Postdoctoral position in Theoretical Chemistry, University of Aarhus, Denmark

3-year postdoc position is available

Starting date: 1 February 2014 or as soon as possible.

The candidate must have a PhD in theoretical chemistry. In addition, the candidate is required to have a strong background in electronic structure theory, in particular coupled cluster theory and experience with massive parallel computer codes.

The successful candidate will be involved in the development and implementation of the Divide-Expand-Consolidate (DEC) coupled cluster method in collaboration with other members of the qLEAP Center. Focus will be on a massively parallel implementation of energies, molecular gradients and molecular properties for the DEC coupled cluster CCSD and CCSD(T) models and on running these implementations on the most powerful supercomputers.

For further information on the position, please visit the webpage (http://qleap.au.dk/job-openings & http://qleap.au.dk) 

Review of Hybrid RHF/MP2 geometry optimizations with the effective fragment molecular orbital method

The reviews of +Anders Steen Christensen and +Casper Steinmann PLoS ONE paper are in. Some preliminary thoughts:

Question 1. I think the main problem is that we left out a lot of details because they have been discussed extensively in this paper. So we need to refer to this paper more extensively.

Question 5. Reviewer #2: 

Point 1. we should clarify

Point 2. don't understand, in what way unclear

Point 3. we should make such a figure.  We shouldn't show individual fragments, but rather which parts are treated with MP2 and which parts are frozen.

------

From: PLOS ONE <plosone@plos.org>

Date: Wed, Dec 11, 2013 at 8:17 PM

Subject: PLOS ONE Decision: Revise [PONE-D-13-43802] - [EMID:f0cd9b87a193051a]

To: "Anders S. Christensen" <xxx>

PONE-D-13-43802

Hybrid RHF/MP2 geometry optimizations with the effective fragment molecular orbital method

PLOS ONE

Dear Mr. S. Christensen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit, but is not suitable for publication as it currently stands. Therefore, my decision is "Major Revision." 

We invite you to submit a revised version of the manuscript that addresses the points below: 

while this manuscript presents a likely technical advance in QM/MM that could be significant, there is a lack of clarity and context in the manuscript. Each reviewer has noted different aspects that suggest a difficulty in understanding to what extent this method improves upon existing methods, and to what extent this method can be applied across multiple systems.

I encourage you to address each point made by the reviewers. The points relating to comparing this method to others and to explaining discrepancy are particularly important. This manuscript would also benefit from a reorganization and a more critical comparison to other methods.

We encourage you to submit your revision within forty-five days of the date of this decision. I recognize this might not be possible given the recommendations, so I encourage you to ask for an extension if necessary.

When your files are ready, please submit your revision by logging on to http://pone.edmgr.com/ and following the Submissions Needing Revision link. Do not submit a revised manuscript as a new submission. Before uploading, you should proofread your manuscript very closely for mistakes and grammatical errors. Should your manuscript be accepted for publication, you may not have another chance to make corrections as we do not offer pre-publication proofs.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. 

Please also include a rebuttal letter that responds to each point brought up by the academic editor and reviewer(s). This letter should be uploaded as a Response to Reviewers file.

In addition, please provide a marked-up copy of the changes made from the previous article file as a Manuscript with Tracked Changes file. This can be done using 'track changes' in programs such as MS Word and/or highlighting any changes in the new document. 

If you choose not to submit a revision, please notify us. 

Yours sincerely, 

xxx

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

Please explain (optional).

Reviewer #1: This is relevant paper on using MP2 with effective fragment molecular orbital method and demonstrated to be alternative to ONIOM. The paper would be potentially valuable but I would suggest more discussion about the potential of the method and its outputs to be done. Chorismate mutase is the "hydrogen atom" for QM/MM modelling so there is vast majority of data from many groups, therefore there is a potential in this paper for more comprehensive discussion.

Reviewer #2: (No Response)

Reviewer #3: This study compared the EFMO method with ONIOM method as for the reaction free energy barrier for the Chorismate Mutase. In general, the results are more consistent than that of the ONIOM. This review agrees that the current manuscript is publishable, and expect the authors to explain the possible reasons for: (1) the calculated free energy barrier is much higher than that of the experimentally measured enthalpy change? (2) The authors claimed that the MP2-geometry optimization make it 3.5 kcal/mol lower for the free energy barrier than that of the ONIOM method, however, the listed data of free energy barrier in Table2 is close to each other at the same calculation level. (3) The portability to other enzyme system of EFMO method?

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: I don't know

Reviewer #3: Yes

Please explain (optional).

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: The data of all tables and figures are clean and good.

3. Does the manuscript adhere to standards in this field for data availability?

Authors must follow field-specific standards for data deposition in publicly available resources and should include accession numbers in the manuscript when relevant. The manuscript should explain what steps have been taken to make data available, particularly in cases where the data cannot be publicly deposited.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

Please explain (optional).

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: This is a typical study on the topic of QM/MM method and application for enzyme reaction.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors below.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Please explain (optional).

Reviewer #1: (No Response)

Reviewer #2: The reference should be gived as [1-13]in the text,but not [1,2,3,4,5,6,7,8,9,10,11,12,13].

Reviewer #3: Yes, the whole manuscript is organized very well, and written well.

5. Additional Comments to the Author (optional)

Please offer any additional comments here, including concerns about dual publication or research or publication ethics.

Reviewer #1: (No Response)

Reviewer #2: The authors implemented the correlated method in the EFMO/FDD approximation on the optimizing a complex of chorismate mutase and chorismate. The authors have presented the transition state structure, reaction barrier, and reaction energy, etc. While the method has more improved the results than the previous work, the paper as present is organized unclearly. There is hardly any insight that can be gained from this word. The manuscript is unsuitable for publication in current version.

To name a few questions.

1. In the theory part, the given molecular system is described, which is defined into tow domains F and A. But in the following description, the b domain (buffer domain) is contained. The system is divided into three domains or two domains? 

2. The Table 1 and 2 is disordered.

3. The complex which divided into different domains should show in a figure, which describes the structure and thedevision of different domains in the complex of chorismate mutase and chorismate. It makes the computed model direct and clear.

Reviewer #3: no additional comments at this time.

6. If you would like your identity to be revealed to the authors, please include your name here (optional).

Your name and review will not be published with the manuscript.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: (No Response)

U Copenhagen PhD course: Biostructures and Molecular Modelling in Drug Research

More information here

Learning objectives
The course objectives are to introduce participants to different experimental methods and methods in molecular modelling (or computational chemistry) for determination and analysis of three-dimensional structures of biologically important molecules. The application of these methods in the study on relationships between molecular structure and biological activity are dealt with in detail. The course will provide the participants with the opportunity to apply molecular modelling methods to their own research problems.

Content
Nearly all drugs exert their effect by an interaction with a biological macromolecule, i.e. by activation of a receptor or by inhibition of an enzyme. This interaction involves a specific molecular interaction between the drug (the ligand) and the macromolecule (often a protein). Today, considerable information has been accumulated about the relationships between structure and activity for most types of drugs. Nevertheless, knowledge about the molecular interactions between the drug molecule and the macromolecule in the organism is still limited in most cases.
The most important experimental method for determination of structures of organic molecules is X-ray crystallography. By X-ray crystallographic methods it is possible to determine high-resolution three-dimensional structures of small molecules as well as macromolecules such as proteins. NMR spectroscopy and molecular modelling methods represent alternative methods for the determination of three-dimensional structures and biologically relevant targets.
The term, molecular modelling, comprises a variety of computer-based methods used to construct three-dimensional models of chemical compounds, and to calculate a number of different characteristics for the compounds (e.g. shape, flexibility, charge distribution, lipophilicity). Computer graphics is very important for visualisation of the molecules and their characteristics.
Molecular modelling makes it possible to construct models of already known molecules, but also unknown or not yet synthesised molecules can be investigated. With molecular modelling it is possible to study the relationships between molecular structure and various properties, and to assist in design of compounds with preselected properties.

Molecular modelling and computer graphics are powerful tools in the study of the relationships between molecular structure and biological activity, and thus essential in the process of rational drug design. Molecular modelling has become an indispensable part of modern medicinal chemistry and during the last decade the methods have been implemented in most pharmaceutical companies.

During the course a number of examples of biological (pharmaceutical) importance will be presented and discussed with special emphasis on the following topics:
- Molecular structures and 3D-databases: Experimental methods (X-ray crystallography and NMR spectroscopy), computational methods (homology building) and 3D-databases including crystallographic databases (Protein Data Bank),.
- Molecular mechanics-based methods: Different force fields (potential functions, parameters, limitations), energy minimisation, charges, electrostatics and molecular dynamics simulations.
- Quantum mechanics methods: Approximations, basis set, determination of properties (e.g. structures, energies, charges).
- Structure-activity analyses: Conformational analysis, conformational energies, conformational search methods, template fitting and pharmacophore identification.
- Protein-ligand interactions: Binding energies, docking, structure-based molecular design, de novo design.
- ADME (absorption, distribution, metabolism and excretion) modelling.

The practical exercises will include tutorials aimed at learning specific tasks and projects based on the participants' own research activities.

Notes on fugacity and activity

This is one of those "note to self" posts where I try to get my head around a concept, this time fugacity and activity for a gas.

$dG=Vdp-SdT \implies dG=Vdp \text{ if } dT=0$

$$G(p)=G^\circ+\int_{p^\circ}^{p}Vdp$$
If the gas is ideal, i.e. for one mole $V=RT/p$, then
$$G(p)=G^\circ+RT\int_{p^\circ}^{p}\frac{dp}{p}=G^\circ+RT\ln\frac{p}{p^\circ}$$
For $A\rightleftharpoons B$
$$G(p_B)-G(p_A)=0 \implies \frac{p_B}{p_A}=e^{-\Delta G^\circ/RT}$$
What about a real gas where $V\neq RT/p$?  We introduce the fugacity $(f)$ for which $V=RT/f$ so that
$$G(p)=G^\circ+RT\ln\frac{f}{p^\circ} \text{ and } \frac{f_B}{f_A}=e^{-\Delta G^\circ/RT}$$
To determine $f$:
$$\int_{p'}^{p} (V-V_{ideal})dp=RT\ln\left(\frac{f}{f'}\cdot \frac{p'}{p}\right) =  RT\ln\left(\frac{f}{p}\cdot \frac{p'}{f'}\right) $$
Gases approach ideality at low pressure: $f'/p'\rightarrow 1$ as $p\rightarrow 0$ so:
$$\ln\left(\frac{f}{p}\right)=\ln(\phi)=\frac{1}{RT}\int_{0}^{p} (V-V_{ideal})dp$$
So for sticky non-ideal gases for which $V<V_{ideal}$ the fugacity coefficient $\phi$ is less than 1.  So even though $V=RT/f$ don't confuse $f$ with $p_{ideal}: f<p<p_{ideal}$ for a given number of gas particles.

Finally the relationship between fugacity and activity ($a$) is
$$a=\frac{f}{p^\circ}$$.

This work is licensed under a Creative Commons Attribution 3.0 Unported License. 
  

PhD position in statistical protein structure prediction, University of Copenhagen

One of the major unsolved problems in bioinformatics is the protein folding problem: given an amino acid sequence, predict the overall three-dimensional structure of the corresponding protein. It has been known since the seminal work of Christian B. Anfinsen in the early seventies that the sequence of a protein encodes its structure, but the exact details of the encoding still remain elusive. Since the protein folding problem is of enormous practical, theoretical and medical importance - and in addition forms a fascinating intellectual challenge - it is often called the holy grail of bioinformatics.Currently, most protein structure prediction methods are based on rather ad hoc approaches. The aim of this project is to develop and implement a statistically rigorous method to predict the structure of proteins, building on various probabilistic models of protein structure developed by the Hamelryck group. The method will also take the dynamic nature of proteins into account.

Requirements:Knowledge of statistics, machine learning and programming (C++ or equivalent). Knowledge of biology or biophysics is a plus, but not a requirement. 

Place of enrollment: Department of Biology, Bioinformatics Center 

Supervisor: Assoc. Prof. Thomas Hamelryck

Co-supervisor: Prof. Michael Sørensen, Department of Mathematical Science 

Application deadline: January, 5th, 2014, with start in 2014.

More information here: http://dsin.ku.dk/positions/

Taking my thermodynamics course online

Readers of this blog will know I occasionally dabble with the flipped classroom/peer instruction approach in my teaching, and this year I finally went whole hog - to use an Iowan expression.

What I did (tl;dr)
This year I abandoned the textbook for my part of the course and replaced the material with videos and Powerpoint slides.  This allowed me to completely change the order I taught subjects in and introduce more of what I think are more relevant subjects.

Why I did it
Last year I had already flipped the classroom and used lecture periods almost exclusively on peer instruction questions based on the assigned reading.  Now that I was finally happy with how I was teaching, I started to realize that I was less happy with what I was teaching.

What one is teaching, and the order it is being taught in, is to a large extent dictated by the textbook one chooses.  We chose Dill's Molecular Driving Forces. Like most textbooks it's written for the instructor rather than the students: an excellent resource for people who already understand the subject.  And why not?  I am the customer after all.

Thermodynamics/statistical mechanics books are essentially physics books that go through the definition and derivation of key equations and concepts first and in great detail and treat the applications as more of an afterthought.  Example: I would argue that $K=e^{-\Delta G^\circ/RT}$ is a more useful equation than, say, $S=q_{rev}/T$ for the practicing chemist, yet most books will spend many more pages discussing the latter. And don't get me started on the Carnot cycle.

Redesigning the curriculum I had five guiding principles in mind:

1. The video shown at the beginning of this post.
2. Start with the most useful (a much less arbitrary term than important) topics to my students.
3. Let the homework problems dictate the material, not the other way around.
4. Reduce the load and spend more time on what you consider most useful.
5. Study test test test – test.

So, one of the first homework questions I wrote involves computing $\Delta G^\circ$ from a binding curve.  Then I wrote the corresponding lecture notes.  Since I introduced this topic early, I also get to use it again and again during the rest of the course, which increases retention.

Similarly, I was able to introduce problems involving the Molecular Calculator, because I could taylor the lectures accordingly.

How I did it
1.  The homework problems.  I rewrote all the homework problems from scratch. It's hard to describe how liberating (and relatively easy) it is to write exactly the problems you want knowing that everything you need by definition will be covered in lecture, exactly how you want it.

As in previous years I put the answer up in form of multiple choice on PeerWise.  Once an answer is selected the solution (copied from my Maple solution) is revealed.  Occasionally, I also supplied intermediate solutions to help guide the student and screen-casts showing how I solve the problem using Maple.

Finally, I the students some choice in the problems they want to solve.  For example, I told them they had to solve any six out of nine questions.  I made sure that the first six were relatively easy, but some of the remaining questions could be quite tricky.  Many students did all of them, and I got few complaints about the most difficult ones since the students themselves had chosen to work on them.

You can find the problem sets here.

2. The video-lectures.  I chose to make video-lectures because it was the fastest way to generate material.  The Powerpoint slides contain mainly equations and pictures and all the explanation is done verbally (remember: the students can rewind and repeat).  This is much quicker than writing everything down in detailed lecture notes.

I make normal Powerpoint slides and use ScreenFlow to record (PC users can use Camtasia). Another option would have been pen-casting but many of the figures were much too complicated to sketch and screen-casting made it easier to introduce videos, simulations, etc. However, if you have handwritten lecture notes you are happy with, this could be a good option.

Each video lecture is quite short (max 10 minutes) and most end with a question. I provide the Powerpoint slides - except the ones containing the answer - along with the videos.  The students have to watch between four and six videos before each two-hour "lecture" period

The editing features in ScreenFlow make it relatively easy to correct mistakes.  If you remember to pause briefly (also verbally) between each slide, then you only have to repeat one slides worth of material.

You can see the videos and slides here

3. "Reading"-quiz.  The students have to take an on-line quiz (no points) the evening before the day of the lecture (at the latest): one question per video that can be easily answered if one has watched the video (often a T/F question).  I do this for two reasons: (1) to make it clear that they must prepare for class since I am not going to repeat the material and (2) that they should pay attention while watching the videos.   The last question on each quiz is whether I should discuss something in more detail in class.

4. The "lecture" period.  During the 2 x 45 min "lecture" period I ask roughly 20 peer instruction questions.  Roughly ten are review questions on previous material and the remaining questions are on the new material.  I use Socrative for voting.  Most are conceptual questions designed with discussion in mind.  

What I learned so far
1. Making the slides and videos and questions is a lot of work.  Even considering I have taught this course many times and knew exactly what I wanted to do.  But ...

2. ... it is much, much faster than writing a textbook yourself. Constructing such a textbook-replacement for your course is a manageable task. And extremely liberating and satisfying.

3. We live in the age of Google (OK, I kinda knew this one already).  You don't need to include a table of dielectric constants or heats of formation in your teaching material.  Just give a few examples of finding this info with Google in one of the early videos.

4. Review is essential.  The data from in-class voting is clear: take a question that 95% of the class answered correctly and ask is a week later.  Half the class will get it wrong.  Research shows that many subject must be reviewed at least 3 times before it sticks.  Keep this in mind when designing your curriculum.  Most courses pack in way too much material.  Very little of it sticks.  See the video at the beginning of the post again.

5. Surprisingly (to me) many of the students take the "reading quiz" at the very last minute and probably wouldn't prepare for class if it wasn't for the reading quiz.

Example: 30 students took the exam.  For the September 30 lecture period, 24 students completed the "reading"-quiz.  Eight of them completed the quiz between 11 pm and midnight (the deadline).

OK. That's it, for now.  Now would be a good time to watch the video a third time.  You know, so it sticks.

More posts one statistical mechanics can be found here.

This work is licensed under a Creative Commons Attribution 3.0 Unported License. 

PhD Position in Computational Chemistry at the University of Southern Denmark

A fully financed three-year PhD position in theoretical/computational chemistry is available for a highly motivated applicant at the Department of Physics, Chemistry and Pharmacy at the University of Southern Denmark starting from 1 February 2014. The position is financed through the Sapere Aude programme under the Danish Council for Independent Research. The research project will consists of - in roughly equal parts – theory/algorithm development and computational modelling within quantum molecular biophysics/biochemistry. The main focus will be on studying multichromophoric electronic processes in complex and biological environments, and the developed methods will rely extensively on quantum mechanical formulations. Of special interest will be models that effectively combine quantum mechanics and molecular mechanics aiming for a realistic description of very large bio-molecules including all physical relevant interactions. The candidate should hold a Master's degree or equivalent in theoretical (bio)physics, modelling, chemistry or computational science. The candidate should document knowledge in one of the following programming languages: C/C++, Python or Fortran. Furthermore, documented experience in computational quantum chemistry/physics is a prerequisite. For further information please contact Jacob Kongsted, kongsted@sdu.dk. Application, salary etc.Appointment as a PhD Research Fellow is for three years. Employment stops automatically at the end of the period. The holder of the scholarship is not allowed to have other paid employment during the three-year period. The successful applicant will be employed in accordance with the agreement of 16 November 2011 on salaried PhD scholars between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). The successful candidate will be enrolled at this university in accordance with faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order). The university encourages all persons interested in the position to apply, regardless of their age, gender, religious affiliation or ethnic background. Application must be made in the form of a Declaration of Interest including the following: - A research proposal/description of your approach to the above project (max one page excluding references) - A letter stating your specific interest, motivation and qualifications for the project in question (max. two pages) (please attach this under box "Application form") - Detailed CV, including personal contact information - Copies of diplomas, Bachelor as well as Master’s degree, including transcript of notes - At least two signed reference letters. Further information about the PhD-study can be found at the homepage of the University. Applications must be submitted electronically using the link below. Attached files must be in Adobe PDF or Word format. Each box can only contain a single file of max. 10 Mb. Please read How to apply before you apply. Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters. Further information for international applicants about entering and working in Denmark.
Tjenestested:
Odense
Ansøgningsfrist:
15/12/2013

PhD position in molecular modeling at University of Copenhagen

Do you want to help prevent drug resistance in viral diseases?

PhD Scholarship available at the University of Copenhagen, Denmark

A PhD position in in Molecular Simulations and Computational Biology is available from January 1, 2014 at the Department of Biology, University of Copenhagen, Denmark. The aim of the project is to study how drug resistance mutations in pathogenic viruses arise and how resistance can be circumvented. The students will work under the primary supervision of Kresten Lindorff-Larsen in tight collaboration with experimental groups both here and abroad.

The PhD student will use a range of methods from computational structural biology to study the interactions of viral drug targets with drug molecules. The goal is to predict and understand how mutations can give rise to drug resistance, and to validate and integrate experimental data in such studies. The student will combine high-throughput calculations with more detailed molecular dynamics simulations to study the interactions between drug molecules and their targets.

It is essential that the candidate has a strong background in protein science and in using computational methods to study e.g. protein structure, function and dynamics. Applicants should hold an MSc degree, and research experience with molecular modelling of proteins or other biomacromolecules is a prerequisite. Hands-on research experience in e.g. molecular dynamics simulations and free energy calculations is a distinct advantage as is experience in computational studies of protein-ligand/drug interactions. Good interpersonal and communication skills. The working language in the group is English, and the candidate must master both written and spoken English.

For further information about the PhD position including salary, the complete set of requirements and how to apply see the full ad at: tinyurl.com/drug-resistance-phd2

The deadline for applications is Dec 1, 2013.

Further information can also be obtained via email to Associate Professor Kresten Lindorff- Larsen, e-mail: lindorff@bio.ku.dk , website: http://www.bio.ku.dk/sbinlab 

Computational Chemistry Course - Exploring a PES

I made this video to illustrate the basic ideas behind the generation of a reaction profile. I show how to "explore" the potential energy surface for a basic Diels-Alder reaction.



The small animations were produced visualizing with Molden actual calculation done with Gaussian at HF/sto-3g level and screencasted with ScrenFlow. The entire video is another ScreenFlow capture of a PowerPoint presentation with my voice over.

Martin got interviewed by PeerJ

Martin continues to strike gold with PeerJ. He just got interviewed for the journal blog! Once again, way to go, Martin!




In his interview Martin talks about his articles published with PeerJ  (you can find them here and here), and his overall experience with publishing in an Open Access journal.