Pymol Free Download For Windows 7 32-bit Download
Eliora Shopbell
Yes, the license file can be placed at $PREFIX/share/pymol/license.lic, for example:
- On Windows: C:\ProgramData\PyMOL\share\pymol\license.lic
- On macOS: /Applications/PyMOL.app/Contents/share/pymol/license.lic (not gatekeeper-friendly)
or: /Library/Application Support/Schrodinger/licenses/*.lic (gatekeeper-friendly, since PyMOL 2.2.2) - On Linux: $HOME/anaconda3/share/pymol/license.lic
For PyMOL 2.5: Transition from previous versions may not work. All dependencies, including python, are based off of conda-forge. More information
Remove all relevant dependencies or create a new environment and:
conda install -c schrodinger -c conda-forge pymol
or
conda install -c schrodinger -c conda-forge pymol-bundleOn macOS: Movie export with ffmpeg brokenThe on-demand installation of ffmpeg may install an incompatible version (Error message: dyld: Library not loaded: @rpath/libopenh264.5.dylib). This can be fixed by running the following command in a terminal: /Applications/PyMOL.app/Contents/bin/conda install conda-forge::ffmpeg
If your MS Office is 32-bit then you need to install 32-bit AxPyMOL. If your MS Office is 64-bit you need to install 64-bit AxPyMOL.
Many people have 64-bit Windows installed but have 32-bit Office installed. The AxPyMOL installation should warn users of this mismatch, but before you download, check your version of MS Office, as shown below.
It is part from science category and is licensed as shareware for Windows 32-bit and 64-bit platform and can be used as a free trial until the trial period will end. The PyMOL demo is available to all software users as a free download with potential restrictions compared with the full version.
If you are still getting an error saying "scipy-0.18.1-cp27-cp27m-win_amd64.whl is not a supported wheel on this platform", then go for the win32 version.By this I mean install scipy-0.18.1-cp27-cp27m-win32.whl instead of the first one.This is because you might be running a 32-bit python on a 64-bit system.The last step successfully installed scipy for me.
I have tried using wheels files (namely gohlke/pythonlibs/#pymol amd64 version) but I have encountered pip problems. See the pip I have came along with my 64-bit Python 2.7.9 installation and the exe file for pip is called pip2.exe. So I changed the system environment variable PYTHONPATH to C:\Python27 (where the python installation is) and PATH to C:\Python27\Scripts which is where pip2.exe is (along with pip2.7.exe, easy_install.exe and easy_install-2.7.exe, if relevant). Then I ran:
I uninstalled python and reinstalled it (64 bit again) as I suspected some errors had occurred in my previous installation (this time the pip that came with it included a file called pip.exe in the Scripts folder), then I ran the pymol installation command again (after running pip install wheel-0.24.0-py2.py3-none-any.whl, downloaded from with this file downloaded from -0.24.0-py2.py3-none-any.whl#md5=4c24453cda2177fd42c5d62d6434679a) and received a different error, the pip.log file may be found here:
Why did you choose to ignore my instruction and run yet another tool, also I do not speak or understand French so have no idea what damage you`ve done. Maybe your best option is to Format your Hard drive and reinstall windows.
NOTE
The pre-compiled windows binaries for Python extension packages are hosted and regularly updated by Christoph Gohlke of the Laboratory for Fluorescence Dynamics, University of California, Irvine, in the source-code repository. Moreover, the links to old windows binaries are removed from the server on the new release of Python extension packages. So, carefully download the apt windows binaries and Python software according to the latest release. As on 24 April 2021, the latest Python software and pre-compiled windows binaries for installing PyMOL are bellow,
1. Python 3.9.4 ( -3.9.4-amd64.exe)
2. PIP v21.0.1 ( -21.0.1-py3-none-any.whl)
3. Numpy+MKL v1.20.2 ( -1.20.2+mkl-cp39-cp39-win_amd64.whl)
4. PMW v2.0.1 ( -2.0.1-py3-none-any.whl)
5. PyMOL v2.5.0 alpha ( -2.5.0a0-cp39-cp39-win_amd64.whl)
6. PyMOL Launcher v2.1 ( _launcher-2.1-cp39-cp39-win_amd64.whl)
- A confirmation email with password will be sent to you, after you register your email in the I-TASSER server.But since the confirmation emails were sent out automatically by computer, it is possible that the confirmation email was filtered out by your email security system. So it is wise to check your junk E-mail folders, if you did not receive a confirmation email in your inbox in time. If you found that you did not receive the confirmation email one hour after you correctly submitted your registration information, please contact yangzh...@umich.edu and let us know the email that you registered. We can resend the registration information to you, manually.
- If you copy and paste your password from the confirmation email, please remember not to include any space before and after the password. For example, if your password is IT_8abcd, please make sure that you did not type in " IT_8abcd" or"IT_8abcd ", which is the mistake most frequently made by new users.
- Are you using the password obtained from I-TASSER server to download I-TASSER Suite? The I-TASSER Server, I-TASSER Suite, I-TASSER Forum, and QUARK webserver are independent systems. You need to register them separately for different passwords.
- (Short answer) No, you can not. The I-TASSER server only accepts for sequence below 1,500 residues.
- (Long answer) The server version of I-TASSER has not been optimized for multi-domain proteins prediction. Therefore, if you upload a large protein with more than one domain, more often than not you will only get accurate prediction for one of your domain. If you have a protein longer than 1,500 residues, you can split the sequence into domains either by Pfam search, or by ThreaDom. You can then submit the sequence of each domain separately. This should generate models of higher accuracy. You can then assemble individual domains into full lengthstructure by DEMO.
- All components of I-TASSER suite were developed on 64-bit Linux. All itsFortran and C++ binary executables are compiled for 64-bit Linux only.This means that it is currently impossible to run I-TASSER suite on Mac OS.It is also impossible to run I-TASSER suite on any 32-bit system, including32-bit Linux. As I-TASSER suite is memory intensive, there is no point tryingto make I-TASSER run on 32-bit system where no more than 4Gb of memory couldbe addressed.It is impossible to run I-TASSER on Windows, including Windows Subsystem for Linux(also known as "Ubuntu on Windows").
- Usually, this happens when you submit invalid SAXS profile. For SAXSTER to work, you need to upload either SAXS Pair Distance Distribution Function p(r) or SAXS Intensity profile I(q). If your uploaded p(r) or I(q) profile is empty (all zeros) or contains at least one p(r) value smaller than zero or greater than one, SAXSTER will not work.
- (Short answer) No, you cannot. Overall topology of I-TASSER models for different mutant of the same protein is usually very similar.
- (Long answer) A structure model can tell you where is the mutation, e.g. if itis near ligand binding site, an active site, or at protein-protein interaction interface, etc. However, unless you have introduced a substantial number of mutations, or introduce long insertion/deletetion, different mutants of thesame protein usually have similar final I-TASSSER structures. This is in accordance with our observation on experimental structure in PDB, wild type protein and mutant protein of a small number of substitution usually sharesalmost identical conformation, even if their function might differsignificantly. We have developed a pipeline called STRUM to address the effect of single mutations on a protein, specifically the stability differences between native protein and its mutants.
- If you have successfully submit jobs via web server, but the webserver did not send any result back after two weeks, you should check whether your input isincorrect. If you are sure it is a bug, please report it to yangzh...@umich.edu using the email you used for job submission and report the web service you used and your Job ID.
- If you find a bug in standalone software downloaded from Yang Zhang lab website, such as I-TASSER suite, please report it to the Service System Discussion Board. You need to provide the following information: [1] input files, [2] output files, [3] command you used to run the software and its screen output, [4] if you recompile the software yourself, instead of using our precompiled binaries, please report the compiler version (e.g. gfortran 4.8) and compilation command you used, [5] the operating system (e.g. Ubuntu Linux Trusty 14.04 amd64, or Mac OSX 10.11.1 EL Capitan) and CPU description; under Linux please send the output of:
- uname -a; lsb_release -a; head -n 25 /proc/cpuinfo; ulimit -a; free
- I-TASSER modeling starts from the structure templates identified by LOMETS fromthe PDB library. LOMETS is a meta-server threading approach containing multiple threading programs,where each program can generate tens of thousands of templates. I-TASSERonly uses the templates of the highest significance in the threadingalignments, which are measured by the Z-score (the difference between theraw and average scores in the unit of standard deviation).The top 10 templates are the 10 templates selected from the LOMETSthreading programs. Usually, one (or two) template of the highest Z-scoreis selected from each threading program, where the threading programs aresorted by the average performance in the large-scale benchmark test experiments.
- For each target, I-TASSER simulations generate tens of thousands conformations (called decoys). To select the final models, I-TASSER uses SPICKER program tocluster all the decoys based on the pair-wise structure similarity, and reportup to five models which corresponds to the five largest structure clusters.In Monte Carlo theory, the largest clusters correspond to the states of thelargest partition function (or lowest free energy) and therefore have thehighest confidence. The confidence of each model is quantitatively measured byC-score (see below). Since the top 5 models are ranked by the cluster size, it is possible that the lower-rank models have a higher C-score. Although the first model has a higher C-score and a better quality in most cases, it is not unusual that the lower-rank models have a better quality than the higher-rank models.If the I-TASSER simulations converge, it is possible to have less than 5 clustersgenerated. This is usually an indication that the models have a good qualitybecause of the converged simulations.
- After the structure-assembly simulation, I-TASSER use TM-align program to match the first I-TASSERmodel to all structures in the PDB library. This section reports the top10 proteins from the PDB which have the closest structural similarity (i.e. the highest TM-score) to thepredicted I-TASSER model. Due to the structural similarity, these proteinsoften have similar function to the target. However, users are encouraged touse the data in 'Predicted function using COACH' to infer the biological function of the target protein, since COACH has been extensively trained toderive function from multi-source of sequence and structure features whichhas on average a much higher accuracy than the function annotations derived only from the global structure comparison.
- C-score is a confidence score for estimating the quality of predicted models by I-TASSER. It is calculated based on the significance of threading template alignments and the convergence parameters of the structure assembly simulations. C-score is typically in the range of [-5,2], where a C-score of higher value signifies a model with a high confidence and vice-versa.
- TM-score is a recently proposed scale for measuring the structural similarity between two structures (see Zhang and Skolnick, Scoring function for automated assessment of protein structure template quality, Proteins, 2004 57: 702-710). The purpose of proposing TM-score is to solve the problem of RMSD whichis sensitive to the local error. Because RMSD is an average distance of all residue pairs in two structures, a local error (e.g. a misorientation of the tail) will arise a big RMSD value although the global topology is correct. In TM-score, however, the small distance is weighted stronger than the big distance which makes the score insensitive to the local modeling error. A TM-score >0.5 indicates a model of correct topology and a TM-score