Why Does Asn71 Deamidate Faster Than Asn15 in the Enzyme Triosephosphate Isomerase? Answers from Microsecond Molecular Dynamics Simulation and QM/MM Free Energy Calculations

Molecular Modeling of the Deamidation Reaction in Solution: A Theoretical-Computational Study

In this work, a theoretical-computational method is applied to study the deamidation reaction, a critical post-translational modification in proteins, using a simple model molecule in solution. The method allows one to comprehensively address the environmental effect, thereby enabling one to accurately derive the kinetic rate constants for the three main steps of the deamidation process. The results presented, in rather good agreement with the available experimental data, underline the necessity for a rigorous treatment of environmental factors and a precise kinetic model to correctly assess the overall kinetics of the deamidation reaction.

Conformational Control of Fast Asparagine Deamidation in a Norovirus Capsid Protein

Accelerated spontaneous deamidation of asparagine 373 and subsequent conversion into an isoaspartate has been shown to attenuate the binding of histo blood group antigens (HBGAs) to the protruding domain (P-domain) of the capsid protein of a prevalent norovirus strain (GII.4). Here, we link an unusual backbone conformation of asparagine 373 to its fast site-specific deamidation. NMR spectroscopy and ion exchange chromatography have been used to monitor the deamidation reaction of P-domains of two closely related GII.4 norovirus strains, specific point mutants, and control peptides. MD simulations over several microseconds have been instrumental to rationalize the experimental findings. While conventional descriptors such as available surface area, root-mean-square fluctuations, or nucleophilic attack distance fail as explanations, the population of a rare syn-backbone conformation distinguishes asparagine 373 from all other asparagine residues. We suggest that stabilization of this unusual conformation enhances the nucleophilicity of the backbone nitrogen of aspartate 374, in turn accelerating the deamidation of asparagine 373. This finding should be relevant to the development of reliable prediction algorithms for sites of rapid asparagine deamidation in proteins.

Deciphering deamidation and isomerization in therapeutic proteins: Effect of neighboring residue

Deamidation of asparagine (Asn) and isomerization of aspartic acid (Asp) residues are among the most commonly observed spontaneous post-translational modifications (PTMs) in proteins. Understanding and predicting a protein sequence's propensity for such PTMs can help expedite protein therapeutic discovery and development. In this study, we used proton-affinity calculations with semi-empirical quantum mechanics and microsecond long equilibrium molecular dynamics simulations to investigate mechanistic roles of structural conformation and chemical environment in dictating spontaneous degradation of Asn and Asp residues in 131 clinical-stage therapeutic antibodies. Backbone secondary structure, side-chain rotamer conformation and solvent accessibility were found to be key molecular indicators of Asp isomerization and Asn deamidation. Comparative analysis of backbone dihedral angles along with N-H proton affinity calculations provides a mechanistic explanation for the strong influence of the identity of the n + 1 residue on the rate of Asn/Asp degradation. With these findings, we propose a minimalistic physics-based classification model that can be leveraged to predict deamidation and isomerization propensity of proteins.

Embedded Mean-Field Theory for Solution-Phase Transition-Metal Polyolefin Catalysis

Decreasing the wall-clock time of quantum mechanics/molecular mechanics (QM/MM) calculations without sacrificing accuracy is a crucial prerequisite for widespread simulation of solution-phase dynamical processes. In this work, we demonstrate the use of embedded mean-field theory (EMFT) as the QM engine in QM/MM molecular dynamics (MD) simulations to examine polyolefin catalysts in solution. We show that employing EMFT in this mode preserves the accuracy of hybrid-functional DFT in the QM region, while providing up to 20-fold reductions in the cost per SCF cycle, thereby increasing the accessible simulation time-scales. We find that EMFT reproduces DFT-computed binding energies and optimized bond lengths to within chemical accuracy, as well as consistently ranking conformer stability. Furthermore, solution-phase EMFT/MM simulations provide insight into the interaction strength of strongly coordinating and bulky counterions.

Semi-Empirical Born-Oppenheimer Molecular Dynamics (SEBOMD) within the Amber Biomolecular Package

Semi-empirical quantum methods from the neglect of differential diatomic overlap (NDDO) family such as MNDO, AM1, or PM3 are fast albeit approximate quantum methods. By combining them with linear scaling methods like the divide & conquer (D&C) method, it is possible to quickly evaluate the energy of systems containing hundreds to thousands of atoms. We here present our implementation in the Amber biomolecular package of a SEBOMD module that provides a way to run semi-empirical Born-Oppenheimer molecular dynamics. At each step of a SEBOMD, a fully converged self-consistent field (SCF) calculation is performed to obtain the semiempirical quantum potential energy of a molecular system encaged or not in periodic boundary conditions. We describe the implementation and the features of our SEBOMD implementation. We show the requirements to conserve the total energy in NVE simulations, and how to accelerate SCF convergence through density matrix extrapolation. Specific ways of handling periodic boundary conditions using mechanical embedding or electrostatic embedding through a tailored quantum Ewald summation is developed. The parallel performance of SEBOMD simulations using the D&C scheme are presented for liquid water systems of various sizes, and a comparison between the traditional full diagonalization scheme and the D&C approach for the reproduction of the structure of liquid water illustrates the potentiality of SEBOMD to simulate molecular systems containing several hundreds of atoms for hundreds of picoseconds with a quantum mechanical potential in a reasonable amount of CPU time.

Assessing protein-ligand binding modes with computational tools: the case of PDE4B

In a first step in the discovery of novel potent inhibitor structures for the PDE4B family with limited side effects, we present a protocol to rank newly designed molecules through the estimation of their IC[Formula: see text] values. Our protocol is based on reproducing the linear relationship between the logarithm of experimental IC[Formula: see text] values [[Formula: see text](IC[Formula: see text])] and their calculated binding free energies ([Formula: see text]). From 13 known PDE4B inhibitors, we show here that (1) binding free energies obtained after a docking process by AutoDock are not accurate enough to reproduce this linear relationship; (2) MM-GB/SA post-processing of molecular dynamics (MD) trajectories of the top ranked AutoDock pose improves the linear relationship; (3) by taking into account all representative structures obtained by AutoDock and by averaging MM-GB/SA computations on a series of 40 independent MD trajectories, a linear relationship between [Formula: see text](IC[Formula: see text]) and the lowest [Formula: see text] is achieved with [Formula: see text].

Biopharmaceutical Informatics: supporting biologic drug development via molecular modelling and informatics

Objectives

The purpose of this article is to introduce an emerging field called ‘Biopharmaceutical Informatics’. It describes how tools from Information technology and Molecular Biophysics can be adapted, developed and gainfully employed in discovery and development of biologic drugs.

Key Findings

The findings described here are based on literature surveys and the authors’ collective experiences in the field of biologic drug product development. A strategic framework to forecast early the hurdles faced during drug product development is weaved together and elucidated using chemical degradation as an example. Efficiency of translating biologic drug discoveries into drug products can be significantly improved by combining learnings from experimental biophysical and analytical data on the drug candidates with molecular properties computed from their sequences and structures via molecular modeling and simulations.

Summary

Biopharmaceutical Informatics seeks to promote applications of computational tools towards discovery and development of biologic drugs. When fully implemented, industry-wide, it will enable rapid materials-free developability assessments of biologic drug candidates at early stages as well as streamline drug product development activities such as commercial scale production, purification, formulation, analytical characterization, safety and in vivo performance.

Molecular dynamics simulations of apo, holo, and inactivator bound GABA-at reveal the role of active site residues in PLP dependent enzymes

The pyridoxal 5-phosphate (PLP) cofactor is a significant organic molecule in medicinal chemistry. It is often found covalently bound to lysine residues in proteins to form PLP dependent enzymes. An example of this family of PLP dependent enzymes is γ-aminobutyric acid aminotransferase (GABA-AT) which is responsible for the degradation of the neurotransmitter GABA. Its inhibition or inactivation can be used to prevent the reduction of GABA concentration in brain which is the source of several neurological disorders. As a test case for PLP dependent enzymes, we have performed molecular dynamics simulations of GABA-AT to reveal the roles of the protein residues and its cofactor. Three different states have been considered: the apoenzyme, the holoenzyme, and the inactive state obtained after the suicide inhibition by vigabatrin. Different protonation states have also been considered for PLP and two key active site residues: Asp298 and His190. Together, 24 independent molecular dynamics trajectories have been simulated for a cumulative total of 2.88 µs. Our results indicate that, unlike in aqueous solution, the PLP pyridine moiety is protonated in GABA-AT. This is a consequence of a pKa shift triggered by a strong charge-charge interaction with an ionic "diad" formed by Asp298 and His190 that would help the activation of the first half-reaction of the catalytic mechanism in GABA-AT: the conversion of PLP to free pyridoxamine phosphate (PMP). In addition, our MD simulations exhibit additional strong hydrogen bond networks between the protein and PLP: the phosphate group is held in place by the donation of at least three hydrogen bonds while the carbonyl oxygen of the pyridine ring interacts with Gln301; Phe181 forms a π-π stacking interaction with the pyridine ring and works as a gate keeper with the assistance of Val300. All these interactions are hypothesized to help maintain free PMP in place inside the protein active site to facilitate the second half-reaction in GABA-AT: the regeneration of PLP-bound GABA-AT (i.e., the holoenzyme). Proteins 2016; 84:875-891. © 2016 Wiley Periodicals, Inc.