Water will find its way: transport through narrow tunnels in hydrolases (water-protein interaction analysis)

Repository including information on the analyses of water-protein interactions by MM/GBSA. hal_mmgbsa_data.tar.gz - contains a minimal set of files necessary to recreate MM/GBSA calculations and also raw calculation results for Hal.epx_mmgbsa_data.tar.gz - contains a minimal set of files necessary to recreate MM/GBSA calculations and also raw calculation results for Epx.lip_mmgbsa_data.tar.gz - contains a minimal set of files necessary to recreate MM/GBSA calculations and also raw calculation results for Lip. In each archive structure is: {supercluster_id}: - supercluster directory {event_nr}_{rounded_radius}: - transport event directory renum.pdb -pdb file containing protein, water of interest and 8 Angstrom radius sphere of surrounding waters water.txt - file denoting water ID for water of interest in the renum.pdb file binding_[implicit|explicit].dat - file containing MMGBSA results for full implicit and partial explicit system decomposition_[implicit|explicit].dat - file containing MMGBSA decomposition results for full implicit and partial explicit system info_{supercluster_id}.csv - file containing descriptions of transport events in supercluster (columns: event_name, radius, frame, simulation, water_id) results.tar.gz - contains csv files generated by script collect_data_minimal.py for each protein for full implicit and partial explicit solvent. Columns in those csv file are: event_name, supercluster, radius, frame, simulation, water_id, delta_total, delta_van_der_waals, delta_electrostatic, delta_G_solv scripts.tar.gz - contains following scripts read_transport_events.py prep_inputs.py run_MMGBSA_single.sh collect_data_minimal.py plot_bin.py To recreate MMGBSA calculations with provided inputs one should:$ python read_transport_events.py [Hal.dat|Epx.dat|Lip.dat] > selection.txtPrepare transport events information in a compatible format. Binary transport events databases are available in the repository. $ python prep_inputs.py selection.txt - {absolute output path} {supercluster_id} 1 Prepare parm and coordinate file for each supercluster id included in computation. Last argument 1 point script to resume preparations from renum.pdb files. $ bash run_MMGBSA_single.sh {residue_count}Runs MMGBSA for both partial explicit and fully implicit systems. Needs to be run for each event in each supercluster.residue_count should be set to 293 for hal, 319 for epx, and 534 for lip. $ python collect_data_minimal.py [hal|epx|lip]/{supercluster_id} [hal|epx|lip]/info_{supercluster_id}.csv [0|1] >> output.csvGathers data from MMGBSA calculations for a single supercluster into csv file. Last argument should be 0 for fully implicit system, 1 for partial explicit system. $ python plot_bin.py {hal_implicit_csv} {hal_explicit_csv} {epx_implicit_csv} {epx_explicit_csv} {lip_implicit_csv} {lip_explicit_csv}Results visualization. Produces "combined.png".本仓库包含基于分子力学/广义玻恩表面积法（MM/GBSA）开展水-蛋白质相互作用分析的相关数据。 `hal_mmgbsa_data.tar.gz`：包含复现MM/GBSA计算所需的最小文件集，以及针对Hal的原始计算结果。 `epx_mmgbsa_data.tar.gz`：包含复现MM/GBSA计算所需的最小文件集，以及针对Epx的原始计算结果。 `lip_mmgbsa_data.tar.gz`：包含复现MM/GBSA计算所需的最小文件集，以及针对Lip的原始计算结果。 每个压缩包的内部目录结构如下： `{supercluster_id}`：超级簇目录 `{event_nr}_{rounded_radius}`：转运事件目录 `renum.pdb`：包含目标蛋白质、目标水分子以及周围8埃半径水域的重编号蛋白质数据银行（PDB）文件 `water.txt`：记录`renum.pdb`文件中目标水分子的ID信息 `binding_[implicit|explicit].dat`：包含全隐式与部分显式溶剂体系下的MM/GBSA计算结果文件 `decomposition_[implicit|explicit].dat`：包含全隐式与部分显式溶剂体系下的MM/GBSA分解结果文件 `info_{supercluster_id}.csv`：记录超级簇内转运事件描述的CSV文件，其列名依次为：event_name、radius、frame、simulation、water_id。 `results.tar.gz`：包含由脚本`collect_data_minimal.py`针对各蛋白质在全隐式与部分显式溶剂体系下生成的CSV文件。此类CSV文件的列名依次为：event_name、supercluster、radius、frame、simulation、water_id、delta_total（总自由能变化量）、delta_van_der_waals（范德华相互作用能变化量）、delta_electrostatic（静电相互作用能变化量）、delta_G_solv（溶剂化自由能变化量）。 `scripts.tar.gz`：包含以下脚本：`read_transport_events.py`、`prep_inputs.py`、`run_MMGBSA_single.sh`、`collect_data_minimal.py`、`plot_bin.py`。 若需基于提供的输入文件复现MM/GBSA计算，请执行以下流程： 1. 生成兼容格式的转运事件信息：执行命令`python read_transport_events.py [Hal.dat|Epx.dat|Lip.dat] > selection.txt`。本仓库中已提供二进制格式的转运事件数据库。 2. 生成拓扑与坐标文件：执行命令`python prep_inputs.py selection.txt - {absolute output path} {supercluster_id} 1`，为计算中涉及的每个超级簇生成拓扑（parm）与坐标文件。其中最后一个参数`1`用于指定脚本从`renum.pdb`文件恢复预处理流程。 3. 运行MM/GBSA计算：执行命令`bash run_MMGBSA_single.sh {residue_count}`，可针对部分显式与全隐式溶剂体系开展MM/GBSA计算。需为每个超级簇内的每个转运事件执行该命令。参数`residue_count`的取值需对应蛋白质种类：Hal为293，Epx为319，Lip为534。 4. 整合计算结果：执行命令`python collect_data_minimal.py [hal|epx|lip]/{supercluster_id} [hal|epx|lip]/info_{supercluster_id}.csv [0|1] >> output.csv`，将单个超级簇的MM/GBSA计算结果整合至CSV文件中。最后一个参数`0`代表全隐式溶剂体系，`1`代表部分显式溶剂体系。 5. 可视化计算结果：执行命令`python plot_bin.py {hal_implicit_csv} {hal_explicit_csv} {epx_implicit_csv} {epx_explicit_csv} {lip_implicit_csv} {lip_explicit_csv}`，用于结果可视化，将生成`combined.png`图片文件。