K. Kuczera

Bio: K. Kuczera is an academic researcher from University of Maryland, Baltimore. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 1, co-authored 1 publications receiving 12333 citations.

All-atom empirical potential for molecular modeling and dynamics studies of proteins.

Abstract: New protein parameters are reported for the all-atom empirical energy function in the CHARMM program. The parameter evaluation was based on a self-consistent approach designed to achieve a balance between the internal (bonding) and interaction (nonbonding) terms of the force field and among the solvent−solvent, solvent−solute, and solute−solute interactions. Optimization of the internal parameters used experimental gas-phase geometries, vibrational spectra, and torsional energy surfaces supplemented with ab initio results. The peptide backbone bonding parameters were optimized with respect to data for N-methylacetamide and the alanine dipeptide. The interaction parameters, particularly the atomic charges, were determined by fitting ab initio interaction energies and geometries of complexes between water and model compounds that represented the backbone and the various side chains. In addition, dipole moments, experimental heats and free energies of vaporization, solvation and sublimation, molecular volume...

A 3D–Predicted Structure of the Amine Oxidase Domain of Lysyl Oxidase–Like 2

Abstract: Lysyl oxidase–like 2 (LOXL2) has been recognized as an attractive drug target for anti–fibrotic and anti–tumor therapies. However, the structure–based drug design of LOXL2 has been very challenging due to the lack of structural information of the catalytically–competent LOXL2. In this study; we generated a 3D–predicted structure of the C–terminal amine oxidase domain of LOXL2 containing the lysine tyrosylquinone (LTQ) cofactor from the 2.4Å crystal structure of the Zn2+–bound precursor (lacking LTQ; PDB:5ZE3); this was achieved by molecular modeling and molecular dynamics simulation based on our solution studies of a mature LOXL2 that is inhibited by 2–hydrazinopyridine. The overall structures of the 3D–modeled mature LOXL2 and the Zn2+–bound precursor are very similar (RMSD = 1.070Å), and disulfide bonds are conserved. The major difference of the mature and the precursor LOXL2 is the secondary structure of the pentapeptide (His652–Lys653–Ala654–Ser655–Phe656) containing Lys653 (the precursor residue of the LTQ cofactor). We anticipate that this peptide is flexible in solution to accommodate the conformation that enables the LTQ cofactor formation as opposed to the β–sheet observed in 5ZE3. We discuss the active site environment surrounding LTQ and Cu2+ of the 3D–predicted structure.

Modulation of human transthyretin stability by the mutations at histidine 88 studied by free energy simulation

Abstract: Human transthyretin (TTR) is a homotetrameric plasma protein associated with a high percentage of β‐sheet, which forms amyloid fibrils and accumulates in tissues or extracellular matrix to cause amyloid diseases. Free energy simulations based on all‐atom molecular dynamics simulations were carried out to analyze the effects of the His88 → Arg, Phe, and Tyr mutations on the stability of human TTR. The calculated free energy change differences (ΔΔG) caused by the His → Arg, Phe, and Tyr mutations at position 88 are 6.48 ± 0.45, −9.99 ± 0.54, and 2.66 ± 0.33 kcal/mol, respectively. These calculated free energy change differences between wild type and the mutants are in excellent agreement with prior experimental values. Our simulation results show that the wild type of the TTR is more stable than H88R and H88Y mutants, whereas it is less stable than the H88F mutant. The free energy component analysis shows that the primary contribution to the free energy change difference (ΔΔG) for the His → Arg mutation arises from electrostatic interaction; the ΔΔG for the His → Phe mutation is from van der Waals and electrostatic interactions and that for the His → Tyr mutation from covalent interaction. The simulation results show that the free energy calculation with thermodynamic integration is beneficial for understanding the detailed microscopic mechanism of protein stability. The implications of the results for understanding stabilizing and destabilizing effect of the mutation and the contribution to protein stability are discussed.

Simulation analysis of selective alanine mutation effect on stability of human prion protein

Abstract: Abstract Prion diseases are neurodegenerative disorders caused by spongiform degeneration of the brain. Understanding the fundamental mechanism of prion protein aggregation caused by mutations is very crucial to resolve the pathology of prion diseases. To help understand the roles of individual residues on the stability of the human prion protein, the computational method of free energy simulations based on atomistic molecular dynamics trajectories is applied to Phe175 → Ala, Val180 → Ala, and Val209 → Ala mutations of the human prion protein. The simulations show that all three alanine mutations destabilize the human prion protein. The calculated free energy change differences, ΔΔG, for the Phe175 → Ala, Val180 → Ala, and Val209 → Ala mutations are in good agreement with the experimental values. The significant destabilizing effects on the mutants relative to the wild-type protein arise from van der Waals terms. Furthermore, our free energy decomposition analysis shows that the major contribution to destabilizing the V180A and V209A mutants relative to the wild-type protein is originated from van der Waals interactions from residues near the mutation sites. In contrast, the contribution to destabilizing the F175A mutant is mainly caused by van der Waals interactions from residues near and far away from the mutation site. Our results show that the free energy simulation with a thermodynamic integration approach for selected alanine scanning mutations is beneficial for understanding the detailed mechanism of human prion protein destabilization, specific residues' role, and the hydrophobic effect on protein stability. Communicated by Ramaswamy H. Sarma

Free energy simulations to study mutational effect of a conserved residue, Trp24, on stability of human serum retinol-binding protein

Abstract: Abstract Human serum retinol-binding protein (RBP) is a plasma transport protein for vitamin A. RBP is a prime subclass of lipocalins, which bind nonpolar ligands within a β-barrel. To understand the role of Trp 24, one of the highly conserved residues in RBP, free energy simulations have been carried out to understand the effects of the mutations from Trp at position 24 to Leu, Phe, and Tyr in the apo-RBP on its thermal stability. We examine various unfolded systems to study the dependence of the free energy differences on the denatured structure. Our calculated free energy difference values for the three mutations are in excellent agreement with the experimental values when the initial coordinates of the seven-residue peptide segments truncated from the crystal structure are used for the denatured systems. Our free energy change differences for the Trp→Leu, Trp→Phe, and Trp→Tyr mutations are 2.50 ± 0.69, 2.58 ± 0.50, and 2.49 ± 0.48 kcal/mol, respectively, when the native-like seven-residue peptides are used as models for the denatured systems. The main contributions to the free energy change differences for the Trp24→Leu and Trp24→Phe mutations are mainly from van der Waals and covalent interactions, respectively. Electrostatic, van der Waals and covalent terms equally contribute to the free energy change difference for the Trp24→Tyr mutation. The free energy simulation helps understand the detailed microscopic mechanism of the stability of the RBP mutants relative to the wild type and the role of the highly conserved residue, Trp24, of the human RBP. Communicated by Ramaswamy H. Sarma

Scalable molecular dynamics with NAMD

Abstract: NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.

Quantum mechanical continuum solvation models.

Abstract: 6.2.2. Definition of Effective Properties 3064 6.3. Response Properties to Magnetic Fields 3066 6.3.1. Nuclear Shielding 3066 6.3.2. Indirect Spin−Spin Coupling 3067 6.3.3. EPR Parameters 3068 6.4. Properties of Chiral Systems 3069 6.4.1. Electronic Circular Dichroism (ECD) 3069 6.4.2. Optical Rotation (OR) 3069 6.4.3. VCD and VROA 3070 7. Continuum and Discrete Models 3071 7.1. Continuum Methods within MD and MC Simulations 3072

CHARMM: the biomolecular simulation program.

Abstract: CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecu- lar simulation program. It has been developed over the last three decades with a primary focus on molecules of bio- logical interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estima- tors, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numer- ous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields.

Abstract: The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like molecules is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chemical groups present in biomolecules and drug-like molecules, including a large number of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. Statistics related to the quality of the parametrization with a focus on experimental validation are presented. Additionally, the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethylpyrrolidine will allow users to readily extend the force field to chemical groups that are not explicitly covered in the force field as well as add functional groups to and link together molecules already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems.