We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

MUSCLE: multiple sequence alignment with high accuracy and high throughput

CHARMM (Chemistry at HARvard Macromolecular Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromolecular systems. The program can read or model build structures, energy minimize them by first- or second-derivative techniques, perform a normal mode or molecular dynamics simulation, and analyze the structural, equilibrium, and dynamic properties determined in these calculations. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.

CHARMM: A program for macromolecular energy, minimization, and dynamics calculations

For a successful analysis of the relation between amino acid sequence and protein structure, an unambiguous and physically meaningful definition of secondary structure is essential. We have developed a set of simple and physically motivated criteria for secondary structure, programmed as a pattern-recognition process of hydrogen-bonded and geometrical features extracted from x-ray coordinates. Cooperative secondary structure is recognized as repeats of the elementary hydrogen-bonding patterns “turn” and “bridge.” Repeating turns are “helices,” repeating bridges are “ladders,” connected ladders are “sheets.” Geometric structure is defined in terms of the concepts torsion and curvature of differential geometry. Local chain “chirality” is the torsional handedness of four consecutive Cα positions and is positive for right-handed helices and negative for ideal twisted β-sheets. Curved pieces are defined as “bends.” Solvent “exposure” is given as the number of water molecules in possible contact with a residue. The end result is a compilation of the primary structure, including SS bonds, secondary structure, and solvent exposure of 62 different globular proteins. The presentation is in linear form: strip graphs for an overall view and strip tables for the details of each of 10.925 residues. The dictionary is also available in computer-readable form for protein structure prediction work.

Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features

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

/pdf/quantum-mechanical-continuum-solvation-models-3edv963g14.pdf

Quantum mechanical continuum solvation models.

This article describes the software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for molecular dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequilibrium dynamics and free energy determinations are incorporated. Interfaces with popular quantum-chemical packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and analysis programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.

/pdf/gromacs-fast-flexible-and-free-15aazpel5u.pdf

GROMACS: Fast, flexible, and free

Proteins can be very tolerant to amino acid substitution, even within their core. Understanding the factors responsible for this behavior is of critical importance for protein engineering and design. Mutations in proteins have been quantified in terms of the changes in stability they induce. For example, guest residues in specific secondary structures have been used as probes of conformational preferences of amino acids, yielding propensity scales. Predicting these amino acid propensities would be a good test of any new potential energy functions used to mimic protein stability. We have recently developed a protein design procedure that optimizes whole sequences for a given target conformation based on the knowledge of the template backbone and on a semiempirical potential energy function. This energy function is purely physical, including steric interactions based on a Lennard-Jones potential, electrostatics based on a Coulomb potential, and hydrophobicity in the form of an environment free energy based on accessible surface area and interatomic contact areas. Sequences designed by this procedure for 10 different proteins were analyzed to extract conformational preferences for amino acids. The resulting structure-based propensity scales show significant agreements with experimental propensity scale values, both for α-helices and β-sheets. These results indicate that amino acid conformational preferences are a natural consequence of the potential energy we use. This confirms the accuracy of our potential and indicates that such preferences should not be added as a design criterion.

https://www.pnas.org/content/pnas/96/22/12524.full.pdf

Structure-based conformational preferences of amino acids

Two methods have been used to measure the single-strand lengths of the DNA fragments produced by deoxyribonuclease I digestion of chromatin. The average lengths obtained are muliples of about 10.4 bases, significantly different from the value of 10 previously reported. This periodicity in fragment lengths is closely related to the periodicity of the DNA double helix in chromatin, but the two values need not be exactly the same.

http://science.sciencemag.org/content/sci/204/4395/855.full.pdf

Periodicity of deoxyribonuclease I digestion of chromatin

Consistent force field for calculation of vibrational spectra and conformations of some amides and lactam rings

Like Sydney Altman 1 , I too was initially rejected by the renowned Medical Research Council (MRC) Laboratory of Molecular Biology in Cambridge, England. The year was 1967 and I was then in my final year of a B.Sc. degree in Physics at Kings College in London. Enthralled by John Kendrew's BBC 1964 television series \" The Thread of Life \" , I wanted desperately to do my Ph.D. at the MRC in Cambridge. Alas there was no room for any new postgraduate students in 1967! After some negotiations, I was accepted for the following year. More importantly, John Kendrew said that I should spend the intervening period at the Weizmann Institute in Israel with Shneior Lifson. Kendrew had just heard of Lifson's initial ideas 2 on the consistent force field (CFF), which was an attempt to simulate the properties of any molecular system from a simple potential energy function. He believed that these methods should be applied to protein and nucleic acid macro-molecules. I arrived in Israel in October, 1967 and set to work programming the consistent force field under the supervision of Lifson and his Ph.D. student Arieh Warshel. At that time, computing at the Weizmann Institute was amongst the best in the world; in 1963 computer engineers there had built their own machine, appropriately known as the Golem, after the Jewish folklore automaton. In a few short months we had a program called CFF that allowed us to calculate the energy, forces (energy first derivatives with respect to atomic positions) and curvature (energy second derivatives with respect to atomic positions) of any molecular system. Warshel went on to use the program to calculate structural, thermodynamic and spectroscopic properties of small organic molecules 3 , while I followed Kendrew's dictum and applied these same programs to proteins. This led to the first energy minimization of an entire protein structure (in fact we did two, myoglobin and lysozyme) in a process that became known as energy refinement 4. I began my Ph.D. at the MRC in Cambridge in September, 1968 and was immediately immersed in the annual tradition of Lab Talks. These talks by members of the three divisions at the Laboratory of Molecular Biology at that time (Structural Studies Division under Kendrew, the Cell Biology Division under Sydney Brenner and Francis Crick, and Protein and Nucleic Acid Chemistry Division under Fred Sanger) were a treat for newcomers to …

Michael Levitt

Papers

Structure-based conformational preferences of amino acids

Periodicity of deoxyribonuclease I digestion of chromatin

Consistent force field for calculation of vibrational spectra and conformations of some amides and lactam rings

The birth of computational structural biology.

Realistic Simulations of Native-Protein Dynamics in Solution and Beyond