucidation of the catalytic mechanism of 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase using QM/MM calculations

This account describes the application of QM/MM calculations to understand the reaction mechanism of HPPK, an important pharmacological target on the folate pathway for the treatment of diseases including anti-microbial resistance, malaria and cancer.

Network of Conformational Transitions Revealed by Molecular Dynamics Simulations of the Carbonic Anhydrase II Apo-Enzyme

Human carbonic anhydrase II (HCA II) is an enzyme that catalyzes the reversible hydration of CO2 into bicarbonate (HCO3-) and a proton (H+) as well as other reactions at an extremely high rate. This enzyme plays fundamental roles in human physiology/pathology, such as controlling the pH level in cells and so on. However, the binding mechanism between apo-HCA II and CO2 or other ligands as well as related conformational changes remains poorly understood, and atomic investigation into it could promote our understanding of related internal physiological/pathological mechanisms. In this study, long-time atomic molecular dynamics simulations as well as the clustering and free-energy analysis were performed to reveal the dynamics of apo-HCA II as well as the mechanism upon ligand binding. Our simulations indicate that the crystallographic B-factors considerably underestimate the loop dynamics: multiple conformations can be adopted by loops 1 and 2, especially for loop 1 because loop 1 is one side of the binding pocket, and its left-to-right movement can compress or extend the binding pocket, leading to one inactive (closed) state, three intermediate (semiopen) states, and one active (open) state; CO2 cannot get into the binding pocket of the inactive state but can get into those of intermediate and active states. The coexistence of multiple conformational states proposes a possible conformational selection model for the binding mechanism between apo-HCA II and CO2 or other ligands, revising our previous view of its functional mechanism of conformational change upon ligand binding and offering valuable structural insights into the workings of HCA II.

A Network of Conformational Transitions in the Apo Form of NDM-1 Enzyme Revealed by MD Simulation and a Markov State Model

New Delhi metallo-β-lactamase-1 (NDM-1) is a novel β-lactamase enzyme that confers enteric bacteria with nearly complete resistance to all β-lactam antibiotics, so it raises a formidable and global threat to human health. However, the binding mechanism between apo-NDM-1 and antibiotics as well as related conformational changes remains poorly understood, which largely hinders the overcoming of its antibiotic resistance. In our study, long-time conventional molecular dynamics simulation and Markov state models were applied to reveal both the dynamical and conformational landscape of apo-NDM-1: the MD simulation demonstrates that loop L3, which is responsible for antibiotic binding, is the most flexible and undergoes dramatic conformational changes; moreover, the Markov state model built from the simulation maps four metastable states including open, semiopen, and closed conformations of loop L3 as well as frequent transitions between the states. Our findings propose a possible conformational selection model for the binding mechanism between apo-NDM-1 and antibiotics, which facilitates the design of novel inhibitors and antibiotics.

Dynamics of the active site loops in catalyzing aminoacylation reaction in seryl and histidyl tRNA synthetases

Aminoacylation reaction is the first step of protein biosynthesis. The catalytic reorganization at the active site of aminoacyl tRNA synthetases (aaRSs) is driven by the loop motions. There remain lacunae of understanding concerning the catalytic loop dynamics in aaRSs. We analyzed the functional loop dynamics in seryl tRNA synthetase from Methanopyrus kandleri (^mkSerRS) and histidyl tRNA synthetases from Thermus thermophilus (^ttHisRS), respectively, using molecular dynamics. Results confirm that the motif 2 loop and other active site loops are flexible spots within the catalytic domain. Catalytic residues of the loops form a network of interaction with the substrates to form a reactive state. The loops undergo transitions between closed state and open state and the relaxation of the constituent residues occurs in femtosecond to nanosecond time scale. Order parameters are higher for constituent catalytic residues which form a specific network of interaction with the substrates to form a reactive state compared to the Gly residues within the loop. The development of interaction is supported from mutation studies where the catalytic domain with mutated loop exhibits unfavorable binding energy with the substrates. During the open-close motion of the loops, the catalytic residues make relaxation by ultrafast librational motion as well as fast diffusive motion and subsequently relax rather slowly via slower diffusive motion. The Gly residues act as a hinge to facilitate the loop closing and opening by their faster relaxation behavior. The role of bound water is analyzed by comparing implicit solvent-based and explicit solvent-based simulations. Loops fail to form catalytically competent geometry in absence of water. The present result, for the first time reveals the nature of the active site loop dynamics in aaRS and their influence on catalysis.

A Network of Conformational Transitions Revealed by Molecular Dynamics Simulations of the Binary Complex of Escherichia coli 6-Hydroxymethyl-7,8-dihydropterin Pyrophosphokinase with MgATP

6-Hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK) catalyzes the first reaction in the folate biosynthetic pathway. Comparison of its X-ray and nuclear magnetic resonance structures suggests that the enzyme undergoes significant conformational change upon binding to its substrates, especially in three catalytic loops. Experimental research has shown that, in its binary form, even bound by analogues of MgATP, loops 2 and 3 remain rather flexible; this raises questions about the putative large-scale induced-fit conformational change of the HPPK-MgATP binary complex. In this work, long-time all-atomic molecular dynamics simulations were conducted to investigate the loop dynamics in this complex. Our simulations show that, with loop 3 closed, multiple conformations of loop 2, including the open, semiopen, and closed forms, are all accessible to the binary complex. These results provide valuable structural insights into the details of conformational changes upon 6-hydroxymethyl-7,8-dihydropterin (HP) binding and biological activities of HPPK. Conformational network analysis and principal component analysis related to the loops are also discussed.