I believe the answer given thus far is that it is highly
system-dependent, case-by-case. No general answer exists.
Dr. Robert Molt Jr., Ph.D.
r.molt.chemical.physics.gmail.com
Nigel Richards Research Group
Department of Chemistry & Chemical Biology
Indiana University-Purdue University Indianapolis
LD 326
402 N. Blackford St.
Indianapolis, IN 46202
On 3/5/14 10:58 AM, Soumendranath Bhakat wrote:
> Okay say for example i have a ligand bound protein,we demonstrated
> that a continuous md leads to an reasonable binding free energy close
> to experiment or statistically siginificant trends. Also this
> continuous md simulation leads to identify prominent motions related
> to conformation. Now some people say running multiple md simulations
> from an intial starting point with different random velocity and then
> combining all trajectories will possibily cover more sampling space.
> So for example a general protein ligand complex which will lead to
> better overall sampling a long continuous sampling or multiple md
> approach? Which technique will cover more sampling space if we go
> for conformational analysis a multiple md or continuous md.
>
> On 3/5/14, Brian Radak <radak004.umn.edu> wrote:
>> Back during my graduate preliminary exams I recall being (somewhat) gently
>> reminded that the validity of (nearly?) all statistical mechanical
>> estimators in use in MD analysis are predicated on the *assumption* of
>> ergodicity. That is, that the trajectory at hand is in fact really really
>> long and has therefore visited all *relevant *regions of phase space.
>>
>> Now I would argue that this depends on how one defines relevant and that
>> this is the great advantage/disadvantage of simulations in general, the
>> complete control one has of defining the system/problem. The validity of
>> this definition will probably reduce to physical arguments based on
>> intuition and empirical knowledge of the problem at hand. Therefore, as
>> Carlos pointed out, which tools are appropriate and which compromises are
>> best is likely to always be a case by case challenge.
>>
>> Regards,
>> Brian
>>
>>
>> On Wed, Mar 5, 2014 at 9:46 AM, Carlos Simmerling <
>> carlos.simmerling.gmail.com> wrote:
>>
>>> In my opinion this is like wondering whether one should do standard MD or
>>> free energy calculations, or explicit vs implicit solvent, or for that
>>> matter QM vs MM. Multiple MD and long continuous MD are just two
>>> different
>>> tools, and which one is the "right" tool depends completely on the
>>> problem
>>> you are trying to solve, and what sort of data it requires. The best
>>> answer
>>> is of course to do multiple very long MD, but I believe that the key to
>>> success in this area (or any other where the tools are not fully mature)
>>> is
>>> to recognize that compromises must often be made, and to carefully choose
>>> the ones that have the least impact on your specific goals for the
>>> project.
>>> For a reviewer to say that in all cases multiple short MD is better than
>>> long MD makes no sense to me. That being said, I am very skeptical of
>>> studies where there is no attempt to quantify precision.
>>> carlos
>>>
>>>
>>> On Wed, Mar 5, 2014 at 9:33 AM, Soumendranath Bhakat <
>>> bhakatsoumendranath.gmail.com> wrote:
>>>
>>>> Dear Amberists;
>>>>
>>>> We have reported long range continuous MD simulations (50ns) in many of
>>> our
>>>> research communications. But we observe that some journals and
>>>> reviewers
>>>> are very much critical of continuous MD simulations and asked for
>>> multiple
>>>> MD simulations.
>>>>
>>>> But recently in a debate many people put different views on multiple MD
>>>> simulations and as per their view this multiple MD simulation does not
>>>> provide a great insight than continuous MD (50/100ns sampling). Some
>>> people
>>>> say in positive aspect to multiple MD saying that it covers a large
>>>> conformational space.
>>>>
>>>> Majority of people agreed that if you are doing long range continuous
>>>> MD
>>>> and proper post dynamics analysis thats enough to demonstrate maximum
>>>> points related to motions of a biological system.
>>>>
>>>> As a continuous learner my question is to AMBER community that which
>>>> one
>>> is
>>>> preferred a long range continuous MD or corresponding Multiple MD
>>>> simulation?
>>>>
>>>> As there are numerous numbers of paper on continuous MD rather than a
>>> very
>>>> few multiple MD papers on aspects like conformational analysis and etc.
>>> so
>>>> which one is the best to go with.
>>>>
>>>> Please put justification in support of your argument. We experience
>>>> that
>>>> some journal and reviewers always point out to do multiple MD over
>>>> continuous MD simulation,but in maximum cases people accept long range
>>>> continuous MD.
>>>>
>>>> Thanks & Regards;
>>>> Soumendranath Bhakat
>>>> Co-Founder Open Source Drug Design and In Silico Molecules (
>>>> www.insilicomolecule.org)
>>>> UKZN, Durban
>>>> Past: Birla Institute of Technology,Mesra, India
>>>> --
>>>> Thanks & Regards;
>>>> Soumendranath Bhakat
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>>>>
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>>
>>
>> --
>> ================================ Current Address =======================
>> Brian Radak : BioMaPS
>> Institute for Quantitative Biology
>> PhD candidate - York Research Group : Rutgers, The State
>> University of New Jersey
>> University of Minnesota - Twin Cities : Center for Integrative
>> Proteomics Room 308
>> Graduate Program in Chemical Physics : 174 Frelinghuysen Road,
>> Department of Chemistry : Piscataway, NJ
>> 08854-8066
>> radak004.umn.edu :
>> radakb.biomaps.rutgers.edu
>> ====================================================================
>> Sorry for the multiple e-mail addresses, just use the institute appropriate
>> address.
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>
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Received on Wed Mar 05 2014 - 08:30:03 PST
